Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traits.

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

It is hoped that advances in our knowledge in disease genomics will contribute to personalized medicine such as individualized preventive strategies or early diagnoses of diseases. With the growth of genome-wide association studies (GWAS) in the past decade, how far have we reached this goal? In this study we explored the predictive ability of polygenic risk scores (PRSs) derived from GWAS for a range of complex disease and traits. We first proposed a new approach to evaluate predictive performances of PRS at arbitrary P -value thresholds. The method was based on corrected estimates of effect sizes, accounting for possible false positives and selection bias. This approach requires no distributional assumptions and only requires summary statistics as input. The validity of the approach was verified in simulations. We explored the predictive power of PRS for ten complex traits, including type 2 diabetes (DM), coronary artery disease (CAD), triglycerides, high- and low-density lipoprotein, total cholesterol, schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder and anxiety disorders. We found that the predictive ability of PRS for CAD and DM were modest (best AUC = 0.608 and 0.607) while for lipid traits the prediction R-squared ranged from 16.1 to 29.8%. For psychiatric disorders, the predictive power for SCZ was estimated to be the highest (best AUC 0.820), followed by BD. Predictive performance of other psychiatric disorders ranged from 0.543 to 0.585. Psychiatric traits tend to have more gradual rise in AUC when significance thresholds increase and achieve the best predictive power at higher P -values than cardiometabolic traits. hcso@cuhk.edu.hk ; pcsham@hku.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Genome-wide association study of resistance to ear rot by Fusarium verticillioides in a tropical field maize and popcorn core collection

USDA-ARS?s Scientific Manuscript database

Fusarium ear rot (caused by Fusarium verticillioides) is one of the most prevalent diseases of maize worldwide, and has one of the greatest negative economic impacts on this cereal crop globally. Fusarium ear rot is a highly complex trait, under polygenic control with minor effects per gene and low ...

Genetic diversity of disease-associated loci in Turkish population.

PubMed

Karaca, Sefayet; Cesuroglu, Tomris; Karaca, Mehmet; Erge, Sema; Polimanti, Renato

2015-04-01

Many consortia and international projects have investigated the human genetic variation of a large number of ethno-geographic groups. However, populations with peculiar genetic features, such as the Turkish population, are still absent in publically available datasets. To explore the genetic predisposition to health-related traits of the Turkish population, we analyzed 34 genes associated with different health-related traits (for example, lipid metabolism, cardio-vascular diseases, hormone metabolism, cellular detoxification, aging and energy metabolism). We observed relevant differences between the Turkish population and populations with non-European ancestries (that is, Africa and East Asia) in some of the investigated genes (that is, AGT, APOE, CYP1B1, GNB3, IL10, IL6, LIPC and PON1). As most complex traits are highly polygenic, we developed polygenic scores associated with different health-related traits to explore the genetic diversity of the Turkish population with respect to other human groups. This approach showed significant differences between the Turkish population and populations with non-European ancestries, as well as between Turkish and Northern European individuals. This last finding is in agreement with the genetic structure of European and Middle East populations, and may also agree with epidemiological evidences about the health disparities of Turkish communities in Northern European countries.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

PubMed

Astle, William J; Elding, Heather; Jiang, Tao; Allen, Dave; Ruklisa, Dace; Mann, Alice L; Mead, Daniel; Bouman, Heleen; Riveros-Mckay, Fernando; Kostadima, Myrto A; Lambourne, John J; Sivapalaratnam, Suthesh; Downes, Kate; Kundu, Kousik; Bomba, Lorenzo; Berentsen, Kim; Bradley, John R; Daugherty, Louise C; Delaneau, Olivier; Freson, Kathleen; Garner, Stephen F; Grassi, Luigi; Guerrero, Jose; Haimel, Matthias; Janssen-Megens, Eva M; Kaan, Anita; Kamat, Mihir; Kim, Bowon; Mandoli, Amit; Marchini, Jonathan; Martens, Joost H A; Meacham, Stuart; Megy, Karyn; O'Connell, Jared; Petersen, Romina; Sharifi, Nilofar; Sheard, Simon M; Staley, James R; Tuna, Salih; van der Ent, Martijn; Walter, Klaudia; Wang, Shuang-Yin; Wheeler, Eleanor; Wilder, Steven P; Iotchkova, Valentina; Moore, Carmel; Sambrook, Jennifer; Stunnenberg, Hendrik G; Di Angelantonio, Emanuele; Kaptoge, Stephen; Kuijpers, Taco W; Carrillo-de-Santa-Pau, Enrique; Juan, David; Rico, Daniel; Valencia, Alfonso; Chen, Lu; Ge, Bing; Vasquez, Louella; Kwan, Tony; Garrido-Martín, Diego; Watt, Stephen; Yang, Ying; Guigo, Roderic; Beck, Stephan; Paul, Dirk S; Pastinen, Tomi; Bujold, David; Bourque, Guillaume; Frontini, Mattia; Danesh, John; Roberts, David J; Ouwehand, Willem H; Butterworth, Adam S; Soranzo, Nicole

2016-11-17

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal. Copyright © 2016 Elsevier Inc. All rights reserved.

Personality Polygenes, Positive Affect, and Life Satisfaction

PubMed Central

Weiss, Alexander; Baselmans, Bart M. L.; Hofer, Edith; Yang, Jingyun; Okbay, Aysu; Lind, Penelope A.; Miller, Mike B.; Nolte, Ilja M.; Zhao, Wei; Hagenaars, Saskia P.; Hottenga, Jouke-Jan; Matteson, Lindsay K.; Snieder, Harold; Faul, Jessica D.; Hartman, Catharina A.; Boyle, Patricia A.; Tiemeier, Henning; Mosing, Miriam A.; Pattie, Alison; Davies, Gail; Liewald, David C.; Schmidt, Reinhold; De Jager, Philip L.; Heath, Andrew C.; Jokela, Markus; Starr, John M.; Oldehinkel, Albertine J.; Johannesson, Magnus; Cesarini, David; Hofman, Albert; Harris, Sarah E.; Smith, Jennifer A.; Keltikangas-Järvinen, Liisa; Pulkki-Råback, Laura; Schmidt, Helena; Smith, Jacqui; Iacono, William G.; McGue, Matt; Bennett, David A.; Pedersen, Nancy L.; Magnusson, Patrik K. E.; Deary, Ian J.; Martin, Nicholas G.; Boomsma, Dorret I.; Bartels, Meike; Luciano, Michelle

2016-01-01

Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of −0.49 and −0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains. PMID:27546527

The Contribution of GWAS Loci in Familial Dyslipidemias

PubMed Central

Söderlund, Sanni; Surakka, Ida; Matikainen, Niina; Pirinen, Matti; Pajukanta, Päivi; Service, Susan K.; Laurila, Pirkka-Pekka; Ehnholm, Christian; Salomaa, Veikko; Wilson, Richard K.; Palotie, Aarno; Freimer, Nelson B.; Taskinen, Marja-Riitta; Ripatti, Samuli

2016-01-01

Familial combined hyperlipidemia (FCH) is a complex and common familial dyslipidemia characterized by elevated total cholesterol and/or triglyceride levels with over five-fold risk of coronary heart disease. The genetic architecture and contribution of rare Mendelian and common variants to FCH susceptibility is unknown. In 53 Finnish FCH families, we genotyped and imputed nine million variants in 715 family members with DNA available. We studied the enrichment of variants previously implicated with monogenic dyslipidemias and/or lipid levels in the general population by comparing allele frequencies between the FCH families and population samples. We also constructed weighted polygenic scores using 212 lipid-associated SNPs and estimated the relative contributions of Mendelian variants and polygenic scores to the risk of FCH in the families. We identified, across the whole allele frequency spectrum, an enrichment of variants known to elevate, and a deficiency of variants known to lower LDL-C and/or TG levels among both probands and affected FCH individuals. The score based on TG associated SNPs was particularly high among affected individuals compared to non-affected family members. Out of 234 affected FCH individuals across the families, seven (3%) carried Mendelian variants and 83 (35%) showed high accumulation of either known LDL-C or TG elevating variants by having either polygenic score over the 90th percentile in the population. The positive predictive value of high score was much higher for affected FCH individuals than for similar sporadic cases in the population. FCH is highly polygenic, supporting the hypothesis that variants across the whole allele frequency spectrum contribute to this complex familial trait. Polygenic SNP panels improve identification of individuals affected with FCH, but their clinical utility remains to be defined. PMID:27227539

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism

PubMed Central

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30–40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log10 p-values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p-values from 1.7 × 10−6 to 1.8 × 10−5. Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 (SORCS3) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 (SLC39A12) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA (KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate. PMID:28702049

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism.

PubMed

Ricard, Anne; Robert, Céline; Blouin, Christine; Baste, Fanny; Torquet, Gwendoline; Morgenthaler, Caroline; Rivière, Julie; Mach, Nuria; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2017-01-01

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30-40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log 10 p -values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p -values from 1.7 × 10 -6 to 1.8 × 10 -5 . Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 ( SORCS3 ) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 ( SLC39A12 ) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA ( KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate.

Common variants at 30 loci contribute to polygenic dyslipidemia

USDA-ARS?s Scientific Manuscript database

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL)cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to ...

The nature of nurture: Effects of parental genotypes.

PubMed

Kong, Augustine; Thorleifsson, Gudmar; Frigge, Michael L; Vilhjalmsson, Bjarni J; Young, Alexander I; Thorgeirsson, Thorgeir E; Benonisdottir, Stefania; Oddsson, Asmundur; Halldorsson, Bjarni V; Masson, Gisli; Gudbjartsson, Daniel F; Helgason, Agnar; Bjornsdottir, Gyda; Thorsteinsdottir, Unnur; Stefansson, Kari

2018-01-26

Sequence variants in the parental genomes that are not transmitted to a child (the proband) are often ignored in genetic studies. Here we show that nontransmitted alleles can affect a child through their impacts on the parents and other relatives, a phenomenon we call "genetic nurture." Using results from a meta-analysis of educational attainment, we find that the polygenic score computed for the nontransmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% ( P = 1.6 × 10 -14 ) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition- and heath-related traits. Copyright © 2018, The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Quantitative Trait Loci (QTL) that Underlie SCN Resistance in the Soybean [Glycine max (L.) Merr.] ‘PI438489B’ by ‘Hamilton’ Recombinant Inbred Line Population

USDA-ARS?s Scientific Manuscript database

Soybean cyst nematode caused by Heterodera glycines is the most devastating pest in soybean [Glycine max (L.) Merr.]. Resistance to SCN is complex, polygenic, race-cultivar specific, and controlled by several QTL. Our objective was to identify and map QTL for SCN resistance to races 3 and 5 using a ...

Divergence and evolution of assortative mating in a polygenic trait model of speciation with gene flow.

PubMed

Sachdeva, Himani; Barton, Nicholas H

2017-06-01

Assortative mating is an important driver of speciation in populations with gene flow and is predicted to evolve under certain conditions in few-locus models. However, the evolution of assortment is less understood for mating based on quantitative traits, which are often characterized by high genetic variability and extensive linkage disequilibrium between trait loci. We explore this scenario for a two-deme model with migration, by considering a single polygenic trait subject to divergent viability selection across demes, as well as assortative mating and sexual selection within demes, and investigate how trait divergence is shaped by various evolutionary forces. Our analysis reveals the existence of sharp thresholds of assortment strength, at which divergence increases dramatically. We also study the evolution of assortment via invasion of modifiers of mate discrimination and show that the ES assortment strength has an intermediate value under a range of migration-selection parameters, even in diverged populations, due to subtle effects which depend sensitively on the extent of phenotypic variation within these populations. The evolutionary dynamics of the polygenic trait is studied using the hypergeometric and infinitesimal models. We further investigate the sensitivity of our results to the assumptions of the hypergeometric model, using individual-based simulations. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide.

PubMed

Chande, Aroon T; Wang, Lu; Rishishwar, Lavanya; Conley, Andrew B; Norris, Emily T; Valderrama-Aguirre, Augusto; Jordan, I King

2018-05-18

Human populations from around the world show striking phenotypic variation across a wide variety of traits. Genome-wide association studies (GWAS) are used to uncover genetic variants that influence the expression of heritable human traits; accordingly, population-specific distributions of GWAS-implicated variants may shed light on the genetic basis of human phenotypic diversity. With this in mind, we developed the GlobAl Distribution of GEnetic Traits web server (GADGET http://gadget.biosci.gatech.edu). The GADGET web server provides users with a dynamic visual platform for exploring the relationship between worldwide genetic diversity and the genetic architecture underlying numerous human phenotypes. GADGET integrates trait-implicated single nucleotide polymorphisms (SNPs) from GWAS, with population genetic data from the 1000 Genomes Project, to calculate genome-wide polygenic trait scores (PTS) for 818 phenotypes in 2504 individual genomes. Population-specific distributions of PTS are shown for 26 human populations across 5 continental population groups, with traits ordered based on the extent of variation observed among populations. Users of GADGET can also upload custom trait SNP sets to visualize global PTS distributions for their own traits of interest.

A family study of dermatoglyphic traits in India: segregation analysis of accessory palmar triradii and the atd angle.

PubMed

Gilligan, S B; Borecki, I B; Mathew, S; Vijaykumar, M; Malhotra, K C; Rao, D C

1987-09-01

Accessory triradii and the atd angle were examined via complex segregation analysis in order to evaluate possible genetic effects on these dermatoglyphic traits, measured in an endogamous Brahmin caste of peninsular India. The phenotypes considered included: presence of accessory palmar triradii a' and d', associated with the interdigital areas II and IV, respectively; presence of an accessory axial triradius tt' associated with the proximal margin of the palm; and an arctanh-transformation of the atd angle measurement. For all accessory triradii considered in the present investigation familial resemblance was evident. The most parsimonious model which could account for the observed resemblance was a multifactorial model that includes polygenic effects as well as transmissible environmental effects that are inherited in the same pattern as polygenes. Evidence of familial resemblance was also found for the arctanh-transformed atd angle, which could be attributed, initially, to both a major effect and a multifactorial component. Tests of transmission of a putative major gene were performed which yielded results consistent with Mendelian transmission, although an alternative test of no transmission of the major effect also fit the data. In light of these contrasting results we are precluded from accepting with confidence the notion of a major gene influence on the atd angle. We have concluded that the accessory triradii a', d', and tt', and the atd angle are influenced by multifactorial effects, including additive polygenes and possible environmental factors, such as intrauterine effects.

QTL meta-analysis provides a comprehensive view of loci controlling partial resistance to Aphanomyces euteiches in four sources of resistance in pea

USDA-ARS?s Scientific Manuscript database

More knowledge about diversity of Quantitative Trait Loci (QTL) controlling polygenic disease resistance in natural genetic variation of crop species is required for durably improving plant genetic resistances to pathogens. Polygenic partial resistance to Aphanomyces root rot, due to Aphanomcyces eu...

Hundreds of variants clustered in genomic loci and biological pathways affect human height

PubMed Central

Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N

2010-01-01

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation.

PubMed

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-08-22

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture.

The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar).

PubMed

Tsai, Hsin Yuan; Hamilton, Alastair; Guy, Derrick R; Tinch, Alan E; Bishop, Stephen C; Houston, Ross D

2015-05-19

Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position. The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits. We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

Marker-assisted selection in plant breeding for salinity tolerance.

PubMed

Ashraf, M; Akram, N A; Mehboob-Ur-Rahman; Foolad, M R

2012-01-01

Marker-assisted selection (MAS) is the process of using morphological, biochemical, or DNA markers as indirect selection criteria for selecting agriculturally important traits in crop breeding. This process is used to improve the effectiveness or efficiency of selection for the traits of interest in breeding programs. The significance of MAS as a tool for crop improvement has been extensively investigated in different crop -species and for different traits. The use of MAS for manipulating simple/qualitative traits is straightforward and has been well reported. However, MAS for the improvement of complex/polygenic traits, including plant tolerance/resistance to abiotic stresses, is more complicated, although its usefulness has been recognized. With the recent advances in marker technology, including high-throughput genotyping of plants, together with the development of nested association mapping populations, it is expected that the utility of MAS for breeding for stress tolerance traits will increase. In this chapter, we describe the basic procedure for using MAS in crop breeding for salt tolerance.

Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

PubMed Central

Paaby, Annalise B; White, Amelia G; Riccardi, David D; Gunsalus, Kristin C; Piano, Fabio; Rockman, Matthew V

2015-01-01

Embryogenesis is an essential and stereotypic process that nevertheless evolves among species. Its essentiality may favor the accumulation of cryptic genetic variation (CGV) that has no effect in the wild-type but that enhances or suppresses the effects of rare disruptions to gene function. Here, we adapted a classical modifier screen to interrogate the alleles segregating in natural populations of Caenorhabditis elegans: we induced gene knockdowns and used quantitative genetic methodology to examine how segregating variants modify the penetrance of embryonic lethality. Each perturbation revealed CGV, indicating that wild-type genomes harbor myriad genetic modifiers that may have little effect individually but which in aggregate can dramatically influence penetrance. Phenotypes were mediated by many modifiers, indicating high polygenicity, but the alleles tend to act very specifically, indicating low pleiotropy. Our findings demonstrate the extent of conditional functionality in complex trait architecture. DOI: http://dx.doi.org/10.7554/eLife.09178.001 PMID:26297805

Genome-wide epigenetic perturbation jump-starts patterns of heritable variation found in nature.

PubMed

Roux, Fabrice; Colomé-Tatché, Maria; Edelist, Cécile; Wardenaar, René; Guerche, Philippe; Hospital, Frédéric; Colot, Vincent; Jansen, Ritsert C; Johannes, Frank

2011-08-01

We extensively phenotyped 6000 Arabidopsis plants with experimentally perturbed DNA methylomes as well as a diverse panel of natural accessions in a common garden. We found that alterations in DNA methylation not only caused heritable phenotypic diversity but also produced heritability patterns closely resembling those of the natural accessions. Our findings indicate that epigenetically induced and naturally occurring variation in complex traits share part of their polygenic architecture and may offer complementary adaptation routes in ecological settings.

Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families.

PubMed

Gormley, Padhraig; Kurki, Mitja I; Hiekkala, Marjo Eveliina; Veerapen, Kumar; Häppölä, Paavo; Mitchell, Adele A; Lal, Dennis; Palta, Priit; Surakka, Ida; Kaunisto, Mari Anneli; Hämäläinen, Eija; Vepsäläinen, Salli; Havanka, Hannele; Harno, Hanna; Ilmavirta, Matti; Nissilä, Markku; Säkö, Erkki; Sumelahti, Marja-Liisa; Liukkonen, Jarmo; Sillanpää, Matti; Metsähonkala, Liisa; Koskinen, Seppo; Lehtimäki, Terho; Raitakari, Olli; Männikkö, Minna; Ran, Caroline; Belin, Andrea Carmine; Jousilahti, Pekka; Anttila, Verneri; Salomaa, Veikko; Artto, Ville; Färkkilä, Markus; Runz, Heiko; Daly, Mark J; Neale, Benjamin M; Ripatti, Samuli; Kallela, Mikko; Wessman, Maija; Palotie, Aarno

2018-05-16

Complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. The aggregation could be explained by rare, penetrant variants that segregate according to Mendelian inheritance or by the sufficient polygenic accumulation of common variants, each with an individually small effect, or a combination of the two hypotheses. In 8,319 individuals across 1,589 migraine families, we calculated migraine polygenic risk scores (PRS) and found a significantly higher common variant burden in familial cases (n = 5,317, OR = 1.76, 95% CI = 1.71-1.81, p = 1.7 × 10 -109 ) compared to population cases from the FINRISK cohort (n = 1,101, OR = 1.32, 95% CI = 1.25-1.38, p = 7.2 × 10 -17 ). The PRS explained 1.6% of the phenotypic variance in the population cases and 3.5% in the familial cases (including 2.9% for migraine without aura, 5.5% for migraine with typical aura, and 8.2% for hemiplegic migraine). The results demonstrate a significant contribution of common polygenic variation to the familial aggregation of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel.

PubMed

Noble, Luke M; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V; Teotónio, Henrique

2017-12-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans , the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. Copyright © 2017 by the Genetics Society of America.

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel

PubMed Central

Noble, Luke M.; Chelo, Ivo; Guzella, Thiago; Afonso, Bruno; Riccardi, David D.; Ammerman, Patrick; Dayarian, Adel; Carvalho, Sara; Crist, Anna; Pino-Querido, Ania; Shraiman, Boris; Rockman, Matthew V.; Teotónio, Henrique

2017-01-01

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140–190 generations, and inbreeding by selfing for 13–16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor (r2<10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms. PMID:29066469

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy.

PubMed

Byars, Sean G; Huang, Qin Qin; Gray, Lesley-Ann; Bakshi, Andrew; Ripatti, Samuli; Abraham, Gad; Stearns, Stephen C; Inouye, Michael

2017-06-01

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

Continuous and discontinuous phase transitions in the evolution of a polygenic trait under stabilizing selective pressure

NASA Astrophysics Data System (ADS)

Fierro, Annalisa; Cocozza, Sergio; Monticelli, Antonella; Scala, Giovanni; Miele, Gennaro

2017-06-01

The presence of phenomena analogous to phase transition in Statistical Mechanics has been suggested in the evolution of a polygenic trait under stabilizing selection, mutation and genetic drift. By using numerical simulations of a model system, we analyze the evolution of a population of N diploid hermaphrodites in random mating regime. The population evolves under the effect of drift, selective pressure in form of viability on an additive polygenic trait, and mutation. The analysis allows to determine a phase diagram in the plane of mutation rate and strength of selection. The involved pattern of phase transitions is characterized by a line of critical points for weak selective pressure (smaller than a threshold), whereas discontinuous phase transitions, characterized by metastable hysteresis, are observed for strong selective pressure. A finite-size scaling analysis suggests the analogy between our system and the mean-field Ising model for selective pressure approaching the threshold from weaker values. In this framework, the mutation rate, which allows the system to explore the accessible microscopic states, is the parameter controlling the transition from large heterozygosity ( disordered phase) to small heterozygosity ( ordered one).

Analysis of Polygenic Mutants Suggests a Role for Mediator in Regulating Transcriptional Activation Distance in Saccharomyces cerevisiae.

PubMed

Reavey, Caitlin T; Hickman, Mark J; Dobi, Krista C; Botstein, David; Winston, Fred

2015-10-01

Studies of natural populations of many organisms have shown that traits are often complex, caused by contributions of mutations in multiple genes. In contrast, genetic studies in the laboratory primarily focus on studying the phenotypes caused by mutations in a single gene. However, the single mutation approach may be limited with respect to the breadth and degree of new phenotypes that can be found. We have taken the approach of isolating complex, or polygenic mutants in the lab to study the regulation of transcriptional activation distance in yeast. While most aspects of eukaryotic transcription are conserved from yeast to human, transcriptional activation distance is not. In Saccharomyces cerevisiae, the upstream activating sequence (UAS) is generally found within 450 base pairs of the transcription start site (TSS) and when the UAS is moved too far away, activation no longer occurs. In contrast, metazoan enhancers can activate from as far as several hundred kilobases from the TSS. Previously, we identified single mutations that allow transcription activation to occur at a greater-than-normal distance from the GAL1 UAS. As the single mutant phenotypes were weak, we have now isolated polygenic mutants that possess strong long-distance phenotypes. By identification of the causative mutations we have accounted for most of the heritability of the phenotype in each strain and have provided evidence that the Mediator coactivator complex plays both positive and negative roles in the regulation of transcription activation distance. Copyright © 2015 by the Genetics Society of America.

The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI

PubMed Central

Whalley, H C; Papmeyer, M; Sprooten, E; Romaniuk, L; Blackwood, D H; Glahn, D C; Hall, J; Lawrie, S M; Sussmann, Je; McIntosh, A M

2012-01-01

Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to bipolar disorder (BD) where disease risk is determined by the summation of many alleles of small individual magnitude. Modelling polygenic risk scores may be a powerful way of identifying disrupted brain regions whose genetic architecture is related to that of BD. We determined the extent to which common genetic variation underlying risk to BD affected neural activation during an executive processing/language task in individuals at familial risk of BD and healthy controls. Polygenic risk scores were calculated for each individual based on GWAS data from the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) of over 16 000 subjects. The familial group had a significantly higher polygene score than the control group (P=0.04). There were no significant group by polygene interaction effects in terms of association with brain activation. However, we did find that an increasing polygenic risk allele load for BD was associated with increased activation in limbic regions previously implicated in BD, including the anterior cingulate cortex and amygdala, across both groups. The findings suggest that this novel polygenic approach to examine brain-imaging data may be a useful means of identifying genetically mediated traits mechanistically linked to the aetiology of BD. PMID:22760554

Bayesian segregation analysis of production traits in two strains of laying chickens.

PubMed

Szydłowski, M; Szwaczkowski, T

2001-02-01

A bayesian marker-free segregation analysis was applied to search for evidence of segregating genes affecting production traits in two strains of laying hens under long-term selection. The study used data from 6 generations of Leghorn (H77) and New Hampshire (N88) breeding nuclei. Estimation of marginal posterior means of variance components and parameters of a single autosomal locus was performed by use of the Gibbs sampler. The results showed evidence for a mixed major gene: -polygenic inheritance of BW and age at sexual maturity (ASM) in both strains. Single genes affecting BW and ASM explained one-third of the genetic variance. For ASM large overdominance effect at single locus was estimated. Initial egg production (IEP) and average egg weight (EW) showed a polygenic model of inheritance. The polygenic heritability estimates for BW, ASM, IEP, and EW were 0.32, 0.25, 0.23, and 0.08 in Strain H77 and 0.25, 0.24, 0.11, and 0.38 in Strain N88, respectively.

Artificial Selection Response due to Polygenic Adaptation from a Multilocus, Multiallelic Genetic Architecture.

PubMed

Zan, Yanjun; Sheng, Zheya; Lillie, Mette; Rönnegård, Lars; Honaker, Christa F; Siegel, Paul B; Carlborg, Örjan

2017-10-01

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Polygenic determinants in extremes of high-density lipoprotein cholesterol[S

PubMed Central

Dron, Jacqueline S.; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A.; Robinson, John F.; McIntyre, Adam D.; Ban, Matthew R.; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J.; Lettre, Guillaume; Tardif, Jean-Claude

2017-01-01

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. PMID:28870971

Polygenic determinants in extremes of high-density lipoprotein cholesterol.

PubMed

Dron, Jacqueline S; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A; Robinson, John F; McIntyre, Adam D; Ban, Matthew R; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A

2017-11-01

HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy

PubMed Central

Byars, Sean G.; Gray, Lesley-Ann; Ripatti, Samuli; Stearns, Stephen C.; Inouye, Michael

2017-01-01

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD. PMID:28640878

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Dissection of complex adult traits in a mouse synthetic population.

PubMed

Burke, David T; Kozloff, Kenneth M; Chen, Shu; West, Joshua L; Wilkowski, Jodi M; Goldstein, Steven A; Miller, Richard A; Galecki, Andrzej T

2012-08-01

Finding the causative genetic variations that underlie complex adult traits is a significant experimental challenge. The unbiased search strategy of genome-wide association (GWAS) has been used extensively in recent human population studies. These efforts, however, typically find only a minor fraction of the genetic loci that are predicted to affect variation. As an experimental model for the analysis of adult polygenic traits, we measured a mouse population for multiple phenotypes and conducted a genome-wide search for effector loci. Complex adult phenotypes, related to body size and bone structure, were measured as component phenotypes, and each subphenotype was associated with a genomic spectrum of candidate effector loci. The strategy successfully detected several loci for the phenotypes, at genome-wide significance, using a single, modest-sized population (N = 505). The effector loci each explain 2%-10% of the measured trait variation and, taken together, the loci can account for over 25% of a trait's total population variation. A replicate population (N = 378) was used to confirm initially observed loci for one trait (femur length), and, when the two groups were merged, the combined population demonstrated increased power to detect loci. In contrast to human population studies, our mouse genome-wide searches find loci that individually explain a larger fraction of the observed variation. Also, the additive effects of our detected mouse loci more closely match the predicted genetic component of variation. The genetic loci discovered are logical candidates for components of the genetic networks having evolutionary conservation with human biology.

Polygenic risk score and heritability estimates reveals a genetic relationship between ASD and OCD.

PubMed

Guo, W; Samuels, J F; Wang, Y; Cao, H; Ritter, M; Nestadt, P S; Krasnow, J; Greenberg, B D; Fyer, A J; McCracken, J T; Geller, D A; Murphy, D L; Knowles, J A; Grados, M A; Riddle, M A; Rasmussen, S A; McLaughlin, N C; Nurmi, E L; Askland, K D; Cullen, B A; Piacentini, J; Pauls, D L; Bienvenu, O J; Stewart, S E; Goes, F S; Maher, B; Pulver, A E; Valle, D; Mattheisen, M; Qian, J; Nestadt, G; Shugart, Y Y

2017-07-01

Obsessive-compulsive disorder (OCD) and Autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders that conceivably share genetic risk factors. However, the underlying genetic determinants remain largely unknown. In this work, the authors describe a combined genome-wide association study (GWAS) of ASD and OCD. The OCD dataset includes 2998 individuals in nuclear families. The ASD dataset includes 6898 individuals in case-parents trios. GWAS summary statistics were examined for potential enrichment of functional variants associated with gene expression levels in brain regions. The top ranked SNP is rs4785741 (chromosome 16) with P value=6.9×10 -7 in our re-analysis. Polygenic risk score analyses were conducted to investigate the genetic relationship within and across the two disorders. These analyses identified a significant polygenic component of ASD, predicting 0.11% of the phenotypic variance in an independent OCD data set. In addition, we examined the genomic architecture of ASD and OCD by estimating heritability on different chromosomes and different allele frequencies, analyzing genome-wide common variant data by using the Genome-wide Complex Trait Analysis (GCTA) program. The estimated global heritability of OCD is 0.427 (se=0.093) and 0.174 (se=0.053) for ASD in these imputed data. Published by Elsevier B.V.

Highly polygenic variation in environmental perception determines dauer larvae formation in growing populations of Caenorhabditis elegans.

PubMed

Green, James W M; Stastna, Jana J; Orbidans, Helen E; Harvey, Simon C

2014-01-01

Determining how complex traits are genetically controlled is a requirement if we are to predict how they evolve and how they might respond to selection. This requires understanding how distinct, and often more simple, life history traits interact and change in response to environmental conditions. In order to begin addressing such issues, we have been analyzing the formation of the developmentally arrested dauer larvae of Caenorhabditis elegans under different conditions. We find that 18 of 22 previously identified quantitative trait loci (QTLs) affecting dauer larvae formation in growing populations, assayed by determining the number of dauer larvae present at food patch exhaustion, can be recovered under various environmental conditions. We also show that food patch size affects both the ability to detect QTLs and estimates of effect size, and demonstrate that an allele of nath-10 affects dauer larvae formation in growing populations. To investigate the component traits that affect dauer larvae formation in growing populations we map, using the same introgression lines, QTLs that affect dauer larvae formation in response to defined amounts of pheromone. This identifies 36 QTLs, again demonstrating the highly polygenic nature of the genetic variation underlying dauer larvae formation. These data indicate that QTLs affecting the number of dauer larvae at food exhaustion in growing populations of C. elegans are highly reproducible, and that nearly all can be explained by variation affecting dauer larvae formation in response to defined amounts of pheromone. This suggests that most variation in dauer larvae formation in growing populations is a consequence of variation in the perception of the food and pheromone environment (i.e. chemosensory variation) and in the integration of these cues.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

PubMed

Snelling, W M; Cushman, R A; Keele, J W; Maltecca, C; Thomas, M G; Fortes, M R S; Reverter, A

2013-02-01

Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by functionally informed genomic predictions being more accurate than naive whole-genome predictions of beef tenderness, coupling evidence from livestock genotypes, phenotypes, gene expression, and genomic variants with existing knowledge of gene functions and interactions may provide greater insight into the genes and genomic mechanisms affecting polygenic traits and facilitate functional genomic selection for economically important traits.

SNP by SNP by environment interaction network of alcoholism.

PubMed

Zollanvari, Amin; Alterovitz, Gil

2017-03-14

Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

Pleiotropic Models of Polygenic Variation, Stabilizing Selection, and Epistasis

PubMed Central

Gavrilets, S.; de-Jong, G.

1993-01-01

We show that in polymorphic populations many polygenic traits pleiotropically related to fitness are expected to be under apparent ``stabilizing selection'' independently of the real selection acting on the population. This occurs, for example, if the genetic system is at a stable polymorphic equilibrium determined by selection and the nonadditive contributions of the loci to the trait value either are absent, or are random and independent of those to fitness. Stabilizing selection is also observed if the polygenic system is at an equilibrium determined by a balance between selection and mutation (or migration) when both additive and nonadditive contributions of the loci to the trait value are random and independent of those to fitness. We also compare different viability models that can maintain genetic variability at many loci with respect to their ability to account for the strong stabilizing selection on an additive trait. Let V(m) be the genetic variance supplied by mutation (or migration) each generation, V(g) be the genotypic variance maintained in the population, and n be the number of the loci influencing fitness. We demonstrate that in mutation (migration)-selection balance models the strength of apparent stabilizing selection is order V(m)/V(g). In the overdominant model and in the symmetric viability model the strength of apparent stabilizing selection is approximately 1/(2n) that of total selection on the whole phenotype. We show that a selection system that involves pairwise additive by additive epistasis in maintaining variability can lead to a lower genetic load and genetic variance in fitness (approximately 1/(2n) times) than an equivalent selection system that involves overdominance. We show that, in the epistatic model, the apparent stabilizing selection on an additive trait can be as strong as the total selection on the whole phenotype. PMID:8325491

Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

PubMed

Franssen, S U; Kofler, R; Schlötterer, C

2017-01-01

The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

Multiethnic GWAS Reveals Polygenic Architecture of Earlobe Attachment.

PubMed

Shaffer, John R; Li, Jinxi; Lee, Myoung Keun; Roosenboom, Jasmien; Orlova, Ekaterina; Adhikari, Kaustabh; Gallo, Carla; Poletti, Giovanni; Schuler-Faccini, Lavinia; Bortolini, Maria-Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; González-José, Rolando; Pfeffer, Paige E; Wollenschlaeger, Christopher A; Hecht, Jacqueline T; Wehby, George L; Moreno, Lina M; Ding, Anan; Jin, Li; Yang, Yajun; Carlson, Jenna C; Leslie, Elizabeth J; Feingold, Eleanor; Marazita, Mary L; Hinds, David A; Cox, Timothy C; Wang, Sijia; Ruiz-Linares, Andrés; Weinberg, Seth M

2017-12-07

The genetic basis of earlobe attachment has been a matter of debate since the early 20 th century, such that geneticists argue both for and against polygenic inheritance. Recent genetic studies have identified a few loci associated with the trait, but large-scale analyses are still lacking. Here, we performed a genome-wide association study of lobe attachment in a multiethnic sample of 74,660 individuals from four cohorts (three with the trait scored by an expert rater and one with the trait self-reported). Meta-analysis of the three expert-rater-scored cohorts revealed six associated loci harboring numerous candidate genes, including EDAR, SP5, MRPS22, ADGRG6 (GPR126), KIAA1217, and PAX9. The large self-reported 23andMe cohort recapitulated each of these six loci. Moreover, meta-analysis across all four cohorts revealed a total of 49 significant (p < 5 × 10 -8 ) loci. Annotation and enrichment analyses of these 49 loci showed strong evidence of genes involved in ear development and syndromes with auricular phenotypes. RNA sequencing data from both human fetal ear and mouse second branchial arch tissue confirmed that genes located among associated loci showed evidence of expression. These results provide strong evidence for the polygenic nature of earlobe attachment and offer insights into the biological basis of normal and abnormal ear development. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

pKWmEB: integration of Kruskal-Wallis test with empirical Bayes under polygenic background control for multi-locus genome-wide association study.

PubMed

Ren, Wen-Long; Wen, Yang-Jun; Dunwell, Jim M; Zhang, Yuan-Ming

2018-03-01

Although nonparametric methods in genome-wide association studies (GWAS) are robust in quantitative trait nucleotide (QTN) detection, the absence of polygenic background control in single-marker association in genome-wide scans results in a high false positive rate. To overcome this issue, we proposed an integrated nonparametric method for multi-locus GWAS. First, a new model transformation was used to whiten the covariance matrix of polygenic matrix K and environmental noise. Using the transferred model, Kruskal-Wallis test along with least angle regression was then used to select all the markers that were potentially associated with the trait. Finally, all the selected markers were placed into multi-locus model, these effects were estimated by empirical Bayes, and all the nonzero effects were further identified by a likelihood ratio test for true QTN detection. This method, named pKWmEB, was validated by a series of Monte Carlo simulation studies. As a result, pKWmEB effectively controlled false positive rate, although a less stringent significance criterion was adopted. More importantly, pKWmEB retained the high power of Kruskal-Wallis test, and provided QTN effect estimates. To further validate pKWmEB, we re-analyzed four flowering time related traits in Arabidopsis thaliana, and detected some previously reported genes that were not identified by the other methods.

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.

PubMed

Hagenaars, S P; Harris, S E; Davies, G; Hill, W D; Liewald, D C M; Ritchie, S J; Marioni, R E; Fawns-Ritchie, C; Cullen, B; Malik, R; Worrall, B B; Sudlow, C L M; Wardlaw, J M; Gallacher, J; Pell, J; McIntosh, A M; Smith, D J; Gale, C R; Deary, I J

2016-11-01

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular-metabolic, neuropsychiatric, physiological-anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples.

Partitioning heritability by functional annotation using genome-wide association summary statistics.

PubMed

Finucane, Hilary K; Bulik-Sullivan, Brendan; Gusev, Alexander; Trynka, Gosia; Reshef, Yakir; Loh, Po-Ru; Anttila, Verneri; Xu, Han; Zang, Chongzhi; Farh, Kyle; Ripke, Stephan; Day, Felix R; Purcell, Shaun; Stahl, Eli; Lindstrom, Sara; Perry, John R B; Okada, Yukinori; Raychaudhuri, Soumya; Daly, Mark J; Patterson, Nick; Neale, Benjamin M; Price, Alkes L

2015-11-01

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Genotyping by sequencing for SNP-based linkage analysis and identification of QTLs linked to fruit quality traits in Japanese plum (Prunus salicina Lindl.)

USDA-ARS?s Scientific Manuscript database

Marker-assisted selection (MAS) in stone fruit (Prunus species) breeding is currently difficult to achieve due to the polygenic nature of themost relevant agronomic traits linked to fruit quality. Genotyping by sequencing (GBS), however, provides a large quantity of useful data suitable for finemapp...

Alternative models in genetic analyses of carcass traits measured by ultrasonography in Guzerá cattle: A Bayesian approach

USDA-ARS?s Scientific Manuscript database

The objective was to study alternative models for genetic analyses of carcass traits assessed by ultrasonography in Guzerá cattle. Data from 947 measurements (655 animals) of Rib-eye area (REA), rump fat thickness (RFT) and backfat thickness (BFT) were used. Finite polygenic models (FPM), infinitesi...

Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment

PubMed Central

Le Hellard, Stéphanie; Wang, Yunpeng; Witoelar, Aree; Zuber, Verena; Bettella, Francesco; Hugdahl, Kenneth; Espeseth, Thomas; Steen, Vidar M.; Melle, Ingrid; Desikan, Rahul; Schork, Andrew J.; Thompson, Wesley K.; Dale, Anders M.; Djurovic, Srdjan

2017-01-01

Abstract There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a “proxy phenotype” for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion (“College,” n = 95 427), and years of education (“EduYears,” n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ. PMID:27338279

Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment.

PubMed

Le Hellard, Stéphanie; Wang, Yunpeng; Witoelar, Aree; Zuber, Verena; Bettella, Francesco; Hugdahl, Kenneth; Espeseth, Thomas; Steen, Vidar M; Melle, Ingrid; Desikan, Rahul; Schork, Andrew J; Thompson, Wesley K; Dale, Anders M; Djurovic, Srdjan; Andreassen, Ole A

2017-05-01

There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder.

PubMed

Mullins, N; Power, R A; Fisher, H L; Hanscombe, K B; Euesden, J; Iniesta, R; Levinson, D F; Weissman, M M; Potash, J B; Shi, J; Uher, R; Cohen-Woods, S; Rivera, M; Jones, L; Jones, I; Craddock, N; Owen, M J; Korszun, A; Craig, I W; Farmer, A E; McGuffin, P; Breen, G; Lewis, C M

2016-03-01

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Evidence of Common Genetic Overlap Between Schizophrenia and Cognition

PubMed Central

Hubbard, Leon; Tansey, Katherine E.; Rai, Dheeraj; Jones, Peter; Ripke, Stephan; Chambert, Kimberly D.; Moran, Jennifer L.; McCarroll, Steven A.; Linden, David E. J.; Owen, Michael J.; O’Donovan, Michael C.; Walters, James T. R.; Zammit, Stanley

2016-01-01

Cognitive impairment is a core feature of schizophrenia but there is limited understanding of the genetic relationship between cognition in the general population and schizophrenia. We examine how common variants associated with schizophrenia en masse contribute to childhood cognitive ability in a population-based sample, and the extent to which common genetic variants associated with childhood cognition explain variation in schizophrenia. Schizophrenia polygenic risk scores were derived from the Psychiatric Genomics Consortium (n = 69 516) and tested for association with IQ, attention, processing speed, working memory, problem solving, and social cognition in over 5000 children aged 8 from the Avon Longitudinal Study of Parents and Children birth cohort. Polygenic scores for these cognitive domains were tested for association with schizophrenia in a large UK schizophrenia sample (n = 11 853). Bivariate genome-wide complex trait analysis (GCTA) estimated the amount of shared genetic factors between schizophrenia and cognitive domains. Schizophrenia polygenic risk score was associated with lower performance IQ (P = .001) and lower full IQ (P = .013). Polygenic score for performance IQ was associated with increased risk for schizophrenia (P = 3.56E-04). Bivariate GCTA revealed moderate genetic correlation between schizophrenia and both performance IQ (r G = −.379, P = 6.62E-05) and full IQ (r G = −.202, P = 5.00E-03), with approximately 14% of the genetic component of schizophrenia shared with that for performance IQ. Our results support the presence of shared common genetic factors between schizophrenia and childhood cognitive ability. We observe a genetic relationship between schizophrenia and performance IQ but not verbal IQ or other cognitive variables, which may have implications for studies utilizing cognitive endophenotypes for psychosis. PMID:26678674

Evidence of Common Genetic Overlap Between Schizophrenia and Cognition.

PubMed

Hubbard, Leon; Tansey, Katherine E; Rai, Dheeraj; Jones, Peter; Ripke, Stephan; Chambert, Kimberly D; Moran, Jennifer L; McCarroll, Steven A; Linden, David E J; Owen, Michael J; O'Donovan, Michael C; Walters, James T R; Zammit, Stanley

2016-05-01

Cognitive impairment is a core feature of schizophrenia but there is limited understanding of the genetic relationship between cognition in the general population and schizophrenia. We examine how common variants associated with schizophreniaen massecontribute to childhood cognitive ability in a population-based sample, and the extent to which common genetic variants associated with childhood cognition explain variation in schizophrenia. Schizophrenia polygenic risk scores were derived from the Psychiatric Genomics Consortium (n= 69 516) and tested for association with IQ, attention, processing speed, working memory, problem solving, and social cognition in over 5000 children aged 8 from the Avon Longitudinal Study of Parents and Children birth cohort. Polygenic scores for these cognitive domains were tested for association with schizophrenia in a large UK schizophrenia sample (n= 11 853). Bivariate genome-wide complex trait analysis (GCTA) estimated the amount of shared genetic factors between schizophrenia and cognitive domains. Schizophrenia polygenic risk score was associated with lower performance IQ (P= .001) and lower full IQ (P= .013). Polygenic score for performance IQ was associated with increased risk for schizophrenia (P= 3.56E-04). Bivariate GCTA revealed moderate genetic correlation between schizophrenia and both performance IQ (rG= -.379,P= 6.62E-05) and full IQ (rG= -.202,P= 5.00E-03), with approximately 14% of the genetic component of schizophrenia shared with that for performance IQ. Our results support the presence of shared common genetic factors between schizophrenia and childhood cognitive ability. We observe a genetic relationship between schizophrenia and performance IQ but not verbal IQ or other cognitive variables, which may have implications for studies utilizing cognitive endophenotypes for psychosis. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Single Nucleotide Polymorphisms Associated with Reading Ability Show Connection to Socio-Economic Outcomes.

PubMed

Luciano, Michelle; Hagenaars, Saskia P; Cox, Simon R; Hill, William David; Davies, Gail; Harris, Sarah E; Deary, Ian J; Evans, David M; Martin, Nicholas G; Wright, Margaret J; Bates, Timothy C

2017-09-01

Impairments in reading and in language have negative consequences on life outcomes, but it is not known to what extent genetic effects influence this association. We constructed polygenic scores for difficulties with language and learning to read from genome-wide data in ~6,600 children, adolescents and young adults, and tested their association with health, socioeconomic outcomes and brain structure measures collected in adults (maximal N = 111,749). Polygenic risk of reading difficulties was associated with reduced income, educational attainment, self-rated health and verbal-numerical reasoning (p < 0.00055). Polygenic risk of language difficulties predicted income (p = 0.0005). The small effect sizes ranged 0.01-0.03 of a standard deviation, but these will increase as genetic studies for reading ability get larger. Polygenic scores for childhood cognitive ability and educational attainment were correlated with polygenic scores of reading and language (up to 0.09 and 0.05, respectively). But when they were included in the prediction models, the observed associations between polygenic reading and adult outcomes mostly remained. This suggests that the pathway from reading ability to social outcomes is not only via associated polygenic loads for general cognitive function and educational attainment. The presence of non-overlapping genetic effect is indicated by the genetic correlations of around 0.40 (childhood intelligence) and 0.70 (educational attainment) with reading ability. Mendelian randomization approaches will be important to dissociate any causal and moderating effects of reading and related traits on social outcomes.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

Nashef, Aysar; Agbaria, Mahmoud; Shusterman, Ariel; Lorè, Nicola Ivan; Bragonzi, Alessandra; Wiess, Ervin; Houri-Haddad, Yael; Iraqi, Fuad A

2017-01-01

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

PubMed

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia

PubMed Central

Hagenaars, S P; Harris, S E; Davies, G; Hill, W D; Liewald, D C M; Ritchie, S J; Marioni, R E; Fawns-Ritchie, C; Cullen, B; Malik, R; Worrall, B B; Sudlow, C L M; Wardlaw, J M; Gallacher, J; Pell, J; McIntosh, A M; Smith, D J; Gale, C R; Deary, I J

2016-01-01

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular–metabolic, neuropsychiatric, physiological–anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples. PMID:26809841

Collective interaction effects associated with mammalian behavioral traits reveal genetic factors connecting fear and hemostasis.

PubMed

Woo, Hyung Jun; Reifman, Jaques

2018-06-05

Investigation of the genetic architectures that influence the behavioral traits of animals can provide important insights into human neuropsychiatric phenotypes. These traits, however, are often highly polygenic, with individual loci contributing only small effects to the overall association. The polygenicity makes it challenging to explain, for example, the widely observed comorbidity between stress and cardiac disease. We present an algorithm for inferring the collective association of a large number of interacting gene variants with a quantitative trait. Using simulated data, we demonstrate that by taking into account the non-uniform distribution of genotypes within a cohort, we can achieve greater power than regression-based methods for high-dimensional inference. We analyzed genome-wide data sets of outbred mice and pet dogs, and found neurobiological pathways whose associations with behavioral traits arose primarily from interaction effects: γ-carboxylated coagulation factors and downstream neuronal signaling were highly associated with conditioned fear, consistent with our previous finding in human post-traumatic stress disorder (PTSD) data. Prepulse inhibition in mice was associated with serotonin transporter and platelet homeostasis, and noise-induced fear in dogs with hemostasis. Our findings suggest a novel explanation for the observed comorbidity between PTSD/anxiety and cardiovascular diseases: key coagulation factors modulating hemostasis also regulate synaptic plasticity affecting the learning and extinction of fear.

Genome editing as a tool to achieve the crop ideotype and de novo domestication of wild relatives: Case study in tomato.

PubMed

Zsögön, Agustin; Cermak, Tomas; Voytas, Dan; Peres, Lázaro Eustáquio Pereira

2017-03-01

The ideotype is a theoretical model of an archetypal cultivated plant. Recent progress in genome editing is aiding the pursuit of this ideal in crop breeding. Breeding is relatively straightforward when the traits in question are monogenic in nature and show Mendelian inheritance. Conversely, traits with a diffuse, polygenic basis such as abiotic stress resistance are more difficult to harness. In recent years, many genes have been identified that are important for plant domestication and act by increasing yield, grain or fruit size or altering plant architecture. Here, we propose that (a) key monogenic traits whose physiology has been unveiled can be molecularly tailored to achieve the ideotype; and (b) wild relatives of crops harboring polygenic stress resistance genes or other traits of interest could be de novo domesticated by manipulating monogenic yield-related traits through state-of-the-art gene editing techniques. An overview of the genomic and physiological challenges in the world's main staple crops is provided. We focus on tomato and its wild Solanum (section Lycopersicon) relatives as a suitable model for molecular design in the pursuit of the ideotype for elite cultivars and to test de novo domestication of wild relatives. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Polygenic Versus Monogenic Causes of Hypercholesterolemia Ascertained Clinically.

PubMed

Wang, Jian; Dron, Jacqueline S; Ban, Matthew R; Robinson, John F; McIntyre, Adam D; Alazzam, Maher; Zhao, Pei Jun; Dilliott, Allison A; Cao, Henian; Huff, Murray W; Rhainds, David; Low-Kam, Cécile; Dubé, Marie-Pierre; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A

2016-12-01

Next-generation sequencing technology is transforming our understanding of heterozygous familial hypercholesterolemia, including revision of prevalence estimates and attribution of polygenic effects. Here, we examined the contributions of monogenic and polygenic factors in patients with severe hypercholesterolemia referred to a specialty clinic. We applied targeted next-generation sequencing with custom annotation, coupled with evaluation of large-scale copy number variation and polygenic scores for raised low-density lipoprotein cholesterol in a cohort of 313 individuals with severe hypercholesterolemia, defined as low-density lipoprotein cholesterol >5.0 mmol/L (>194 mg/dL). We found that (1) monogenic familial hypercholesterolemia-causing mutations detected by targeted next-generation sequencing were present in 47.3% of individuals; (2) the percentage of individuals with monogenic mutations increased to 53.7% when copy number variations were included; (3) the percentage further increased to 67.1% when individuals with extreme polygenic scores were included; and (4) the percentage of individuals with an identified genetic component increased from 57.0% to 92.0% as low-density lipoprotein cholesterol level increased from 5.0 to >8.0 mmol/L (194 to >310 mg/dL). In a clinically ascertained sample with severe hypercholesterolemia, we found that most patients had a discrete genetic basis detected using a comprehensive screening approach that includes targeted next-generation sequencing, an assay for copy number variations, and polygenic trait scores. © 2016 American Heart Association, Inc.

Comparative Polygenic Analysis of Maximal Ethanol Accumulation Capacity and Tolerance to High Ethanol Levels of Cell Proliferation in Yeast

PubMed Central

Pais, Thiago M.; Foulquié-Moreno, María R.; Hubmann, Georg; Duitama, Jorge; Swinnen, Steve; Goovaerts, Annelies; Yang, Yudi; Dumortier, Françoise; Thevelein, Johan M.

2013-01-01

The yeast Saccharomyces cerevisiae is able to accumulate ≥17% ethanol (v/v) by fermentation in the absence of cell proliferation. The genetic basis of this unique capacity is unknown. Up to now, all research has focused on tolerance of yeast cell proliferation to high ethanol levels. Comparison of maximal ethanol accumulation capacity and ethanol tolerance of cell proliferation in 68 yeast strains showed a poor correlation, but higher ethanol tolerance of cell proliferation clearly increased the likelihood of superior maximal ethanol accumulation capacity. We have applied pooled-segregant whole-genome sequence analysis to identify the polygenic basis of these two complex traits using segregants from a cross of a haploid derivative of the sake strain CBS1585 and the lab strain BY. From a total of 301 segregants, 22 superior segregants accumulating ≥17% ethanol in small-scale fermentations and 32 superior segregants growing in the presence of 18% ethanol, were separately pooled and sequenced. Plotting SNP variant frequency against chromosomal position revealed eleven and eight Quantitative Trait Loci (QTLs) for the two traits, respectively, and showed that the genetic basis of the two traits is partially different. Fine-mapping and Reciprocal Hemizygosity Analysis identified ADE1, URA3, and KIN3, encoding a protein kinase involved in DNA damage repair, as specific causative genes for maximal ethanol accumulation capacity. These genes, as well as the previously identified MKT1 gene, were not linked in this genetic background to tolerance of cell proliferation to high ethanol levels. The superior KIN3 allele contained two SNPs, which are absent in all yeast strains sequenced up to now. This work provides the first insight in the genetic basis of maximal ethanol accumulation capacity in yeast and reveals for the first time the importance of DNA damage repair in yeast ethanol tolerance. PMID:23754966

Posttraumatic stress disorder symptom severity is associated with reduced default mode network connectivity in individuals with elevated genetic risk for psychopathology.

PubMed

Miller, Danielle R; Logue, Mark W; Wolf, Erika J; Maniates, Hannah; Robinson, Meghan E; Hayes, Jasmeet P; Stone, Annjanette; Schichman, Steven; McGlinchey, Regina E; Milberg, William P; Miller, Mark W

2017-07-01

Accumulating evidence suggests that posttraumatic stress disorder (PTSD) is associated with disrupted default mode network (DMN) connectivity, but findings across studies have not been uniform. Individual differences in relevant genes may account for some of the reported variability in the relationship between DMN connectivity and PTSD. In this study, we investigated this possibility using genome-wide association study (GWAS) derived polygenic risk scores (PRSs) for relevant psychiatric traits. We hypothesized that the association between PTSD and DMN connectivity would be moderated by genetic risk for one or more psychiatric traits such that individuals with elevated polygenic risk for psychopathology and severe PTSD would exhibit disrupted DMN connectivity. Participants were 156 white, non-Hispanic veterans of the wars in Iraq and Afghanistan who were genotyped and underwent resting state functional magnetic resonance imaging and clinical assessment. PRSs for neuroticism, anxiety, major depressive disorder, and cross-disorder risk (based on five psychiatric disorders) were calculated using summary statistics from published large-scale consortia-based GWASs. Cross-disorder polygenic risk influenced the relationship between DMN connectivity and PTSD symptom severity such that individuals at greater genetic risk showed a significant negative association between PTSD symptom severity and connectivity between the posterior cingulate cortex and right middle temporal gyrus. Polygenic risk for neuroticism, anxiety, and major depressive disorder did not influence DMN connectivity directly or through an interaction with PTSD. Findings illustrate the potential power of genome-wide PRSs to advance understanding of the relationship between PTSD and DMN connectivity, a putative neural endophenotype of the disorder. © 2017 Wiley Periodicals, Inc.

Genomic estimation of complex traits reveals ancient maize adaptation to temperate North America.

PubMed

Swarts, Kelly; Gutaker, Rafal M; Benz, Bruce; Blake, Michael; Bukowski, Robert; Holland, James; Kruse-Peeples, Melissa; Lepak, Nicholas; Prim, Lynda; Romay, M Cinta; Ross-Ibarra, Jeffrey; Sanchez-Gonzalez, Jose de Jesus; Schmidt, Chris; Schuenemann, Verena J; Krause, Johannes; Matson, R G; Weigel, Detlef; Buckler, Edward S; Burbano, Hernán A

2017-08-04

By 4000 years ago, people had introduced maize to the southwestern United States; full agriculture was established quickly in the lowland deserts but delayed in the temperate highlands for 2000 years. We test if the earliest upland maize was adapted for early flowering, a characteristic of modern temperate maize. We sequenced fifteen 1900-year-old maize cobs from Turkey Pen Shelter in the temperate Southwest. Indirectly validated genomic models predicted that Turkey Pen maize was marginally adapted with respect to flowering, as well as short, tillering, and segregating for yellow kernel color. Temperate adaptation drove modern population differentiation and was selected in situ from ancient standing variation. Validated prediction of polygenic traits improves our understanding of ancient phenotypes and the dynamics of environmental adaptation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Single-Nucleotide-Polymorphism-Based Association Mapping of Dog Stereotypes

PubMed Central

Jones, Paul; Chase, Kevin; Martin, Alan; Davern, Pluis; Ostrander, Elaine A.; Lark, Karl G.

2008-01-01

Phenotypic stereotypes are traits, often polygenic, that have been stringently selected to conform to specific criteria. In dogs, Canis familiaris, stereotypes result from breed standards set for conformation, performance (behaviors), etc. As a consequence, phenotypic values measured on a few individuals are representative of the breed stereotype. We used DNA samples isolated from 148 dog breeds to associate SNP markers with breed stereotypes. Using size as a trait to test the method, we identified six significant quantitative trait loci (QTL) on five chromosomes that include candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Less well-documented data for behavioral stereotypes tentatively identified loci for herding, pointing, boldness, and trainability. Four significant loci were identified for longevity, a breed characteristic not under direct selection, but inversely correlated with breed size. The strengths and limitations of the approach are discussed as well as its potential to identify loci regulating the within-breed incidence of specific polygenic diseases. PMID:18505865

Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder: A Genome-Wide Association Study.

PubMed

Amare, Azmeraw T; Schubert, Klaus Oliver; Hou, Liping; Clark, Scott R; Papiol, Sergi; Heilbronner, Urs; Degenhardt, Franziska; Tekola-Ayele, Fasil; Hsu, Yi-Hsiang; Shekhtman, Tatyana; Adli, Mazda; Akula, Nirmala; Akiyama, Kazufumi; Ardau, Raffaella; Arias, Bárbara; Aubry, Jean-Michel; Backlund, Lena; Bhattacharjee, Abesh Kumar; Bellivier, Frank; Benabarre, Antonio; Bengesser, Susanne; Biernacka, Joanna M; Birner, Armin; Brichant-Petitjean, Clara; Cervantes, Pablo; Chen, Hsi-Chung; Chillotti, Caterina; Cichon, Sven; Cruceanu, Cristiana; Czerski, Piotr M; Dalkner, Nina; Dayer, Alexandre; Del Zompo, Maria; DePaulo, J Raymond; Étain, Bruno; Falkai, Peter; Forstner, Andreas J; Frisen, Louise; Frye, Mark A; Fullerton, Janice M; Gard, Sébastien; Garnham, Julie S; Goes, Fernando S; Grigoroiu-Serbanescu, Maria; Grof, Paul; Hashimoto, Ryota; Hauser, Joanna; Herms, Stefan; Hoffmann, Per; Hofmann, Andrea; Jamain, Stephane; Jiménez, Esther; Kahn, Jean-Pierre; Kassem, Layla; Kuo, Po-Hsiu; Kato, Tadafumi; Kelsoe, John; Kittel-Schneider, Sarah; Kliwicki, Sebastian; König, Barbara; Kusumi, Ichiro; Laje, Gonzalo; Landén, Mikael; Lavebratt, Catharina; Leboyer, Marion; Leckband, Susan G; Tortorella, Alfonso; Manchia, Mirko; Martinsson, Lina; McCarthy, Michael J; McElroy, Susan; Colom, Francesc; Mitjans, Marina; Mondimore, Francis M; Monteleone, Palmiero; Nievergelt, Caroline M; Nöthen, Markus M; Novák, Tomas; O'Donovan, Claire; Ozaki, Norio; Ösby, Urban; Pfennig, Andrea; Potash, James B; Reif, Andreas; Reininghaus, Eva; Rouleau, Guy A; Rybakowski, Janusz K; Schalling, Martin; Schofield, Peter R; Schweizer, Barbara W; Severino, Giovanni; Shilling, Paul D; Shimoda, Katzutaka; Simhandl, Christian; Slaney, Claire M; Squassina, Alessio; Stamm, Thomas; Stopkova, Pavla; Maj, Mario; Turecki, Gustavo; Vieta, Eduard; Volkert, Julia; Witt, Stephanie; Wright, Adam; Zandi, Peter P; Mitchell, Philip B; Bauer, Michael; Alda, Martin; Rietschel, Marcella; McMahon, Francis J; Schulze, Thomas G; Baune, Bernhard T

2018-01-01

Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 × 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines. This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

Genetics of canid skeletal variation: Size and shape of the pelvis

PubMed Central

Carrier, David R.; Chase, Kevin; Lark, Karl G.

2005-01-01

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the “X.” A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed. PMID:16339381

Genetics of canid skeletal variation: size and shape of the pelvis.

PubMed

Carrier, David R; Chase, Kevin; Lark, Karl G

2005-12-01

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the "X." A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed.

Technical note: Equivalent genomic models with a residual polygenic effect.

PubMed

Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R

2016-03-01

Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prefrontal gray matter volume mediates genetic risks for obesity.

PubMed

Opel, N; Redlich, R; Kaehler, C; Grotegerd, D; Dohm, K; Heindel, W; Kugel, H; Thalamuthu, A; Koutsouleris, N; Arolt, V; Teuber, A; Wersching, H; Baune, B T; Berger, K; Dannlowski, U

2017-05-01

Genetic and neuroimaging research has identified neurobiological correlates of obesity. However, evidence for an integrated model of genetic risk and brain structural alterations in the pathophysiology of obesity is still absent. Here we investigated the relationship between polygenic risk for obesity, gray matter structure and body mass index (BMI) by the use of univariate and multivariate analyses in two large, independent cohorts (n=330 and n=347). Higher BMI and higher polygenic risk for obesity were significantly associated with medial prefrontal gray matter decrease, and prefrontal gray matter was further shown to significantly mediate the effect of polygenic risk for obesity on BMI in both samples. Building on this, the successful individualized prediction of BMI by means of multivariate pattern classification algorithms trained on whole-brain imaging data and external validations in the second cohort points to potential clinical applications of this imaging trait marker.

Integrating Genetic and Functional Genomic Data to Elucidate Common Disease Tra

NASA Astrophysics Data System (ADS)

Schadt, Eric

2005-03-01

The reconstruction of genetic networks in mammalian systems is one of the primary goals in biological research, especially as such reconstructions relate to elucidating not only common, polygenic human diseases, but living systems more generally. Here I present a statistical procedure for inferring causal relationships between gene expression traits and more classic clinical traits, including complex disease traits. This procedure has been generalized to the gene network reconstruction problem, where naturally occurring genetic variations in segregating mouse populations are used as a source of perturbations to elucidate tissue-specific gene networks. Differences in the extent of genetic control between genders and among four different tissues are highlighted. I also demonstrate that the networks derived from expression data in segregating mouse populations using the novel network reconstruction algorithm are able to capture causal associations between genes that result in increased predictive power, compared to more classically reconstructed networks derived from the same data. This approach to causal inference in large segregating mouse populations over multiple tissues not only elucidates fundamental aspects of transcriptional control, it also allows for the objective identification of key drivers of common human diseases.

Genetic approaches in comparative and evolutionary physiology

PubMed Central

Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

Genetic approaches in comparative and evolutionary physiology.

PubMed

Storz, Jay F; Bridgham, Jamie T; Kelly, Scott A; Garland, Theodore

2015-08-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. Copyright © 2015 the American Physiological Society.

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

Feed efficiency and the microbiota of the alimentary tract

USDA-ARS?s Scientific Manuscript database

There is considerable variation in the efficiency that cattle convert feed for maintenance and product (body weight gain, milk, and conceptus). Both intake and gain are polygenic traits and to better understand factors that contribute to variation in feed efficiency more defined phenotypes are need...

[Progress in genetic research of human height].

PubMed

Chen, Kaixu; Wang, Weilan; Zhang, Fuchun; Zheng, Xiufen

2015-08-01

It is well known that both environmental and genetic factors contribute to adult height variation in general population. However, heritability studies have shown that the variation in height is more affected by genetic factors. Height is a typical polygenic trait which has been studied by traditional linkage analysis and association analysis to identify common DNA sequence variation associated with height, but progress has been slow. More recently, with the development of genotyping and DNA sequencing technologies, tremendous achievements have been made in genetic research of human height. Hundreds of single nucleotide polymorphisms (SNPs) associated with human height have been identified and validated with the application of genome-wide association studies (GWAS) methodology, which deepens our understanding of the genetics of human growth and development and also provides theoretic basis and reference for studying other complex human traits. In this review, we summarize recent progress in genetic research of human height and discuss problems and prospects in this research area which may provide some insights into future genetic studies of human height.

Genome-wide QTL mapping of saltwater tolerance in sibling species of Anopheles (malaria vector) mosquitoes

PubMed Central

Smith, H A; White, B J; Kundert, P; Cheng, C; Romero-Severson, J; Andolfatto, P; Besansky, N J

2015-01-01

Although freshwater (FW) is the ancestral habitat for larval mosquitoes, multiple species independently evolved the ability to survive in saltwater (SW). Here, we use quantitative trait locus (QTL) mapping to investigate the genetic architecture of osmoregulation in Anopheles mosquitoes, vectors of human malaria. We analyzed 1134 backcross progeny from a cross between the obligate FW species An. coluzzii, and its closely related euryhaline sibling species An. merus. Tests of 2387 markers with Bayesian interval mapping and machine learning (random forests) yielded six genomic regions associated with SW tolerance. Overlap in QTL regions from both approaches enhances confidence in QTL identification. Evidence exists for synergistic as well as disruptive epistasis among loci. Intriguingly, one QTL region containing ion transporters spans the 2Rop chromosomal inversion that distinguishes these species. Rather than a simple trait controlled by one or a few loci, our data are most consistent with a complex, polygenic mode of inheritance. PMID:25920668

Contribution of Large Region Joint Associations to Complex Traits Genetics

PubMed Central

Paré, Guillaume; Asma, Senay; Deng, Wei Q.

2015-01-01

A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs. PMID:25856144

Using genomics to characterize evolutionary potential for conservation of wild populations

PubMed Central

Harrisson, Katherine A; Pavlova, Alexandra; Telonis-Scott, Marina; Sunnucks, Paul

2014-01-01

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework. PMID:25553064

The genetic architecture of economic and political preferences

PubMed Central

Benjamin, Daniel J.; Cesarini, David; van der Loos, Matthijs J. H. M.; Dawes, Christopher T.; Koellinger, Philipp D.; Magnusson, Patrik K. E.; Chabris, Christopher F.; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M.

2012-01-01

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic–based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs. PMID:22566634

The genetic architecture of economic and political preferences.

PubMed

Benjamin, Daniel J; Cesarini, David; van der Loos, Matthijs J H M; Dawes, Christopher T; Koellinger, Philipp D; Magnusson, Patrik K E; Chabris, Christopher F; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M

2012-05-22

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.

Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

PubMed Central

Medland, Sarah E; Loesch, Danuta Z; Mdzewski, Bogdan; Zhu, Gu; Montgomery, Grant W; Martin, Nicholas G

2007-01-01

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. PMID:17907812

Polygenic overlap between kidney function and large artery atherosclerotic stroke

PubMed Central

Holliday, Elizabeth G.; Traylor, Matthew; Malik, Rainer; Bevan, Stephen; Maguire, Jane; Koblar, Simon A.; Sturm, Jonathan; Hankey, Graeme J.; Oldmeadow, Christopher; McEvoy, Mark; Sudlow, Cathie; Rothwell, Peter M.; Coresh, Josef; Hamet, Pavel; Tremblay, Johanne; Turner, Stephen T.; de Andrade, Mariza; Rao, Madhumathi; Schmidt, Reinhold; Crick, Peter A.; Robino, Antonietta; Peralta, Carmen A.; Jukema, J. Wouter; Mitchell, Paul; Rosas, Sylvia E.; Wang, Jie Jin; Scott, Rodney J.; Dichgans, Martin; Mitchell, Braxton D.; Linda Kao, W. H.; Fox, Caroline S.; Levi, Christopher; Attia, John; Markus, Hugh S

2014-01-01

Background and Purpose Epidemiological studies show strong associations between kidney dysfunction and risk of ischaemic stroke, the mechanisms of which are incompletely understood. We investigated whether these associations may reflect shared heritability due to a common polygenic basis and whether this differed for ischaemic stroke subtypes. Methods Polygenic models were derived using GWAS meta-analysis results for three kidney traits: estimated glomerular filtration rate using serum creatinine (eGFRcrea: N=73,998), eGFR using cystatin C (eGFRcys: N=22,937) and urinary albumin to creatinine ratio (UACR: N=31,580). For each, SNPs passing ten P-value thresholds were used to form profile scores in 4,561 ischaemic stroke cases and 7,094 controls from the UK, Germany and Australia. Scores were tested for association with ischaemic stroke and its three aetiological subtypes: large artery atherosclerosis (LAA), cardioembolism (CE) and small vessel disease (SVD). Results Polygenic scores correlating with higher eGFRcrea were associated with reduced risk of LAA, with five scores reaching P<0.05 (peak P=0.004) and all showing the epidemiologically expected direction of effect. A similar pattern was observed for polygenic scores reflecting higher UACR, of which three associated with LAA (peak P=0.01) and all showed the expected directional association. One UACR-based score also associated with SVD (P=0.03). The global pattern of results was unlikely to have occurred by chance (P=0.02). Conclusions This study suggests possible polygenic correlation between renal dysfunction and ischaemic stroke. The shared genetic components may be specific to stroke subtypes, particularly large artery atherosclerotic stroke. Further study of the genetic relationships between these disorders appears merited. PMID:25352485

Performance of polygenic scores for predicting phobic anxiety.

PubMed

Walter, Stefan; Glymour, M Maria; Koenen, Karestan; Liang, Liming; Tchetgen Tchetgen, Eric J; Cornelis, Marilyn; Chang, Shun-Chiao; Rimm, Eric; Kawachi, Ichiro; Kubzansky, Laura D

2013-01-01

Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits. To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes. Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort. Study participants (n = 11,127) were individuals from the Nurses' Health Study and Health Professionals Follow-up Study. Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived. We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety. There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20-40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify significant genetic predictors of anxiety.

Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders

PubMed Central

Marian, Ali J.; van Rooij, Eva; Roberts, Robert

2016-01-01

This is the first of 2 review papers on genetics and genomics appearing as part of the series on “omics.” Genomics pertains to all components of an organism’s genes, whereas genetics involves analysis of a specific gene(s) in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. PMID:28007145

Deciphering the evolution of herbicide resistance in weeds.

PubMed

Délye, Christophe; Jasieniuk, Marie; Le Corre, Valérie

2013-11-01

Resistance to herbicides in arable weeds is increasing rapidly worldwide and threatening global food security. Resistance has now been reported to all major herbicide modes of action despite the development of resistance management strategies in the 1990s. We review here recent advances in understanding the genetic bases and evolutionary drivers of herbicide resistance that highlight the complex nature of selection for this adaptive trait. Whereas early studied cases of resistance were highly herbicide-specific and largely under monogenic control, cases of greatest concern today generally involve resistance to multiple modes of action, are under polygenic control, and are derived from pre-existing stress response pathways. Although 'omics' approaches should enable unraveling the genetic bases of complex resistances, the appearance, selection, and spread of herbicide resistance in weed populations can only be fully elucidated by focusing on evolutionary dynamics and implementing integrative modeling efforts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Scrotal tongue and geographic tongue: polygenic and associated traits.

PubMed

Eidelman, E; Chosack, A; Cohen, T

1976-11-01

The familial nature of scrotal and geographic tongue was investigated in parents and siblings of 156 probands having these conditions. The prevalence in parents and siblings was significantly higher than that in the control populations. The prevalence in sibilings from families in which at least one parent was also affected was significantly higher than that in siblings from families in which neither parent was affected. The prevalence of scrotal tongue alone in siblins was similar irrespective of the condition in the proband. The prevalence of geographic tongue alone was highest in siblins of probands having only geographic tongue. A polygenic mode of inheritance with some genes common to both conditions is suggested.

Effect of IGF1, GH, and PIT1 markers on the genetic parameters of growth and reproduction traits in Canchim cattle.

PubMed

Grossi, Daniela do Amaral; Buzanskas, Marcos Eli; Grupioni, Natalia Vinhal; de Paz, Claudia Cristina Paro; Regitano, Luciana Correia de Almeida; de Alencar, Maurício Mello; Schenkel, Flávio Schramm; Munari, Danísio Prado

2015-01-01

The availability of dense genomic information has increased genome-wide association studies for the bovine species; however research to assess the effect of single genes on production traits is still important to elucidate the genes functions. On this study the association of IGF1, GH, and PIT1 markers with growth and reproductive traits (birth weight, weaning weight, weight at 12 and 18 months of age, preweaning average daily weight gain, age and weight at first calving, and scrotal circumference at 12 and 18 months of age) were assessed by means of the variance component approach. The phenotypes were adjusted and then analyzed under two animal models, one which considered the polygenic and genotype (IGF1, GH or PIT1 markers) effects (Model 1), and the other which considers only the polygenic effect (Model 2). When the likelihood ratio test and the Bonferroni correction was applied at 5 % significance level, the genetic markers for the IGF1, GH, and PIT1 genes did not influence significantly the traits (p > 0.002). However, evidence of association of IGF1 with birth weight (p = 0.06) and GH with weight at first calving (p = 0.03) and with weight at 12 months of age (p = 0.08) was observed. In conclusion we could not confirm the associations between IGF1, GH, and PIT1 and growth traits that were previously reported in Canchim cattle, and no association was observed between these genes and reproductive traits. Future studies involving functional markers of IGF1, GH and PIT1 genes may help to clarify the role of these genes in growth and reproductive processes.

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

PubMed Central

2012-01-01

Background A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix. PMID:22455934

Stability and Response of Polygenic Traits to Stabilizing Selection and Mutation

PubMed Central

de Vladar, Harold P.; Barton, Nick

2014-01-01

When polygenic traits are under stabilizing selection, many different combinations of alleles allow close adaptation to the optimum. If alleles have equal effects, all combinations that result in the same deviation from the optimum are equivalent. Furthermore, the genetic variance that is maintained by mutation–selection balance is 2μ/S per locus, where μ is the mutation rate and S the strength of stabilizing selection. In reality, alleles vary in their effects, making the fitness landscape asymmetric and complicating analysis of the equilibria. We show that that the resulting genetic variance depends on the fraction of alleles near fixation, which contribute by 2μ/S, and on the total mutational effects of alleles that are at intermediate frequency. The interplay between stabilizing selection and mutation leads to a sharp transition: alleles with effects smaller than a threshold value of 2μ/S remain polymorphic, whereas those with larger effects are fixed. The genetic load in equilibrium is less than for traits of equal effects, and the fitness equilibria are more similar. We find that if the optimum is displaced, alleles with effects close to the threshold value sweep first, and their rate of increase is bounded by μS. Long-term response leads in general to well-adapted traits, unlike the case of equal effects that often end up at a suboptimal fitness peak. However, the particular peaks to which the populations converge are extremely sensitive to the initial states and to the speed of the shift of the optimum trait value. PMID:24709633

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

PubMed

Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung

2016-11-01

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

Quantitative trait locus mapping and analysis of heritable variation in affiliative social behavior and co-occurring traits.

PubMed

Knoll, A T; Jiang, K; Levitt, P

2018-06-01

Humans exhibit broad heterogeneity in affiliative social behavior. Twin and family studies show that individual differences in core dimensions of social behavior are heritable, yet there are knowledge gaps in understanding the underlying genetic and neurobiological mechanisms. Animal genetic reference panels (GRPs) provide a tractable strategy for examining the behavioral and genetic architecture of complex traits. Here, using males from 50 mouse strains from the BXD GRP, 4 domains of affiliative social behavior-social approach, social recognition, direct social interaction (DSI) (partner sniffing) and vocal communication-were examined in 2 widely used behavioral tasks-the 3-chamber and DSI tasks. There was continuous and broad variation in social and nonsocial traits, with moderate to high heritability of social approach sniff preference (0.31), ultrasonic vocalization (USV) count (0.39), partner sniffing (0.51), locomotor activity (0.54-0.66) and anxiety-like behavior (0.36). Principal component analysis shows that variation in social and nonsocial traits are attributable to 5 independent factors. Genome-wide mapping identified significant quantitative trait loci for USV count on chromosome (Chr) 18 and locomotor activity on Chr X, with suggestive loci and candidate quantitative trait genes identified for all traits with one notable exception-partner sniffing in the DSI task. The results show heritable variation in sociability, which is independent of variation in activity and anxiety-like traits. In addition, a highly heritable and ethological domain of affiliative sociability-partner sniffing-appears highly polygenic. These findings establish a basis for identifying functional natural variants, leading to a new understanding typical and atypical sociability. © 2017 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

Identification of Traits Associated with Stuttering

ERIC Educational Resources Information Center

Subramanian, Anu; Yairi, Ehud

2006-01-01

Stuttering has been considered a heritable disorder since the 1930s. There have been different models of transmission that have been proposed most involving a polygenic component with or without a major locus. In spite of these models, the characteristics being transmitted are not known. This study used two different tasks--a tapping task that is…

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

USDA-ARS?s Scientific Manuscript database

Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Multi-trait analysis of genome-wide association summary statistics using MTAG.

PubMed

Turley, Patrick; Walters, Raymond K; Maghzian, Omeed; Okbay, Aysu; Lee, James J; Fontana, Mark Alan; Nguyen-Viet, Tuan Anh; Wedow, Robbee; Zacher, Meghan; Furlotte, Nicholas A; Magnusson, Patrik; Oskarsson, Sven; Johannesson, Magnus; Visscher, Peter M; Laibson, David; Cesarini, David; Neale, Benjamin M; Benjamin, Daniel J

2018-02-01

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff  = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

Genomic architecture of habitat-related divergence and signature of directional selection in the body shapes of Gnathopogon fishes.

PubMed

Kakioka, Ryo; Kokita, Tomoyuki; Kumada, Hiroki; Watanabe, Katsutoshi; Okuda, Noboru

2015-08-01

Evolution of ecomorphologically relevant traits such as body shapes is important to colonize and persist in a novel environment. Habitat-related adaptive divergence of these traits is therefore common among animals. We studied the genomic architecture of habitat-related divergence in the body shape of Gnathopogon fishes, a novel example of lake-stream ecomorphological divergence, and tested for the action of directional selection on body shape differentiation. Compared to stream-dwelling Gnathopogon elongatus, the sister species Gnathopogon caerulescens, exclusively inhabiting a large ancient lake, had an elongated body, increased proportion of the caudal region and small head, which would be advantageous in the limnetic environment. Using an F2 interspecific cross between the two Gnathopogon species (195 individuals), quantitative trait locus (QTL) analysis with geometric morphometric quantification of body shape and restriction-site associated DNA sequencing-derived markers (1622 loci) identified 26 significant QTLs associated with the interspecific differences of body shape-related traits. These QTLs had small to moderate effects, supporting polygenic inheritance of the body shape-related traits. Each QTL was mostly located on different genomic regions, while colocalized QTLs were detected for some ecomorphologically relevant traits that are proxy of body and caudal peduncle depths, suggesting different degree of modularity among traits. The directions of the body shape QTLs were mostly consistent with the interspecific difference, and QTL sign test suggested a genetic signature of directional selection in the body shape divergence. Thus, we successfully elucidated the genomic architecture underlying the adaptive changes of the quantitative and complex morphological trait in a novel system. © 2015 John Wiley & Sons Ltd.

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

New consistent QTL in pea associated with partial resistance to Aphanomyces euteiches in multiple field and controlled environments from France and the United States

USDA-ARS?s Scientific Manuscript database

Partial resistances, often controlled by QTL (Quantitative Trait Loci), are considered to be more durable than monogenic resistances. Prior to develop efficient breeding programs for polygenic resistance to pathogens, a higher understanding of genetic diversity and stability of resistance QTL in pla...

Performance of Polygenic Scores for Predicting Phobic Anxiety

PubMed Central

Walter, Stefan; Glymour, M. Maria; Koenen, Karestan; Liang, Liming; Tchetgen Tchetgen, Eric J.; Cornelis, Marilyn; Chang, Shun-Chiao; Rimm, Eric; Kawachi, Ichiro; Kubzansky, Laura D.

2013-01-01

Context Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits. Objective To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes. Design Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort. Setting and Participants Study participants (n = 11,127) were individuals from the Nurses' Health Study and Health Professionals Follow-up Study. Main Outcome Measure Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived. Results We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety. Conclusion There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20–40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify significant genetic predictors of anxiety. PMID:24278274

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

PubMed

Christoforou, A; Espeseth, T; Davies, G; Fernandes, C P D; Giddaluru, S; Mattheisen, M; Tenesa, A; Harris, S E; Liewald, D C; Payton, A; Ollier, W; Horan, M; Pendleton, N; Haggarty, P; Djurovic, S; Herms, S; Hoffman, P; Cichon, S; Starr, J M; Lundervold, A; Reinvang, I; Steen, V M; Deary, I J; Le Hellard, S

2014-09-01

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation. © 2014 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait

PubMed Central

Duthie, A. Bradley; Bocedi, Greta; Reid, Jane M.

2016-01-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual‐based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. PMID:27464756

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

PubMed

Viana, Joana; Hannon, Eilis; Dempster, Emma; Pidsley, Ruth; Macdonald, Ruby; Knox, Olivia; Spiers, Helen; Troakes, Claire; Al-Saraj, Safa; Turecki, Gustavo; Schalkwyk, Leonard C; Mill, Jonathan

2017-01-01

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease. © The Author 2016. Published by Oxford University Press.

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank

PubMed Central

Reus, L. M.; Shen, X.; Gibson, J.; Wigmore, E.; Ligthart, L.; Adams, M. J.; Davies, G.; Cox, S. R.; Hagenaars, S. P.; Bastin, M. E.; Deary, I. J.; Whalley, H. C.; McIntosh, A. M.

2017-01-01

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders. PMID:28186152

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank.

PubMed

Reus, L M; Shen, X; Gibson, J; Wigmore, E; Ligthart, L; Adams, M J; Davies, G; Cox, S R; Hagenaars, S P; Bastin, M E; Deary, I J; Whalley, H C; McIntosh, A M

2017-02-10

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.

Genetics and the making of Homo sapiens.

PubMed

Carroll, Sean B

2003-04-24

Understanding the genetic basis of the physical and behavioural traits that distinguish humans from other primates presents one of the great new challenges in biology. Of the millions of base-pair differences between humans and chimpanzees, which particular changes contributed to the evolution of human features after the separation of the Pan and Homo lineages 5-7 million years ago? How can we identify the 'smoking guns' of human genetic evolution from neutral ticks of the molecular evolutionary clock? The magnitude and rate of morphological evolution in hominids suggests that many independent and incremental developmental changes have occurred that, on the basis of recent findings in model animals, are expected to be polygenic and regulatory in nature. Comparative genomics, population genetics, gene-expression analyses and medical genetics have begun to make complementary inroads into the complex genetic architecture of human evolution.

A sampling algorithm for segregation analysis

PubMed Central

Tier, Bruce; Henshall, John

2001-01-01

Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated. PMID:11742631

A Population Genetic Signal of Polygenic Adaptation

PubMed Central

Berg, Jeremy J.; Coop, Graham

2014-01-01

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G x E interactions.

PubMed Central

Turelli, Michael; Barton, N H

2004-01-01

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms. PMID:15020487

Genetics of dispersal.

PubMed

Saastamoinen, Marjo; Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W; Fronhofer, Emanuel A; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M; Travis, Justin M J; Donohue, Kathleen; Bullock, James M; Del Mar Delgado, Maria

2018-02-01

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Genetics of dispersal

PubMed Central

Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W.; Fronhofer, Emanuel A.; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M.; Travis, Justin M. J.; Donohue, Kathleen; Bullock, James M.; del Mar Delgado, Maria

2017-01-01

ABSTRACT Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. PMID:28776950

The genetic architecture of sexually selected traits in two natural populations of Drosophila montana

PubMed Central

Veltsos, P; Gregson, E; Morrissey, B; Slate, J; Hoikkala, A; Butlin, R K; Ritchie, M G

2015-01-01

We investigated the genetic architecture of courtship song and cuticular hydrocarbon traits in two phygenetically distinct populations of Drosophila montana. To study natural variation in these two important traits, we analysed within-population crosses among individuals sampled from the wild. Hence, the genetic variation analysed should represent that available for natural and sexual selection to act upon. In contrast to previous between-population crosses in this species, no major quantitative trait loci (QTLs) were detected, perhaps because the between-population QTLs were due to fixed differences between the populations. Partitioning the trait variation to chromosomes suggested a broadly polygenic genetic architecture of within-population variation, although some chromosomes explained more variation in one population compared with the other. Studies of natural variation provide an important contrast to crosses between species or divergent lines, but our analysis highlights recent concerns that segregating variation within populations for important quantitative ecological traits may largely consist of small effect alleles, difficult to detect with studies of moderate power. PMID:26198076

Genome-wide association uncovers shared genetic effects among personality traits and mood states.

PubMed

Luciano, Michelle; Huffman, Jennifer E; Arias-Vásquez, Alejandro; Vinkhuyzen, Anna A E; Middeldorp, Christel M; Giegling, Ina; Payton, Antony; Davies, Gail; Zgaga, Lina; Janzing, Joost; Ke, Xiayi; Galesloot, Tessel; Hartmann, Annette M; Ollier, William; Tenesa, Albert; Hayward, Caroline; Verhagen, Maaike; Montgomery, Grant W; Hottenga, Jouke-Jan; Konte, Bettina; Starr, John M; Vitart, Veronique; Vos, Pieter E; Madden, Pamela A F; Willemsen, Gonneke; Konnerth, Heike; Horan, Michael A; Porteous, David J; Campbell, Harry; Vermeulen, Sita H; Heath, Andrew C; Wright, Alan; Polasek, Ozren; Kovacevic, Sanja B; Hastie, Nicholas D; Franke, Barbara; Boomsma, Dorret I; Martin, Nicholas G; Rujescu, Dan; Wilson, James F; Buitelaar, Jan; Pendleton, Neil; Rudan, Igor; Deary, Ian J

2012-09-01

Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (~2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546-1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta-analysis of the cohort results was performed, with follow-up associations of the top SNPs and genes investigated in independent cohorts (n = 527-6,032). Suggestive association (P = 8 × 10(-8)) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10(-6)) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene-based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits. Copyright © 2012 Wiley Periodicals, Inc.

Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

PubMed Central

Davies, G; Armstrong, N; Bis, J C; Bressler, J; Chouraki, V; Giddaluru, S; Hofer, E; Ibrahim-Verbaas, C A; Kirin, M; Lahti, J; van der Lee, S J; Le Hellard, S; Liu, T; Marioni, R E; Oldmeadow, C; Postmus, I; Smith, A V; Smith, J A; Thalamuthu, A; Thomson, R; Vitart, V; Wang, J; Yu, L; Zgaga, L; Zhao, W; Boxall, R; Harris, S E; Hill, W D; Liewald, D C; Luciano, M; Adams, H; Ames, D; Amin, N; Amouyel, P; Assareh, A A; Au, R; Becker, J T; Beiser, A; Berr, C; Bertram, L; Boerwinkle, E; Buckley, B M; Campbell, H; Corley, J; De Jager, P L; Dufouil, C; Eriksson, J G; Espeseth, T; Faul, J D; Ford, I; Scotland, Generation; Gottesman, R F; Griswold, M E; Gudnason, V; Harris, T B; Heiss, G; Hofman, A; Holliday, E G; Huffman, J; Kardia, S L R; Kochan, N; Knopman, D S; Kwok, J B; Lambert, J-C; Lee, T; Li, G; Li, S-C; Loitfelder, M; Lopez, O L; Lundervold, A J; Lundqvist, A; Mather, K A; Mirza, S S; Nyberg, L; Oostra, B A; Palotie, A; Papenberg, G; Pattie, A; Petrovic, K; Polasek, O; Psaty, B M; Redmond, P; Reppermund, S; Rotter, J I; Schmidt, H; Schuur, M; Schofield, P W; Scott, R J; Steen, V M; Stott, D J; van Swieten, J C; Taylor, K D; Trollor, J; Trompet, S; Uitterlinden, A G; Weinstein, G; Widen, E; Windham, B G; Jukema, J W; Wright, A F; Wright, M J; Yang, Q; Amieva, H; Attia, J R; Bennett, D A; Brodaty, H; de Craen, A J M; Hayward, C; Ikram, M A; Lindenberger, U; Nilsson, L-G; Porteous, D J; Räikkönen, K; Reinvang, I; Rudan, I; Sachdev, P S; Schmidt, R; Schofield, P R; Srikanth, V; Starr, J M; Turner, S T; Weir, D R; Wilson, J F; van Duijn, C; Launer, L; Fitzpatrick, A L; Seshadri, S; Mosley, T H; Deary, I J

2015-01-01

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C. PMID:25644384

Parenting Interacts with Oxytocin Polymorphisms to Predict Adolescent Social Anxiety Symptom Development: A Novel Polygenic Approach.

PubMed

Nelemans, Stefanie A; van Assche, Evelien; Bijttebier, Patricia; Colpin, Hilde; van Leeuwen, Karla; Verschueren, Karine; Claes, Stephan; van den Noortgate, Wim; Goossens, Luc

2018-04-26

Guided by a developmental psychopathology framework, research has increasingly focused on the interplay of genetics and environment as a predictor of different forms of psychopathology, including social anxiety. In these efforts, the polygenic nature of complex phenotypes such as social anxiety is increasingly recognized, but studies applying polygenic approaches are still scarce. In this study, we applied Principal Covariates Regression as a novel approach to creating polygenic components for the oxytocin system, which has recently been put forward as particularly relevant to social anxiety. Participants were 978 adolescents (49.4% girls; M age T 1  = 13.8 years). Across 3 years, questionnaires were used to assess adolescent social anxiety symptoms and multi-informant reports of parental psychological control and autonomy support. All adolescents were genotyped for 223 oxytocin single nucleotide polymorphisms (SNPs) in 14 genes. Using Principal Covariates Regression, these SNPs could be reduced to five polygenic components. Four components reflected the underlying linkage disequilibrium and ancestry structure, whereas the fifth component, which consisted of small contributions of many SNPs across multiple genes, was strongly positively associated with adolescent social anxiety symptoms, pointing to an index of genetic risk. Moreover, significant interactions were found with this polygenic component and the environmental variables of interest. Specifically, adolescents who scored high on this polygenic component and experienced less adequate parenting (i.e., high psychological control or low autonomy support) showed the highest levels of social anxiety. Implications of these findings are discussed in the context of individual-by-environment models.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

PubMed

Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L

2015-01-01

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

When does female multiple mating evolve to adjust inbreeding? Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait.

PubMed

Duthie, A Bradley; Bocedi, Greta; Reid, Jane M

2016-09-01

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual-based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M.J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. Although no individual single nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels, i.e. expression quantitative loci (eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10−4), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, TS had a smaller, non-significant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and TS/CT were included in the analysis (p=0.01). Previous work has shown that TS and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Genome‐wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders

PubMed Central

Coleman, Jonathan R.I.; Lester, Kathryn J.; Keers, Robert; Munafò, Marcus R.; Breen, Gerome

2017-01-01

Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight‐year‐old participants (n = 4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non‐Verbal Accuracy (DANVA) faces test. Genome‐wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome‐wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP‐chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non‐zero estimates of SNP‐heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype. PMID:28608620

High-resolution mapping of a fruit firmness-related quantitative trait locus in tomato reveals epistatic interactions associated with a complex combinatorial locus.

PubMed

Chapman, Natalie H; Bonnet, Julien; Grivet, Laurent; Lynn, James; Graham, Neil; Smith, Rebecca; Sun, Guiping; Walley, Peter G; Poole, Mervin; Causse, Mathilde; King, Graham J; Baxter, Charles; Seymour, Graham B

2012-08-01

Fruit firmness in tomato (Solanum lycopersicum) is determined by a number of factors including cell wall structure, turgor, and cuticle properties. Firmness is a complex polygenic trait involving the coregulation of many genes and has proved especially challenging to unravel. In this study, a quantitative trait locus (QTL) for fruit firmness was mapped to tomato chromosome 2 using the Zamir Solanum pennellii interspecific introgression lines (ILs) and fine-mapped in a population consisting of 7,500 F2 and F3 lines from IL 2-3 and IL 2-4. This firmness QTL contained five distinct subpeaks, Fir(s.p.)QTL2.1 to Fir(s.p.)QTL2.5, and an effect on a distal region of IL 2-4 that was nonoverlapping with IL 2-3. All these effects were located within an 8.6-Mb region. Using genetic markers, each subpeak within this combinatorial locus was mapped to a physical location within the genome, and an ethylene response factor (ERF) underlying Fir(s.p.)QTL2.2 and a region containing three pectin methylesterase (PME) genes underlying Fir(s.p.)QTL2.5 were nominated as QTL candidate genes. Statistical models used to explain the observed variability between lines indicated that these candidates and the nonoverlapping portion of IL 2-4 were sufficient to account for the majority of the fruit firmness effects. Quantitative reverse transcription-polymerase chain reaction was used to quantify the expression of each candidate gene. ERF showed increased expression associated with soft fruit texture in the mapping population. In contrast, PME expression was tightly linked with firm fruit texture. Analysis of a range of recombinant lines revealed evidence for an epistatic interaction that was associated with this combinatorial locus.

A Comparison Study of Multivariate Fixed Models and Gene Association with Multiple Traits (GAMuT) for Next-Generation Sequencing

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Wang, Yifan; Weeks, Daniel E.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Amos, Christopher I.; Mills, James L.; Boehnke, Michael; Xiong, Momiao; Fan, Ruzong

2016-01-01

In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for: (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models which perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods. PMID:27917525

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection.

PubMed

Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

2013-11-20

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.

PubMed

Gandal, Michael J; Haney, Jillian R; Parikshak, Neelroop N; Leppa, Virpi; Ramaswami, Gokul; Hartl, Chris; Schork, Andrew J; Appadurai, Vivek; Buil, Alfonso; Werge, Thomas M; Liu, Chunyu; White, Kevin P; Horvath, Steve; Geschwind, Daniel H

2018-02-09

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Quantitative Trait Loci Differentiating the Outbreeding Mimulus Guttatus from the Inbreeding M. Platycalyx

PubMed Central

Lin, J. Z.; Ritland, K.

1997-01-01

Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6-28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect. PMID:9215912

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value.

PubMed

Shin, Donghyun; Lee, Chul; Park, Kyoung-Do; Kim, Heebal; Cho, Kwang-Hyeon

2017-03-01

Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value

PubMed Central

Shin, Donghyun; Lee, Chul; Park, Kyoung-Do; Kim, Heebal; Cho, Kwang-hyeon

2017-01-01

Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins. PMID:26954162

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Genomic analysis of morphometric traits in bighorn sheep using the Ovine Infinium® HD SNP BeadChip.

PubMed

Miller, Joshua M; Festa-Bianchet, Marco; Coltman, David W

2018-01-01

Elucidating the genetic basis of fitness-related traits is a major goal of molecular ecology. Traits subject to sexual selection are particularly interesting, as non-random mate choice should deplete genetic variation and thereby their evolutionary benefits. We examined the genetic basis of three sexually selected morphometric traits in bighorn sheep ( Ovis canadensis ): horn length, horn base circumference, and body mass. These traits are of specific concern in bighorn sheep as artificial selection through trophy hunting opposes sexual selection. Specifically, horn size determines trophy status and, in most North American jurisdictions, if an individual can be legally harvested. Using between 7,994-9,552 phenotypic measures from the long-term individual-based study at Ram Mountain (Alberta, Canada), we first showed that all three traits are heritable ( h 2  = 0.15-0.23). We then conducted a genome-wide association study (GWAS) utilizing a set of 3,777 SNPs typed in 76 individuals using the Ovine Infinium ®  HD SNP BeadChip. We found suggestive association for body mass at a single locus (OAR9_91647990). The absence of strong associations with SNPs suggests that the traits are likely polygenic. These results represent a step forward for characterizing the genetic architecture of fitness related traits in sexually dimorphic ungulates.

Detecting genotypic changes associated with selective mortality at sea in Atlantic salmon: polygenic multilocus analysis surpasses genome scan.

PubMed

Bourret, Vincent; Dionne, Mélanie; Bernatchez, Louis

2014-09-01

Wild populations of Atlantic salmon have declined worldwide. While the causes for this decline may be complex and numerous, increased mortality at sea is predicted to be one of the major contributing factors. Examining the potential changes occurring in the genome-wide composition of populations during this migration has the potential to tease apart some of the factors influencing marine mortality. Here, we genotyped 5568 SNPs in Atlantic salmon populations representing two distinct regional genetic groups and across two cohorts to test for differential allelic and genotypic frequencies between juveniles (smolts) migrating to sea and adults (grilses) returning to freshwater after 1 year at sea. Given the complexity of the traits potentially associated with sea mortality, we contrasted the outcomes of a single-locus F(ST) based genome scan method with a new multilocus framework to test for genetically based differential mortality at sea. While numerous outliers were identified by the single-locus analysis, no evidence for parallel, temporally repeated selection was found. In contrast, the multilocus approach detected repeated patterns of selection for a multilocus group of 34 covarying SNPs in one of the two populations. No significant pattern of selective mortality was detected in the other population, suggesting different causes of mortality among populations. These results first support the hypothesis that selection mainly causes small changes in allele frequencies among many covarying loci rather than a small number of changes in loci with large effects. They also point out that moving away from the a strict 'selective sweep paradigm' towards a multilocus genetics framework may be a more useful approach for studying the genomic signatures of natural selection on complex traits in wild populations. © 2014 John Wiley & Sons Ltd.

The Biological Contributions to Gender Identity and Gender Diversity: Bringing Data to the Table.

PubMed

Polderman, Tinca J C; Kreukels, Baudewijntje P C; Irwig, Michael S; Beach, Lauren; Chan, Yee-Ming; Derks, Eske M; Esteva, Isabel; Ehrenfeld, Jesse; Heijer, Martin Den; Posthuma, Danielle; Raynor, Lewis; Tishelman, Amy; Davis, Lea K

2018-03-01

The American Psychological Association defines gender identity as, "A person's deeply-felt, inherent sense of being a boy, a man, or a male; a girl, a woman, or a female; or an alternative gender (e.g., genderqueer, gender nonconforming, gender neutral) that may or may not correspond to a person's sex assigned at birth or to a person's primary or secondary sex characteristics" (American Psychological Association, Am Psychol 70(9):832-864, 2015). Here we review the evidence that gender identity and related socially defined gender constructs are influenced in part by innate factors including genes. Based on the data reviewed, we hypothesize that gender identity is a multifactorial complex trait with a heritable polygenic component. We argue that increasing the awareness of the biological diversity underlying gender identity development is relevant to all domains of social, medical, and neuroscience research and foundational for reducing health disparities and promoting human-rights protections for gender minorities.

Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis

PubMed Central

van Rheenen, Wouter; Shatunov, Aleksey; Dekker, Annelot M; McLaughlin, Russell L; Diekstra, Frank P; Pulit, Sara L; van der Spek, Rick A A; Võsa, Urmo; de Jong, Simone; Robinson, Matthew R; Yang, Jian; Fogh, Isabella; van Doormaal, Perry TC; Tazelaar, Gijs H P; Koppers, Max; Blokhuis, Anna M; Sproviero, William; Jones, Ashley R; Kenna, Kevin P; van Eijk, Kristel R; Harschnitz, Oliver; Schellevis, Raymond D; Brands, William J; Medic, Jelena; Menelaou, Androniki; Vajda, Alice; Ticozzi, Nicola; Lin, Kuang; Rogelj, Boris; Vrabec, Katarina; Ravnik-Glavač, Metka; Koritnik, Blaž; Zidar, Janez; Leonardis, Lea; Grošelj, Leja Dolenc; Millecamps, Stéphanie; Salachas, François; Meininger, Vincent; de Carvalho, Mamede; Pinto, Susana; Mora, Jesus S; Rojas-García, Ricardo; Polak, Meraida; Chandran, Siddharthan; Colville, Shuna; Swingler, Robert; Morrison, Karen E; Shaw, Pamela J; Hardy, John; Orrell, Richard W; Pittman, Alan; Sidle, Katie; Fratta, Pietro; Malaspina, Andrea; Topp, Simon; Petri, Susanne; Abdulla, Susanne; Drepper, Carsten; Sendtner, Michael; Meyer, Thomas; Ophoff, Roel A; Staats, Kim A; Wiedau-Pazos, Martina; Lomen-Hoerth, Catherine; Van Deerlin, Vivianna M; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Basak, A Nazli; Tunca, Ceren; Hamzeiy, Hamid; Parman, Yesim; Meitinger, Thomas; Lichtner, Peter; Radivojkov-Blagojevic, Milena; Andres, Christian R; Maurel, Cindy; Bensimon, Gilbert; Landwehrmeyer, Bernhard; Brice, Alexis; Payan, Christine A M; Saker-Delye, Safaa; Dürr, Alexandra; Wood, Nicholas W; Tittmann, Lukas; Lieb, Wolfgang; Franke, Andre; Rietschel, Marcella; Cichon, Sven; Nöthen, Markus M; Amouyel, Philippe; Tzourio, Christophe; Dartigues, Jean-François; Uitterlinden, Andre G; Rivadeneira, Fernando; Estrada, Karol; Hofman, Albert; Curtis, Charles; Blauw, Hylke M; van der Kooi, Anneke J; de Visser, Marianne; Goris, An; Weber, Markus; Shaw, Christopher E; Smith, Bradley N; Pansarasa, Orietta; Cereda, Cristina; Bo, Roberto Del; Comi, Giacomo P; D’Alfonso, Sandra; Bertolin, Cinzia; Sorarù, Gianni; Mazzini, Letizia; Pensato, Viviana; Gellera, Cinzia; Tiloca, Cinzia; Ratti, Antonia; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Arcuti, Simona; Capozzo, Rosa; Zecca, Chiara; Lunetta, Christian; Penco, Silvana; Riva, Nilo; Padovani, Alessandro; Filosto, Massimiliano; Muller, Bernard; Stuit, Robbert Jan; Blair, Ian; Zhang, Katharine; McCann, Emily P; Fifita, Jennifer A; Nicholson, Garth A; Rowe, Dominic B; Pamphlett, Roger; Kiernan, Matthew C; Grosskreutz, Julian; Witte, Otto W; Ringer, Thomas; Prell, Tino; Stubendorff, Beatrice; Kurth, Ingo; Hübner, Christian A; Leigh, P Nigel; Casale, Federico; Chio, Adriano; Beghi, Ettore; Pupillo, Elisabetta; Tortelli, Rosanna; Logroscino, Giancarlo; Powell, John; Ludolph, Albert C; Weishaupt, Jochen H; Robberecht, Wim; Van Damme, Philip; Franke, Lude; Pers, Tune H; Brown, Robert H; Glass, Jonathan D; Landers, John E; Hardiman, Orla; Andersen, Peter M; Corcia, Philippe; Vourc’h, Patrick; Silani, Vincenzo; Wray, Naomi R; Visscher, Peter M; de Bakker, Paul I W; van Es, Michael A; Pasterkamp, R Jeroen; Lewis, Cathryn M; Breen, Gerome; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan H

2017-01-01

To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1–10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk. PMID:27455348

Implications of sex-specific selection for the genetic basis of disease.

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia: A Danish Population-Based Study and Meta-analysis.

PubMed

Agerbo, Esben; Sullivan, Patrick F; Vilhjálmsson, Bjarni J; Pedersen, Carsten B; Mors, Ole; Børglum, Anders D; Hougaard, David M; Hollegaard, Mads V; Meier, Sandra; Mattheisen, Manuel; Ripke, Stephan; Wray, Naomi R; Mortensen, Preben B

2015-07-01

Schizophrenia has a complex etiology influenced both by genetic and nongenetic factors but disentangling these factors is difficult. To estimate (1) how strongly the risk for schizophrenia relates to the mutual effect of the polygenic risk score, parental socioeconomic status, and family history of psychiatric disorders; (2) the fraction of cases that could be prevented if no one was exposed to these factors; (3) whether family background interacts with an individual's genetic liability so that specific subgroups are particularly risk prone; and (4) to what extent a proband's genetic makeup mediates the risk associated with familial background. We conducted a nested case-control study based on Danish population-based registers. The study consisted of 866 patients diagnosed as having schizophrenia between January 1, 1994, and December 31, 2006, and 871 matched control individuals. Genome-wide data and family psychiatric and socioeconomic background information were obtained from neonatal biobanks and national registers. Results from a separate meta-analysis (34,600 cases and 45,968 control individuals) were applied to calculate polygenic risk scores. Polygenic risk scores, parental socioeconomic status, and family psychiatric history. Odds ratios (ORs), attributable risks, liability R2 values, and proportions mediated. Schizophrenia was associated with the polygenic risk score (OR, 8.01; 95% CI, 4.53-14.16 for highest vs lowest decile), socioeconomic status (OR, 8.10; 95% CI, 3.24-20.3 for 6 vs no exposures), and a history of schizophrenia/psychoses (OR, 4.18; 95% CI, 2.57-6.79). The R2 values were 3.4% (95% CI, 2.1-4.6) for the polygenic risk score, 3.1% (95% CI, 1.9-4.3) for parental socioeconomic status, and 3.4% (95% CI, 2.1-4.6) for family history. Socioeconomic status and psychiatric history accounted for 45.8% (95% CI, 36.1-55.5) and 25.8% (95% CI, 21.2-30.5) of cases, respectively. There was an interaction between the polygenic risk score and family history (P = .03). A total of 17.4% (95% CI, 9.1-26.6) of the effect associated with family history of schizophrenia/psychoses was mediated through the polygenic risk score. Schizophrenia was associated with the polygenic risk score, family psychiatric history, and socioeconomic status. Our study demonstrated that family history of schizophrenia/psychoses is partly mediated through the individual's genetic liability.

Assessing the genetic overlap between BMI and cognitive function

PubMed Central

Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J

2016-01-01

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

PubMed

Evans, Luke M; Tahmasbi, Rasool; Jones, Matt; Vrieze, Scott I; Abecasis, Gonçalo R; Das, Sayantan; Bjelland, Douglas W; de Candia, Teresa R; Yang, Jian; Goddard, Michael E; Visscher, Peter M; Keller, Matthew C

2018-03-28

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

PubMed

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

PubMed

Trampush, J W; Yang, M L Z; Yu, J; Knowles, E; Davies, G; Liewald, D C; Starr, J M; Djurovic, S; Melle, I; Sundet, K; Christoforou, A; Reinvang, I; DeRosse, P; Lundervold, A J; Steen, V M; Espeseth, T; Räikkönen, K; Widen, E; Palotie, A; Eriksson, J G; Giegling, I; Konte, B; Roussos, P; Giakoumaki, S; Burdick, K E; Payton, A; Ollier, W; Horan, M; Chiba-Falek, O; Attix, D K; Need, A C; Cirulli, E T; Voineskos, A N; Stefanis, N C; Avramopoulos, D; Hatzimanolis, A; Arking, D E; Smyrnis, N; Bilder, R M; Freimer, N A; Cannon, T D; London, E; Poldrack, R A; Sabb, F W; Congdon, E; Conley, E D; Scult, M A; Dickinson, D; Straub, R E; Donohoe, G; Morris, D; Corvin, A; Gill, M; Hariri, A R; Weinberger, D R; Pendleton, N; Bitsios, P; Rujescu, D; Lahti, J; Le Hellard, S; Keller, M C; Andreassen, O A; Deary, I J; Glahn, D C; Malhotra, A K; Lencz, T

2017-03-01

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10 -8 ). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

PubMed Central

Trampush, J W; Yang, M L Z; Yu, J; Knowles, E; Davies, G; Liewald, D C; Starr, J M; Djurovic, S; Melle, I; Sundet, K; Christoforou, A; Reinvang, I; DeRosse, P; Lundervold, A J; Steen, V M; Espeseth, T; Räikkönen, K; Widen, E; Palotie, A; Eriksson, J G; Giegling, I; Konte, B; Roussos, P; Giakoumaki, S; Burdick, K E; Payton, A; Ollier, W; Horan, M; Chiba-Falek, O; Attix, D K; Need, A C; Cirulli, E T; Voineskos, A N; Stefanis, N C; Avramopoulos, D; Hatzimanolis, A; Arking, D E; Smyrnis, N; Bilder, R M; Freimer, N A; Cannon, T D; London, E; Poldrack, R A; Sabb, F W; Congdon, E; Conley, E D; Scult, M A; Dickinson, D; Straub, R E; Donohoe, G; Morris, D; Corvin, A; Gill, M; Hariri, A R; Weinberger, D R; Pendleton, N; Bitsios, P; Rujescu, D; Lahti, J; Le Hellard, S; Keller, M C; Andreassen, O A; Deary, I J; Glahn, D C; Malhotra, A K; Lencz, T

2017-01-01

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness. PMID:28093568

Prediction of individual genetic risk to prostate cancer using a polygenic score.

PubMed

Szulkin, Robert; Whitington, Thomas; Eklund, Martin; Aly, Markus; Eeles, Rosalind A; Easton, Douglas; Kote-Jarai, Z Sofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel M; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Lubiński, Jan; Kluźniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Stegmaier, Christa; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Lim, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Gronberg, Henrik; Wiklund, Fredrik

2015-09-01

Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. © 2015 Wiley Periodicals, Inc.

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder

PubMed Central

Wiste, Anna; Robinson, Elise B; Milaneschi, Yuri; Meier, Sandra; Ripke, Stephan; Clements, Caitlin C; Fitzmaurice, Garrett M; Rietschel, Marcella; Penninx, Brenda W; Smoller, Jordan W; Perlis, Roy H

2014-01-01

Objectives Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of this study was to determine whether this shared genetic liability influences clinical presentation. Methods A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European–American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts. Results A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04). Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ≤ 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8–1.1%. However, analyses in two replication cohorts testing a five feature model did not support this association. Conclusions Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, results are at most inconclusive because of lack of replication. Replication efforts are challenged by different ascertainment and assessment strategies in the different cohorts. The methodological approach described here may prove useful in applying genetic data to clarify psychiatric nosology in future studies. PMID:24725193

SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE.

PubMed

Docherty, A R; Moscati, A; Peterson, R; Edwards, A C; Adkins, D E; Bacanu, S A; Bigdeli, T B; Webb, B T; Flint, J; Kendler, K S

2016-10-25

Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10 064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort. Heritability of neuroticism as measured by the Eysenck Personality Questionnaire (EPQ) was estimated to be low but statistically significant at 10% (s.e.=0.03, P=0.0001). In addition to EPQ, neuroticism based on a three-factor model, data for the Big Five (BF) personality dimensions (neuroticism, openness, conscientiousness, extraversion and agreeableness) measured by the Big Five Inventory were available for controls (n=5596). Heritability estimates of the BF were not statistically significant despite high power (>0.85) to detect heritabilities of 0.10. Polygenic risk scores constructed by best linear unbiased prediction weights applied to split-half samples failed to significantly predict any of the personality traits, but polygenic risk for neuroticism, calculated with LDpred and based on predictive variants previously identified from European populations (N=171 911), significantly predicted major depressive disorder case-control status (P=0.0004) after false discovery rate correction. The scores also significantly predicted EPQ neuroticism (P=6.3 × 10 -6 ). Factor analytic results of the measures indicated that any differences in heritabilities across samples may be due to genetic variation or variation in haplotype structure between samples, rather than measurement non-invariance. Findings demonstrate that neuroticism can be significantly predicted across ancestry, and highlight the importance of studying polygenic contributions to personality in non-European populations.

Dissection of major depressive disorder using polygenic risk scores for schizophrenia in two independent cohorts.

PubMed

Whalley, H C; Adams, M J; Hall, L S; Clarke, T-K; Fernandez-Pujals, A M; Gibson, J; Wigmore, E; Hafferty, J; Hagenaars, S P; Davies, G; Campbell, A; Hayward, C; Lawrie, S M; Porteous, D J; Deary, I J; McIntosh, A M

2016-11-01

Major depressive disorder (MDD) is known for its substantial clinical and suspected causal heterogeneity. It is characterized by low mood, psychomotor slowing and increased levels of the personality trait neuroticism; factors also associated with schizophrenia (SCZ). It is possible that some cases of MDD may have a substantial genetic loading for SCZ. The presence of SCZ-like MDD subgroups would be indicated by an interaction between MDD status and polygenic risk of SCZ on cognitive, personality and mood measures. Here, we hypothesized that higher SCZ polygenic risk would define larger MDD case-control differences in cognitive ability, and smaller differences in distress and neuroticism. Polygenic risk scores (PRSs) for SCZ and their association with cognitive variables, neuroticism, mood and psychological distress were estimated in a large population-based cohort (Generation Scotland: Scottish Family Health Study, GS:SFHS). The individuals were divided into those with, and without, depression (n=2587 and n=16 764, respectively) to test for the interactions between MDD status and schizophrenia risk. Replication was sought in UK Biobank (UKB; n=6049 and n=27 476 cases and controls, respectively). In both the cohorts, we found significant interactions between SCZ-PRS and MDD status for measures of psychological distress (β GS =-0.04, P GS =0.014 and β UKB =-0.09, P UKB ⩽0.001 for GS:SFHS and UKB, respectively) and neuroticism (β GS =-0.04, P GS =0.002 and β UKB =-0.06, P UKB =0.023). In both the cohorts, there was a reduction of case-control differences on a background of higher genetic risk of SCZ. These findings suggest that depression on a background of high genetic risk for SCZ may show attenuated associations with distress and neuroticism. This may represent a causally distinct form of MDD more closely related to SCZ.

Genetic Marker Discovery in Complex Traits: A Field Example on Fat Content and Composition in Pigs.

PubMed

Pena, Ramona Natacha; Ros-Freixedes, Roger; Tor, Marc; Estany, Joan

2016-12-14

Among the large number of attributes that define pork quality, fat content and composition have attracted the attention of breeders in the recent years due to their interaction with human health and technological and sensorial properties of meat. In livestock species, fat accumulates in different depots following a temporal pattern that is also recognized in humans. Intramuscular fat deposition rate and fatty acid composition change with life. Despite indication that it might be possible to select for intramuscular fat without affecting other fat depots, to date only one depot-specific genetic marker ( PCK1 c.2456C>A) has been reported. In contrast, identification of polymorphisms related to fat composition has been more successful. For instance, our group has described a variant in the stearoyl-coA desaturase ( SCD ) gene that improves the desaturation index of fat without affecting overall fatness or growth. Identification of mutations in candidate genes can be a tedious and costly process. Genome-wide association studies can help in narrowing down the number of candidate genes by highlighting those which contribute most to the genetic variation of the trait. Results from our group and others indicate that fat content and composition are highly polygenic and that very few genes explain more than 5% of the variance of the trait. Moreover, as the complexity of the genome emerges, the role of non-coding genes and regulatory elements cannot be disregarded. Prediction of breeding values from genomic data is discussed in comparison with conventional best linear predictors of breeding values. An example based on real data is given, and the implications in phenotype prediction are discussed in detail. The benefits and limitations of using large SNP sets versus a few very informative markers as predictors of genetic merit of breeding candidates are evaluated using field data as an example.

Polygenic Risk for Schizophrenia Influences Cortical Gyrification in 2 Independent General Populations.

PubMed

Liu, Bing; Zhang, Xiaolong; Cui, Yue; Qin, Wen; Tao, Yan; Li, Jin; Yu, Chunshui; Jiang, Tianzi

2017-05-01

Schizophrenia is highly heritable, whereas the effect of each genetic variant is very weak. Since clinical heterogeneity and complexity of schizophrenia is high, considerable effort has been made to relate genetic variants to underlying neurobiological aspects of schizophrenia (endophenotypes). Given the polygenic nature of schizophrenia, our goal was to form a measure of additive genetic risk and explore its relationship to cortical morphology. Utilizing the data from a recent genome-wide association study that included nearly 37 000 cases of schizophrenia, we computed a polygenic risk score (PGRS) for each subject in 2 independent and healthy general populations. We then investigated the effect of polygenic risk for schizophrenia on cortical gyrification calculated from 3.0T structural imaging data in the discovery dataset (N = 315) and replication dataset (N = 357). We found a consistent effect of the polygenic risk for schizophrenia on cortical gyrification in the inferior parietal lobules in 2 independent general-population samples. A higher PGRS was significantly associated with a lower local gyrification index in the bilateral inferior parietal lobles, where case-control differences have been reported in previous studies on schizophrenia. Our findings strongly support the effectiveness of both PGRSs and endophenotypes in establishing the genetic architecture of psychiatry. Our findings may provide some implications regarding individual differences in the genetic risk for schizophrenia to cortical morphology and brain development. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

[Genetic testing in polygenic diseases : Atrial fibrillation, arterial hypertension and coronary artery disease].

PubMed

Trenkwalder, T; Kessler, T; Schunkert, H

2017-08-01

Genetic testing plays an increasing role in cardiovascular medicine. Advances in technology and the development of novel and more affordable (high throughput) methods have led to the identification of genetic risk factors in research and clinical practice. Also, this progress has simplified the screening of patients and individuals at risk. In case of rare monogenic diseases, diagnostics, risk stratification, and, in some cases, treatment decisions have become easier. For common, polygenic cardiovascular diseases, the situation is more complex due to interaction of modifiable external risk factors and nonmodifiable factors like genetic predisposition. Over the last few years, it has been shown that multiple genes are involved in the pathophysiology of these cardiovascular diseases rather than one single gene. In the following article, we give an overview of the genetic risk factors in polygenic cardiovascular diseases as atrial fibrillation, arterial hypertension and coronary artery disease. Furthermore, we aim to illustrate in which cases genetic testing is recommended in these diseases.

Identification, Replication, and Fine-Mapping of Loci Associated with Adult Height in Individuals of African Ancestry

PubMed Central

Ge, Bing; Tayo, Bamidele; Mathias, Rasika A.; Ding, Jingzhong; Nalls, Michael A.; Adeyemo, Adebowale; Adoue, Véronique; Ambrosone, Christine B.; Atwood, Larry; Bandera, Elisa V.; Becker, Lewis C.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Boerwinkle, Eric; Britton, Angela; Casey, Graham; Chanock, Stephen J.; Demerath, Ellen; Deming, Sandra L.; Diver, W. Ryan; Fox, Caroline; Harris, Tamara B.; Hernandez, Dena G.; Hu, Jennifer J.; Ingles, Sue A.; John, Esther M.; Johnson, Craig; Keating, Brendan; Kittles, Rick A.; Kolonel, Laurence N.; Kritchevsky, Stephen B.; Le Marchand, Loic; Lohman, Kurt; Liu, Jiankang; Millikan, Robert C.; Murphy, Adam; Musani, Solomon; Neslund-Dudas, Christine; North, Kari E.; Nyante, Sarah; Ogunniyi, Adesola; Ostrander, Elaine A.; Papanicolaou, George; Patel, Sanjay; Pettaway, Curtis A.; Press, Michael F.; Redline, Susan; Rodriguez-Gil, Jorge L.; Rotimi, Charles; Rybicki, Benjamin A.; Salako, Babatunde; Schreiner, Pamela J.; Signorello, Lisa B.; Singleton, Andrew B.; Stanford, Janet L.; Stram, Alex H.; Stram, Daniel O.; Strom, Sara S.; Suktitipat, Bhoom; Thun, Michael J.; Witte, John S.; Yanek, Lisa R.; Ziegler, Regina G.; Zheng, Wei; Zhu, Xiaofeng; Zmuda, Joseph M.; Zonderman, Alan B.; Evans, Michele K.; Liu, Yongmei; Becker, Diane M.; Cooper, Richard S.; Pastinen, Tomi; Henderson, Brian E.; Hirschhorn, Joel N.; Lettre, Guillaume; Haiman, Christopher A.

2011-01-01

Adult height is a classic polygenic trait of high heritability (h 2 ∼0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain ∼10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10−12 and 2p14-rs4315565, P = 1.2×10−8). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10−4 for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits. PMID:21998595

The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

PubMed Central

Boardman, Jason D.; Harris, Kathleen Mullan

2018-01-01

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. Although there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social–genetic effects in which polygenic scores of an individual’s friends and schoolmates predict the individual’s own educational attainment. In contrast, an individual’s height is unassociated with the height genetics of peers. PMID:29317533

Rare and low-frequency coding variants alter human adult height

PubMed Central

Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; Justice, Anne E; Lamparter, David; Stirrups, Kathleen E; Turcot, Valérie; Young, Kristin L; Winkler, Thomas W; Esko, Tõnu; Karaderi, Tugce; Locke, Adam E; Masca, Nicholas GD; Ng, Maggie CY; Mudgal, Poorva; Rivas, Manuel A; Vedantam, Sailaja; Mahajan, Anubha; Guo, Xiuqing; Abecasis, Goncalo; Aben, Katja K; Adair, Linda S; Alam, Dewan S; Albrecht, Eva; Allin, Kristine H; Allison, Matthew; Amouyel, Philippe; Appel, Emil V; Arveiler, Dominique; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Banas, Bernhard; Bang, Lia E; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bonnycastle, Lori L; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Burt, Amber A; Butterworth, Adam S; Carey, David J; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Cuellar-Partida, Gabriel; Danesh, John; Davies, Gail; de Bakker, Paul IW; de Borst, Gert J.; de Denus, Simon; de Groot, Mark CH; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Hollander, Anneke I; Dennis, Joe G; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dunning, Alison M; Easton, Douglas F; Ebeling, Tapani; Edwards, Todd L; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Faul, Jessica D; Feitosa, Mary F; Feng, Shuang; Ferrannini, Ele; Ferrario, Marco M; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franks, Paul W; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Giedraitis, Vilmantas; Giri, Ayush; Girotto, Giorgia; Gordon, Scott D; Gordon-Larsen, Penny; Gorski, Mathias; Grarup, Niels; Grove, Megan L.; Gudnason, Vilmundur; Gustafsson, Stefan; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Hayward, Caroline; He, Liang; Heid, Iris M; Heikkilä, Kauko; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Hovingh, G. Kees; Howson, Joanna MM; Hoyng, Carel B; Huang, Paul L; Hveem, Kristian; Ikram, M. Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jhun, Min A; Jia, Yucheng; Jiang, Xuejuan; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jousilahti, Pekka; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon LR; Karpe, Fredrik; Kee, Frank; Keeman, Renske; Kiemeney, Lambertus A; Kitajima, Hidetoshi; Kluivers, Kirsten B; Kocher, Thomas; Komulainen, Pirjo; Kontto, Jukka; Kooner, Jaspal S; Kooperberg, Charles; Kovacs, Peter; Kriebel, Jennifer; Kuivaniemi, Helena; Küry, Sébastien; Kuusisto, Johanna; La Bianca, Martina; Laakso, Markku; Lakka, Timo A; Lange, Ethan M; Lange, Leslie A; Langefeld, Carl D; Langenberg, Claudia; Larson, Eric B; Lee, I-Te; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Yeheng; Liu, Yongmei; Lophatananon, Artitaya; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Mackey, David A; Madden, Pamela AF; Manning, Alisa K; Männistö, Satu; Marenne, Gaëlle; Marten, Jonathan; Martin, Nicholas G; Mazul, Angela L; Meidtner, Karina; Metspalu, Andres; Mitchell, Paul; Mohlke, Karen L; Mook-Kanamori, Dennis O; Morgan, Anna; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Nauck, Matthias; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Ntalla, Ioanna; O'Connel, Jeffrey R; Oksa, Heikki; Loohuis, Loes M Olde; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin NA; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R.B.; Person, Thomas N; Pirie, Ailith; Polasek, Ozren; Posthuma, Danielle; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Reiner, Alex P; Renström, Frida; Ridker, Paul M; Rioux, John D; Robertson, Neil; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sandow, Kevin; Sapkota, Yadav; Sattar, Naveed; Schmidt, Marjanka K; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati; Sim, Xueling; Sivapalaratnam, Suthesh; Small, Kerrin S; Smith, Albert Vernon; Smith, Jennifer A; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Steinthorsdottir, Valgerdur; Stringham, Heather M; Stumvoll, Michael; Surendran, Praveen; Hart, Leen M ‘t; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Ulivi, Sheila; van der Laan, Sander W; Van Der Leij, Andries R; van Duijn, Cornelia M; van Schoor, Natasja M; van Setten, Jessica; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Edwards, Digna R Velez; Vermeulen, Sita H; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Vozzi, Diego; Walker, Mark; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Wareham, Nicholas J; Warren, Helen R; Wessel, Jennifer; Willems, Sara M; Wilson, James G; Witte, Daniel R; Woods, Michael O; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zheng, He; Zhou, Wei; Rotter, Jerome I; Boehnke, Michael; Kathiresan, Sekar; McCarthy, Mark I; Willer, Cristen J; Stefansson, Kari; Borecki, Ingrid B; Liu, Dajiang J; North, Kari E; Heard-Costa, Nancy L; Pers, Tune H; Lindgren, Cecilia M; Oxvig, Claus; Kutalik, Zoltán; Rivadeneira, Fernando; Loos, Ruth JF; Frayling, Timothy M; Hirschhorn, Joel N; Deloukas, Panos; Lettre, Guillaume

2016-01-01

Summary Height is a highly heritable, classic polygenic trait with ∼700 common associated variants identified so far through genome-wide association studies. Here, we report 83 height-associated coding variants with lower minor allele frequencies (range of 0.1-4.8%) and effects of up to 2 cm/allele (e.g. in IHH, STC2, AR and CRISPLD2), >10 times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (+1-2 cm/allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates (e.g. ADAMTS3, IL11RA, NOX4) and pathways (e.g. proteoglycan/glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate to large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways. PMID:28146470

Investigating genetic loci that encode plant-derived paleoclimate proxies

NASA Astrophysics Data System (ADS)

Bender, A. L. D.; Suess, M.; Chitwood, D. H.; Bradley, A. S.

2016-12-01

Long chain (>C25) n-alkanes in sediments predominantly derive from terrestrial plant waxes. Hydrogen isotope ratios (δD) of leaf wax hydrocarbons correlate with δDH2O of precipitation and are commonly used as paleoclimate proxies. However, biological variability in the isotopic fractionations between water and plant materials also affects the n-alkane δD values. Correct interpretation of this paleoclimate proxy requires that we resolve genetic and environmental effects. Genetic variability underlying differences in leaf wax structure and isotopic composition can be quantitatively determined through the use of model organisms. Interfertile Solanum sect. Lycopersicon (tomato) species provide an ideal model species complex for this approach. We used a set of 76 precisely defined near-isogenic lines (introgression lines [ILs]) in which small genomic regions from the wild tomato relative Solanum pennellii have been introduced into the genome of the domestic tomato, S. lycopersicum. By characterizing quantitative traits of these ILs (leaf wax structure and isotopic composition), we can resolve the degree to which each trait is regulated by genetic versus environmental factors. We present data from two growth experiments conducted with all 76 ILs. In this study, we quantify leaf wax traits, including δD values, δ13C values, and structural metrics including the methylation index (a variable that describes the ratio of iso­- and anteiso- to n-alkanes). Among ILs, δD values vary by up to 35‰ and 60‰ for C31 and C33 n-alkanes, respectively. Many ILs have methylation indices that are discernably different from the parent domesticated tomato (p < 0.001), which suggests that methylation is a highly polygenic trait. This pattern is similar to the genetics that control leaf shape, another trait commonly used as a paleoclimate proxy. Based on our preliminary analysis, we propose candidate genes that control aspects of plant physiology that affect these quantitative traits. Our results have important implications for uncovering the degree to which we can expect environmental versus genetic factors to modulate variability in n-alkane δD values. These findings can inform the interpretation of the proxy signal recovered from the geological record.

Single Nucleotide Variants Associated With Polygenic Hypercholesterolemia in Families Diagnosed Clinically With Familial Hypercholesterolemia.

PubMed

Lamiquiz-Moneo, Itziar; Pérez-Ruiz, María Rosario; Jarauta, Estíbaliz; Tejedor, María Teresa; Bea, Ana M; Mateo-Gallego, Rocío; Pérez-Calahorra, Sofía; Baila-Rueda, Lucía; Marco-Benedí, Victoria; de Castro-Orós, Isabel; Cenarro, Ana; Civeira, Fernando

2018-05-01

Approximately 20% to 40% of clinically defined familial hypercholesterolemia cases do not show a causative mutation in candidate genes, and some of them may have a polygenic origin. A cholesterol gene risk score for the diagnosis of polygenic hypercholesterolemia has been demonstrated to be valuable to differentiate polygenic and monogenic hypercholesterolemia. The aim of this study was to determine the contribution to low-density lipoprotein cholesterol (LDL-C) of the single nucleotide variants associated with polygenic hypercholesterolemia in probands with genetic hypercholesterolemia without mutations in candidate genes (nonfamilial hypercholesterolemia genetic hypercholesterolemia) and the genetic score in cascade screening in their family members. We recruited 49 nonfamilial hypercholesterolemia genetic hypercholesterolemia families (294 participants) and calculated cholesterol gene scores, derived from single nucleotide variants in SORT1, APOB, ABCG8, APOE and LDLR and lipoprotein(a) plasma concentration. Risk alleles in SORT1, ABCG8, APOE, and LDLR showed a statistically significantly higher frequency in blood relatives than in the 1000 Genomes Project. However, there were no differences between affected and nonaffected members. The contribution of the cholesterol gene score to LDL-C was significantly higher in affected than in nonaffected participants (P = .048). The percentage of the LDL-C variation explained by the score was 3.1%, and this percentage increased to 6.9% in those families with the highest genetic score in the proband. Nonfamilial hypercholesterolemia genetic hypercholesterolemia families concentrate risk alleles for high LDL-C. Their contribution varies greatly among families, indicating the complexity and heterogeneity of these forms of hypercholesterolemias. The gene score explains a small percentage of LDL-C, which limits its use in diagnosis. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

The genetic architecture of maize height.

PubMed

Peiffer, Jason A; Romay, Maria C; Gore, Michael A; Flint-Garcia, Sherry A; Zhang, Zhiwu; Millard, Mark J; Gardner, Candice A C; McMullen, Michael D; Holland, James B; Bradbury, Peter J; Buckler, Edward S

2014-04-01

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population's variation in maize height, but they may vary in predictive efficacy.

Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.

PubMed

Hall, Lynsey S; Adams, Mark J; Arnau-Soler, Aleix; Clarke, Toni-Kim; Howard, David M; Zeng, Yanni; Davies, Gail; Hagenaars, Saskia P; Maria Fernandez-Pujals, Ana; Gibson, Jude; Wigmore, Eleanor M; Boutin, Thibaud S; Hayward, Caroline; Scotland, Generation; Porteous, David J; Deary, Ian J; Thomson, Pippa A; Haley, Chris S; McIntosh, Andrew M

2018-01-10

Few replicable genetic associations for Major Depressive Disorder (MDD) have been identified. Recent studies of MDD have identified common risk variants by using a broader phenotype definition in very large samples, or by reducing phenotypic and ancestral heterogeneity. We sought to ascertain whether it is more informative to maximize the sample size using data from all available cases and controls, or to use a sex or recurrent stratified subset of affected individuals. To test this, we compared heritability estimates, genetic correlation with other traits, variance explained by MDD polygenic score, and variants identified by genome-wide meta-analysis for broad and narrow MDD classifications in two large British cohorts - Generation Scotland and UK Biobank. Genome-wide meta-analysis of MDD in males yielded one genome-wide significant locus on 3p22.3, with three genes in this region (CRTAP, GLB1, and TMPPE) demonstrating a significant association in gene-based tests. Meta-analyzed MDD, recurrent MDD and female MDD yielded equivalent heritability estimates, showed no detectable difference in association with polygenic scores, and were each genetically correlated with six health-correlated traits (neuroticism, depressive symptoms, subjective well-being, MDD, a cross-disorder phenotype and Bipolar Disorder). Whilst stratified GWAS analysis revealed a genome-wide significant locus for male MDD, the lack of independent replication, and the consistent pattern of results in other MDD classifications suggests that phenotypic stratification using recurrence or sex in currently available sample sizes is currently weakly justified. Based upon existing studies and our findings, the strategy of maximizing sample sizes is likely to provide the greater gain.

Genetic effects influencing risk for major depressive disorder in China and Europe.

PubMed

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-03-28

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log 10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Genetic effects influencing risk for major depressive disorder in China and Europe

PubMed Central

Bigdeli, T B; Ripke, S; Peterson, R E; Trzaskowski, M; Bacanu, S-A; Abdellaoui, A; Andlauer, T F M; Beekman, A T F; Berger, K; Blackwood, D H R; Boomsma, D I; Breen, G; Buttenschøn, H N; Byrne, E M; Cichon, S; Clarke, T-K; Couvy-Duchesne, B; Craddock, N; de Geus, E J C; Degenhardt, F; Dunn, E C; Edwards, A C; Fanous, A H; Forstner, A J; Frank, J; Gill, M; Gordon, S D; Grabe, H J; Hamilton, S P; Hardiman, O; Hayward, C; Heath, A C; Henders, A K; Herms, S; Hickie, I B; Hoffmann, P; Homuth, G; Hottenga, J-J; Ising, M; Jansen, R; Kloiber, S; Knowles, J A; Lang, M; Li, Q S; Lucae, S; MacIntyre, D J; Madden, P A F; Martin, N G; McGrath, P J; McGuffin, P; McIntosh, A M; Medland, S E; Mehta, D; Middeldorp, C M; Milaneschi, Y; Montgomery, G W; Mors, O; Müller-Myhsok, B; Nauck, M; Nyholt, D R; Nöthen, M M; Owen, M J; Penninx, B W J H; Pergadia, M L; Perlis, R H; Peyrot, W J; Porteous, D J; Potash, J B; Rice, J P; Rietschel, M; Riley, B P; Rivera, M; Schoevers, R; Schulze, T G; Shi, J; Shyn, S I; Smit, J H; Smoller, J W; Streit, F; Strohmaier, J; Teumer, A; Treutlein, J; Van der Auwera, S; van Grootheest, G; van Hemert, A M; Völzke, H; Webb, B T; Weissman, M M; Wellmann, J; Willemsen, G; Witt, S H; Levinson, D F; Lewis, C M; Wray, N R; Flint, J; Sullivan, P F; Kendler, K S

2017-01-01

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies. PMID:28350396

Short communication: Genetic association between schizophrenia and cannabis use.

PubMed

Verweij, Karin J H; Abdellaoui, Abdel; Nivard, Michel G; Sainz Cort, Alberto; Ligthart, Lannie; Draisma, Harmen H M; Minică, Camelia C; Gillespie, Nathan A; Willemsen, Gonneke; Hottenga, Jouke-Jan; Boomsma, Dorret I; Vink, Jacqueline M

2017-02-01

Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use. Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation. Polygenic risk scores for schizophrenia were significantly (α<0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of r g =0.22 (SE=0.07, p=0.003) between schizophrenia and lifetime cannabis use. Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Brief Overview of a Decade of Genome-Wide Association Studies on Primary Hypertension.

PubMed

Azam, Afifah Binti; Azizan, Elena Aisha Binti

2018-01-01

Primary hypertension is widely believed to be a complex polygenic disorder with the manifestation influenced by the interactions of genomic and environmental factors making identification of susceptibility genes a major challenge. With major advancement in high-throughput genotyping technology, genome-wide association study (GWAS) has become a powerful tool for researchers studying genetically complex diseases. GWASs work through revealing links between DNA sequence variation and a disease or trait with biomedical importance. The human genome is a very long DNA sequence which consists of billions of nucleotides arranged in a unique way. A single base-pair change in the DNA sequence is known as a single nucleotide polymorphism (SNP). With the help of modern genotyping techniques such as chip-based genotyping arrays, thousands of SNPs can be genotyped easily. Large-scale GWASs, in which more than half a million of common SNPs are genotyped and analyzed for disease association in hundreds of thousands of cases and controls, have been broadly successful in identifying SNPs associated with heart diseases, diabetes, autoimmune diseases, and psychiatric disorders. It is however still debatable whether GWAS is the best approach for hypertension. The following is a brief overview on the outcomes of a decade of GWASs on primary hypertension.

The complex genetics of gait speed: genome-wide meta-analysis approach

PubMed Central

Lunetta, Kathryn L.; Smith, Jennifer A.; Eicher, John D.; Vered, Rotem; Deelen, Joris; Arnold, Alice M.; Buchman, Aron S.; Tanaka, Toshiko; Faul, Jessica D.; Nethander, Maria; Fornage, Myriam; Adams, Hieab H.; Matteini, Amy M.; Callisaya, Michele L.; Smith, Albert V.; Yu, Lei; De Jager, Philip L.; Evans, Denis A.; Gudnason, Vilmundur; Hofman, Albert; Pattie, Alison; Corley, Janie; Launer, Lenore J.; Knopman, Davis S.; Parimi, Neeta; Turner, Stephen T.; Bandinelli, Stefania; Beekman, Marian; Gutman, Danielle; Sharvit, Lital; Mooijaart, Simon P.; Liewald, David C.; Houwing-Duistermaat, Jeanine J.; Ohlsson, Claes; Moed, Matthijs; Verlinden, Vincent J.; Mellström, Dan; van der Geest, Jos N.; Karlsson, Magnus; Hernandez, Dena; McWhirter, Rebekah; Liu, Yongmei; Thomson, Russell; Tranah, Gregory J.; Uitterlinden, Andre G.; Weir, David R.; Zhao, Wei; Starr, John M.; Johnson, Andrew D.; Ikram, M. Arfan; Bennett, David A.; Cummings, Steven R.; Deary, Ian J.; Harris, Tamara B.; Kardia, Sharon L. R.; Mosley, Thomas H.; Srikanth, Velandai K.; Windham, Beverly G.; Newman, Ann B.; Walston, Jeremy D.; Davies, Gail; Evans, Daniel S.; Slagboom, Eline P.; Ferrucci, Luigi; Kiel, Douglas P.; Murabito, Joanne M.; Atzmon, Gil

2017-01-01

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging. PMID:28077804

Metabolic syndrome-related composite factors over 5 years in the STANISLAS family study: genetic heritability and common environmental influences.

PubMed

Herbeth, Bernard; Samara, Anastasia; Ndiaye, Coumba; Marteau, Jean-Brice; Berrahmoune, Hind; Siest, Gérard; Visvikis-Siest, Sophie

2010-06-03

We estimated genetic heritability and common environmental influences for various traits related to metabolic syndrome in young families from France. At entrance and after 5 years, nineteen traits related to metabolic syndrome were measured in a sample of families drawn from the STANISLAS study. In addition, 5 aggregates of these traits were identified using factor analysis. At entrance, genetic heritability was high (20 to 44%) for plasma lipids and lipoproteins, uric acid, fasting glucose, and the related clusters "risk lipids" and "protective lipids". Intermediate or low genetic heritability (less than 20%) was shown for triglycerides, adiposity indices, blood pressure, hepatic enzyme activity, inflammatory makers and the related clusters: "liver enzymes", "adiposity/blood pressure" and "inflammation". Moreover, common environmental influences were significant for all the parameters. With regard to 5-year changes, polygenic variance was low and not statistically significant for any of the individual variables or clusters whereas shared environment influence was significant. In these young families, genetic heritability of metabolic syndrome-related traits was generally lower than previously reported while the common environmental influences were greater. In addition, only shared environment contributed to short-term changes of these traits. Copyright 2010 Elsevier B.V. All rights reserved.

Public health genomics and personalized prevention: lessons from the COGS project.

PubMed

Pashayan, N; Hall, A; Chowdhury, S; Dent, T; Pharoah, P D P; Burton, H

2013-11-01

Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with 'one-size-fits-all' screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed. © 2013 The Association for the Publication of the Journal of Internal Medicine.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

PubMed

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

2017-06-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

PubMed Central

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Smith, George Davey; de Geus, Eco JCN; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian’an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O’Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Velez Edwards, Digna R; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

2018-01-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10−8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility. PMID:28436984

Characterizing the genetic influences on risk aversion.

PubMed

Harrati, Amal

2014-01-01

Risk aversion has long been cited as an important factor in retirement decisions, investment behavior, and health. Some of the heterogeneity in individual risk tolerance is well understood, reflecting age gradients, wealth gradients, and similar effects, but much remains unexplained. This study explores genetic contributions to heterogeneity in risk aversion among older Americans. Using over 2 million genetic markers per individual from the U.S. Health and Retirement Study, I report results from a genome-wide association study (GWAS) on risk preferences using a sample of 10,455 adults. None of the single-nucleotide polymorphisms (SNPs) are found to be statistically significant determinants of risk preferences at levels stricter than 5 × 10(-8). These results suggest that risk aversion is a complex trait that is highly polygenic. The analysis leads to upper bounds on the number of genetic effects that could exceed certain thresholds of significance and still remain undetected at the current sample size. The findings suggest that the known heritability in risk aversion is likely to be driven by large numbers of genetic variants, each with a small effect size.

Integrating Genetics and Social Science: Genetic Risk Scores

PubMed Central

Belsky, Daniel W.; Israel, Salomon

2014-01-01

The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry. PMID:25343363

Genetics and Psychopharmacology: Prospects for Individualized Treatment

PubMed Central

Nnadi, Charles U.; Goldberg, Joseph F.; Malhotra, Anil K.

2008-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to indicate a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices. PMID:16041916

Genetics and psychopharmacology: prospects for individualized treatment.

PubMed

Nnadi, Charles U; Goldberg, Joseph F; Malhotra, Anil K

2005-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to predict a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices.

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae.

PubMed

García-Ríos, Estéfani; Morard, Miguel; Parts, Leopold; Liti, Gianni; Guillamón, José M

2017-02-14

Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci. In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions' adaptive nature. The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.

An analysis of variation in expression of neurofibromatosis (NF) type I (NFI): Evidence for modifying genes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Easton, D.F.; Ponder, B.A.J.; Huson, S.M.

Neurofibromatosis (NF) type 1 (NF1) is notable for its variable expression. To determine whether variation in expression has an inherited component, the authors examined 175 individuals in 48 NF families, including six MZ twin pairs. Three quantitative traits were scored - number of cafe-au-lait patches, number of cutaneous neurofibromas, and head circumference; and five binary traits were scored - the presence or absence of plexiform neurofibromas, optic gliomas, scoliosis, epilepsy, and referral for remedial education. For cafe-au-lait patches and neurofibromas, correlation was highest between MZ twins, less high between first-degree relatives, and lower still between more distant relatives. The highmore » correlation between distant relatives suggests that the type of mutation at the NF1 locus itself plays only a minor role. All of the five binary traits, with the exception of plexiformneurofibromas, also showed significant familial clustering. The familial effects for these traits were consistent with polygenic effects, but there were insufficient data to rule out other models, including a significant effect of different NF1 mutations. There was no evidence of any association between the different traits in affected individuals. The authors conclude that the phenotypic expression of NF1 is to a large extent determined by the genotype at other [open quotes]modifying[close quotes] loci and that these modifying genes are trait specific. 22 refs., 8 tabs.« less

SRC-2 orchestrates polygenic inputs for fine-tuning glucose homeostasis

PubMed Central

Fleet, Tiffany; Zhang, Bin; Lin, Fumin; Zhu, Bokai; Dasgupta, Subhamoy; Stashi, Erin; Tackett, Bryan; Thevananther, Sundararajah; Rajapakshe, Kimal I.; Gonzales, Naomi; Dean, Adam; Mao, Jianqiang; Timchenko, Nikolai; Malovannaya, Anna; Qin, Jun; Coarfa, Cristian; DeMayo, Francesco; Dacso, Clifford C.; Foulds, Charles E.; O’Malley, Bert W.; York, Brian

2015-01-01

Despite extensive efforts to understand the monogenic contributions to perturbed glucose homeostasis, the complexity of genetic events that fractionally contribute to the spectrum of this pathology remain poorly understood. Proper maintenance of glucose homeostasis is the central feature of a constellation of comorbidities that define the metabolic syndrome. The ability of the liver to balance carbohydrate uptake and release during the feeding-to-fasting transition is essential to the regulation of peripheral glucose availability. The liver coordinates the expression of gene programs that control glucose absorption, storage, and secretion. Herein, we demonstrate that Steroid Receptor Coactivator 2 (SRC-2) orchestrates a hierarchy of nutritionally responsive transcriptional complexes to precisely modulate plasma glucose availability. Using DNA pull-down technology coupled with mass spectrometry, we have identified SRC-2 as an indispensable integrator of transcriptional complexes that control the rate-limiting steps of hepatic glucose release and accretion. Collectively, these findings position SRC-2 as a major regulator of polygenic inputs to metabolic gene regulation and perhaps identify a previously unappreciated model that helps to explain the clinical spectrum of glucose dysregulation. PMID:26487680

Strategy and model building in the fourth dimension: a null model for genotype x age interaction as a Gaussian stationary stochastic process.

PubMed

Diego, Vincent P; Almasy, Laura; Dyer, Thomas D; Soler, Júlia M P; Blangero, John

2003-12-31

Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype x age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. We found evidence for genotype x age interaction for fasting glucose and systolic blood pressure. There is polygenic genotype x age interaction for fasting glucose and systolic blood pressure and quantitative trait locus x age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM.

An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures.

PubMed

Kang, Eun Yong; Lee, Cue Hyunkyu; Furlotte, Nicholas A; Joo, Jong Wha J; Kostem, Emrah; Zaitlen, Noah; Eskin, Eleazar; Han, Buhm

2018-05-11

Over the past few years, genome-wide association studies have identified many trait-associated loci that have different effects on females and males, which increased attention to the genetic architecture differences between the sexes. The between-sex differences in genetic architectures can cause a variety of phenomena such as differences in the effect sizes at trait-associated loci, differences in the magnitudes of polygenic background effects, and differences in the phenotypic variances. However, current association testing approaches for dealing with sex, such as including sex as a covariate, cannot fully account for these phenomena and can be suboptimal in statistical power. We present a novel association mapping framework, MetaSex, that can comprehensively account for the genetic architecture differences between the sexes. Through simulations and applications to real data, we show that our framework has superior performance than previous approaches in association mapping. Copyright © 2018, Genetics.

Targeted Recombinant Progeny: a design for ultra-high resolution mapping of Quantitative Trait Loci in crosses between inbred or pure lines.

PubMed

Heifetz, Eliyahu M; Soller, Morris

2015-07-07

High-resolution mapping of the loci (QTN) responsible for genetic variation in quantitative traits is essential for positional cloning of candidate genes, and for effective marker assisted selection. The confidence interval (QTL) flanking the point estimate of QTN-location is proportional to the number of individuals in the mapping population carrying chromosomes recombinant in the given interval. Consequently, many designs for high resolution QTN mapping are based on increasing the proportion of recombinants in the mapping population. The "Targeted Recombinant Progeny" (TRP) design is a new design for high resolution mapping of a target QTN in crosses between pure, or inbred lines. It is a three-generation procedure generating a large number of recombinant individuals within a QTL previously shown to contain a QTN. This is achieved by having individuals that carry chromosomes recombinant across the target QTL interval as parents of a large mapping population; most of whom will therefore carry recombinant chromosomes targeted to the given QTL. The TRP design is particularly useful for high resolution mapping of QTN that differentiate inbred or pure lines, and hence are not amenable to high resolution mapping by genome-wide association tests. In the absence of residual polygenic variation, population sizes required for achieving given mapping resolution by the TRP-F2 design relative to a standard F2 design ranged from 0.289 for a QTN with standardized allele substitution effect = 0.2, mapped to an initial QTL of 0.2 Morgan to 0.041 for equivalent QTN mapped to an initial QTL of 0.02 M. In the presence of residual polygenic variation, the relative effectiveness of the TRP design ranges from 1.068 to 0.151 for the same initial QTL intervals and QTN effect. Thus even in the presence of polygenic variation, the TRP can still provide major savings. Simulation showed that mapping by TRP should be based on 30-50 markers spanning the initial interval; and on at least 50 or more G2 families representing this number of recombination points,. The TRP design can be an effective procedure for achieving high and ultra-high mapping resolution of a target QTN previously mapped to a known confidence interval (QTL).

Rare and low-frequency coding variants alter human adult height.

PubMed

Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; Justice, Anne E; Lamparter, David; Stirrups, Kathleen E; Turcot, Valérie; Young, Kristin L; Winkler, Thomas W; Esko, Tõnu; Karaderi, Tugce; Locke, Adam E; Masca, Nicholas G D; Ng, Maggie C Y; Mudgal, Poorva; Rivas, Manuel A; Vedantam, Sailaja; Mahajan, Anubha; Guo, Xiuqing; Abecasis, Goncalo; Aben, Katja K; Adair, Linda S; Alam, Dewan S; Albrecht, Eva; Allin, Kristine H; Allison, Matthew; Amouyel, Philippe; Appel, Emil V; Arveiler, Dominique; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Banas, Bernhard; Bang, Lia E; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bonnycastle, Lori L; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Burt, Amber A; Butterworth, Adam S; Carey, David J; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Cuellar-Partida, Gabriel; Danesh, John; Davies, Gail; de Bakker, Paul I W; de Borst, Gert J; de Denus, Simon; de Groot, Mark C H; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Hollander, Anneke I; Dennis, Joe G; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dunning, Alison M; Easton, Douglas F; Ebeling, Tapani; Edwards, Todd L; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Faul, Jessica D; Feitosa, Mary F; Feng, Shuang; Ferrannini, Ele; Ferrario, Marco M; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franks, Paul W; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Giedraitis, Vilmantas; Giri, Ayush; Girotto, Giorgia; Gordon, Scott D; Gordon-Larsen, Penny; Gorski, Mathias; Grarup, Niels; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Hayward, Caroline; He, Liang; Heid, Iris M; Heikkilä, Kauko; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna M M; Hoyng, Carel B; Huang, Paul L; Hveem, Kristian; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jhun, Min A; Jia, Yucheng; Jiang, Xuejuan; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jousilahti, Pekka; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon L R; Karpe, Fredrik; Kee, Frank; Keeman, Renske; Kiemeney, Lambertus A; Kitajima, Hidetoshi; Kluivers, Kirsten B; Kocher, Thomas; Komulainen, Pirjo; Kontto, Jukka; Kooner, Jaspal S; Kooperberg, Charles; Kovacs, Peter; Kriebel, Jennifer; Kuivaniemi, Helena; Küry, Sébastien; Kuusisto, Johanna; La Bianca, Martina; Laakso, Markku; Lakka, Timo A; Lange, Ethan M; Lange, Leslie A; Langefeld, Carl D; Langenberg, Claudia; Larson, Eric B; Lee, I-Te; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Yeheng; Liu, Yongmei; Lophatananon, Artitaya; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Mackey, David A; Madden, Pamela A F; Manning, Alisa K; Männistö, Satu; Marenne, Gaëlle; Marten, Jonathan; Martin, Nicholas G; Mazul, Angela L; Meidtner, Karina; Metspalu, Andres; Mitchell, Paul; Mohlke, Karen L; Mook-Kanamori, Dennis O; Morgan, Anna; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Nauck, Matthias; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Ntalla, Ioanna; O'Connel, Jeffrey R; Oksa, Heikki; Loohuis, Loes M Olde; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin N A; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R B; Person, Thomas N; Pirie, Ailith; Polasek, Ozren; Posthuma, Danielle; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Reiner, Alex P; Renström, Frida; Ridker, Paul M; Rioux, John D; Robertson, Neil; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sandow, Kevin; Sapkota, Yadav; Sattar, Naveed; Schmidt, Marjanka K; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati; Sim, Xueling; Sivapalaratnam, Suthesh; Small, Kerrin S; Smith, Albert Vernon; Smith, Jennifer A; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Steinthorsdottir, Valgerdur; Stringham, Heather M; Stumvoll, Michael; Surendran, Praveen; 't Hart, Leen M; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Ulivi, Sheila; van der Laan, Sander W; Van Der Leij, Andries R; van Duijn, Cornelia M; van Schoor, Natasja M; van Setten, Jessica; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Edwards, Digna R Velez; Vermeulen, Sita H; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Vozzi, Diego; Walker, Mark; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Wareham, Nicholas J; Warren, Helen R; Wessel, Jennifer; Willems, Sara M; Wilson, James G; Witte, Daniel R; Woods, Michael O; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zheng, He; Zhou, Wei; Rotter, Jerome I; Boehnke, Michael; Kathiresan, Sekar; McCarthy, Mark I; Willer, Cristen J; Stefansson, Kari; Borecki, Ingrid B; Liu, Dajiang J; North, Kari E; Heard-Costa, Nancy L; Pers, Tune H; Lindgren, Cecilia M; Oxvig, Claus; Kutalik, Zoltán; Rivadeneira, Fernando; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Deloukas, Panos; Lettre, Guillaume

2017-02-09

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity

PubMed Central

Athanasiadis, Georgios; Cheng, Jade Y.; Vilhjálmsson, Bjarni J.; Jørgensen, Frank G.; Als, Thomas D.; Le Hellard, Stephanie; Espeseth, Thomas; Sullivan, Patrick F.; Hultman, Christina M.; Kjærgaard, Peter C.; Schierup, Mikkel H.; Mailund, Thomas

2016-01-01

Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country. PMID:27535931

Detection of quantitative trait loci causing abnormal spermatogenesis and reduced testis weight in the small testis (Smt) mutant mouse.

PubMed

Bolor, Hasbaira; Wakasugi, Noboru; Zhao, Wei Dong; Ishikawa, Akira

2006-04-01

The small testis (Smt) mutant mouse is characterized by a small testis of one third to one half the size of a normal testis, and its spermatogenesis is mostly arrested at early stages of meiosis, although a small number of spermatocytes at the late prophase of meiosis and a few spermatids can sometimes be seen. We performed quantitative trait locus (QTL) analysis of these spermatogenic traits and testis weight using 221 F2 males obtained from a cross between Smt and MOM (Mus musculus molossinus) mice. At the genome-wide 5% level, we detected two QTLs affecting meiosis on chromosomes 4 and 13, and two QTLs for paired testis weight as a percentage of body weight on chromosomes 4 and X. In addition, we found several QTLs for degenerated germ cells and multinuclear giant cells on chromosomes 4, 7 and 13. Interestingly, for cell degeneration, the QTL on chromosome 13 interacted epistatically with the QTL on chromosome 4. These results reveal polygenic participation in the abnormal spermatogenesis and small testis size in the Smt mutant.

Predictive accuracy of combined genetic and environmental risk scores.

PubMed

Dudbridge, Frank; Pashayan, Nora; Yang, Jian

2018-02-01

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.

Predictive accuracy of combined genetic and environmental risk scores

PubMed Central

Pashayan, Nora; Yang, Jian

2017-01-01

ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508

Common polygenic variation contributes to risk of schizophrenia that overlaps with bipolar disorder

PubMed Central

2013-01-01

Schizophrenia (SCZ) is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits with heritability estimated at up to 80%1,2. We adopted two analytic approaches to determine the extent to which common genetic variation underlies risk of SCZ using genome-wide association study (GWAS) data from 3,322 European individuals with SCZ and 3,587 controls. First, we implicate the major histocompatibility complex (MHC). Second, we provide molecular genetic evidence for a substantial polygenic component to risk of SCZ involving thousands of common alleles of very small effect. We show that this component also contributes to risk of bipolar disorder (BPD), but not to multiple non-psychiatric diseases. PMID:19571811

Individual Differences in Amygdala-Medial Prefrontal Anatomy Link Negative Affect, Impaired Social Functioning, and Polygenic Depression Risk

PubMed Central

Holmes, Avram J.; Lee, Phil H.; Hollinshead, Marisa O.; Bakst, Leah; Roffman, Joshua L.; Smoller, Jordan W.; Buckner, Randy L.

2013-01-01

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n = 206) and emotional (n = 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala–mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n = 438) using risk scores derived from a large genome-wide association analysis (n = 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala–mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD. PMID:23238724

Application of linear mixed models to study genetic stability of height and body mass index across countries and time.

PubMed

Trzaskowski, Maciej; Lichtenstein, Paul; Magnusson, Patrik K; Pedersen, Nancy L; Plomin, Robert

2016-01-27

It is now possible to estimate genetic correlations between two independent samples when there is no overlapping phenotypic information. We applied the latest bivariate genomic methods to children in the UK and older adults in Sweden to ask two questions. Are the same variants driving individual differences in anthropometric traits in these two populations, and are these variants as important in childhood as they are later in life? A sample of 3152 11-year-old children in the UK was compared with a sample of 6813 adults with an average age of 65 in Sweden. Genotypes were imputed from 1000 genomes with combined 9 767 136 single nucleotide polymorphisms meeting quality control criteria in both samples. Two cross-sample GCTA-GREML analyses and linkage disequilibrium (LD) score regressions were conducted to assess genetic correlations across more than 50 years: child versus adult height and child versus adult body mass index (BMI). Consistency of effects was tested using the recently proposed polygenic scoring method. For height, GCTA-GREML and LD score indicated strong genetic stability between children and adults, 0.58 (0.16) and 1.335 (1.09), respectively. For BMI, both methods produced similarly strong estimates of genetic stability 0.75 (0.26) and 0.855 (0.49), respectively. In height, adult polygenic score explained 60% of genetic variance in childhood and 10% of variance in BMI. Here we replicated and extended previous findings of longitudinal genetic stability in anthropometric traits to cross-cultural dimensions, and showed that for height but not BMI these variants are as important in childhood as they are in adulthood. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Two candidate genes for two quantitative trait loci epistatically attenuate hypertension in a novel pathway.

PubMed

Chauvet, Cristina; Ménard, Annie; Deng, Alan Y

2015-09-01

Multiple quantitative trait loci (QTLs) for blood pressure (BP) have been detected in rat models of human polygenic hypertension. They influence BP physiologically via epistatic modules. Little is known about the causal genes and virtually nothing is known on modularized mechanisms governing their regulatory connections. Two genes responsible for two individual BP QTLs on rat Chromosome 18 have been identified that belong to the same epistatic module. Treacher Collins-Franceschetti syndrome 1 (Tcof1) gene is the only function candidate for C18QTL3. Haloacid dehalogenase like hydrolase domain containing 2 (Hdhd2), although a gene of previously unknown function, is C18QTL4, and encodes a newly identified phosphatase. The current work has provided the premier evidence that Hdhd2/C18QTL4 and Tcof1/C18QTL3 may be involved in polygenic hypertension. Hdhd2/C18QTL4 can regulate the function of Tcof1/C18QTL3 via de-phosphorylation, and, for the first time, furbishes a molecular mechanism in support of a genetically epistatic hierarchy between two BP QTLs, and thus authenticates the epistasis-common pathway paradigm. The pathway initiated by Hdhd2/C18QTL4 upstream of Tcof1/C18QTL3 reveals novel mechanistic insights into BP modulations. Their discovery might yield innovative therapeutic targets and diagnostic tools predicated on a novel BP cause and mechanism that is determined by a regulatory hierarchy. Optimizing the de-phosphorylation capability and its downstream target could be antihypertensive. The conceptual paradigm of an order and regulatory hierarchy may help unravel genetic and molecular relationships among certain human BP QTLs.

PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

PubMed

Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X

2016-05-01

The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

Genetic risk for neurodegenerative disorders, and its overlap with cognitive ability and physical function.

PubMed

Hagenaars, Saskia P; Radaković, Ratko; Crockford, Christopher; Fawns-Ritchie, Chloe; Harris, Sarah E; Gale, Catharine R; Deary, Ian J

2018-01-01

Neurodegenerative disorders are associated with impaired cognitive function and worse physical health outcomes. This study aims to test whether polygenic risk for Alzheimer's disease, Amyotrophic Lateral Sclerosis (ALS), or frontotemporal dementia (FTD) is associated with cognitive function and physical health in the UK Biobank, a cohort of healthy individuals. Group-based analyses were then performed to compare the top and bottom 10% for the three neurodegenerative polygenic risk scores; these groups were compared on the cognitive and physical health variables. Higher polygenic risk for AD, ALS, and FTD was associated with lower cognitive performance. Higher polygenic risk for FTD was also associated with increased forced expiratory volume in 1s and peak expiratory flow. A significant group difference was observed on the symbol digit substitution task between individuals with high polygenic risk for FTD and high polygenic risk for ALS. The results suggest some overlap between polygenic risk for neurodegenerative disorders, cognitive function and physical health.

Ecosensitivity and genetic polymorphism of somatic traits in the perinatal development of twins.

PubMed

Waszak, Małgorzata; Cieślik, Krystyna; Skrzypczak-Zielińska, Marzena; Szalata, Marlena; Wielgus, Karolina; Kempiak, Joanna; Bręborowicz, Grzegorz; Słomski, Ryszard

2016-04-01

In view of criticism regarding the usefulness of heritability coefficients, the aim of this study was to analyze separately the information on genetic and environmental variability. Such an approach, based on the normalization of trait's variability for its value, is determined by the coefficients of genetic polymorphism (Pg) and ecosensitivity (De). The studied material included 1263 twin pairs of both sexes (among them 424 pairs of monozygotic twins and 839 pairs of dizygotic twins) born between the 22nd and 41st week of gestation. Variability of six somatic traits was analyzed. The zygosity of same-sex twins was determined based on the polymorphism of DNA from lymphocytes of the umbilical cord blood, obtained at birth. The coefficients of genetic polymorphism and ecosensitivity for analyzed traits of male and female twins born at various months of gestation were calculated. Our study revealed that a contribution of the genetic component predominated over that of the environmental component in determining the phenotypic variability of somatic traits of newborns from twin pregnancies. The genetically determined phenotypic variability in male twins was greater than in the females. The genetic polymorphism and ecosensitivity of somatic traits were relatively stable during the period of fetal ontogeny analyzed in this study. Only in the case of body weight, a slight increase in the genetic contribution of polygenes to the phenotypic variance could be observed with gestational age, along with a slight decrease in the influence of environmental factors. Copyright © 2015 Elsevier GmbH. All rights reserved.

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development

PubMed Central

Germine, L; Robinson, E B; Smoller, J W; Calkins, M E; Moore, T M; Hakonarson, H; Daly, M J; Lee, P H; Holmes, A J; Buckner, R L; Gur, R C; Gur, R E

2016-01-01

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8–21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18–35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development. PMID:27754483

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development.

PubMed

Germine, L; Robinson, E B; Smoller, J W; Calkins, M E; Moore, T M; Hakonarson, H; Daly, M J; Lee, P H; Holmes, A J; Buckner, R L; Gur, R C; Gur, R E

2016-10-18

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8-21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18-35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development.

Association of Autistic Traits With Depression From Childhood to Age 18 Years.

PubMed

Rai, Dheeraj; Culpin, Iryna; Heuvelman, Hein; Magnusson, Cecilia M K; Carpenter, Peter; Jones, Hannah J; Emond, Alan M; Zammit, Stanley; Golding, Jean; Pearson, Rebecca M

2018-06-13

Population-based studies following trajectories of depression in autism spectrum disorders (ASD) from childhood into early adulthood are rare. The role of genetic confounding and of potential environmental intermediaries, such as bullying, in any associations is unclear. To compare trajectories of depressive symptoms from ages 10 to 18 years for children with or without ASD and autistic traits, to assess associations between ASD and autistic traits and an International Statistical Classification of Diseases, 10th Revision (ICD-10) depression diagnosis at age 18 years, and to explore the importance of genetic confounding and bullying. Longitudinal study of participants in the Avon Longitudinal Study of Parents and Children birth cohort in Bristol, United Kingdom, followed up through age 18 years. Data analysis was conducted from January to November 2017. Depressive symptoms were assessed using the Short Mood and Feelings Questionnaire (SMFQ) at 6 time points between ages 10 and 18 years. An ICD-10 depression diagnosis at age 18 years was established using the Clinical Interview Schedule-Revised. Exposures were ASD diagnosis and 4 dichotomized autistic traits (social communication, coherence, repetitive behavior, and sociability). An autism polygenic risk score was derived using the Psychiatric Genomics Consortium autism discovery genome-wide association study summary data. Bullying was assessed at ages 8, 10, and 13 years. The maximum sample with complete data was 6091 for the trajectory analysis (48.8% male) and 3168 for analysis of depression diagnosis at age 18 years (44.4% male). Children with ASD and autistic traits had higher average SMFQ depressive symptom scores than the general population at age 10 years (eg, for social communication 5.55 [95% CI, 5.16-5.95] vs 3.73 [95% CI, 3.61-3.85], for ASD 7.31 [95% CI, 6.22-8.40] vs 3.94 [95% CI, 3.83-4.05], remaining elevated in an upward trajectory until age 18 years (eg, for social communication 7.65 [95% CI, 6.92-8.37] vs 6.50 [95% CI, 6.29-6.71], for ASD 7.66 [95% CI, 5.96-9.35] vs 6.62 [95% CI, 6.43-6.81]). Social communication impairments were associated with depression at age 18 years (adjusted relative risk, 1.68; 95% CI, 1.05-2.70), and bullying explained a substantial proportion of this risk. There was no evidence of confounding by the autism polygenic risk score. Analysis in larger samples using multiple imputation led to similar but more precise results. Children with ASD and ASD traits have higher depressive symptom scores than the general population by age 10 years, which persist to age 18 years, particularly in the context of bullying. Social communication impairments are an important autistic trait in relation to depression. Bullying, as an environmental intermediary, could be a target for interventions.

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

PubMed Central

Morton, Nicholas M.; Nelson, Yvonne B.; Michailidou, Zoi; Di Rollo, Emma M.; Ramage, Lynne; Hadoke, Patrick W. F.; Seckl, Jonathan R.; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J.; Dunbar, Donald R.

2011-01-01

Background Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. Results To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. Conclusions A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity. PMID:21915269

A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes.

PubMed

Morton, Nicholas M; Nelson, Yvonne B; Michailidou, Zoi; Di Rollo, Emma M; Ramage, Lynne; Hadoke, Patrick W F; Seckl, Jonathan R; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J; Dunbar, Donald R

2011-01-01

Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

Converging evidence for an impact of a functional NOS gene variation on anxiety-related processes

PubMed Central

Haaker, Jan; Glotzbach-Schoon, Evelyn; Schümann, Dirk; Andreatta, Marta; Mechias, Marie-Luise; Raczka, Karolina; Gartmann, Nina; Büchel, Christian; Mühlberger, Andreas; Pauli, Paul; Reif, Andreas; Kalisch, Raffael; Lonsdorf, Tina B.

2016-01-01

Abstract Being a complex phenotype with substantial heritability, anxiety and related phenotypes are characterized by a complex polygenic basis. Thereby, one candidate pathway is neuronal nitric oxide (NO) signaling, and accordingly, rodent studies have identified NO synthase (NOS-I), encoded by NOS1, as a strong molecular candidate for modulating anxiety and hippocampus-dependent learning processes. Using a multi-dimensional and -methodological replication approach, we investigated the impact of a functional promoter polymorphism (NOS1-ex1f-VNTR) on human anxiety-related phenotypes in a total of 1019 healthy controls in five different studies. Homozygous carriers of the NOS1-ex1f short-allele displayed enhanced trait anxiety, worrying and depression scores. Furthermore, short-allele carriers were characterized by increased anxious apprehension during contextual fear conditioning. While autonomous measures (fear-potentiated startle) provided only suggestive evidence for a modulatory role of NOS1-ex1f-VNTR on (contextual) fear conditioning processes, neural activation at the amygdala/anterior hippocampus junction was significantly increased in short-allele carriers during context conditioning. Notably, this could not be attributed to morphological differences. In accordance with data from a plethora of rodent studies, we here provide converging evidence from behavioral, subjective, psychophysiological and neuroimaging studies in large human cohorts that NOS-I plays an important role in anxious apprehension but provide only limited evidence for a role in (contextual) fear conditioning. PMID:26746182

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability

PubMed Central

Chen, Huan; Gu, Xiao-hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-01-01

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10−10, maximum β −2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level. PMID:28155865

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability.

PubMed

Chen, Huan; Gu, Xiao-Hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-02-03

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10 -10 , maximum β -2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level.

Quantitative trait loci for magnitude of the plasma cortisol response to confinement in rainbow trout.

PubMed

Quillet, E; Krieg, F; Dechamp, N; Hervet, C; Bérard, A; Le Roy, P; Guyomard, R; Prunet, P; Pottinger, T G

2014-04-01

Better understanding of the mechanisms underlying interindividual variation in stress responses and their links with production traits is a key issue for sustainable animal breeding. In this study, we searched for quantitative trait loci (QTL) controlling the magnitude of the plasma cortisol stress response and compared them to body size traits in five F2 full-sib families issued from two rainbow trout lines divergently selected for high or low post-confinement plasma cortisol level. Approximately 1000 F2 individuals were individually tagged and exposed to two successive acute confinement challenges (1 month interval). Post-stress plasma cortisol concentrations were determined for each fish. A medium density genome scan was carried out (268 markers, overall marker spacing less than 10 cM). QTL detection was performed using qtlmap software, based on an interval mapping method (http://www.inra.fr/qtlmap). Overall, QTL of medium individual effects on cortisol responsiveness (<10% of phenotypic variance) were detected on 18 chromosomes, strongly supporting the hypothesis that control of the trait is polygenic. Although a core array of QTL controlled cortisol concentrations at both challenges, several QTL seemed challenge specific, suggesting that responses to the first and to a subsequent exposure to the confinement stressor are distinct traits sharing only part of their genetic control. Chromosomal location of the steroidogenic acute regulatory protein (STAR) makes it a good potential candidate gene for one of the QTL. Finally, comparison of body size traits QTL (weight, length and body conformation) with cortisol-associated QTL did not support evidence for negative genetic relationships between the two types of traits. © 2014 Stichting International Foundation for Animal Genetics.

Genetic Association of Waist-to-Hip Ratio With Cardiometabolic Traits, Type 2 Diabetes, and Coronary Heart Disease.

PubMed

Emdin, Connor A; Khera, Amit V; Natarajan, Pradeep; Klarin, Derek; Zekavat, Seyedeh M; Hsiao, Allan J; Kathiresan, Sekar

2017-02-14

In observational studies, abdominal adiposity has been associated with type 2 diabetes and coronary heart disease (CHD). Whether these associations represent causal relationships remains uncertain. To test the association of a polygenic risk score for waist-to-hip ratio (WHR) adjusted for body mass index (BMI), a measure of abdominal adiposity, with type 2 diabetes and CHD through the potential intermediates of blood lipids, blood pressure, and glycemic phenotypes. A polygenic risk score for WHR adjusted for BMI, a measure of genetic predisposition to abdominal adiposity, was constructed with 48 single-nucleotide polymorphisms. The association of this score with cardiometabolic traits, type 2 diabetes, and CHD was tested in a mendelian randomization analysis that combined case-control and cross-sectional data sets. Estimates for cardiometabolic traits were based on a combined data set consisting of summary results from 4 genome-wide association studies conducted from 2007 to 2015, including up to 322 154 participants, as well as individual-level, cross-sectional data from the UK Biobank collected from 2007-2011, including 111 986 individuals. Estimates for type 2 diabetes and CHD were derived from summary statistics of 2 separate genome-wide association studies conducted from 2007 to 2015 and including 149 821 individuals and 184 305 individuals, respectively, combined with individual-level data from the UK Biobank. Genetic predisposition to increased WHR adjusted for BMI. Type 2 diabetes and CHD. Among 111 986 individuals in the UK Biobank, the mean age was 57 (SD, 8) years, 58 845 participants (52.5%) were women, and mean WHR was 0.875. Analysis of summary-level genome-wide association study results and individual-level UK Biobank data demonstrated that a 1-SD increase in WHR adjusted for BMI mediated by the polygenic risk score was associated with 27-mg/dL higher triglyceride levels, 4.1-mg/dL higher 2-hour glucose levels, and 2.1-mm Hg higher systolic blood pressure (each P < .001). A 1-SD genetic increase in WHR adjusted for BMI was also associated with a higher risk of type 2 diabetes (odds ratio, 1.77 [95% CI, 1.57-2.00]; absolute risk increase per 1000 participant-years, 6.0 [95% CI, CI, 4.4-7.8]; number of participants with type 2 diabetes outcome, 40 530) and CHD (odds ratio, 1.46 [95% CI, 1.32-1.62]; absolute risk increase per 1000 participant-years, 1.8 [95% CI, 1.3-2.4]; number of participants with CHD outcome, 66 440). A genetic predisposition to higher waist-to-hip ratio adjusted for body mass index was associated with increased risk of type 2 diabetes and coronary heart disease. These results provide evidence supportive of a causal association between abdominal adiposity and these outcomes.

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

Common Neurogenetic Diagnosis and Meso-Limbic Manipulation of Hypodopaminergic Function in Reward Deficiency Syndrome (RDS): Changing the Recovery Landscape.

PubMed

Blum, Kenneth; Febo, Marcelo; Badgaiyan, Rajendra D; Demetrovics, Zsolt; Simpatico, Thomas; Fahlke, Claudia; M, Oscar-Berman; Li, Mona; Dushaj, Kristina; Gold, Mark S

2017-01-01

In 1990, Blum and associates provided the first confirmed genetic link between the DRD2 polymorphisms and alcoholism. This finding was based on an earlier conceptual framework, which served as a blueprint for their seminal genetic association discovery they termed "Brain Reward Cascade." These findings were followed by a new way of understanding all addictive behaviors (substance and non-substance) termed "Reward Deficiency Syndrome" (RDS). RDS incorporates a complex multifaceted array of inheritable behaviors that are polygenic. In this review article, we attempt to clarify these terms and provide a working model to accurately diagnose and treat these unwanted behaviors. We are hereby proposing the development of a translational model we term "Reward Deficiency Solution System™" that incorporates neurogenetic testing and meso-limbic manipulation of a "hypodopaminergic" trait/state, which provides dopamine agonistic therapy (DAT) as well as reduced "dopamine resistance," while embracing "dopamine homeostasis." The result is better recovery and relapse prevention, despite DNA antecedents, which could impact the recovery process and relapse. Understanding the commonality of mental illness will transform erroneous labeling based on symptomatology, into a genetic and anatomical etiology. WC: 184.

Shorter telomere length in Europeans than in Africans due to polygenetic adaptation.

PubMed

Hansen, Matthew E B; Hunt, Steven C; Stone, Rivka C; Horvath, Kent; Herbig, Utz; Ranciaro, Alessia; Hirbo, Jibril; Beggs, William; Reiner, Alexander P; Wilson, James G; Kimura, Masayuki; De Vivo, Immaculata; Chen, Maxine M; Kark, Jeremy D; Levy, Daniel; Nyambo, Thomas; Tishkoff, Sarah A; Aviv, Abraham

2016-06-01

Leukocyte telomere length (LTL), which reflects telomere length in other somatic tissues, is a complex genetic trait. Eleven SNPs have been shown in genome-wide association studies to be associated with LTL at a genome-wide level of significance within cohorts of European ancestry. It has been observed that LTL is longer in African Americans than in Europeans. The underlying reason for this difference is unknown. Here we show that LTL is significantly longer in sub-Saharan Africans than in both Europeans and African Americans. Based on the 11 LTL-associated alleles and genetic data in phase 3 of the 1000 Genomes Project, we show that the shifts in allele frequency within Europe and between Europe and Africa do not fit the pattern expected by neutral genetic drift. Our findings suggest that differences in LTL within Europeans and between Europeans and Africans is influenced by polygenic adaptation and that differences in LTL between Europeans and Africans might explain, in part, ethnic differences in risks for human diseases that have been linked to LTL. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Polygenic Score × Intervention Moderation: an Application of Discrete-Time Survival Analysis to Model the Timing of First Marijuana Use Among Urban Youth.

PubMed

Musci, Rashelle J; Fairman, Brian; Masyn, Katherine E; Uhl, George; Maher, Brion; Sisto, Danielle Y; Kellam, Sheppard G; Ialongo, Nicholas S

2018-01-01

The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.

The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development.

PubMed

Belsky, Daniel W; Moffitt, Terrie E; Corcoran, David L; Domingue, Benjamin; Harrington, HonaLee; Hogan, Sean; Houts, Renate; Ramrakha, Sandhya; Sugden, Karen; Williams, Benjamin S; Poulton, Richie; Caspi, Avshalom

2016-07-01

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children's polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development. © The Author(s) 2016.

Effects of autozygosity and schizophrenia polygenic risk on cognitive and brain developmental trajectories.

PubMed

Córdova-Palomera, Aldo; Kaufmann, Tobias; Bettella, Francesco; Wang, Yunpeng; Doan, Nhat Trung; van der Meer, Dennis; Alnæs, Dag; Rokicki, Jaroslav; Moberget, Torgeir; Sønderby, Ida Elken; Andreassen, Ole A; Westlye, Lars T

2018-04-27

Cognitive and brain development are determined by dynamic interactions between genes and environment across the lifespan. Aside from marker-by-marker analyses of polymorphisms, biologically meaningful features of the whole genome (derived from the combined effect of individual markers) have been postulated to inform on human phenotypes including cognitive traits and their underlying biological substrate. Here, estimates of inbreeding and genetic susceptibility for schizophrenia calculated from genome-wide data-runs of homozygosity (ROH) and schizophrenia polygenic risk score (PGRS)-are analyzed in relation to cognitive abilities (n = 4183) and brain structure (n = 516) in a general-population sample of European-ancestry participants aged 8-22, from the Philadelphia Neurodevelopmental Cohort. The findings suggest that a higher ROH burden and higher schizophrenia PGRS are associated with higher intelligence. Cognition-ROH and cognition-PGRS associations obtained in this cohort may, respectively, evidence that assortative mating influences intelligence, and that individuals with high schizophrenia genetic risk who do not transition to disease status are cognitively resilient. Neuroanatomical data showed that the effects of schizophrenia PGRS on cognition could be modulated by brain structure, although larger imaging datasets are needed to accurately disentangle the underlying neural mechanisms linking IQ with both inbreeding and the genetic burden for schizophrenia.

Common polygenic variation enhances risk prediction for Alzheimer’s disease

PubMed Central

Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D.; Amouyel, Philippe

2015-01-01

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. PMID:26490334

Genetics of Lipid and Lipoprotein Disorders and Traits.

PubMed

Dron, Jacqueline S; Hegele, Robert A

2016-01-01

Plasma lipids, namely cholesterol and triglyceride, and lipoproteins, such as low-density lipoprotein (LDL) and high-density lipoprotein, serve numerous physiological roles. Perturbed levels of these traits underlie monogenic dyslipidemias, a diverse group of multisystem disorders. We are on the verge of having a relatively complete picture of the human dyslipidemias and their components. Recent advances in genetics of plasma lipids and lipoproteins include the following: (1) expanding the range of genes causing monogenic dyslipidemias, particularly elevated LDL cholesterol; (2) appreciating the role of polygenic effects in such traits as familial hypercholesterolemia and combined hyperlipidemia; (3) accumulating a list of common variants that determine plasma lipids and lipoproteins; (4) applying exome sequencing to identify collections of rare variants determining plasma lipids and lipoproteins that via Mendelian randomization have also implicated gene products such as NPC1L1 , APOC3 , LDLR , APOA5 , and ANGPTL4 as causal for atherosclerotic cardiovascular disease; and (5) using naturally occurring genetic variation to identify new drug targets, including inhibitors of apolipoprotein (apo) C-III, apo(a), ANGPTL3, and ANGPTL4. Here, we compile this disparate range of data linking human genetic variation to plasma lipids and lipoproteins, providing a "one stop shop" for the interested reader.

The Genetics of Success: How SNPs Associated with Educational Attainment Relate to Life-Course Development

PubMed Central

Belsky, Daniel W; Moffitt, Terrie E; Corcoran, David L; Domingue, Benjamin; Harrington, HonaLee; Hogan, Sean; Houts, Renate; Ramrakha, Sandhya; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Caspi, Avshalom

2016-01-01

Previous genome-wide association analysis (GWAS) of >100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N=918). There were five main findings. First, polygenic scores predicted adult economic outcomes over and above completed education. Second, genes and environments were correlated; children with higher polygenic scores were born into better-off homes. Third, polygenic scores predicted children’s adult outcomes net of social-class origins; children with higher scores tended to be upwardly-socially-mobile. Fourth, polygenic scores predicted behavior across the life-course, from learning to talk earlier to acquiring reading skills more quickly, through geographic mobility and mate choice, on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics including intelligence, self-control, and interpersonal skill. Effects were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development. PMID:27251486

Replicability and Robustness of GWAS for Behavioral Traits

PubMed Central

Rietveld, Cornelius A.; Conley, Dalton; Eriksson, Nicholas; Esko, Tõnu; Medland, Sarah E.; Vinkhuyzen, Anna A.E.; Yang, Jian; Boardman, Jason D.; Chabris, Christopher F.; Dawes, Christopher T.; Domingue, Benjamin W.; Hinds, David A.; Johannesson, Magnus; Kiefer, Amy K.; Laibson, David; Magnusson, Patrik K. E.; Mountain, Joanna L.; Oskarsson, Sven; Rostapshova, Olga; Teumer, Alexander; Tung, Joyce Y.; Visscher, Peter M.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.

2015-01-01

A recent genome-wide association study (GWAS) of educational attainment identified three single-nucleotide polymorphisms (SNPs) that, despite their small effect sizes (each R2 ≈ 0.02%), reached genome-wide significance (p < 5×10−8) in a large discovery sample and replicated in an independent sample (p < 0.05). The study also reported associations between educational attainment and indices of SNPs called “polygenic scores.” We evaluate the robustness of these findings. Study 1 finds that all three SNPs replicate in another large (N = 34,428) independent sample. We also find that the scores remain predictive (R2 ≈ 2%) with stringent controls for stratification (Study 2) and in new within-family analyses (Study 3). Our results show that large and therefore well-powered GWASs can identify replicable genetic associations with behavioral traits. The small effect sizes of individual SNPs are likely to be a major contributing explanation for the striking contrast between our results and the disappointing replication record of most candidate gene studies. PMID:25287667

Effects of environmental changes on natural selection active on human polygenic traits.

PubMed

Ulizzi, L

1993-06-01

During the last century, industrialized countries experienced such an improvement in socioeconomic conditions and in sanitation that it is likely that the selective forces active on human metric traits have been modified. Perinatal mortality as a function of birth weight is one of the clearest examples of natural selection in humans. Here, trends over time of stabilizing and directional selection associated with birth weight have been analyzed in Japan from 1969 to 1989. The population of newborns has been subdivided according to gestational age, which is one of the main covariates of birth weight. The results show that in full-term babies both stabilizing and directional selection are coming to an end, whereas in babies born after 8 months of gestation these selective forces are still active, even if at much lower levels than in the past. The peculiar results found in the 7-month-gestation population are probably due to grossly abnormal cases of immaturity.

Molecular mapping and breeding with microsatellite markers.

PubMed

Lightfoot, David A; Iqbal, Muhammad J

2013-01-01

In genetics databases for crop plant species across the world, there are thousands of mapped loci that underlie quantitative traits, oligogenic traits, and simple traits recognized by association mapping in populations. The number of loci will increase as new phenotypes are measured in more diverse genotypes and genetic maps based on saturating numbers of markers are developed. A period of locus reevaluation will decrease the number of important loci as those underlying mega-environmental effects are recognized. A second wave of reevaluation of loci will follow from developmental series analysis, especially for harvest traits like seed yield and composition. Breeding methods to properly use the accurate maps of QTL are being developed. New methods to map, fine map, and isolate the genes underlying the loci will be critical to future advances in crop biotechnology. Microsatellite markers are the most useful tool for breeders. They are codominant, abundant in all genomes, highly polymorphic so useful in many populations, and both economical and technically easy to use. The selective genotyping approaches, including genotype ranking (indexing) based on partial phenotype data combined with favorable allele data and bulked segregation event (segregant) analysis (BSA), will be increasingly important uses for microsatellites. Examples of the methods for developing and using microsatellites derived from genomic sequences are presented for monogenic, oligogenic, and polygenic traits. Examples of successful mapping, fine mapping, and gene isolation are given. When combined with high-throughput methods for genotyping and a genome sequence, the use of association mapping with microsatellite markers will provide critical advances in the analysis of crop traits.

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus.

PubMed

Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L; Kreiner, Eskil; Chesi, Alessandra; Zemel, Babette S; Bønnelykke, Klaus; Boer, Cindy G; Ahluwalia, Tarunveer S; Bisgaard, Hans; Evangelou, Evangelos; Heppe, Denise H M; Bonewald, Lynda F; Gorski, Jeffrey P; Ghanbari, Mohsen; Demissie, Serkalem; Duque, Gustavo; Maurano, Matthew T; Kiel, Douglas P; Hsu, Yi-Hsiang; C J van der Eerden, Bram; Ackert-Bicknell, Cheryl; Reppe, Sjur; Gautvik, Kaare M; Raastad, Truls; Karasik, David; van de Peppel, Jeroen; Jaddoe, Vincent W V; Uitterlinden, André G; Tobias, Jonathan H; Grant, Struan F A; Bagos, Pantelis G; Evans, David M; Rivadeneira, Fernando

2017-07-25

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.

Water Deficit and Salinity Stress Reveal Many Specific QTL for Plant Growth and Fruit Quality Traits in Tomato

PubMed Central

Diouf, Isidore A.; Derivot, Laurent; Bitton, Frédérique; Pascual, Laura; Causse, Mathilde

2018-01-01

Quality is a key trait in plant breeding, especially for fruit and vegetables. Quality involves several polygenic components, often influenced by environmental conditions with variable levels of genotype × environment interaction that must be considered in breeding strategies aiming to improve quality. In order to assess the impact of water deficit and salinity on tomato fruit quality, we evaluated a multi-parent advanced generation intercross (MAGIC) tomato population in contrasted environmental conditions over 2 years, one year in control vs. drought condition and the other in control vs. salt condition. Overall 250 individual lines from the MAGIC population—derived from eight parental lines covering a large diversity in cultivated tomato—were used to identify QTL in both experiments for fruit quality and yield component traits (fruit weight, number of fruit, Soluble Solid Content, firmness), phenology traits (time to flower and ripe) and a vegetative trait, leaf length. All the traits showed a large genotype variation (33–86% of total phenotypic variation) in both experiments and high heritability whatever the year or treatment. Significant genotype × treatment interactions were detected for five of the seven traits over the 2 years of experiments. QTL were mapped using 1,345 SNP markers. A total of 54 QTL were found among which 15 revealed genotype × environment interactions and 65% (35 QTL) were treatment specific. Confidence intervals of the QTL were projected on the genome physical map and allowed identifying regions carrying QTL co-localizations, suggesting pleiotropic regulation. We then applied a strategy for candidate gene detection based on the high resolution mapping offered by the MAGIC population, the allelic effect of each parental line at the QTL and the sequence information of the eight parental lines. PMID:29559986

Identification of two heritable cross-disorder endophenotypes for Tourette Syndrome

PubMed Central

Darrow, Sabrina M.; Hirschtritt, Matthew E.; Davis, Lea K.; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert; Pauls, David; Budman, Cathy L.; Cath, Danielle C.; Greenberg, Erica; Lyon, Gholson J.; Yu, Dongmei; McGrath, Lauren M.; McMahon, William M.; Lee, Paul C.; Delucchi, Kevin L.; Scharf, Jeremiah M.; Mathews, Carol A.

2016-01-01

Objective Phenotypic heterogeneity in Tourette syndrome (TS) is partly due to complex genetic relationships between TS, obsessive-compulsive disorder (OCD) and attention deficit/hyperactivity disorder (ADHD). Identifying symptom-based endophenotypes across diagnoses may aid gene-finding efforts. Method 3494 individuals recruited for genetic studies were assessed for TS, OCD, and ADHD symptoms. Symptom-level factor and latent class analyses were conducted in TS families and replicated in an independent sample. Classes were characterized by comorbidity rates and proportion of parents. Heritability and TS-, OCD-, and ADHD-associated polygenic load were estimated. Results We identified two cross-disorder symptom-based phenotypes across analyses: symmetry (symmetry, evening up, checking obsessions; ordering, arranging, counting, writing-rewriting compulsions, repetitive writing tics) and disinhibition (uttering syllables/words, echolalia/palilalia, coprolalia/copropraxia and obsessive urges to offend/mutilate/be destructive). Heritability estimates for both endophenotypes were high (disinhibition factor= 0.35, SE=0.03, p= 4.2 ×10−34; symmetry factor= 0.39, SE=0.03, p= 7.2 ×10−31; symmetry class=0.38, SE=0.10, p=0.001). Mothers of TS probands had high rates of symmetry (49%) but not disinhibition (5%). Polygenic risk scores derived from a TS genome-wide association study (GWAS) were associated with symmetry (p= 0.02), while risk scores derived from an OCD GWAS were not. OCD polygenic risk scores were associated with disinhibition (p =0.03), while TS and ADHD risk scores were not. Conclusions We identified two heritable TS-related endophenotypes that cross traditional diagnostic boundaries. The symmetry phenotype correlated with TS polygenic load, and was present in otherwise “TS-unaffected” mothers, suggesting that this phenotype may reflect additional TS (rather than OCD) genetic liability that is not captured by traditional DSM-based diagnoses. PMID:27809572

Identification of Two Heritable Cross-Disorder Endophenotypes for Tourette Syndrome.

PubMed

Darrow, Sabrina M; Hirschtritt, Matthew E; Davis, Lea K; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert; Pauls, David; Budman, Cathy L; Cath, Danielle C; Greenberg, Erica; Lyon, Gholson J; Yu, Dongmei; McGrath, Lauren M; McMahon, William M; Lee, Paul C; Delucchi, Kevin L; Scharf, Jeremiah M; Mathews, Carol A

2017-04-01

Phenotypic heterogeneity in Tourette syndrome is partly due to complex genetic relationships among Tourette syndrome, obsessive-compulsive disorder (OCD), and attention deficit hyperactivity disorder (ADHD). Identifying symptom-based endophenotypes across diagnoses may aid gene-finding efforts. Assessments for Tourette syndrome, OCD, and ADHD symptoms were conducted in a discovery sample of 3,494 individuals recruited for genetic studies. Symptom-level factor and latent class analyses were conducted in Tourette syndrome families and replicated in an independent sample of 882 individuals. Classes were characterized by comorbidity rates and proportion of parents included. Heritability and polygenic load associated with Tourette syndrome, OCD, and ADHD were estimated. The authors identified two cross-disorder symptom-based phenotypes across analyses: symmetry (symmetry, evening up, checking obsessions; ordering, arranging, counting, writing-rewriting compulsions, repetitive writing tics) and disinhibition (uttering syllables/words, echolalia/palilalia, coprolalia/copropraxia, and obsessive urges to offend/mutilate/be destructive). Heritability estimates for both endophenotypes were high and statistically significant (disinhibition factor=0.35, SE=0.03; symmetry factor=0.39, SE=0.03; symmetry class=0.38, SE=0.10). Mothers of Tourette syndrome probands had high rates of symmetry (49%) but not disinhibition (5%). Polygenic risk scores derived from a Tourette syndrome genome-wide association study (GWAS) were significantly associated with symmetry, while risk scores derived from an OCD GWAS were not. OCD polygenic risk scores were significantly associated with disinhibition, while Tourette syndrome and ADHD risk scores were not. The analyses identified two heritable endophenotypes related to Tourette syndrome that cross traditional diagnostic boundaries. The symmetry phenotype correlated with Tourette syndrome polygenic load and was present in otherwise Tourette-unaffected mothers, suggesting that this phenotype may reflect additional Tourette syndrome (rather than OCD) genetic liability that is not captured by traditional DSM-based diagnoses.

Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle.

PubMed

Bolormaa, S; Pryce, J E; Kemper, K; Savin, K; Hayes, B J; Barendse, W; Zhang, Y; Reich, C M; Mason, B A; Bunch, R J; Harrison, B E; Reverter, A; Herd, R M; Tier, B; Graser, H-U; Goddard, M E

2013-07-01

The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

Identification of Single-Nucleotide Polymorphic Loci Associated with Biomass Yield under Water Deficit in Alfalfa (Medicago sativa L.) Using Genome-Wide Sequencing and Association Mapping

PubMed Central

Yu, Long-Xi

2017-01-01

Alfalfa is a worldwide grown forage crop and is important due to its high biomass production and nutritional value. However, the production of alfalfa is challenged by adverse environmental factors such as drought and other stresses. Developing drought resistance alfalfa is an important breeding target for enhancing alfalfa productivity in arid and semi-arid regions. In the present study, we used genotyping-by-sequencing and genome-wide association to identify marker loci associated with biomass yield under drought in the field in a panel of diverse germplasm of alfalfa. A total of 28 markers at 22 genetic loci were associated with yield under water deficit, whereas only four markers associated with the same trait under well-watered condition. Comparisons of marker-trait associations between water deficit and well-watered conditions showed non-similarity except one. Most of the markers were identical across harvest periods within the treatment, although different levels of significance were found among the three harvests. The loci associated with biomass yield under water deficit located throughout all chromosomes in the alfalfa genome agreed with previous reports. Our results suggest that biomass yield under drought is a complex quantitative trait with polygenic inheritance and may involve a different mechanism compared to that of non-stress. BLAST searches of the flanking sequences of the associated loci against DNA databases revealed several stress-responsive genes linked to the drought resistance loci, including leucine-rich repeat receptor-like kinase, B3 DNA-binding domain protein, translation initiation factor IF2, and phospholipase-like protein. With further investigation, those markers closely linked to drought resistance can be used for MAS to accelerate the development of new alfalfa cultivars with improved resistance to drought and other abiotic stresses. PMID:28706532

Major depressive disorder and current psychological distress moderate the effect of polygenic risk for obesity on body mass index.

PubMed

Clarke, T-K; Hall, L S; Fernandez-Pujals, A M; MacIntyre, D J; Thomson, P; Hayward, C; Smith, B H; Padmanabhan, S; Hocking, L J; Deary, I J; Porteous, D J; McIntosh, A M

2015-06-30

Major depressive disorder (MDD) and obesity are frequently co-morbid and this correlation is partly due to genetic factors. Although specific genetic risk variants are associated with body mass index (BMI) and with larger effect sizes in depressed individuals, the genetic overlap and interaction with depression has not been addressed using whole-genome data. Polygenic profile scores for MDD and BMI were created in 13,921 members of Generation Scotland: the Scottish Family Health Study and tested for their association with BMI, MDD, neuroticism and scores on the General Health Questionnaire (GHQ) (current psychological distress). The association between BMI polygenic profile scores and BMI was tested fitting GHQ, neuroticism or MDD status as an interaction term to test for a moderating effect of mood disorder. BMI polygenic profile scores were not associated with lifetime MDD status or neuroticism although a significant positive association with GHQ scores was found (P = 0.0001, β = 0.034, r(2) = 0.001). Polygenic risk for MDD was not associated with BMI. A significant interaction between BMI polygenic profile scores and MDD (P = 0.0003, β = 0.064), GHQ (P = 0.0005, β = 0.027) and neuroticism (P = 0.003, β = 0.023) was found when BMI was the dependent variable. The effect of BMI-increasing alleles was greater in those with MDD, high neuroticism or current psychological distress. MDD, neuroticism and current psychological distress amplify the effect of BMI polygenic profile scores on BMI. Depressed individuals with a greater polygenic load for obesity are at greater risk of becoming obese than control individuals.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

PubMed

Escott-Price, Valentina; Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D; Amouyel, Philippe; Williams, Julie

2015-12-01

The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Long-term selection strategies for complex traits using high-density genetic markers.

PubMed

Kemper, K E; Bowman, P J; Pryce, J E; Hayes, B J; Goddard, M E

2012-08-01

Selection of animals for breeding ranked on estimated breeding value maximizes genetic gain in the next generation but does not necessarily maximize long-term response. An alternative method, as practiced by plant breeders, is to build a desired genotype by selection on specific loci. Maximal long-term response in animal breeding requires selection on estimated breeding values with constraints on coancestry. In this paper, we compared long-term genetic response using either a genotype building or a genomic estimated breeding value (GEBV) strategy for the Australian Selection Index (ASI), a measure of profit. First, we used real marker effects from the Australian Dairy Herd Improvement Scheme to estimate breeding values for chromosome segments (approximately 25 cM long) for 2,650 Holstein bulls. Second, we selected 16 animals to be founders for a simulated breeding program where, between them, founders contain the best possible combination of 2 segments from 2 animals at each position in the genome. Third, we mated founder animals and their descendants over 30 generations with 2 breeding objectives: (1) to create a population with the "ideal genotype," where the best 2 segments from the founders segregate at each position, or (2) obtain the highest possible response in ASI with coancestry lower than that achieved under breeding objective 1. Results show that genotype building achieved the ideal genotype for breeding objective 1 and obtained a large gain in ASI over the current population (+A$864.99). However, selection on overall GEBV had greater short-term response and almost as much long-term gain (+A$820.42). When coancestry was lowered under breeding objective 2, selection on overall GEBV achieved a higher response in ASI than the genotype building strategy. Selection on overall GEBV seems more flexible in its selection decisions and was therefore better able to precisely control coancestry while maximizing ASI. We conclude that selection on overall GEBV while minimizing average coancestry is the more practical strategy for dairy cattle where selection is for highly polygenic traits, the reproductive rate is relatively low, and there is low tolerance of coancestry. The outcome may be different for traits controlled by few loci of relatively large effects or for different species. In contrast to other simulations, our results indicate that response to selection on overall GEBV may continue for several generations. This is because long-term genetic change in complex traits requires favorable changes to allele frequencies for many loci located throughout the genome. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Variability in working memory performance explained by epistasis vs polygenic scores in the ZNF804A pathway.

PubMed

Nicodemus, Kristin K; Hargreaves, April; Morris, Derek; Anney, Richard; Gill, Michael; Corvin, Aiden; Donohoe, Gary

2014-07-01

We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. Patients with psychosis (n = 424) were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition. We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1% to 3% of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2% using the polygenic score only to 4.8% (P = .11 and .001, respectively) but did not explain additional variation in control participants. These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score.

Six low-penetrance SNPs for the estimation of breast cancer heritability: A family-based study in Caucasian Italian patients

PubMed Central

De Summa, Simona; Graziano, Francesca; Pilato, Brunella; Pinto, Rosamaria; Danza, Katia; Lacalamita, Rosanna; Serratì, Simona; Sambiasi, Domenico; Grassi, Mario; Tommasi, Stefania

2017-01-01

Breast cancer is a malignancy with a strong heritable component. Genetic counseling has been principally focused on families carrying high-penetrance breast cancer 1/2, early onset genes. Current modeling suggests that the majority of the unexplained fraction of familial risk is likely to be explained by a polygenic model. The aim of the present study was to estimate the heritability (h2) of breast cancer susceptibility through the analysis of 6 single nucleotide polymorphisms (SNPs), nuclear mitotic apparatus protein 1, cyclin D1, cytochrome C oxidase copper chaperone, fibroblast growth factor receptor 2, TOX high mobility group box family member 3 and solute carrier family 4 member 7. These 6 SNPs, previously identified by genome-wide association studies, were considered to evaluate the additive and common environmental components that contribute to the development of breast cancer in nuclear (pedigrees including only first degree relationships) and in extended families (with at most third degree relationships). A total of 22 extended pedigrees, subsequently split into 52 nuclear pedigrees were analyzed. An example of splitting process from extended to nuclear pedigree is shown in Fig. 1. Firstly, an underline latent continuous trait (Y*) using breast cancer status and information of 6 breast cancer-associated SNPs was calculated. This novel trait summarized the susceptibility of breast cancer in each individual. Secondly, the h2 of Y* was estimated using an additive polygenic-common environment-unique error model. h2 was evaluated in extended and immediate pedigrees, obtaining comparable results. h2 accounts for ~40% of the total phenotypic variance, indicating a fairly strong additive genetic effect of breast cancer susceptibility. The present study indicated the importance of the evaluation and consideration of these six SNPs, which can be used as instrumental variables in order to obtain improved genetic models that are useful for h2 analysis. PMID:28943953

A polygenic burden of rare disruptive mutations in schizophrenia

PubMed Central

Purcell, Shaun M.; Moran, Jennifer L.; Fromer, Menachem; Ruderfer, Douglas; Solovieff, Nadia; Roussos, Panos; O’Dushlaine, Colm; Chambert, Kimberly; Bergen, Sarah E.; Kähler, Anna; Duncan, Laramie; Stahl, Eli; Genovese, Giulio; Fernández, Esperanza; Collins, Mark O; Komiyama, Noboru H.; Choudhary, Jyoti S.; Magnusson, Patrik K. E.; Banks, Eric; Shakir, Khalid; Garimella, Kiran; Fennell, Tim; de Pristo, Mark; Grant, Seth G.N.; Haggarty, Stephen; Gabriel, Stacey; Scolnick, Edward M.; Lander, Eric S.; Hultman, Christina; Sullivan, Patrick F.; McCarroll, Steven A.; Sklar, Pamela

2014-01-01

By analyzing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we have demonstrated a polygenic burden primarily arising from rare (<1/10,000), disruptive mutations distributed across many genes. Especially enriched genesets included the voltage-gated calcium ion channel and the signaling complex formed by the activity-regulated cytoskeleton-associated (ARC) scaffold protein of the postsynaptic density (PSD), sets previously implicated by genome-wide association studies (GWAS) and copy-number variation (CNV) studies. Similar to reports in autism, targets of the fragile × mental retardation protein (FMRP, product of FMR1) were enriched for case mutations. No individual gene-based test achieved significance after correction for multiple testing and we did not detect any alleles of moderately low frequency (~0.5-1%) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene mapping paradigms in neuropsychiatric disease. PMID:24463508

Converging evidence for an impact of a functional NOS gene variation on anxiety-related processes.

PubMed

Kuhn, Manuel; Haaker, Jan; Glotzbach-Schoon, Evelyn; Schümann, Dirk; Andreatta, Marta; Mechias, Marie-Luise; Raczka, Karolina; Gartmann, Nina; Büchel, Christian; Mühlberger, Andreas; Pauli, Paul; Reif, Andreas; Kalisch, Raffael; Lonsdorf, Tina B

2016-05-01

Being a complex phenotype with substantial heritability, anxiety and related phenotypes are characterized by a complex polygenic basis. Thereby, one candidate pathway is neuronal nitric oxide (NO) signaling, and accordingly, rodent studies have identified NO synthase (NOS-I), encoded by NOS1, as a strong molecular candidate for modulating anxiety and hippocampus-dependent learning processes. Using a multi-dimensional and -methodological replication approach, we investigated the impact of a functional promoter polymorphism (NOS1-ex1f-VNTR) on human anxiety-related phenotypes in a total of 1019 healthy controls in five different studies. Homozygous carriers of the NOS1-ex1f short-allele displayed enhanced trait anxiety, worrying and depression scores. Furthermore, short-allele carriers were characterized by increased anxious apprehension during contextual fear conditioning. While autonomous measures (fear-potentiated startle) provided only suggestive evidence for a modulatory role of NOS1-ex1f-VNTR on (contextual) fear conditioning processes, neural activation at the amygdala/anterior hippocampus junction was significantly increased in short-allele carriers during context conditioning. Notably, this could not be attributed to morphological differences. In accordance with data from a plethora of rodent studies, we here provide converging evidence from behavioral, subjective, psychophysiological and neuroimaging studies in large human cohorts that NOS-I plays an important role in anxious apprehension but provide only limited evidence for a role in (contextual) fear conditioning. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Increased waist circumference is independently associated with hypothyroidism in Mexican Americans: replicative evidence from two large, population-based studies

PubMed Central

2014-01-01

Background Mexican Americans are at an increased risk of both thyroid dysfunction and metabolic syndrome (MS). Thus it is conceivable that some components of the MS may be associated with the risk of thyroid dysfunction in these individuals. Our objective was to investigate and replicate the potential association of MS traits with thyroid dysfunction in Mexican Americans. Methods We conducted association testing for 18 MS traits in two large studies on Mexican Americans – the San Antonio Family Heart Study (SAFHS) and the National Health and Nutrition Examination Survey (NHANES) 2007–10. A total of 907 participants from 42 families in SAFHS and 1633 unrelated participants from NHANES 2007–10 were included in this study. The outcome measures were prevalence of clinical and subclinical hypothyroidism and thyroid function index (TFI) – a measure of thyroid function. For the SAFHS, we used polygenic regression analyses with multiple covariates to test associations in setting of family studies. For the NHANES 2007–10, we corrected for the survey design variables as needed for association analyses in survey data. In both datasets, we corrected for age, sex and their linear and quadratic interactions. Results TFI was an accurate indicator of clinical thyroid status (area under the receiver-operating-characteristic curve to detect clinical hypothyroidism, 0.98) in both SAFHS and NHANES 2007–10. Of the 18 MS traits, waist circumference (WC) showed the most consistent association with TFI in both studies independently of age, sex and body mass index (BMI). In the SAFHS and NHANES 2007–10 datasets, each standard deviation increase in WC was associated with 0.13 (p < 0.001) and 0.11 (p < 0.001) unit increase in the TFI, respectively. In a series of polygenic and linear regression models, central obesity (defined as WC ≥ 102 cm in men and ≥88 cm in women) was associated with clinical and subclinical hypothyroidism independent of age, sex, BMI and type 2 diabetes in both datasets. Estimated prevalence of hypothyroidism was consistently high in those with central obesity, especially below 45y of age. Conclusions WC independently associates with increased risk of thyroid dysfunction. Use of WC to identify Mexican American subjects at high risk of thyroid dysfunction should be investigated in future studies. PMID:24913450

Increased waist circumference is independently associated with hypothyroidism in Mexican Americans: replicative evidence from two large, population-based studies.

PubMed

Mamtani, Manju; Kulkarni, Hemant; Dyer, Thomas D; Almasy, Laura; Mahaney, Michael C; Duggirala, Ravindranath; Comuzzie, Anthony G; Samollow, Paul B; Blangero, John; Curran, Joanne E

2014-06-10

Mexican Americans are at an increased risk of both thyroid dysfunction and metabolic syndrome (MS). Thus it is conceivable that some components of the MS may be associated with the risk of thyroid dysfunction in these individuals. Our objective was to investigate and replicate the potential association of MS traits with thyroid dysfunction in Mexican Americans. We conducted association testing for 18 MS traits in two large studies on Mexican Americans - the San Antonio Family Heart Study (SAFHS) and the National Health and Nutrition Examination Survey (NHANES) 2007-10. A total of 907 participants from 42 families in SAFHS and 1633 unrelated participants from NHANES 2007-10 were included in this study. The outcome measures were prevalence of clinical and subclinical hypothyroidism and thyroid function index (TFI) - a measure of thyroid function. For the SAFHS, we used polygenic regression analyses with multiple covariates to test associations in setting of family studies. For the NHANES 2007-10, we corrected for the survey design variables as needed for association analyses in survey data. In both datasets, we corrected for age, sex and their linear and quadratic interactions. TFI was an accurate indicator of clinical thyroid status (area under the receiver-operating-characteristic curve to detect clinical hypothyroidism, 0.98) in both SAFHS and NHANES 2007-10. Of the 18 MS traits, waist circumference (WC) showed the most consistent association with TFI in both studies independently of age, sex and body mass index (BMI). In the SAFHS and NHANES 2007-10 datasets, each standard deviation increase in WC was associated with 0.13 (p < 0.001) and 0.11 (p < 0.001) unit increase in the TFI, respectively. In a series of polygenic and linear regression models, central obesity (defined as WC ≥ 102 cm in men and ≥88 cm in women) was associated with clinical and subclinical hypothyroidism independent of age, sex, BMI and type 2 diabetes in both datasets. Estimated prevalence of hypothyroidism was consistently high in those with central obesity, especially below 45y of age. WC independently associates with increased risk of thyroid dysfunction. Use of WC to identify Mexican American subjects at high risk of thyroid dysfunction should be investigated in future studies.

Genetic basis of Spodoptera frugiperda (Lepidoptera: Noctuidae) resistance to the chitin synthesis inhibitor lufenuron.

PubMed

do Nascimento, Antonio Rogério Bezerra; Farias, Juliano Ricardo; Bernardi, Daniel; Horikoshi, Renato Jun; Omoto, Celso

2016-04-01

An understanding of the genetic basis of insect resistance to insecticides is important for the establishment of insect resistance management (IRM) strategies. In this study we evaluated the inheritance pattern of resistance to the chitin synthesis inhibitor lufenuron in Spodoptera frugiperda. The LC50 values (95% CI) were 0.23 µg lufenuron mL(-1) water (ppm) (0.18-0.28) for the susceptible strain (SUS) and 210.6 µg mL(-1) (175.90-258.10) for the lufenuron-resistant strain (LUF-R), based on diet-overlay bioassay. The resistance ratio was ≈ 915-fold. The LC50 values for reciprocal crosses were 4.89 µg mL(-1) (3.79-5.97) for female LUF-R and male SUS and 5.74 µg mL(-1) (4.70-6.91) for female SUS and male LUF-R, indicating that the inheritance of S. frugiperda resistance to lufenuron is an autosomal, incompletely recessive trait. Backcrosses of the progeny of reciprocal crosses with the parental LUF-R showed a polygenic effect. The estimated minimum number of independent segregations was in the 11.02 range, indicating that resistance to lufenuron is associated with multiple genes in S. frugiperda. Based on genetic crosses, the inheritance pattern of lufenuron resistance in S. frugiperda was autosomal, incompletely recessive and polygenic. Implications of this finding to IRM are discussed in this paper. © 2015 Society of Chemical Industry.

A major locus controls local adaptation and adaptive life history variation in a perennial plant.

PubMed

Wang, Jing; Ding, Jihua; Tan, Biyue; Robinson, Kathryn M; Michelson, Ingrid H; Johansson, Anna; Nystedt, Björn; Scofield, Douglas G; Nilsson, Ove; Jansson, Stefan; Street, Nathaniel R; Ingvarsson, Pär K

2018-06-04

The initiation of growth cessation and dormancy represent critical life-history trade-offs between survival and growth and have important fitness effects in perennial plants. Such adaptive life-history traits often show strong local adaptation along environmental gradients but, despite their importance, the genetic architecture of these traits remains poorly understood. We integrate whole genome re-sequencing with environmental and phenotypic data from common garden experiments to investigate the genomic basis of local adaptation across a latitudinal gradient in European aspen (Populus tremula). A single genomic region containing the PtFT2 gene mediates local adaptation in the timing of bud set and explains 65% of the observed genetic variation in bud set. This locus is the likely target of a recent selective sweep that originated right before or during colonization of northern Scandinavia following the last glaciation. Field and greenhouse experiments confirm that variation in PtFT2 gene expression affects the phenotypic variation in bud set that we observe in wild natural populations. Our results reveal a major effect locus that determines the timing of bud set and that has facilitated rapid adaptation to shorter growing seasons and colder climates in European aspen. The discovery of a single locus explaining a substantial fraction of the variation in a key life-history trait is remarkable, given that such traits are generally considered to be highly polygenic. These findings provide a dramatic illustration of how loci of large-effect for adaptive traits can arise and be maintained over large geographical scales in natural populations.

Insights into the genetic architecture of morphological traits in two passerine bird species.

PubMed

Silva, C N S; McFarlane, S E; Hagen, I J; Rönnegård, L; Billing, A M; Kvalnes, T; Kemppainen, P; Rønning, B; Ringsby, T H; Sæther, B-E; Qvarnström, A; Ellegren, H; Jensen, H; Husby, A

2017-09-01

Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (V P ), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of V P ). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.

Appetitive traits as behavioural pathways in genetic susceptibility to obesity: a population-based cross-sectional study.

PubMed

Konttinen, Hanna; Llewellyn, Clare; Wardle, Jane; Silventoinen, Karri; Joensuu, Anni; Männistö, Satu; Salomaa, Veikko; Jousilahti, Pekka; Kaprio, Jaakko; Perola, Markus; Haukkala, Ari

2015-10-01

The mechanisms through which genes influence body weight are not well understood, but appetite has been implicated as one mediating pathway. Here we use data from two independent population-based Finnish cohorts (4632 adults aged 25-74 years from the DILGOM study and 1231 twin individuals aged 21-26 years from the FinnTwin12 study) to investigate whether two appetitive traits mediate the associations between known obesity-related genetic variants and adiposity. The results from structural equation modelling indicate that the effects of a polygenic risk score (90 obesity-related loci) on measured body mass index and waist circumference are partly mediated through higher levels of uncontrolled eating (βindirect = 0.030-0.032, P < 0.001 in DILGOM) and emotional eating (βindirect = 0.020-0.022, P < 0.001 in DILGOM and βindirect = 0.013-0.015, P = 0.043-0.044 in FinnTwin12). Our findings suggest that genetic predispositions to obesity may partly exert their effects through appetitive traits reflecting lack of control over eating or eating in response to negative emotions. Obesity prevention and treatment studies should examine the impact of targeting these eating behaviours, especially among individuals having a high genetic predisposition to obesity.

Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments.

PubMed

Cerrudo, Diego; Cao, Shiliang; Yuan, Yibing; Martinez, Carlos; Suarez, Edgar Antonio; Babu, Raman; Zhang, Xuecai; Trachsel, Samuel

2018-01-01

To increase genetic gain for tolerance to drought, we aimed to identify environmentally stable QTL in per se and testcross combination under well-watered (WW) and drought stressed (DS) conditions and evaluate the possible deployment of QTL using marker assisted and/or genomic selection (QTL/GS-MAS). A total of 169 doubled haploid lines derived from the cross between CML495 and LPSC7F64 and 190 testcrosses (tester CML494) were evaluated in a total of 11 treatment-by-population combinations under WW and DS conditions. In response to DS, grain yield (GY) and plant height (PHT) were reduced while time to anthesis and the anthesis silking interval (ASI) increased for both lines and hybrids. Forty-eight QTL were detected for a total of nine traits. The allele derived from CML495 generally increased trait values for anthesis, ASI, PHT, the normalized difference vegetative index (NDVI) and the green leaf area duration (GLAD; a composite trait of NDVI, PHT and senescence) while it reduced trait values for leaf rolling and senescence. The LOD scores for all detected QTL ranged from 2.0 to 7.2 explaining 4.4 to 19.4% of the observed phenotypic variance with R 2 ranging from 0 (GY, DS, lines) to 37.3% (PHT, WW, lines). Prediction accuracy of the model used for genomic selection was generally higher than phenotypic variance explained by the sum of QTL for individual traits indicative of the polygenic control of traits evaluated here. We therefore propose to use QTL-MAS in forward breeding to enrich the allelic frequency for a few desired traits with strong additive QTL in early selection cycles while GS-MAS could be used in more mature breeding programs to additionally capture alleles with smaller additive effects.

QTL mapping of stalk bending strength in a recombinant inbred line maize population.

PubMed

Hu, Haixiao; Liu, Wenxin; Fu, Zhiyi; Homann, Linda; Technow, Frank; Wang, Hongwu; Song, Chengliang; Li, Shitu; Melchinger, Albrecht E; Chen, Shaojiang

2013-09-01

Stalk bending strength (SBS) is a reliable indicator for evaluating stalk lodging resistance of maize plants. Based on biomechanical considerations, the maximum load exerted to breaking (F max), the breaking moment (M max) and critical stress (σ max) are three important parameters to characterize SBS. We investigated the genetic architecture of SBS by phenotyping F max, M max and σ max of the fourth internode of maize plants in a population of 216 recombinant inbred lines derived from the cross B73 × Ce03005 evaluated in four environments. Heritability of F max, M max and σ max was 0.81, 0.79 and 0.75, respectively. F max and σ max were positively correlated with several other stalk characters. By using a linkage map with 129 SSR markers, we detected two, three and two quantitative trait loci (QTL) explaining 22.4, 26.1 and 17.2 % of the genotypic variance for F max, M max and σ max, respectively. The QTL for F max, M max and σ max located in adjacent bins 5.02 and 5.03 as well as in bin 10.04 for F max were detected with high frequencies in cross-validation. As our QTL mapping results suggested a complex polygenic inheritance for SBS-related traits, we also evaluated the prediction accuracy of two genomic prediction methods (GBLUP and BayesB). In general, we found that both explained considerably higher proportions of the genetic variance than the values obtained in QTL mapping with cross-validation. Nevertheless, the identified QTL regions could be used as a starting point for fine mapping and gene cloning.

Molecular Basis of Resistance to Fusarium Ear Rot in Maize.

PubMed

Lanubile, Alessandra; Maschietto, Valentina; Borrelli, Virginia M; Stagnati, Lorenzo; Logrieco, Antonio F; Marocco, Adriano

2017-01-01

The impact of climate change has been identified as an emerging issue for food security and safety, and the increased incidence of mycotoxin contamination in maize over the last two decades is considered a potential emerging hazard. Disease control by chemical and agronomic approaches is often ineffective and increases the cost of production; for this reason the exploitation of genetic resistance is the most sustainable method for reducing contamination. The review focuses on the significant advances that have been made in the development of transcriptomic, genetic and genomic information for maize, Fusarium verticillioides molds, and their interactions, over recent years. Findings from transcriptomic studies have been used to outline a specific model for the intracellular signaling cascade occurring in maize cells against F. verticillioides infection. Several recognition receptors, such as receptor-like kinases and R genes, are involved in pathogen perception, and trigger down-stream signaling networks mediated by mitogen-associated protein kinases. These signals could be orchestrated primarily by hormones, including salicylic acid, auxin, abscisic acid, ethylene, and jasmonic acid, in association with calcium signaling, targeting multiple transcription factors that in turn promote the down-stream activation of defensive response genes, such as those related to detoxification processes, phenylpropanoid, and oxylipin metabolic pathways. At the genetic and genomic levels, several quantitative trait loci (QTL) and single-nucleotide polymorphism markers for resistance to Fusarium ear rot deriving from QTL mapping and genome-wide association studies are described, indicating the complexity of this polygenic trait. All these findings will contribute to identifying candidate genes for resistance and to applying genomic technologies for selecting resistant maize genotypes and speeding up a strategy of breeding to contrast disease, through plants resistant to mycotoxin-producing pathogens.

Molecular Basis of Resistance to Fusarium Ear Rot in Maize

PubMed Central

Lanubile, Alessandra; Maschietto, Valentina; Borrelli, Virginia M.; Stagnati, Lorenzo; Logrieco, Antonio F.; Marocco, Adriano

2017-01-01

The impact of climate change has been identified as an emerging issue for food security and safety, and the increased incidence of mycotoxin contamination in maize over the last two decades is considered a potential emerging hazard. Disease control by chemical and agronomic approaches is often ineffective and increases the cost of production; for this reason the exploitation of genetic resistance is the most sustainable method for reducing contamination. The review focuses on the significant advances that have been made in the development of transcriptomic, genetic and genomic information for maize, Fusarium verticillioides molds, and their interactions, over recent years. Findings from transcriptomic studies have been used to outline a specific model for the intracellular signaling cascade occurring in maize cells against F. verticillioides infection. Several recognition receptors, such as receptor-like kinases and R genes, are involved in pathogen perception, and trigger down-stream signaling networks mediated by mitogen-associated protein kinases. These signals could be orchestrated primarily by hormones, including salicylic acid, auxin, abscisic acid, ethylene, and jasmonic acid, in association with calcium signaling, targeting multiple transcription factors that in turn promote the down-stream activation of defensive response genes, such as those related to detoxification processes, phenylpropanoid, and oxylipin metabolic pathways. At the genetic and genomic levels, several quantitative trait loci (QTL) and single-nucleotide polymorphism markers for resistance to Fusarium ear rot deriving from QTL mapping and genome-wide association studies are described, indicating the complexity of this polygenic trait. All these findings will contribute to identifying candidate genes for resistance and to applying genomic technologies for selecting resistant maize genotypes and speeding up a strategy of breeding to contrast disease, through plants resistant to mycotoxin-producing pathogens. PMID:29075283

Genome-wide association analysis in dogs implicates 99 loci as risk variants for anterior cruciate ligament rupture

PubMed Central

Baker, Lauren A.; Kirkpatrick, Brian; Rosa, Guilherme J. M.; Gianola, Daniel; Valente, Bruno; Sumner, Julia P.; Baltzer, Wendy; Hao, Zhengling; Binversie, Emily E.; Volstad, Nicola; Piazza, Alexander; Sample, Susannah J.

2017-01-01

Anterior cruciate ligament (ACL) rupture is a common condition that can be devastating and life changing, particularly in young adults. A non-contact mechanism is typical. Second ACL ruptures through rupture of the contralateral ACL or rupture of a graft repair is also common. Risk of rupture is increased in females. ACL rupture is also common in dogs. Disease prevalence exceeds 5% in several dog breeds, ~100 fold higher than human beings. We provide insight into the genetic etiology of ACL rupture by genome-wide association study (GWAS) in a high-risk breed using 98 case and 139 control Labrador Retrievers. We identified 129 single nucleotide polymorphisms (SNPs) within 99 risk loci. Associated loci (P<5E-04) explained approximately half of phenotypic variance in the ACL rupture trait. Two of these loci were located in uncharacterized or non-coding regions of the genome. A chromosome 24 locus containing nine genes with diverse functions met genome-wide significance (P = 3.63E-0.6). GWAS pathways were enriched for c-type lectins, a gene set that includes aggrecan, a gene set encoding antimicrobial proteins, and a gene set encoding membrane transport proteins with a variety of physiological functions. Genotypic risk estimated for each dog based on the risk contributed by each GWAS locus showed clear separation of ACL rupture cases and controls. Power analysis of the GWAS data set estimated that ~172 loci explain the genetic contribution to ACL rupture in the Labrador Retriever. Heritability was estimated at 0.48. We conclude ACL rupture is a moderately heritable highly polygenic complex trait. Our results implicate c-type lectin pathways in ACL homeostasis. PMID:28379989

Direct evidence for positive selection of skin, hair, and eye pigmentation in Europeans during the last 5,000 y.

PubMed

Wilde, Sandra; Timpson, Adrian; Kirsanow, Karola; Kaiser, Elke; Kayser, Manfred; Unterländer, Martina; Hollfelder, Nina; Potekhina, Inna D; Schier, Wolfram; Thomas, Mark G; Burger, Joachim

2014-04-01

Pigmentation is a polygenic trait encompassing some of the most visible phenotypic variation observed in humans. Here we present direct estimates of selection acting on functional alleles in three key genes known to be involved in human pigmentation pathways--HERC2, SLC45A2, and TYR--using allele frequency estimates from Eneolithic, Bronze Age, and modern Eastern European samples and forward simulations. Neutrality was overwhelmingly rejected for all alleles studied, with point estimates of selection ranging from around 2-10% per generation. Our results provide direct evidence that strong selection favoring lighter skin, hair, and eye pigmentation has been operating in European populations over the last 5,000 y.

Common Neurogenetic Diagnosis and Meso-Limbic Manipulation of Hypodopaminergic Function in Reward Deficiency Syndrome (RDS): Changing the Recovery Landscape

PubMed Central

Blum, Kenneth; Febo, Marcelo; Badgaiyan, Rajendra D.; Demetrovics, Zsolt; Simpatico, Thomas; Fahlke, Claudia; Li, Mona; Dushaj, Kristina; Gold, Mark S.

2017-01-01

Abstract: Background: In 1990, Blum and associates provided the first confirmed genetic link between the DRD2 polymorphisms and alcoholism. This finding was based on an earlier conceptual framework, which served as a blueprint for their seminal genetic association discovery they termed “Brain Reward Cascade.” These findings were followed by a new way of understanding all addictive behaviors (substance and non-substance) termed “Reward Deficiency Syndrome” (RDS). RDS incorporates a complex multifaceted array of inheritable behaviors that are polygenic. Objective: In this review article, we attempt to clarify these terms and provide a working model to accurately diagnose and treat these unwanted behaviors. Method: We are hereby proposing the development of a translational model we term “Reward Deficiency Solution System™” that incorporates neurogenetic testing and meso-limbic manipulation of a “hypodopaminergic” trait/state, which provides dopamine agonistic therapy (DAT) as well as reduced “dopamine resistance,” while embracing “dopamine homeostasis.” Result: The result is better recovery and relapse prevention, despite DNA antecedents, which could impact the recovery process and relapse. Understanding the commonality of mental illness will transform erroneous labeling based on symptomatology, into a genetic and anatomical etiology. WC: 184. PMID:27174576

Mapping PrBn and Other Quantitative Trait Loci Responsible for the Control of Homeologous Chromosome Pairing in Oilseed Rape (Brassica napus L.) Haploids

PubMed Central

Liu, Zhiqian; Adamczyk, Katarzyna; Manzanares-Dauleux, Maria; Eber, Frédérique; Lucas, Marie-Odile; Delourme, Régine; Chèvre, Anne Marie; Jenczewski, Eric

2006-01-01

In allopolyploid species, fair meiosis could be challenged by homeologous chromosome pairing and is usually achieved by the action of homeologous pairing suppressor genes. Oilseed rape (Brassica napus) haploids (AC, n = 19) represent an attractive model for studying the mechanisms used by allopolyploids to ensure the diploid-like meiotic pairing pattern. In oilseed rape haploids, homeologous chromosome pairing at metaphase I was found to be genetically based and controlled by a major gene, PrBn, segregating in a background of polygenic variation. In this study, we have mapped PrBn within a 10-cM interval on the C genome linkage group DY15 and shown that PrBn displays incomplete penetrance or variable expressivity. We have identified three to six minor QTL/BTL that have slight additive effects on the amount of pairing at metaphase I but do not interact with PrBn. We have also detected a number of other loci that interact epistatically, notably with PrBn. Our results support the idea that, as in other polyploid species, metaphase I homeologous pairing in oilseed rape haploids is controlled by an integrated system of several genes, which function in a complex manner. PMID:16951054

Quantitative genetic analysis of brain copper and zinc in BXD recombinant inbred mice.

PubMed

Jones, Leslie C; McCarthy, Kristin A; Beard, John L; Keen, Carl L; Jones, Byron C

2006-01-01

Copper and zinc are trace nutrients essential for normal brain function, yet an excess of these elements can be toxic. It is important therefore that these metals be closely regulated. We recently conducted a quantitative trait loci (QTL) analysis to identify chromosomal regions in the mouse containing possible regulatory genes. The animals came from 15 strains of the BXD/Ty recombinant inbred (RI) strain panel and the brain regions analyzed were frontal cortex, caudate-putamen, nucleus accumbens and ventral midbrain. Several QTL were identified for copper and/or zinc, most notably on chromosomes 1, 8, 16 and 17. Genetic correlational analysis also revealed associations between these metals and dopamine, cocaine responses, saccharine preference, immune response and seizure susceptibility. Notably, the QTL on chromosome 17 is also associated with seizure susceptibility and contains the histocompatibility H2 complex. This work shows that regulation of zinc and copper is under polygenic influence and is intimately related to CNS function. Future work will reveal genes underlying the QTL and how they interact with other genes and the environment. More importantly, revelation of the genetic underpinnings of copper and zinc brain homeostasis will aid our understanding of neurological diseases that are related to copper and zinc imbalance.

Novel QTLs for HDL levels identified in mice by controlling for Apoa2 allelic effects: confirmation of a chromosome 6 locus in a congenic strain.

PubMed

Welch, Carrie L; Bretschger, Sara; Wen, Ping-Zi; Mehrabian, Margarete; Latib, Nashat; Fruchart-Najib, Jamila; Fruchart, Jean Charles; Myrick, Christy; Lusis, Aldons J

2004-03-12

Atherosclerosis is a complex disease resulting from the interaction of multiple genes, including those causing dyslipidemia. Relatively few of the causative genes have been identified. Previously, we identified Apoa2 as a major determinant of high-density lipoprotein cholesterol (HDL-C) levels in the mouse model. To identify additional HDL-C level quantitative trait loci (QTLs), while controlling for the effect of the Apoa2 locus, we performed linkage analysis in 179 standard diet-fed F(2) mice derived from strains BALB/cJ and B6.C-H25(c) (a congenic strain carrying the BALB/c Apoa2 allele). Three significant QTLs and one suggestive locus were identified. A female-specific locus mapping to chromosome 6 (Chr 6) also exhibited effects on plasma non-HDL-C, apolipoprotein AII (apoAII), apoB, and apoE levels. A Chr 6 QTL was independently isolated in a related congenic strain (C57BL/6J vs. B6.NODc6: P = 0.003 and P = 0.0001 for HDL-C and non-HDL-C levels, respectively). These data are consistent with polygenic inheritance of HDL-C levels in the mouse model and provide candidate loci for HDL-C and non-HDL-C level determination in humans.

Frequencies of Null Alleles at Enzyme Loci in Natural Populations of Ponderosa and Red Pine

PubMed Central

Allendorf, Fred W.; Knudsen, Kathy L.; Blake, George M.

1982-01-01

Pinus ponderosa and P. resinosa population samples have mean frequencies of enzymatically inactive alleles of 0.0031 and 0.0028 at 29 and 27 enzyme loci, respectively. Such alleles are rare and are apparently maintained by selection-mutation balance. Ponderosa pine have much higher amounts of allozymic and polygenic phenotypic variation than red pine, yet both species have similar frequencies of null alleles. Thus, null alleles apparently do not contribute to polygenic variation, as has been suggested. The concordance between allozymic and polygenic variation adds support to the view that allozyme studies may be valuable in predicting the relative amount of polygenic variation in populations. PMID:17246067

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

PubMed Central

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary; Ripke, Stephan; Yang, Jian; Patterson, Nick; Daly, Mark J.; Price, Alkes L.; Neale, Benjamin M.

2015-01-01

Both polygenicity (i.e., many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size. PMID:25642630

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

PubMed

Malki, Karim; Tosto, Maria Grazia; Mouriño-Talín, Héctor; Rodríguez-Lorenzo, Sabela; Pain, Oliver; Jumhaboy, Irfan; Liu, Tina; Parpas, Panos; Newman, Stuart; Malykh, Artem; Carboni, Lucia; Uher, Rudolf; McGuffin, Peter; Schalkwyk, Leonard C; Bryson, Kevin; Herbster, Mark

2017-04-01

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts.

PubMed

Oguz, Cihan; Sen, Shurjo K; Davis, Adam R; Fu, Yi-Ping; O'Donnell, Christopher J; Gibbons, Gary H

2017-10-26

One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89 th -99 th CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males). These inputs included clinical variables and genotypes of 56 single nucleotide polymorphisms (SNPs) ranked highest in terms of their nominal correlation with the advanced CAC state in the discovery cohort. Predictive performance was assessed by computing the areas under receiver operating characteristic curves (ROC-AUC). RF models trained and tested with clinical variables generated ROC-AUC values of 0.69 and 0.61 in the discovery and replication cohorts, respectively. In contrast, in both cohorts, the set of SNPs derived from the discovery cohort were highly predictive (ROC-AUC ≥0.85) with no significant change in predictive performance upon integration of clinical and genotype variables. Using the 21 SNPs that produced optimal predictive performance in both cohorts, we developed NN models trained with ClinSeq®; data and tested with FHS data and obtained high predictive accuracy (ROC-AUC=0.80-0.85) with several topologies. Several CAD and "vascular aging" related biological processes were enriched in the network of genes constructed from the predictive SNPs. We identified a molecular network predictive of advanced coronary calcium using genotype data from ClinSeq®; and FHS cohorts. Our results illustrate that machine learning tools, which utilize complex interactions between disease predictors intrinsic to the pathogenesis of polygenic disorders, hold promise for deriving predictive disease models and networks.

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

Genetic Architecture of the Variation in Male-Specific Ossified Processes on the Anal Fins of Japanese Medaka.

PubMed

Kawajiri, Maiko; Fujimoto, Shingo; Yoshida, Kohta; Yamahira, Kazunori; Kitano, Jun

2015-10-28

Traits involved in reproduction evolve rapidly and show great diversity among closely related species. However, the genetic mechanisms that underlie the diversification of courtship traits are mostly unknown. Japanese medaka fishes (Oryzias latipes) use anal fins to attract females and to grasp females during courtship; the males have longer anal fins with male-specific ossified papillary processes on the fin rays. However, anal fin morphology varies between populations: the southern populations tend to have longer anal fins and more processes than the northern populations. In the present study, we conducted quantitative trait locus (QTL) mapping to investigate the genetic architecture underlying the variation in the number of papillary processes of Japanese medaka fish and compared the QTL with previously identified QTL controlling anal fin length. First, we found that only a few QTL were shared between anal fin length and papillary process number. Second, we found that the numbers of papillary processes on different fin rays often were controlled by different QTL. Finally, we produced another independent cross and found that some QTL were repeatable between the two crosses, whereas others were specific to only one cross. These results suggest that variation in the number of papillary processes is polygenic and controlled by QTL that are distinct from those controlling anal fin length. Thus, different courtship traits in Japanese medaka share a small number of QTL and have the potential for independent evolution. Copyright © 2015 Kawajiri et al.

Genetic Mapping of Fixed Phenotypes: Disease Frequency as a Breed Characteristic

PubMed Central

Jones, Paul; Martin, Alan; Ostrander, Elaine A.; Lark, Karl G.

2009-01-01

Traits that have been stringently selected to conform to specific criteria in a closed population are phenotypic stereotypes. In dogs, Canis familiaris, such stereotypes have been produced by breeding for conformation, performance (behaviors), etc. We measured phenotypes on a representative sample to establish breed stereotypes. DNA samples from 147 dog breeds were used to characterize single nucleotide polymorphism allele frequencies for association mapping of breed stereotypes. We identified significant size loci (quantitative trait loci [QTLs]), implicating candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Behavioral loci for herding, pointing, and boldness implicated candidate genes appropriate to behavior (e.g., MC2R, DRD1, and PCDH9). Significant loci for longevity, a breed characteristic inversely correlated with breed size, were identified. The power of this approach to identify loci regulating the incidence of specific polygenic diseases is demonstrated by the association of a specific IGF1 haplotype with hip dysplasia, patella luxation, and pacreatitis. PMID:19321632

Quantitative Variation in Responses to Root Spatial Constraint within Arabidopsis thaliana[OPEN

PubMed Central

Joseph, Bindu; Lau, Lillian; Kliebenstein, Daniel J.

2015-01-01

Among the myriad of environmental stimuli that plants utilize to regulate growth and development to optimize fitness are signals obtained from various sources in the rhizosphere that give an indication of the nutrient status and volume of media available. These signals include chemical signals from other plants, nutrient signals, and thigmotropic interactions that reveal the presence of obstacles to growth. Little is known about the genetics underlying the response of plants to physical constraints present within the rhizosphere. In this study, we show that there is natural variation among Arabidopsis thaliana accessions in their growth response to physical rhizosphere constraints and competition. We mapped growth quantitative trait loci that regulate a positive response of foliar growth to short physical constraints surrounding the root. This is a highly polygenic trait and, using quantitative validation studies, we showed that natural variation in EARLY FLOWERING3 (ELF3) controls the link between root constraint and altered shoot growth. This provides an entry point to study how root and shoot growth are integrated to respond to environmental stimuli. PMID:26243313

Genetic mapping of fixed phenotypes: disease frequency as a breed characteristic.

PubMed

Chase, Kevin; Jones, Paul; Martin, Alan; Ostrander, Elaine A; Lark, Karl G

2009-01-01

Traits that have been stringently selected to conform to specific criteria in a closed population are phenotypic stereotypes. In dogs, Canis familiaris, such stereotypes have been produced by breeding for conformation, performance (behaviors), etc. We measured phenotypes on a representative sample to establish breed stereotypes. DNA samples from 147 dog breeds were used to characterize single nucleotide polymorphism allele frequencies for association mapping of breed stereotypes. We identified significant size loci (quantitative trait loci [QTLs]), implicating candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Behavioral loci for herding, pointing, and boldness implicated candidate genes appropriate to behavior (e.g., MC2R, DRD1, and PCDH9). Significant loci for longevity, a breed characteristic inversely correlated with breed size, were identified. The power of this approach to identify loci regulating the incidence of specific polygenic diseases is demonstrated by the association of a specific IGF1 haplotype with hip dysplasia, patella luxation, and pancreatitis.

High Loading of Polygenic Risk for ADHD in Children With Comorbid Aggression

PubMed Central

Hamshere, Marian L.; Langley, Kate; Martin, Joanna; Agha, Sharifah Shameem; Stergiakouli, Evangelia; Anney, Richard J.L.; Buitelaar, Jan; Faraone, Stephen V.; Lesch, Klaus-Peter; Neale, Benjamin M.; Franke, Barbara; Sonuga-Barke, Edmund; Asherson, Philip; Merwood, Andrew; Kuntsi, Jonna; Medland, Sarah E.; Ripke, Stephan; Steinhausen, Hans-Christoph; Freitag, Christine; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Meyer, Jobst; Palmason, Haukur; Vasquez, Alejandro Arias; Lambregts-Rommelse, Nanda; Roeyers, Herbert; Biederman, Joseph; Doyle, Alysa E.; Hakonarson, Hakon; Rothenberger, Aribert; Banaschewski, Tobias; Oades, Robert D.; McGough, James J.; Kent, Lindsey; Williams, Nigel; Owen, Michael J.; Holmans, Peter

2013-01-01

Objective Although attention deficit hyperactivity disorder (ADHD) is highly heritable, genome-wide association studies (GWAS) have not yet identified any common genetic variants that contribute to risk. There is evidence that aggression or conduct disorder in children with ADHD indexes higher genetic loading and clinical severity. The authors examine whether common genetic variants considered en masse as polygenic scores for ADHD are especially enriched in children with comorbid conduct disorder. Method Polygenic scores derived from an ADHD GWAS meta-analysis were calculated in an independent ADHD sample (452 case subjects, 5,081 comparison subjects). Multivariate logistic regression analyses were employed to compare polygenic scores in the ADHD and comparison groups and test for higher scores in ADHD case subjects with comorbid conduct disorder relative to comparison subjects and relative to those without comorbid conduct disorder. Association with symptom scores was tested using linear regression. Results Polygenic risk for ADHD, derived from the meta-analysis, was higher in the independent ADHD group than in the comparison group. Polygenic score was significantly higher in ADHD case subjects with conduct disorder relative to ADHD case subjects without conduct disorder. ADHD polygenic score showed significant association with comorbid conduct disorder symptoms. This relationship was explained by the aggression items. Conclusions Common genetic variation is relevant to ADHD, especially in individuals with comorbid aggression. The findings suggest that the previously published ADHD GWAS meta-analysis contains weak but true associations with common variants, support for which falls below genome-wide significance levels. The findings also highlight the fact that aggression in ADHD indexes genetic as well as clinical severity. PMID:23599091

Polygenic risk for depression and the neural correlates of working memory in healthy subjects.

PubMed

Yüksel, Dilara; Dietsche, Bruno; Forstner, Andreas J; Witt, Stephanie H; Maier, Robert; Rietschel, Marcella; Konrad, Carsten; Nöthen, Markus M; Dannlowski, Udo; Baune, Bernhard T; Kircher, Tilo; Krug, Axel

2017-10-03

Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients. In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results. A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition. The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

PubMed Central

Pecetti, Luciano; Brummer, E. Charles; Palmonari, Alberto; Tava, Aldo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3–0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield. PMID:28068350

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits.

PubMed

Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield.

Genetic heterogeneity in depressive symptoms following the death of a spouse: Polygenic score analysis of the US Health and Retirement Study

PubMed Central

Domingue, Benjamin W.; Liu, Hexuan; Okbay, Aysu; Belsky, Daniel W.

2017-01-01

Objective Experience of stressful life events is associated with risk of depression. Yet many exposed individuals do not become depressed. A controversial hypothesis is that genetic factors influence vulnerability to depression following stress. This hypothesis is often tested with a “diathesis-stress” model, in which genes confer excess vulnerability. We tested an alternative formulation of this model: genes may buffer against depressogenic effects of life stress. Method We measured the hypothesized genetic buffer using a polygenic score derived from a published genome-wide association study (GWAS) of subjective wellbeing. We tested if married older adults who had higher polygenic scores were less vulnerable to depressive symptoms following the death of their spouse as compared to age-peers who had also lost their spouse and who had lower polygenic scores. We analyzed data from N=8,588 non-Hispanic white adults in the Health and Retirement Study (HRS), a population-representative longitudinal study of older adults in the United States. Results HRS adults with higher wellbeing polygenic scores experienced fewer depressive symptoms during follow-up. Those who survived death of their spouses (n=1,647) experienced a sharp increase in depressive symptoms following the death and returned toward baseline over the following two years. Having a higher polygenic score buffered against increased depressive symptoms following a spouse’s death. Conclusions Effects were small and clinical relevance is uncertain, although polygenic score analyses may provide clues to behavioral pathways that can serve as therapeutic targets. Future studies of gene-environment interplay in depression may benefit from focus on genetics discovered for putative protective factors. PMID:28335623

Genome-wide analysis of adolescent psychotic-like experiences shows genetic overlap with psychiatric disorders.

PubMed

Pain, Oliver; Dudbridge, Frank; Cardno, Alastair G; Freeman, Daniel; Lu, Yi; Lundstrom, Sebastian; Lichtenstein, Paul; Ronald, Angelica

2018-03-31

This study aimed to test for overlap in genetic influences between psychotic-like experience traits shown by adolescents in the community, and clinically-recognized psychiatric disorders in adulthood, specifically schizophrenia, bipolar disorder, and major depression. The full spectra of psychotic-like experience domains, both in terms of their severity and type (positive, cognitive, and negative), were assessed using self- and parent-ratings in three European community samples aged 15-19 years (Final N incl. siblings = 6,297-10,098). A mega-genome-wide association study (mega-GWAS) for each psychotic-like experience domain was performed. Single nucleotide polymorphism (SNP)-heritability of each psychotic-like experience domain was estimated using genomic-relatedness-based restricted maximum-likelihood (GREML) and linkage disequilibrium- (LD-) score regression. Genetic overlap between specific psychotic-like experience domains and schizophrenia, bipolar disorder, and major depression was assessed using polygenic risk score (PRS) and LD-score regression. GREML returned SNP-heritability estimates of 3-9% for psychotic-like experience trait domains, with higher estimates for less skewed traits (Anhedonia, Cognitive Disorganization) than for more skewed traits (Paranoia and Hallucinations, Parent-rated Negative Symptoms). Mega-GWAS analysis identified one genome-wide significant association for Anhedonia within IDO2 but which did not replicate in an independent sample. PRS analysis revealed that the schizophrenia PRS significantly predicted all adolescent psychotic-like experience trait domains (Paranoia and Hallucinations only in non-zero scorers). The major depression PRS significantly predicted Anhedonia and Parent-rated Negative Symptoms in adolescence. Psychotic-like experiences during adolescence in the community show additive genetic effects and partly share genetic influences with clinically-recognized psychiatric disorders, specifically schizophrenia and major depression. © 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Contrasting results from GWAS and QTL mapping on wing length in great reed warblers.

PubMed

Hansson, Bengt; Sigeman, Hanna; Stervander, Martin; Tarka, Maja; Ponnikas, Suvi; Strandh, Maria; Westerdahl, Helena; Hasselquist, Dennis

2018-04-15

A major goal in evolutionary biology is to understand the genetic basis of adaptive traits. In migratory birds, wing morphology is such a trait. Our previous work on the great reed warbler (Acrocephalus arundinaceus) shows that wing length is highly heritable and under sexually antagonistic selection. Moreover, a quantitative trait locus (QTL) mapping analysis detected a pronounced QTL for wing length on chromosome 2, suggesting that wing morphology is partly controlled by genes with large effects. Here, we re-evaluate the genetic basis of wing length in great reed warblers using a genomewide association study (GWAS) approach based on restriction site-associated DNA sequencing (RADseq) data. We use GWAS models that account for relatedness between individuals and include covariates (sex, age and tarsus length). The resulting association landscape was flat with no peaks on chromosome 2 or elsewhere, which is in line with expectations for polygenic traits. Analysis of the distribution of p-values did not reveal biases, and the inflation factor was low. Effect sizes were however not uniformly distributed on some chromosomes, and the Z chromosome had weaker associations than autosomes. The level of linkage disequilibrium (LD) in the population decayed to background levels within c. 1 kbp. There could be several reasons to why our QTL study and GWAS gave contrasting results including differences in how associations are modelled (cosegregation in pedigree vs. LD associations), how covariates are accounted for in the models, type of marker used (multi- vs. biallelic), difference in power or a combination of these. Our study highlights that the genetic architecture even of highly heritable traits is difficult to characterize in wild populations. © 2018 John Wiley & Sons Ltd.

The effects of intraspecific competition and stabilizing selection on a polygenic trait.

PubMed Central

Bürger, Reinhard; Gimelfarb, Alexander

2004-01-01

The equilibrium properties of an additive multilocus model of a quantitative trait under frequency- and density-dependent selection are investigated. Two opposing evolutionary forces are assumed to act: (i) stabilizing selection on the trait, which favors genotypes with an intermediate phenotype, and (ii) intraspecific competition mediated by that trait, which favors genotypes whose effect on the trait deviates most from that of the prevailing genotypes. Accordingly, fitnesses of genotypes have a frequency-independent component describing stabilizing selection and a frequency- and density-dependent component modeling competition. We study how the equilibrium structure, in particular, number, degree of polymorphism, and genetic variance of stable equilibria, is affected by the strength of frequency dependence, and what role the number of loci, the amount of recombination, and the demographic parameters play. To this end, we employ a statistical and numerical approach, complemented by analytical results, and explore how the equilibrium properties averaged over a large number of genetic systems with a given number of loci and average amount of recombination depend on the ecological and demographic parameters. We identify two parameter regions with a transitory region in between, in which the equilibrium properties of genetic systems are distinctively different. These regions depend on the strength of frequency dependence relative to pure stabilizing selection and on the demographic parameters, but not on the number of loci or the amount of recombination. We further study the shape of the fitness function observed at equilibrium and the extent to which the dynamics in this model are adaptive, and we present examples of equilibrium distributions of genotypic values under strong frequency dependence. Consequences for the maintenance of genetic variation, the detection of disruptive selection, and models of sympatric speciation are discussed. PMID:15280253

Identification of multiple interacting alleles conferring low glycerol and high ethanol yield in Saccharomyces cerevisiae ethanolic fermentation

PubMed Central

2013-01-01

Background Genetic engineering of industrial microorganisms often suffers from undesirable side effects on essential functions. Reverse engineering is an alternative strategy to improve multifactorial traits like low glycerol/high ethanol yield in yeast fermentation. Previous rational engineering of this trait always affected essential functions like growth and stress tolerance. We have screened Saccharomyces cerevisiae biodiversity for specific alleles causing lower glycerol/higher ethanol yield, assuming higher compatibility with normal cellular functionality. Previous work identified ssk1E330N…K356N as causative allele in strain CBS6412, which displayed the lowest glycerol/ethanol ratio. Results We have now identified a unique segregant, 26B, that shows similar low glycerol/high ethanol production as the superior parent, but lacks the ssk1E330N…K356N allele. Using segregants from the backcross of 26B with the inferior parent strain, we applied pooled-segregant whole-genome sequence analysis and identified three minor quantitative trait loci (QTLs) linked to low glycerol/high ethanol production. Within these QTLs, we identified three novel alleles of known regulatory and structural genes of glycerol metabolism, smp1R110Q,P269Q, hot1P107S,H274Y and gpd1L164P as causative genes. All three genes separately caused a significant drop in the glycerol/ethanol production ratio, while gpd1L164P appeared to be epistatically suppressed by other alleles in the superior parent. The order of potency in reducing the glycerol/ethanol ratio of the three alleles was: gpd1L164P > hot1P107S,H274Y ≥ smp1R110Q,P269Q. Conclusions Our results show that natural yeast strains harbor multiple specific alleles of genes controlling essential functions, that are apparently compatible with survival in the natural environment. These newly identified alleles can be used as gene tools for engineering industrial yeast strains with multiple subtle changes, minimizing the risk of negatively affecting other essential functions. The gene tools act at the transcriptional, regulatory or structural gene level, distributing the impact over multiple targets and thus further minimizing possible side-effects. In addition, the results suggest polygenic analysis of complex traits as a promising new avenue to identify novel components involved in cellular functions, including those important in industrial applications. PMID:23759206

Contrasting modes and tempos of venom expression evolution in two snake species.

PubMed

Margres, Mark J; McGivern, James J; Seavy, Margaret; Wray, Kenneth P; Facente, Jack; Rokyta, Darin R

2015-01-01

Selection is predicted to drive diversification within species and lead to local adaptation, but understanding the mechanistic details underlying this process and thus the genetic basis of adaptive evolution requires the mapping of genotype to phenotype. Venom is complex and involves many genes, but the specialization of the venom gland toward toxin production allows specific transcripts to be correlated with specific toxic proteins, establishing a direct link from genotype to phenotype. To determine the extent of expression variation and identify the processes driving patterns of phenotypic diversity, we constructed genotype-phenotype maps and compared range-wide toxin-protein expression variation for two species of snake with nearly identical ranges: the eastern diamondback rattlesnake (Crotalus adamanteus) and the eastern coral snake (Micrurus fulvius). We detected significant expression variation in C. adamanteus, identified the specific loci associated with population differentiation, and found that loci expressed at all levels contributed to this divergence. Contrary to expectations, we found no expression variation in M. fulvius, suggesting that M. fulvius populations are not locally adapted. Our results not only linked expression variation at specific loci to divergence in a polygenic, complex trait but also have extensive conservation and biomedical implications. C. adamanteus is currently a candidate for federal listing under the Endangered Species Act, and the loss of any major population would result in the irrevocable loss of a unique venom phenotype. The lack of variation in M. fulvius has significant biomedical application because our data will assist in the development of effective antivenom for this species. Copyright © 2015 by the Genetics Society of America.

Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

PubMed Central

Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.

2013-01-01

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047

Convergent local adaptation to climate in distantly related conifers.

PubMed

Yeaman, Sam; Hodgins, Kathryn A; Lotterhos, Katie E; Suren, Haktan; Nadeau, Simon; Degner, Jon C; Nurkowski, Kristin A; Smets, Pia; Wang, Tongli; Gray, Laura K; Liepe, Katharina J; Hamann, Andreas; Holliday, Jason A; Whitlock, Michael C; Rieseberg, Loren H; Aitken, Sally N

2016-09-23

When confronted with an adaptive challenge, such as extreme temperature, closely related species frequently evolve similar phenotypes using the same genes. Although such repeated evolution is thought to be less likely in highly polygenic traits and distantly related species, this has not been tested at the genome scale. We performed a population genomic study of convergent local adaptation among two distantly related species, lodgepole pine and interior spruce. We identified a suite of 47 genes, enriched for duplicated genes, with variants associated with spatial variation in temperature or cold hardiness in both species, providing evidence of convergent local adaptation despite 140 million years of separate evolution. These results show that adaptation to climate can be genetically constrained, with certain key genes playing nonredundant roles. Copyright © 2016, American Association for the Advancement of Science.

Genetical genomics of Populus leaf shape variation

DOE PAGES

Drost, Derek R.; Puranik, Swati; Novaes, Evandro; ...

2015-06-30

Leaf morphology varies extensively among plant species and is under strong genetic control. Mutagenic screens in model systems have identified genes and established molecular mechanisms regulating leaf initiation, development, and shape. However, it is not known whether this diversity across plant species is related to naturally occurring variation at these genes. Quantitative trait locus (QTL) analysis has revealed a polygenic control for leaf shape variation in different species suggesting that loci discovered by mutagenesis may only explain part of the naturally occurring variation in leaf shape. Here we undertook a genetical genomics study in a poplar intersectional pseudo-backcross pedigree tomore » identify genetic factors controlling leaf shape. Here, the approach combined QTL discovery in a genetic linkage map anchored to the Populus trichocarpa reference genome sequence and transcriptome analysis.« less

Shovel-shaped incisors and associated invagination in some Asian and African populations.

PubMed

Kharat, D U; Saini, T S; Mokeem, S

1990-08-01

Shovelling of the incisors is considered to be a polygenic inheritable trait. Shovelling differs considerably between groups of racial populations but is relatively stable within each group. Presence or absence of shovelling helps in racial identification and in exploration of ancestry. Periapical radiographs of patients of several nationalities from Asian and African continents were obtained. Shovelling and invaginations associated with the shovel-shaped incisors was studied according to nationality. Results indicated that the incidence of shovelling in Syrians, Jordanians, Palestinians and Filipinos was 5-6 per cent. In Saudi Arabians, Pakistanis and Indians, the incidence of shovelling was 10-12 per cent. Among Yemenis, Sudanese and Egyptians, the incidence of shovelling was 20-25 percent. The occurrence of invaginations in shovel-shaped incisors was 11 per cent.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

PubMed

Coleman, Jonathan R I; Lester, Kathryn J; Roberts, Susanna; Keers, Robert; Lee, Sang Hyuck; De Jong, Simone; Gaspar, Héléna; Teismann, Tobias; Wannemüller, André; Schneider, Silvia; Jöhren, Peter; Margraf, Jürgen; Breen, Gerome; Eley, Thalia C

2017-04-01

Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

On the Origin of Complex Adaptive Traits: Progress Since the Darwin Versus Mivart Debate.

PubMed

Suzuki, Takao K

2017-06-01

The evolutionary origin of complex adaptive traits has been a controversial topic in the history of evolutionary biology. Although Darwin argued for the gradual origins of complex adaptive traits within the theory of natural selection, Mivart insisted that natural selection could not account for the incipient stages of complex traits. The debate starting from Darwin and Mivart eventually engendered two opposite views: gradualism and saltationism. Although this has been a long-standing debate, the issue remains unresolved. However, recent studies have interrogated classic examples of complex traits, such as the asymmetrical eyes of flatfishes and leaf mimicry of butterfly wings, whose origins were debated by Darwin and Mivart. Here, I review recent findings as a starting point to provide a modern picture of the evolution of complex adaptive traits. First, I summarize the empirical evidence that unveils the evolutionary steps toward complex traits. I then argue that the evolution of complex traits could be understood within the concept of "reducible complexity." Through these discussions, I propose a conceptual framework for the formation of complex traits, named as reducible-composable multicomponent systems, that satisfy two major characteristics: reducibility into a sum of subcomponents and composability to construct traits from various additional and combinatorial arrangements of the subcomponents. This conceptual framework provides an analytical foundation for exploring evolutionary pathways to build up complex traits. This review provides certain essential avenues for deciphering the origin of complex adaptive traits. © 2017 Wiley Periodicals, Inc.

On the maintenance of genetic variation and adaptation to environmental change: considerations from population genomics in fishes.

PubMed

Bernatchez, L

2016-12-01

The first goal of this paper was to overview modern approaches to local adaptation, with a focus on the use of population genomics data to detect signals of natural selection in fishes. Several mechanisms are discussed that may enhance the maintenance of genetic variation and evolutionary potential, which have been overlooked and should be considered in future theoretical development and predictive models: the prevalence of soft sweeps, polygenic basis of adaptation, balancing selection and transient polymorphisms, parallel evolution, as well as epigenetic variation. Research on fish population genomics has provided ample evidence for local adaptation at the genome level. Pervasive adaptive evolution, however, seems to almost never involve the fixation of beneficial alleles. Instead, adaptation apparently proceeds most commonly by soft sweeps entailing shifts in frequencies of alleles being shared between differentially adapted populations. One obvious factor contributing to the maintenance of standing genetic variation in the face of selective pressures is that adaptive phenotypic traits are most often highly polygenic, and consequently the response to selection should derive mostly from allelic co-variances among causative loci rather than pronounced allele frequency changes. Balancing selection in its various forms may also play an important role in maintaining adaptive genetic variation and the evolutionary potential of species to cope with environmental change. A large body of literature on fishes also shows that repeated evolution of adaptive phenotypes is a ubiquitous evolutionary phenomenon that seems to occur most often via different genetic solutions, further adding to the potential options of species to cope with a changing environment. Moreover, a paradox is emerging from recent fish studies whereby populations of highly reduced effective population sizes and impoverished genetic diversity can apparently retain their adaptive potential in some circumstances. Although more empirical support is needed, several recent studies suggest that epigenetic variation could account for this apparent paradox. Therefore, epigenetic variation should be fully integrated with considerations pertaining to role of soft sweeps, polygenic and balancing selection, as well as repeated adaptation involving different genetic basis towards improving models predicting the evolutionary potential of species to cope with a changing world. © 2016 The Fisheries Society of the British Isles.

Polygenic risk for coronary artery disease is associated with cognitive ability in older adults

PubMed Central

Hagenaars, Saskia P; Harris, Sarah E; Clarke, Toni-Kim; Hall, Lynsey; Luciano, Michelle; Fernandez-Pujals, Ana Maria; Davies, Gail; Hayward, Caroline; Starr, John M; Porteous, David J; McIntosh, Andrew M; Deary, Ian J

2016-01-01

Abstract Background: Coronary artery disease (CAD) is associated with cognitive decrements and risk of later dementia, but it is not known if shared genetic factors underlie this association. We tested whether polygenic risk for CAD was associated with cognitive ability in community-dwelling cohorts of middle-aged and older adults. Methods: Individuals from Generation Scotland: Scottish Family Health Study (GS:SFHS, N = 9865) and from the Lothian Birth Cohorts of 1921 (LBC1921, N  = 517) and 1936 (LBC1936, N  = 1005) provided cognitive data and genome-wide genotype data. Polygenic risk profile scores for CAD were calculated for all of the cohorts using the largest available genome-wide association studies (GWAS) data set, the CARDIoGRAM consortium (22 233 cases and 64 762 controls). Polygenic risk profile scores for CAD were then tested for their association with cognitive abilities in the presence and absence of manifest cardiovascular disease. Results: A meta-analysis of all three cohorts showed a negative association between CAD polygenic risk and fluid cognitive ability (β = −0.022, P  = 0.016), verbal intelligence (β = −0.024, P  = 0.011) and memory (β = −0.021, P  = 0.028). Conclusions: Increased polygenic risk for CAD is associated with lower cognitive ability in older adults. Common genetic variants may underlie some of the association between age-related cognitive decrements and the risk for CAD. PMID:26822939

A systematic review of genome-wide research on psychotic experiences and negative symptom traits: New revelations and implications for psychiatry.

PubMed

Ronald, Angelica; Pain, Oliver

2018-05-08

We present a systematic review of genome-wide research on psychotic experience and negative symptom traits (PENS) in the community. We integrate these new findings, most of which have emerged over the last four years, with more established behaviour genetic and epidemiological research. The review includes the first genome-wide association studies of PENS, including a recent meta-analysis, and the first SNP heritability estimates. Sample sizes of < 10,000 participants mean that no genome-wide significant variants have yet been replicated. Importantly, however, in the most recent and well-powered studies, polygenic risk score prediction and linkage disequilibrium (LD) score regression analyses show that all types of PENS share genetic influences with diagnosed schizophrenia and that negative symptom traits also share genetic influences with major depression. These genetic findings corroborate other evidence in supporting a link between PENS in the community and psychiatric conditions. Beyond the systematic review, we highlight recent work on gene-environment correlation, which appears to be a relevant process for psychotic experiences. Genes that influence risk factors such as tobacco use and stressful life events are likely to be harbouring 'hits' that also influence PENS. We argue for the acceptance of PENS within the mainstream, as heritable traits in the same vein as other subclinical psychopathology and personality styles such as neuroticism. While acknowledging some mixed findings, new evidence shows genetic overlap between PENS and psychiatric conditions. In sum, normal variations in adolescent and adult thinking styles, such as feeling paranoid, are heritable and show genetic associations with schizophrenia and major depression.

Genome-Wide Association Studies of a Broad Spectrum of Antisocial Behavior.

PubMed

Tielbeek, Jorim J; Johansson, Ada; Polderman, Tinca J C; Rautiainen, Marja-Riitta; Jansen, Philip; Taylor, Michelle; Tong, Xiaoran; Lu, Qing; Burt, Alexandra S; Tiemeier, Henning; Viding, Essi; Plomin, Robert; Martin, Nicholas G; Heath, Andrew C; Madden, Pamela A F; Montgomery, Grant; Beaver, Kevin M; Waldman, Irwin; Gelernter, Joel; Kranzler, Henry R; Farrer, Lindsay A; Perry, John R B; Munafò, Marcus; LoParo, Devon; Paunio, Tiina; Tiihonen, Jari; Mous, Sabine E; Pappa, Irene; de Leeuw, Christiaan; Watanabe, Kyoko; Hammerschlag, Anke R; Salvatore, Jessica E; Aliev, Fazil; Bigdeli, Tim B; Dick, Danielle; Faraone, Stephen V; Popma, Arne; Medland, Sarah E; Posthuma, Danielle

2017-12-01

Antisocial behavior (ASB) places a large burden on perpetrators, survivors, and society. Twin studies indicate that half of the variation in this trait is genetic. Specific causal genetic variants have, however, not been identified. To estimate the single-nucleotide polymorphism-based heritability of ASB; to identify novel genetic risk variants, genes, or biological pathways; to test for pleiotropic associations with other psychiatric traits; and to reevaluate the candidate gene era data through the Broad Antisocial Behavior Consortium. Genome-wide association data from 5 large population-based cohorts and 3 target samples with genome-wide genotype and ASB data were used for meta-analysis from March 1, 2014, to May 1, 2016. All data sets used quantitative phenotypes, except for the Finnish Crime Study, which applied a case-control design (370 patients and 5850 control individuals). This study adopted relatively broad inclusion criteria to achieve a quantitative measure of ASB derived from multiple measures, maximizing the sample size over different age ranges. The discovery samples comprised 16 400 individuals, whereas the target samples consisted of 9381 individuals (all individuals were of European descent), including child and adult samples (mean age range, 6.7-56.1 years). Three promising loci with sex-discordant associations were found (8535 female individuals, chromosome 1: rs2764450, chromosome 11: rs11215217; 7772 male individuals, chromosome X, rs41456347). Polygenic risk score analyses showed prognostication of antisocial phenotypes in an independent Finnish Crime Study (2536 male individuals and 3684 female individuals) and shared genetic origin with conduct problems in a population-based sample (394 male individuals and 431 female individuals) but not with conduct disorder in a substance-dependent sample (950 male individuals and 1386 female individuals) (R2 = 0.0017 in the most optimal model, P = 0.03). Significant inverse genetic correlation of ASB with educational attainment (r = -0.52, P = .005) was detected. The Broad Antisocial Behavior Consortium entails the largest collaboration to date on the genetic architecture of ASB, and the first results suggest that ASB may be highly polygenic and has potential heterogeneous genetic effects across sex.

Genome-Wide Association Study for Indicator Traits of Sexual Precocity in Nellore Cattle

PubMed Central

Irano, Natalia; de Camargo, Gregório Miguel Ferreira; Costa, Raphael Bermal; Terakado, Ana Paula Nascimento; Magalhães, Ana Fabrícia Braga; Silva, Rafael Medeiros de Oliveira; Dias, Marina Mortati; Bignardi, Annaiza Braga; Baldi, Fernando; Carvalheiro, Roberto; de Oliveira, Henrique Nunes; de Albuquerque, Lucia Galvão

2016-01-01

The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen® and Paint® animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations. PMID:27494397

Epistasis between 5-HTTLPR and ADRA2B polymorphisms influences attentional bias for emotional information in healthy volunteers.

PubMed

Naudts, Kris H; Azevedo, Ruben T; David, Anthony S; van Heeringen, Kees; Gibbs, Ayana A

2012-09-01

Individual differences in emotional processing are likely to contribute to vulnerability and resilience to emotional disorders such as depression and anxiety. Genetic variation is known to contribute to these differences but they remain incompletely understood. The serotonin transporter (5-HTTLPR) and α2B-adrenergic autoreceptor (ADRA2B) insertion/deletion polymorphisms impact on two separate but interacting monaminergic signalling mechanisms that have been implicated in both emotional processing and emotional disorders. Recent studies suggest that the 5-HTTLPR s allele is associated with a negative attentional bias and an increased risk of emotional disorders. However, such complex behavioural traits are likely to exhibit polygenicity, including epistasis. This study examined the contribution of the 5-HTTLPR and ADRA2B insertion/deletion polymorphisms to attentional biases for aversive information in 94 healthy male volunteers and found evidence of a significant epistatic effect (p<0.001). Specifically, in the presence of the 5-HTTLPR s allele, the attentional bias for aversive information was attenuated by possession of the ADRA2B deletion variant whereas in the absence of the s allele, the bias was enhanced. These data identify a cognitive mechanism linking genotype-dependent serotonergic and noradrenergic signalling that is likely to have implications for the development of cognitive markers for depression/anxiety as well as therapeutic drug effects and personalized approaches to treatment.

Association of human height-related genetic variants with familial short stature in Han Chinese in Taiwan.

PubMed

Lin, Ying-Ju; Liao, Wen-Ling; Wang, Chung-Hsing; Tsai, Li-Ping; Tang, Chih-Hsin; Chen, Chien-Hsiun; Wu, Jer-Yuarn; Liang, Wen-Miin; Hsieh, Ai-Ru; Cheng, Chi-Fung; Chen, Jin-Hua; Chien, Wen-Kuei; Lin, Ting-Hsu; Wu, Chia-Ming; Liao, Chiu-Chu; Huang, Shao-Mei; Tsai, Fuu-Jen

2017-07-25

Human height can be described as a classical and inherited trait model. Genome-wide association studies (GWAS) have revealed susceptible loci and provided insights into the polygenic nature of human height. Familial short stature (FSS) represents a suitable trait for investigating short stature genetics because disease associations with short stature have been ruled out in this case. In addition, FSS is caused only by genetically inherited factors. In this study, we explored the correlations of FSS risk with the genetic loci associated with human height in previous GWAS, alone and cumulatively. We systematically evaluated 34 known human height single nucleotide polymorphisms (SNPs) in relation to FSS in the additive model (p < 0.00005). A cumulative effect was observed: the odds ratios gradually increased with increasing genetic risk score quartiles (p < 0.001; Cochran-Armitage trend test). Six affected genes-ZBTB38, ZNF638, LCORL, CABLES1, CDK10, and TSEN15-are located in the nucleus and have been implicated in embryonic, organismal, and tissue development. In conclusion, our study suggests that 13 human height GWAS-identified SNPs are associated with FSS risk both alone and cumulatively.

Population-Based Resequencing of Experimentally Evolved Populations Reveals the Genetic Basis of Body Size Variation in Drosophila melanogaster

PubMed Central

Turner, Thomas L.; Stewart, Andrew D.; Fields, Andrew T.; Rice, William R.; Tarone, Aaron M.

2011-01-01

Body size is a classic quantitative trait with evolutionarily significant variation within many species. Locating the alleles responsible for this variation would help understand the maintenance of variation in body size in particular, as well as quantitative traits in general. However, successful genome-wide association of genotype and phenotype may require very large sample sizes if alleles have low population frequencies or modest effects. As a complementary approach, we propose that population-based resequencing of experimentally evolved populations allows for considerable power to map functional variation. Here, we use this technique to investigate the genetic basis of natural variation in body size in Drosophila melanogaster. Significant differentiation of hundreds of loci in replicate selection populations supports the hypothesis that the genetic basis of body size variation is very polygenic in D. melanogaster. Significantly differentiated variants are limited to single genes at some loci, allowing precise hypotheses to be formed regarding causal polymorphisms, while other significant regions are large and contain many genes. By using significantly associated polymorphisms as a priori candidates in follow-up studies, these data are expected to provide considerable power to determine the genetic basis of natural variation in body size. PMID:21437274

BMD Loci Contribute to Ethnic and Developmental Differences in Skeletal Fragility across Populations: Assessment of Evolutionary Selection Pressures

PubMed Central

Medina-Gómez, Carolina; Chesi, Alessandra; Heppe, Denise H.M.; Zemel, Babette S.; Yin, Jia-Lian; Kalkwarf, Heidi J.; Hofman, Albert; Lappe, Joan M.; Kelly, Andrea; Kayser, Manfred; Oberfield, Sharon E.; Gilsanz, Vicente; Uitterlinden, André G.; Shepherd, John A.; Jaddoe, Vincent W.V.; Grant, Struan F.A.; Lao, Oscar; Rivadeneira, Fernando

2015-01-01

Bone mineral density (BMD) is a highly heritable trait used both for the diagnosis of osteoporosis in adults and to assess bone health in children. Ethnic differences in BMD have been documented, with markedly higher levels in individuals of African descent, which partially explain disparity in osteoporosis risk across populations. To date, 63 independent genetic variants have been associated with BMD in adults of Northern-European ancestry. Here, we demonstrate that at least 61 of these variants are predictive of BMD early in life by studying their compound effect within two multiethnic pediatric cohorts. Furthermore, we show that within these cohorts and across populations worldwide the frequency of those alleles associated with increased BMD is systematically elevated in individuals of Sub-Saharan African ancestry. The amount of differentiation in the BMD genetic scores among Sub-Saharan and non-Sub-Saharan populations together with neutrality tests, suggest that these allelic differences are compatible with the hypothesis of selective pressures acting on the genetic determinants of BMD. These findings constitute an explorative contribution to the role of selection on ethnic BMD differences and likely a new example of polygenic adaptation acting on a human trait. PMID:26226985

Trait-specific long-term consequences of genomic selection in beef cattle.

PubMed

de Rezende Neves, Haroldo Henrique; Carvalheiro, Roberto; de Queiroz, Sandra Aidar

2018-02-01

Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS.

Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

PubMed

Vink, Jacqueline M; Hottenga, Jouke Jan; de Geus, Eco J C; Willemsen, Gonneke; Neale, Michael C; Furberg, Helena; Boomsma, Dorret I

2014-07-01

A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking. Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subjects). Using different P-value thresholds (0.1, 0.2 and 0.5) from the meta-analysis, sets of 'risk alleles' were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis. The polygenic scores for 'cigarettes per day' were associated significantly with the number of glasses alcohol per week (P = 0.005, R2 = 0.4-0.5%) and cannabis initiation (P = 0.004, R2 = 0.6-0.9%). The polygenic scores for 'age at onset of smoking' were associated significantly with 'age at regular drinking' (P = 0.001, R2 = 1.1-1.5%), while the scores for 'smoking initiation' and 'smoking cessation' did not significantly predict alcohol or cannabis use. Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size. © 2014 Society for the Study of Addiction.

Neurogenomics and the role of a large mutational target on rapid behavioral change.

PubMed

Stanley, Craig E; Kulathinal, Rob J

2016-11-08

Behavior, while complex and dynamic, is among the most diverse, derived, and rapidly evolving traits in animals. The highly labile nature of heritable behavioral change is observed in such evolutionary phenomena as the emergence of converged behaviors in domesticated animals, the rapid evolution of preferences, and the routine development of ethological isolation between diverging populations and species. In fact, it is believed that nervous system development and its potential to evolve a seemingly infinite array of behavioral innovations played a major role in the successful diversification of metazoans, including our own human lineage. However, unlike other rapidly evolving functional systems such as sperm-egg interactions and immune defense, the genetic basis of rapid behavioral change remains elusive. Here we propose that the rapid divergence and widespread novelty of innate and adaptive behavior is primarily a function of its genomic architecture. Specifically, we hypothesize that the broad diversity of behavioral phenotypes present at micro- and macroevolutionary scales is promoted by a disproportionately large mutational target of neurogenic genes. We present evidence that these large neuro-behavioral targets are significant and ubiquitous in animal genomes and suggest that behavior's novelty and rapid emergence are driven by a number of factors including more selection on a larger pool of variants, a greater role of phenotypic plasticity, and/or unique molecular features present in large genes. We briefly discuss the origins of these large neurogenic genes, as they relate to the remarkable diversity of metazoan behaviors, and highlight key consequences on both behavioral traits and neurogenic disease across, respectively, evolutionary and ontogenetic time scales. Current approaches to studying the genetic mechanisms underlying rapid phenotypic change primarily focus on identifying signatures of Darwinian selection in protein-coding regions. In contrast, the large mutational target hypothesis places genomic architecture and a larger allelic pool at the forefront of rapid evolutionary change, particularly in genetic systems that are polygenic and regulatory in nature. Genomic data from brain and neural tissues in mammals as well as a preliminary survey of neurogenic genes from comparative genomic data support this hypothesis while rejecting both positive and relaxed selection on proteins or higher mutation rates. In mammals and invertebrates, neurogenic genes harbor larger protein-coding regions and possess a richer regulatory repertoire of miRNA targets and transcription factor binding sites. Overall, neurogenic genes cover a disproportionately large genomic fraction, providing a sizeable substrate for evolutionary, genetic, and molecular mechanisms to act upon. Readily available comparative and functional genomic data provide unexplored opportunities to test whether a distinct neurogenomic architecture can promote rapid behavioral change via several mechanisms unique to large genes, and which components of this large footprint are uniquely metazoan. The large mutational target hypothesis highlights the eminent roles of mutation and functional genomic architecture in generating rapid developmental and evolutionary change. It has broad implications on our understanding of the genetics of complex adaptive traits such as behavior by focusing on the importance of mutational input, from SNPs to alternative transcripts to transposable elements, on driving evolutionary rates of functional systems. Such functional divergence has important implications in promoting behavioral isolation across short- and long-term timescales. Due to genome-scaled polygenic adaptation, the large target effect also contributes to our inability to identify adapted behavioral candidate genes. The presence of large neurogenic genes, particularly in the mammalian brain and other neural tissues, further offers emerging insight into the etiology of neurodevelopmental and neurodegenerative diseases. The well-known correlation between neurological spectrum disorders in children and paternal age may simply be a direct result of aging fathers accumulating mutations across these large neurodevelopmental genes. The large mutational target hypothesis can also explain the rapid evolution of other functional systems covering a large genomic fraction such as male fertility and its preferential association with hybrid male sterility among closely related taxa. Overall, a focus on mutational potential may increase our power in understanding the genetic basis of complex phenotypes such as behavior while filling a general gap in understanding their evolution.

A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism

PubMed Central

Carayol, Jérôme; Schellenberg, Gerard D.; Dombroski, Beth; Amiet, Claire; Génin, Bérengère; Fontaine, Karine; Rousseau, Francis; Vazart, Céline; Cohen, David; Frazier, Thomas W.; Hardan, Antonio Y.; Dawson, Geraldine; Rio Frio, Thomas

2014-01-01

Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40–60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10−7 in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism. PMID:24600472

Sequence-Based Prioritization of Nonsynonymous Single-Nucleotide Polymorphisms for the Study of Disease Mutations

PubMed Central

Jiang, Rui ; Yang, Hua ; Zhou, Linqi ; Kuo, C.-C. Jay ; Sun, Fengzhu ; Chen, Ting 

2007-01-01

The increasing demand for the identification of genetic variation responsible for common diseases has translated into a need for sophisticated methods for effectively prioritizing mutations occurring in disease-associated genetic regions. In this article, we prioritize candidate nonsynonymous single-nucleotide polymorphisms (nsSNPs) through a bioinformatics approach that takes advantages of a set of improved numeric features derived from protein-sequence information and a new statistical learning model called “multiple selection rule voting” (MSRV). The sequence-based features can maximize the scope of applications of our approach, and the MSRV model can capture subtle characteristics of individual mutations. Systematic validation of the approach demonstrates that this approach is capable of prioritizing causal mutations for both simple monogenic diseases and complex polygenic diseases. Further studies of familial Alzheimer diseases and diabetes show that the approach can enrich mutations underlying these polygenic diseases among the top of candidate mutations. Application of this approach to unclassified mutations suggests that there are 10 suspicious mutations likely to cause diseases, and there is strong support for this in the literature. PMID:17668383

Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy.

PubMed

Leu, Costin; Balestrini, Simona; Maher, Bridget; Hernández-Hernández, Laura; Gormley, Padhraig; Hämäläinen, Eija; Heggeli, Kristin; Schoeler, Natasha; Novy, Jan; Willis, Joseph; Plagnol, Vincent; Ellis, Rachael; Reavey, Eleanor; O'Regan, Mary; Pickrell, William O; Thomas, Rhys H; Chung, Seo-Kyung; Delanty, Norman; McMahon, Jacinta M; Malone, Stephen; Sadleir, Lynette G; Berkovic, Samuel F; Nashef, Lina; Zuberi, Sameer M; Rees, Mark I; Cavalleri, Gianpiero L; Sander, Josemir W; Hughes, Elaine; Helen Cross, J; Scheffer, Ingrid E; Palotie, Aarno; Sisodiya, Sanjay M

2015-09-01

Sudden unexpected death in epilepsy (SUDEP) represents the most severe degree of the spectrum of epilepsy severity and is the commonest cause of epilepsy-related premature mortality. The precise pathophysiology and the genetic architecture of SUDEP remain elusive. Aiming to elucidate the genetic basis of SUDEP, we analysed rare, protein-changing variants from whole-exome sequences of 18 people who died of SUDEP, 87 living people with epilepsy and 1479 non-epilepsy disease controls. Association analysis revealed a significantly increased genome-wide polygenic burden per individual in the SUDEP cohort when compared to epilepsy (P = 5.7 × 10(- 3)) and non-epilepsy disease controls (P = 1.2 × 10(- 3)). The polygenic burden was driven both by the number of variants per individual, and over-representation of variants likely to be deleterious in the SUDEP cohort. As determined by this study, more than a thousand genes contribute to the observed polygenic burden within the framework of this study. Subsequent gene-based association analysis revealed five possible candidate genes significantly associated with SUDEP or epilepsy, but no one single gene emerges as common to the SUDEP cases. Our findings provide further evidence for a genetic susceptibility to SUDEP, and suggest an extensive polygenic contribution to SUDEP causation. Thus, an overall increased burden of deleterious variants in a highly polygenic background might be important in rendering a given individual more susceptible to SUDEP. Our findings suggest that exome sequencing in people with epilepsy might eventually contribute to generating SUDEP risk estimates, promoting stratified medicine in epilepsy, with the eventual aim of reducing an individual patient's risk of SUDEP.

Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones.

PubMed

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Ziv, Elad; Kerlikowske, Karla; Cummings, Steven R

2017-11-01

Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms. We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC). Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65). Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

Genome-wide Polygenic Burden of Rare Deleterious Variants in Sudden Unexpected Death in Epilepsy

PubMed Central

Leu, Costin; Balestrini, Simona; Maher, Bridget; Hernández-Hernández, Laura; Gormley, Padhraig; Hämäläinen, Eija; Heggeli, Kristin; Schoeler, Natasha; Novy, Jan; Willis, Joseph; Plagnol, Vincent; Ellis, Rachael; Reavey, Eleanor; O'Regan, Mary; Pickrell, William O.; Thomas, Rhys H.; Chung, Seo-Kyung; Delanty, Norman; McMahon, Jacinta M.; Malone, Stephen; Sadleir, Lynette G.; Berkovic, Samuel F.; Nashef, Lina; Zuberi, Sameer M.; Rees, Mark I.; Cavalleri, Gianpiero L.; Sander, Josemir W.; Hughes, Elaine; Helen Cross, J.; Scheffer, Ingrid E.; Palotie, Aarno; Sisodiya, Sanjay M.

2015-01-01

Sudden unexpected death in epilepsy (SUDEP) represents the most severe degree of the spectrum of epilepsy severity and is the commonest cause of epilepsy-related premature mortality. The precise pathophysiology and the genetic architecture of SUDEP remain elusive. Aiming to elucidate the genetic basis of SUDEP, we analysed rare, protein-changing variants from whole-exome sequences of 18 people who died of SUDEP, 87 living people with epilepsy and 1479 non-epilepsy disease controls. Association analysis revealed a significantly increased genome-wide polygenic burden per individual in the SUDEP cohort when compared to epilepsy (P = 5.7 × 10− 3) and non-epilepsy disease controls (P = 1.2 × 10− 3). The polygenic burden was driven both by the number of variants per individual, and over-representation of variants likely to be deleterious in the SUDEP cohort. As determined by this study, more than a thousand genes contribute to the observed polygenic burden within the framework of this study. Subsequent gene-based association analysis revealed five possible candidate genes significantly associated with SUDEP or epilepsy, but no one single gene emerges as common to the SUDEP cases. Our findings provide further evidence for a genetic susceptibility to SUDEP, and suggest an extensive polygenic contribution to SUDEP causation. Thus, an overall increased burden of deleterious variants in a highly polygenic background might be important in rendering a given individual more susceptible to SUDEP. Our findings suggest that exome sequencing in people with epilepsy might eventually contribute to generating SUDEP risk estimates, promoting stratified medicine in epilepsy, with the eventual aim of reducing an individual patient's risk of SUDEP. PMID:26501104

Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis

PubMed Central

McIntosh, Andrew M.; Zeng, Yanni; Davies, Gail; Clarke, Toni-Kim; Hayward, Caroline; Haley, Chris S.; Porteous, David J.; Deary, Ian J.; Smith, Daniel J.; Hinds, David A.; Jones, Amy V.; Scollen, Serena; Meng, Weihua; Hocking, Lynne J.

2016-01-01

Background Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study. Methods and Findings Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10−2, 95% CI 4.70x10-2 to 6.65x10-2 , p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2 , p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2 , p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes. Conclusions Genetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD. PMID:27529168

Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis.

PubMed

McIntosh, Andrew M; Hall, Lynsey S; Zeng, Yanni; Adams, Mark J; Gibson, Jude; Wigmore, Eleanor; Hagenaars, Saskia P; Davies, Gail; Fernandez-Pujals, Ana Maria; Campbell, Archie I; Clarke, Toni-Kim; Hayward, Caroline; Haley, Chris S; Porteous, David J; Deary, Ian J; Smith, Daniel J; Nicholl, Barbara I; Hinds, David A; Jones, Amy V; Scollen, Serena; Meng, Weihua; Smith, Blair H; Hocking, Lynne J

2016-08-01

Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study. Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10-2, 95% CI 4.70x10-2 to 6.65x10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2, p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes. Genetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data.

PubMed

Gompert, Zachariah

2016-01-01

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild. © 2015 John Wiley & Sons Ltd.

Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population.

PubMed

Dai, Juncheng; Shen, Wei; Wen, Wanqing; Chang, Jiang; Wang, Tongmin; Chen, Haitao; Jin, Guangfu; Ma, Hongxia; Wu, Chen; Li, Lian; Song, Fengju; Zeng, YiXin; Jiang, Yue; Chen, Jiaping; Wang, Cheng; Zhu, Meng; Zhou, Wen; Du, Jiangbo; Xiang, Yongbing; Shu, Xiao-Ou; Hu, Zhibin; Zhou, Weiping; Chen, Kexin; Xu, Jianfeng; Jia, Weihua; Lin, Dongxin; Zheng, Wei; Shen, Hongbing

2017-01-15

The familial aggregation indicated the inheritance of cancer risk. Recent genome-wide association studies (GWASs) have identified a number of common single-nucleotide polymorphisms (SNPs). Following heritability analyses have shown that SNPs could explain a moderate amount of variance for different cancer phenotypes among Caucasians. However, little information was available in Chinese population. We performed a genome-wide complex trait analysis for common cancers at nine anatomical sites in Chinese population (14,629 cancer cases vs. 17,554 controls) and estimated the heritability of these cancers based on the common SNPs. We found that common SNPs explained certain amount of heritability with significance for all nine cancer sites: gastric cancer (20.26%), esophageal squamous cell carcinoma (19.86%), colorectal cancer (16.30%), lung cancer (LC) (15.17%), and epithelial ovarian cancer (13.31%), and a similar heritability around 10% for hepatitis B virus-related hepatocellular carcinoma, prostate cancer, breast cancer and nasopharyngeal carcinoma. We found that nearly or less than 25% change was shown when removing the regions expanding 250 kb or 500 kb upward and downward of the GWAS-reported SNPs. We also found strong linear correlations between variance partitioned by each chromosome and chromosomal length only for LC (R 2  = 0.641, p = 0.001) and esophageal squamous cell cancer (R 2  = 0.633, p = 0.002), which implied us the complex heterogeneity of cancers. These results indicate polygenic genetic architecture of the nine common cancers in Chinese population. Further efforts should be made to discover the hidden heritability of different cancer types among Chinese. © 2016 UICC.

CCL2 and CCR2 variants are associated with skeletal muscle strength and change in strength with resistance training.

PubMed

Harmon, Brennan T; Orkunoglu-Suer, E Funda; Adham, Kasra; Larkin, Justin S; Gordish-Dressman, Heather; Clarkson, Priscilla M; Thompson, Paul D; Angelopoulos, Theodore J; Gordon, Paul M; Moyna, Niall M; Pescatello, Linda S; Visich, Paul S; Zoeller, Robert F; Hubal, Monica J; Tosi, Laura L; Hoffman, Eric P; Devaney, Joseph M

2010-12-01

Baseline muscle size and muscle adaptation to exercise are traits with high variability across individuals. Recent research has implicated several chemokines and their receptors in the pathogenesis of many conditions that are influenced by inflammatory processes, including muscle damage and repair. One specific chemokine, chemokine (C-C motif) ligand 2 (CCL2), is expressed by macrophages and muscle satellite cells, increases expression dramatically following muscle damage, and increases expression further with repeated bouts of exercise, suggesting that CCL2 plays a key role in muscle adaptation. The present study hypothesizes that genetic variations in CCL2 and its receptor (CCR2) may help explain muscle trait variability. College-aged subjects [n = 874, Functional Single-Nucleotide Polymorphisms Associated With Muscle Size and Strength (FAMUSS) cohort] underwent a 12-wk supervised strength-training program for the upper arm muscles. Muscle size (via MR imaging) and elbow flexion strength (1 repetition maximum and isometric) measurements were taken before and after training. The study participants were then genotyped for 11 genetic variants in CCL2 and five variants in CCR2. Variants in the CCL2 and CCR2 genes show strong associations with several pretraining muscle strength traits, indicating that inflammatory genes in skeletal muscle contribute to the polygenic system that determines muscle phenotypes. These associations extend across both sexes, and several of these genetic variants have been shown to influence gene regulation.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

PubMed

Santos, Daniel M V; Katzmarzyk, Peter T; Diego, Vincent P; Souza, Michele C; Chaves, Raquel N; Blangero, John; Maia, José A R

2013-01-01

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Affiliation with substance-using peers: Examining gene-environment correlations among parent monitoring, polygenic risk, and children's impulsivity.

PubMed

Elam, Kit K; Chassin, Laurie; Lemery-Chalfant, Kathryn; Pandika, Danielle; Wang, Frances L; Bountress, Kaitlin; Dick, Danielle; Agrawal, Arpana

2017-07-01

Parental monitoring can buffer the effect of deviant peers on adolescents' substance use by reducing affiliation with substance-using peers. However, children's genetic predispositions may evoke poorer monitoring, contributing to negative child outcomes. We examined evocative genotype-environment correlations underlying children's genetic predisposition for behavioral undercontrol and parental monitoring in early adolescence via children's impulsivity in middle childhood, and the influence of parental monitoring on affiliation with substance-using peers a year and a half later (n = 359). Genetic predisposition for behavioral undercontrol was captured using a polygenic risk score, and a portion of passive rGE was controlled by including parents' polygenic risk scores. Children's polygenic risk predicted poorer parental monitoring via greater children's impulsivity, indicating evocative rGE, controlling for a portion of passive rGE. Poorer parental monitoring predicted greater children's affiliation with substance-using peers a year and a half later. Results are discussed with respect to gene-environment correlations within developmental cascades. © 2017 Wiley Periodicals, Inc.

Genetics and Crime: Integrating New Genomic Discoveries Into Psychological Research About Antisocial Behavior.

PubMed

Wertz, J; Caspi, A; Belsky, D W; Beckley, A L; Arseneault, L; Barnes, J C; Corcoran, D L; Hogan, S; Houts, R M; Morgan, N; Odgers, C L; Prinz, J A; Sugden, K; Williams, B S; Poulton, R; Moffitt, T E

2018-05-01

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) is associated with criminal offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and Environmental Risk (E-Risk) birth cohorts of individuals growing up 20 years and 20,000 kilometers apart, education polygenic scores predicted risk of a criminal record with modest effects. Polygenic risk manifested during primary schooling in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and it was associated with a life-course-persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature-nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest that improving school experiences might prevent genetic influences on crime from unfolding.

Genetics and crime: Integrating new genomic discoveries into psychological research about antisocial behavior

PubMed Central

Wertz, J.; Caspi, A.; Belsky, D. W.; Beckley, A. L.; Arseneault, L.; Barnes, J. C.; Corcoran, D. L.; Hogan, S.; Houts, R. M.; Morgan, N.; Odgers, C. L.; Prinz, J. A.; Sugden, K.; Williams, B. S.; Poulton, R.; Moffitt, T. E.

2018-01-01

Drawing on psychological and sociological theories of crime causation, we tested the hypothesis that genetic risk for low educational attainment (assessed via a genome-wide polygenic score) is associated with offending. We further tested hypotheses of how polygenic risk relates to the development of antisocial behavior from childhood through adulthood. Across the Dunedin and E-Risk birth cohorts of individuals growing up 20 years and 20,000 kilometres apart, education polygenic scores predicted risk of a criminal record, with modest effects. Polygenic risk manifested during primary schooling, in lower cognitive abilities, lower self-control, academic difficulties, and truancy, and predicted a life-course persistent pattern of antisocial behavior that onsets in childhood and persists into adulthood. Crime is central in the nature/nurture debate, and findings reported here demonstrate how molecular-genetic discoveries can be incorporated into established theories of antisocial behavior. They also suggest the hypothesis that improving school experiences might prevent genetic influences on crime from unfolding. PMID:29513605

Development and Validation of a High-Density SNP Genotyping Array for African Oil Palm.

PubMed

Kwong, Qi Bin; Teh, Chee Keng; Ong, Ai Ling; Heng, Huey Ying; Lee, Heng Leng; Mohamed, Mohaimi; Low, Joel Zi-Bin; Apparow, Sukganah; Chew, Fook Tim; Mayes, Sean; Kulaveerasingam, Harikrishna; Tammi, Martti; Appleton, David Ross

2016-08-01

High-density single nucleotide polymorphism (SNP) genotyping arrays are powerful tools that can measure the level of genetic polymorphism within a population. To develop a whole-genome SNP array for oil palms, SNP discovery was performed using deep resequencing of eight libraries derived from 132 Elaeis guineensis and Elaeis oleifera palms belonging to 59 origins, resulting in the discovery of >3 million putative SNPs. After SNP filtering, the Illumina OP200K custom array was built with 170 860 successful probes. Phenetic clustering analysis revealed that the array could distinguish between palms of different origins in a way consistent with pedigree records. Genome-wide linkage disequilibrium declined more slowly for the commercial populations (ranging from 120 kb at r(2) = 0.43 to 146 kb at r(2) = 0.50) when compared with the semi-wild populations (19.5 kb at r(2) = 0.22). Genetic fixation mapping comparing the semi-wild and commercial population identified 321 selective sweeps. A genome-wide association study (GWAS) detected a significant peak on chromosome 2 associated with the polygenic component of the shell thickness trait (based on the trait shell-to-fruit; S/F %) in tenera palms. Testing of a genomic selection model on the same trait resulted in good prediction accuracy (r = 0.65) with 42% of the S/F % variation explained. The first high-density SNP genotyping array for oil palm has been developed and shown to be robust for use in genetic studies and with potential for developing early trait prediction to shorten the oil palm breeding cycle. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Genome-Wide Association Study for Carcass Traits in an Experimental Nelore Cattle Population

PubMed Central

Medeiros de Oliveira Silva, Rafael; Bonvino Stafuzza, Nedenia; de Oliveira Fragomeni, Breno; Miguel Ferreira de Camargo, Gregório; Matos Ceacero, Thaís; Noely dos Santos Gonçalves Cyrillo, Joslaine; Baldi, Fernando; Augusti Boligon, Arione; Zerlotti Mercadante, Maria Eugênia; Lino Lourenco, Daniela; Misztal, Ignacy; Galvão de Albuquerque, Lucia

2017-01-01

The purpose of this study was to identify genomic regions associated with carcass traits in an experimental Nelore cattle population. The studied data set contained 2,306 ultrasound records for longissimus muscle area (LMA), 1,832 for backfat thickness (BF), and 1,830 for rump fat thickness (RF). A high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA) was used for genotyping. After genomic data quality control, 437,197 SNPs from 761 animals were available, of which 721 had phenotypes for LMA, 669 for BF, and 718 for RF. The SNP solutions were estimated using a single-step genomic BLUP approach (ssGWAS), which calculated the variance for windows of 50 consecutive SNPs and the regions that accounted for more than 0.5% of the additive genetic variance were used to search for candidate genes. The results indicated that 12, 18, and 15 different windows were associated to LMA, BF, and RF, respectively. Confirming the polygenic nature of the studied traits, 43, 65, and 53 genes were found in those associated windows, respectively for LMA, BF, and RF. Among the candidate genes, some of them, which already had their functions associated with the expression of energy metabolism, were found associated with fat deposition in this study. In addition, ALKBH3 and HSD17B12 genes, which are related in fibroblast death and metabolism of steroids, were found associated with LMA. The results presented here should help to better understand the genetic and physiologic mechanism regulating the muscle tissue deposition and subcutaneous fat cover expression of Zebu animals. The identification of candidate genes should contribute for Zebu breeding programs in order to consider carcass traits as selection criteria in their genetic evaluation. PMID:28118362

Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production.

PubMed

Rincent, R; Nicolas, S; Bouchet, S; Altmann, T; Brunel, D; Revilla, P; Malvar, R A; Moreno-Gonzalez, J; Campo, L; Melchinger, A E; Schipprack, W; Bauer, E; Schoen, C-C; Meyer, N; Ouzunova, M; Dubreuil, P; Giauffret, C; Madur, D; Combes, V; Dumas, F; Bauland, C; Jamin, P; Laborde, J; Flament, P; Moreau, L; Charcosset, A

2014-11-01

Genetic and phenotypic analysis of two complementary maize panels revealed an important variation for biomass yield. Flowering and biomass QTL were discovered by association mapping in both panels. The high whole plant biomass productivity of maize makes it a potential source of energy in animal feeding and biofuel production. The variability and the genetic determinism of traits related to biomass are poorly known. We analyzed two highly diverse panels of Dent and Flint lines representing complementary heterotic groups for Northern Europe. They were genotyped with the 50 k SNP-array and phenotyped as hybrids (crossed to a tester of the complementary pool) in a western European field trial network for traits related to flowering time, plant height, and biomass. The molecular information revealed to be a powerful tool for discovering different levels of structure and relatedness in both panels. This study revealed important variation and potential genetic progress for biomass production, even at constant precocity. Association mapping was run by combining genotypes and phenotypes in a mixed model with a random polygenic effect. This permitted the detection of significant associations, confirming height and flowering time quantitative trait loci (QTL) found in literature. Biomass yield QTL were detected in both panels but were unstable across the environments. Alternative kinship estimator only based on markers unlinked to the tested SNP increased the number of significant associations by around 40% with a satisfying control of the false positive rate. This study gave insights into the variability and the genetic architectures of biomass-related traits in Flint and Dent lines and suggests important potential of these two pools for breeding high biomass yielding hybrid varieties.

Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

PubMed

Bateman, A W; Anholt, B R

2017-05-01

R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Exome Sequencing Provides Evidence of Polygenic Adaptation to a Fat-Rich Animal Diet in Indigenous Siberian Populations.

PubMed

Hsieh, PingHsun; Hallmark, Brian; Watkins, Joseph; Karafet, Tatiana M; Osipova, Ludmila P; Gutenkunst, Ryan N; Hammer, Michael F

2017-11-01

Siberia is one of the coldest environments on Earth and has great seasonal temperature variation. Long-term settlement in northern Siberia undoubtedly required biological adaptation to severe cold stress, dramatic variation in photoperiod, and limited food resources. In addition, recent archeological studies show that humans first occupied Siberia at least 45,000 years ago; yet our understanding of the demographic history of modern indigenous Siberians remains incomplete. In this study, we use whole-exome sequencing data from the Nganasans and Yakuts to infer the evolutionary history of these two indigenous Siberian populations. Recognizing the complexity of the adaptive process, we designed a model-based test to systematically search for signatures of polygenic selection. Our approach accounts for stochasticity in the demographic process and the hitchhiking effect of classic selective sweeps, as well as potential biases resulting from recombination rate and mutation rate heterogeneity. Our demographic inference shows that the Nganasans and Yakuts diverged ∼12,000-13,000 years ago from East-Asian ancestors in a process involving continuous gene flow. Our polygenic selection scan identifies seven candidate gene sets with Siberian-specific signals. Three of these gene sets are related to diet, especially to fat metabolism, consistent with the hypothesis of adaptation to a fat-rich animal diet. Additional testing rejects the effect of hitchhiking and favors a model in which selection yields small allele frequency changes at multiple unlinked genes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

cerebral Markers of the Serotonergic System in Rat Models of Obesity and After Roux-en-Y Gastric Bypass

PubMed Central

Ratner, Cecilia; Ettrup, Anders; Bueter, Marco; Haahr, Mette E.; Compan, Valérie; le Roux, Carel W.; Levin, Barry; Hansen, Henrik H.; Knudsen, Gitte M.

2013-01-01

Food intake and body weight are regulated by a complex system of neural and hormonal signals, of which the anorexigenic neurotransmitter serotonin (5-hydroxytryptamine or 5-HT) is central. In this study, rat models of obesity and weight loss intervention were compared with regard to several 5-HT markers. Using receptor autoradiography, brain regional-densities of the serotonin transporter (SERT) and the 5-HT2A and 5-HT4 receptors were measured in (i) selectively bred polygenic diet-induced obese (pgDIO) rats, (ii) outbred DIO rats, and (iii) Roux-en-Y gastric bypass (RYGB)-operated rats. pgDIO rats had higher 5-HT4 and 5-HT2A receptor binding and lower SERT binding when compared to polygenic diet-resistant (pgDR) rats. The most pronounced difference between pgDIO and pgDR rats was observed in the nucleus accumbens shell (NAcS), a brain region regulating reward aspects of feeding. No differences were found in the 5-HT markers between DIO rats, chow-fed control rats, and DIO rats experiencing a weight loss. The 5-HT markers were also similar in RYGB and sham-operated rats except for a downregulation of 5-HT2A receptors in the NAcS. The higher receptor and lower SERT binding in pgDIO as compared to pgDR rats corresponds to what is reported in overweight humans and suggests that the dysfunctions of the 5-HT system associated with overeating or propensity to become overweight are polygenically determined. Our results support that the obesity-prone rat model has high translational value and suggests that susceptibility to develop obesity is associated with changed 5-HT tone in the brain that may also regulate hedonic aspects of feeding. PMID:22450706

A genetic approach to evaluation of short stature of undetermined cause.

PubMed

Murray, Philip G; Clayton, Peter E; Chernausek, Steven D

2018-01-31

Short stature is a common presentation to paediatric endocrinologists. After exclusion of major endocrine or systemic disease, most children with short stature are diagnosed based on a description of their growth pattern and the height of their parents (eg, familial short stature). Height is a polygenic trait and genome-wide association studies have identified many of the associated genetic loci. Here we review the application of genetic studies, including copy number variant analysis, targeted gene panels, and whole-exome sequencing in children with idiopathic short stature. We estimate 25-40% of children diagnosed with idiopathic short stature could receive a molecular diagnosis using these technologies. A molecular diagnosis for short stature is important for affected individuals and their families and might inform treatment decisions surrounding use of growth hormone or insulin-like growth factor 1 therapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neuroendocrine regulation of somatic growth in fishes.

PubMed

Dai, XiangYan; Zhang, Wei; Zhuo, ZiJian; He, JiangYan; Yin, Zhan

2015-02-01

Growth is a polygenic trait that is under the influence of multiple physiological pathways regulating energy metabolism and muscle growth. Among the possible growth-regulating pathways in vertebrates, components of the somatotropic axis are thought to have the greatest influence. There is growing body of literature focusing on the somatotropic axis and its role regulating growth in fish. This includes research into growth hormone, upstream hypothalamic hormones, insulin-like growth factors, and downstream signaling molecules. Many of these signals have both somatic effects stimulating the growth of tissues and metabolic effects that play a role in nutrient metabolism. Signals of other endocrine axes exhibit profound effects on the function of the somatotropic axis in vivo. In this review we highlight recent advances in our understanding of the teleost fish endocrine somatotropic axis, including emerging research using genetic modified models. These studies have revealed new aspects and challenges associated with regulation of the important steps of somatic growth.

Introgression of a Block of Genome Under Infinitesimal Selection.

PubMed

Sachdeva, Himani; Barton, Nicholas H

2018-06-12

Adaptive introgression is common in nature and can be driven by selection acting on multiple, linked genes. We explore the effects of polygenic selection on introgression under the infinitesimal model with linkage. This model assumes that the introgressing block has an effectively infinite number of loci, each with an infinitesimal effect on the trait under selection. The block is assumed to introgress under directional selection within a native population that is genetically homogeneous. We use individual-based simulations and a branching process approximation to compute various statistics of the introgressing block, and explore how these depend on parameters such as the map length and initial trait value associated with the introgressing block, the genetic variability along the block, and the strength of selection. Our results show that the introgression dynamics of a block under infinitesimal selection are qualitatively different from the dynamics of neutral introgression. We also find that in the long run, surviving descendant blocks are likely to have intermediate lengths, and clarify how their length is shaped by the interplay between linkage and infinitesimal selection. Our results suggest that it may be difficult to distinguish the long-term introgression of a block of genome with a single strongly selected locus from the introgression of a block with multiple, tightly linked and weakly selected loci. Copyright © 2018, Genetics.

Privacy-preserving genomic testing in the clinic: a model using HIV treatment.

PubMed

McLaren, Paul J; Raisaro, Jean Louis; Aouri, Manel; Rotger, Margalida; Ayday, Erman; Bartha, István; Delgado, Maria B; Vallet, Yannick; Günthard, Huldrych F; Cavassini, Matthias; Furrer, Hansjakob; Doco-Lecompte, Thanh; Marzolini, Catia; Schmid, Patrick; Di Benedetto, Caroline; Decosterd, Laurent A; Fellay, Jacques; Hubaux, Jean-Pierre; Telenti, Amalio

2016-08-01

The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med 18 8, 814-822.

Acylcarnitine Profiles in Plasma and Tissues of Hyperglycemic NZO Mice Correlate with Metabolite Changes of Human Diabetes

PubMed Central

Daniel, Hannelore

2018-01-01

The New Zealand obese (NZO) mouse is a polygenic model for obesity and diabetes with obese females and obese, diabetes-prone males, used to study traits of the metabolic syndrome like type 2 diabetes mellitus (T2DM), obesity, and dyslipidaemia. By using LC-MS/MS, we here examine the suitability of this model to mirror tissue-specific changes in acylcarnitine (AC) and amino acid (AA) species preceding T2DM which may reflect patterns investigated in human metabolism. We observed high concentrations of fatty acid-derived ACs in 11 female mice, high abundance of branched-chain amino acid- (BCAA-) derived ACs in 6 male mice, and slight increases in BCAA-derived ACs in the remaining 6 males. Principal component analysis (PCA) including all ACs and AAs confirmed our hypothesis especially in plasma samples by clustering females, males with high BCAA-derived ACs, and males with slight increases in BCAA-derived ACs. Concentrations of insulin, blood glucose, NEFAs, and triacylglycerols (TAGs) further supported the hypothesis of high BCAA-derived ACs being able to mirror the onset of diabetic traits in male individuals. In conclusion, alterations in AC and AA profiles overlap with observations from human studies indicating the suitability of NZO mice to study metabolic changes preceding human T2DM. PMID:29854816

Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations.

PubMed

Wang, Tianqi; Zhang, Xiaolong; Li, Ang; Zhu, Meifang; Liu, Shu; Qin, Wen; Li, Jin; Yu, Chunshui; Jiang, Tianzi; Liu, Bing

2017-01-01

Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders.

Evidence of a major gene from Bayesian segregation analyses of liability to osteochondral diseases in pigs.

PubMed

Kadarmideen, Haja N; Janss, Luc L G

2005-11-01

Bayesian segregation analyses were used to investigate the mode of inheritance of osteochondral lesions (osteochondrosis, OC) in pigs. Data consisted of 1163 animals with OC and their pedigrees included 2891 animals. Mixed-inheritance threshold models (MITM) and several variants of MITM, in conjunction with Markov chain Monte Carlo methods, were developed for the analysis of these (categorical) data. Results showed major genes with significant and substantially higher variances (range 1.384-37.81), compared to the polygenic variance (sigmau2). Consequently, heritabilities for a mixed inheritance (range 0.65-0.90) were much higher than the heritabilities from the polygenes. Disease allele frequencies range was 0.38-0.88. Additional analyses estimating the transmission probabilities of the major gene showed clear evidence for Mendelian segregation of a major gene affecting osteochondrosis. The variants, MITM with informative prior on sigmau2, showed significant improvement in marginal distributions and accuracy of parameters. MITM with a "reduced polygenic model" for parameterization of polygenic effects avoided convergence problems and poor mixing encountered in an "individual polygenic model." In all cases, "shrinkage estimators" for fixed effects avoided unidentifiability for these parameters. The mixed-inheritance linear model (MILM) was also applied to all OC lesions and compared with the MITM. This is the first study to report evidence of major genes for osteochondral lesions in pigs; these results may also form a basis for underpinning the genetic inheritance of this disease in other animals as well as in humans.

Obesity genetics in mouse and human: back and forth, and back again

PubMed Central

Yazdi, Fereshteh T.; Clee, Susanne M.

2015-01-01

Obesity is a major public health concern. This condition results from a constant and complex interplay between predisposing genes and environmental stimuli. Current attempts to manage obesity have been moderately effective and a better understanding of the etiology of obesity is required for the development of more successful and personalized prevention and treatment options. To that effect, mouse models have been an essential tool in expanding our understanding of obesity, due to the availability of their complete genome sequence, genetically identified and defined strains, various tools for genetic manipulation and the accessibility of target tissues for obesity that are not easily attainable from humans. Our knowledge of monogenic obesity in humans greatly benefited from the mouse obesity genetics field. Genes underlying highly penetrant forms of monogenic obesity are part of the leptin-melanocortin pathway in the hypothalamus. Recently, hypothesis-generating genome-wide association studies for polygenic obesity traits in humans have led to the identification of 119 common gene variants with modest effect, most of them having an unknown function. These discoveries have led to novel animal models and have illuminated new biologic pathways. Integrated mouse-human genetic approaches have firmly established new obesity candidate genes. Innovative strategies recently developed by scientists are described in this review to accelerate the identification of causal genes and deepen our understanding of obesity etiology. An exhaustive dissection of the molecular roots of obesity may ultimately help to tackle the growing obesity epidemic worldwide. PMID:25825681

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

Genetic variation and effects of candidate-gene polymorphisms on coagulation properties, curd firmness modeling and acidity in milk from Brown Swiss cows.

PubMed

Cecchinato, A; Chessa, S; Ribeca, C; Cipolat-Gotet, C; Bobbo, T; Casellas, J; Bittante, G

2015-07-01

The aims of this study were to estimate the genetic variation of traditional milk coagulation properties (MCPs), milk acidity, curd firmness (CF) modeled on time t (CF(t) ; comprising: RCT(eq), rennet coagulation time estimated from the equation; CF(P), the asymptotic potential curd firmness; k(CF), the curd firming instant rate constant; and k(SR), the syneresis instant rate constant) and maximum CF traits (MCF; comprising CF(max), the maximum CF value; and tmax, the time of attainment). Furthermore, we investigated 96 single nucleotide polymorphisms (SNPs) from 54 candidate genes, testing their associations with the above-listed traits. Milk and blood samples were collected from 1271 cows (each sampled once) from 85 herds. Genotyping was performed using a custom Illumina VeraCode GoldenGate approach. A Bayesian linear animal model (including the effects of herd, days in milk, parity and additive polygenic effects) was used to estimate the genetic parameters of the studied traits. The same model with the addition of the SNP genotype effect was used for our association analysis. The heritability estimates of CF t and the MCF traits (RCT(eq)=0.258; k(CF)=0.230; CF(max)=0.191; t(max)=0.278) were similar to those obtained using traditional MCPs (0.187 to 0.267), except for the lower estimates for CF(P) (0.064) and k(SR) (0.077). A total of 13 of the 51 tested SNPs had relevant additive effects on at least one trait. We observed associations between MCPs and SNPs in the genes encoding ATP-binding cassette sub-family G member 2 (ABCG2), chemokine ligand 2 (CCL2), growth hormone 1 (GH1), prolactin (PRL) and toll-like receptor 2 (TLR2). Whereas, CF(t) and the MCF traits were associated with polymorphisms in the α-s1-casein (CSN1S1), β-casein (CSN2), GH1, oxidized low-density lipoprotein receptor 1 (OLR1), phospholipase C β1 (PLCB1), PRL and signal transducer and activator of transcription 5A (STAT5A) genes.

Sexual selection and the evolution of genital shape and complexity in water striders.

PubMed

Rowe, Locke; Arnqvist, Göran

2012-01-01

Animal genitalia show two striking but incompletely understood evolutionary trends: a great evolutionary divergence in the shape of genitalic structures, and characteristic structural complexity. Both features are thought to result from sexual selection, but explicit comparative tests are hampered by the fact that it is difficult to quantify both morphological complexity and divergence in shape. We undertake a comparative study of multiple nongenitalic and male genital traits in a clade of 15 water strider species to quantify complexity and shape divergence. We show that genital structures are more complex and their shape more divergent among species than nongenital traits. Further, intromittent genital traits are more complex and have evolved more divergently than nonintromittent genital traits. More importantly, shape and complexity of nonintromittent genital traits show correlated evolution with indices of premating sexual selection and intromittent genital traits with postmating sexual selection, suggesting that the evolution of different components of genital morphology are shaped independently by distinct forms of sexual selection. Our quantitative results provide direct comparative support for the hypothesis that sexual selection is associated with morphological complexity in genitalic traits and highlight the importance of quantifying morphological shape and complexity, rather than size in studies of genital evolution. © 2011 The Author(s). Evolution © 2011 The Society for the Study of Evolution.

A genome-wide association study identifies candidate loci associated to syringomyelia secondary to Chiari-like malformation in Cavalier King Charles Spaniels.

PubMed

Ancot, Frédéric; Lemay, Philippe; Knowler, Susan P; Kennedy, Karen; Griffiths, Sandra; Cherubini, Giunio Bruto; Sykes, Jane; Mandigers, Paul J J; Rouleau, Guy A; Rusbridge, Clare; Kibar, Zoha

2018-03-22

Syringomyelia (SM) is a common condition affecting brachycephalic toy breed dogs and is characterized by the development of fluid-filled cavities within the spinal cord. It is often concurrent with a complex developmental malformation of the skull and craniocervical vertebrae called Chiari-like malformation (CM) characterized by a conformational change and overcrowding of the brain and cervical spinal cord particularly at the craniocervical junction. CM and SM have a polygenic mode of inheritance with variable penetrance. We identified six cranial T1-weighted sagittal MRI measurements that were associated to maximum transverse diameter of the syrinx cavity. Increased syrinx transverse diameter has been correlated previously with increased likelihood of behavioral signs of pain. We next conducted a whole genome association study of these traits in 65 Cavalier King Charles Spaniel (CKCS) dogs (33 controls, 32 with extreme phenotypes). Two loci on CFA22 and CFA26 were found to be significantly associated to two traits associated with a reduced volume and altered orientation of the caudal cranial fossa. Their reconstructed haplotypes defined two associated regions that harbor only two genes: PCDH17 on CFA22 and ZWINT on CFA26. PCDH17 codes for a cell adhesion molecule expressed specifically in the brain and spinal cord. ZWINT plays a role in chromosome segregation and its expression is increased with the onset of neuropathic pain. Targeted genomic sequencing of these regions identified respectively 37 and 339 SNPs with significantly associated P values. Genotyping of tagSNPs selected from these 2 candidate loci in an extended cohort of 461 CKCS (187 unaffected, 274 SM affected) identified 2 SNPs on CFA22 that were significantly associated to SM strengthening the candidacy of this locus in SM development. We identified 2 loci on CFA22 and CFA26 that contained only 2 genes, PCDH17 and ZWINT, significantly associated to two traits associated with syrinx transverse diameter. The locus on CFA22 was significantly associated to SM secondary to CM in the CKCS dog breed strengthening its candidacy for this disease. This study will provide an entry point for identification of the genetic factors predisposing to this condition and its underlying pathogenic mechanisms.

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice.

PubMed

Stewart, Taryn P; Kim, Hyoung Yon; Saxton, Arnold M; Kim, Jung Han

2010-12-19

Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. In order to determine the genetic factors that contribute to these T2D related characteristics in TH mice, we interbred TH mice with C57BL/6J (B6) mice. The parental, F1, and F2 mice were phenotyped at 8, 12, 16, 20, and 24 weeks of age for 4-hour fasting plasma triglyceride, cholesterol, insulin, and glucose levels and body, fat pad and carcass weights. The F2 mice were genotyped genome-wide and used for quantitative trait locus (QTL) mapping. We also applied a genetical genomic approach using a subset of the F2 mice to seek candidate genes underlying the QTLs. Major QTLs were detected on chromosomes (Chrs) 1, 11, 4, and 8 for hypertriglyceridemia, 1 and 3 for hypercholesterolemia, 4 for hyperglycemia, 11 and 1 for body weight, 1 for fat pad weight, and 11 and 14 for carcass weight. Most alleles, except for Chr 3 and 14 QTLs, increased phenotypic values when contributed by the TH strain. Fourteen pairs of interacting loci were detected, none of which overlapped the major QTLs. The QTL interval linked to hypercholesterolemia and hypertriglyceridemia on distal Chr 1 contains Apoa2 gene. Sequencing analysis revealed polymorphisms of Apoa2 in TH mice, suggesting Apoa2 as the candidate gene for the hyperlipidemia QTL. Gene expression analysis added novel information and aided in selection of candidates underlying the QTLs. We identified several genetic loci that affect the quantitative variations of plasma lipid and glucose levels and obesity traits in a TH × B6 intercross. Polymorphisms in Apoa2 gene are suggested to be responsible for the Chr 1 QTL linked to hypercholesterolemia and hypertriglyceridemia. Further, genetical genomic analysis led to potential candidate genes for the QTLs.

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice

PubMed Central

2010-01-01

Background Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. Results In order to determine the genetic factors that contribute to these T2D related characteristics in TH mice, we interbred TH mice with C57BL/6J (B6) mice. The parental, F1, and F2 mice were phenotyped at 8, 12, 16, 20, and 24 weeks of age for 4-hour fasting plasma triglyceride, cholesterol, insulin, and glucose levels and body, fat pad and carcass weights. The F2 mice were genotyped genome-wide and used for quantitative trait locus (QTL) mapping. We also applied a genetical genomic approach using a subset of the F2 mice to seek candidate genes underlying the QTLs. Major QTLs were detected on chromosomes (Chrs) 1, 11, 4, and 8 for hypertriglyceridemia, 1 and 3 for hypercholesterolemia, 4 for hyperglycemia, 11 and 1 for body weight, 1 for fat pad weight, and 11 and 14 for carcass weight. Most alleles, except for Chr 3 and 14 QTLs, increased phenotypic values when contributed by the TH strain. Fourteen pairs of interacting loci were detected, none of which overlapped the major QTLs. The QTL interval linked to hypercholesterolemia and hypertriglyceridemia on distal Chr 1 contains Apoa2 gene. Sequencing analysis revealed polymorphisms of Apoa2 in TH mice, suggesting Apoa2 as the candidate gene for the hyperlipidemia QTL. Gene expression analysis added novel information and aided in selection of candidates underlying the QTLs. Conclusions We identified several genetic loci that affect the quantitative variations of plasma lipid and glucose levels and obesity traits in a TH × B6 intercross. Polymorphisms in Apoa2 gene are suggested to be responsible for the Chr 1 QTL linked to hypercholesterolemia and hypertriglyceridemia. Further, genetical genomic analysis led to potential candidate genes for the QTLs. PMID:21167066

Influence of polygenic risk scores on lipid levels and dyslipidemia in a psychiatric population receiving weight gain-inducing psychotropic drugs.

PubMed

Delacrétaz, Aurélie; Lagares Santos, Patricia; Saigi Morgui, Nuria; Vandenberghe, Frederik; Glatard, Anaïs; Gholam-Rezaee, Mehdi; von Gunten, Armin; Conus, Philippe; Eap, Chin B

2017-12-01

Dyslipidemia represents a major health issue in psychiatry. We determined whether weighted polygenic risk scores (wPRSs) combining multiple single-nucleotide polymorphisms (SNPs) associated with lipid levels in the general population are associated with lipid levels [high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides] and/or dyslipidemia in patients receiving weight gain-inducing psychotropic drugs. We also determined whether genetics improve the predictive power of dyslipidemia. The influence of wPRS on lipid levels was firstly assessed in a discovery psychiatric sample (n=332) and was then tested for replication in an independent psychiatric sample (n=140). The contribution of genetic markers to predict dyslipidemia was evaluated in the combined psychiatric sample. wPRSs were significantly associated with the four lipid traits in the discovery (P≤0.02) and in the replication sample (P≤0.03). Patients whose wPRS was higher than the median wPRS had significantly higher LDL, TC, and triglyceride levels (0.20, 0.32 and 0.26 mmol/l, respectively; P≤0.004) and significantly lower HDL levels (0.13 mmol/l; P<0.0001) compared with others. Adding wPRS to clinical data significantly improved dyslipidemia prediction of HDL (P=0.03) and a trend for improvement was observed for the prediction of TC dyslipidemia (P=0.08). Population-based wPRSs have thus significant effects on lipid levels in the psychiatric population. As genetics improved the predictive power of dyslipidemia development, only 24 patients need to be genotyped to prevent the development of one case of HDL hypocholesterolemia. If confirmed by further prospective investigations, the present results could be used for individualizing psychotropic treatment.

Genetic Overlap Between Schizophrenia and Developmental Psychopathology: Longitudinal and Multivariate Polygenic Risk Prediction of Common Psychiatric Traits During Development.

PubMed

Nivard, Michel G; Gage, Suzanne H; Hottenga, Jouke J; van Beijsterveldt, Catharina E M; Abdellaoui, Abdel; Bartels, Meike; Baselmans, Bart M L; Ligthart, Lannie; Pourcain, Beate St; Boomsma, Dorret I; Munafò, Marcus R; Middeldorp, Christel M

2017-10-21

Several nonpsychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the etiology of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by correlated genetic risk factors. Polygenic risk scores (PRS), reflecting an individual's genetic risk for schizophrenia, were constructed for 2588 children from the Netherlands Twin Register (NTR) and 6127 from the Avon Longitudinal Study of Parents And Children (ALSPAC). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13, and 15 years in the 2 cohorts. Results were then meta-analyzed, and a meta-regression analysis was performed to test differences in effects sizes over, age and disorders. Schizophrenia PRS were associated with childhood and adolescent psychopathology. Meta-regression analysis showed differences in the associations over disorders, with the strongest association with childhood and adolescent depression and a weaker association for ODD/CD at age 7. The associations increased with age and this increase was steepest for ADHD and ODD/CD. Genetic correlations varied between 0.10 and 0.25. By optimally using longitudinal data across diagnoses in a multivariate meta-analysis this study sheds light on the development of childhood disorders into severe adult psychiatric disorders. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com

Inheritance and fitness costs of Spodoptera frugiperda (Lepidoptera: Noctuidae) resistance to spinosad in Brazil.

PubMed

Okuma, Daniela M; Bernardi, Daniel; Horikoshi, Renato J; Bernardi, Oderlei; Silva, Aline P; Omoto, Celso

2018-06-01

Spodoptera frugiperda is a pest of economically important crops in South America. In Brazil, this species is considered the most destructive pest of maize. Use of spinosyn insecticides in insect resistance management (IRM) has been one strategy to control this pest. In this study, we selected a strain of S. frugiperda resistant to spinosad and evaluated the inheritance and fitness costs of the resistance. Estimated LC 50 (concentration required to kill 50% of larvae) values were 0.011 and 9.80 µg cm -2 for the spinosad-susceptible (Sus) and -resistant (Spin-res) strains, respectively. This represents an 890-fold resistance ratio. LC 50 values for reciprocal crosses were 0.18 and 0.14 µg cm -2 , indicating that resistance to spinosad is an autosomal incompletely recessive trait. Backcrosses of the F 1 progeny from reciprocal crosses with the parental Spin-res strain showed a polygenic effect. The estimated minimum number of independent segregations was ∼ 2.45, indicating that resistance to spinosad is associated with multiple genes. In greenhouse assays, third-instar larvae from the Spin-res strain showed >92% survival on spinosad-treated maize. By contrast Sus and reciprocal crosses exhibited 0% and <5% survival, respectively, indicating that resistance is recessive. Life history studies to investigate the fitness cost of resistance revealed a 41% reduction in the rate of survival to adulthood and a 49% lower reproductive rate in the Spin-res strain compared with the Sus strain. The autosomal, incompletely recessive and polygenic resistance to spinosad in S. frugiperda and the fitness costs associated with this resistance can be exploited in IRM strategies to preserve the lifetime of spinosad for control of S. frugiperda in Brazil. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Genome-wide dissection of hybrid sterility in Drosophila confirms a polygenic threshold architecture.

PubMed

Morán, Tomás; Fontdevila, Antonio

2014-01-01

To date, different studies about the genetic basis of hybrid male sterility (HMS), a postzygotic reproductive barrier thoroughly investigated using Drosophila species, have demonstrated that no single major gene can produce hybrid sterility without the cooperation of several genetic factors. Early work using hybrids between Drosophila koepferae (Dk) and Drosophila buzzatii (Db) was consistent with the idea that HMS requires the cooperation of several genetic factors, supporting a polygenic threshold (PT) model. Here we present a genome-wide mapping strategy to test the PT model, analyzing serially backcrossed fertile and sterile males in which the Dk genome was introgressed into the Db background. We identified 32 Dk-specific markers significantly associated with hybrid sterility. Our results demonstrate 1) a strong correlation between the number of segregated sterility markers and males' degree of sterility, 2) the exchangeability among markers, 3) their tendency to cluster into low-recombining chromosomal regions, and 4) the requirement for a minimum number (threshold) of markers to elicit sterility. Although our findings do not contradict a role for occasional major hybrid-sterility genes, they conform more to the view that HMS primarily evolves by the cumulative action of many interacting genes of minor effect in a complex PT architecture.

Heritability of body size in the polar bears of Western Hudson Bay.

PubMed

Malenfant, René M; Davis, Corey S; Richardson, Evan S; Lunn, Nicholas J; Coltman, David W

2018-04-18

Among polar bears (Ursus maritimus), fitness is dependent on body size through males' abilities to win mates, females' abilities to provide for their young and all bears' abilities to survive increasingly longer fasting periods caused by climate change. In the Western Hudson Bay subpopulation (near Churchill, Manitoba, Canada), polar bears have declined in body size and condition, but nothing is known about the genetic underpinnings of body size variation, which may be subject to natural selection. Here, we combine a 4449-individual pedigree and an array of 5,433 single nucleotide polymorphisms (SNPs) to provide the first quantitative genetic study of polar bears. We used animal models to estimate heritability (h 2 ) among polar bears handled between 1966 and 2011, obtaining h 2 estimates of 0.34-0.48 for strictly skeletal traits and 0.18 for axillary girth (which is also dependent on fatness). We genotyped 859 individuals with the SNP array to test for marker-trait association and combined p-values over genetic pathways using gene-set analysis. Variation in all traits appeared to be polygenic, but we detected one region of moderately large effect size in body length near a putative noncoding RNA in an unannotated region of the genome. Gene-set analysis suggested that variation in body length was associated with genes in the regulatory cascade of cyclin expression, which has previously been associated with body size in mice. A greater understanding of the genetic architecture of body size variation will be valuable in understanding the potential for adaptation in polar bear populations challenged by climate change. © 2018 John Wiley & Sons Ltd.

Standing genetic variation as a major contributor to adaptation in the Virginia chicken lines selection experiment.

PubMed

Sheng, Zheya; Pettersson, Mats E; Honaker, Christa F; Siegel, Paul B; Carlborg, Örjan

2015-10-01

Artificial selection provides a powerful approach to study the genetics of adaptation. Using selective-sweep mapping, it is possible to identify genomic regions where allele-frequencies have diverged during selection. To avoid false positive signatures of selection, it is necessary to show that a sweep affects a selected trait before it can be considered adaptive. Here, we confirm candidate, genome-wide distributed selective sweeps originating from the standing genetic variation in a long-term selection experiment on high and low body weight of chickens. Using an intercross between the two divergent chicken lines, 16 adaptive selective sweeps were confirmed based on their association with the body weight at 56 days of age. Although individual additive effects were small, the fixation for alternative alleles across the loci contributed at least 40 % of the phenotypic difference for the selected trait between these lines. The sweeps contributed about half of the additive genetic variance present within and between the lines after 40 generations of selection, corresponding to a considerable portion of the additive genetic variance of the base population. Long-term, single-trait, bi-directional selection in the Virginia chicken lines has resulted in a gradual response to selection for extreme phenotypes without a drastic reduction in the genetic variation. We find that fixation of several standing genetic variants across a highly polygenic genetic architecture made a considerable contribution to long-term selection response. This provides new fundamental insights into the dynamics of standing genetic variation during long-term selection and adaptation.

A Major Locus for Chloride Accumulation on Chromosome 5A in Bread Wheat

PubMed Central

Genc, Yusuf; Taylor, Julian; Rongala, Jay; Oldach, Klaus

2014-01-01

Chloride (Cl−) is an essential micronutrient for plant growth, but can be toxic at high concentrations resulting in reduced growth and yield. Although saline soils are generally dominated by both sodium (Na+) and Cl− ions, compared to Na+ toxicity, very little is known about physiological and genetic control mechanisms of tolerance to Cl− toxicity. In hydroponics and field studies, a bread wheat mapping population was tested to examine the relationships between physiological traits [Na+, potassium (K+) and Cl− concentration] involved in salinity tolerance (ST) and seedling growth or grain yield, and to elucidate the genetic control mechanism of plant Cl− accumulation using a quantitative trait loci (QTL) analysis approach. Plant Na+ or Cl− concentration were moderately correlated (genetically) with seedling biomass in hydroponics, but showed no correlations with grain yield in the field, indicating little value in selecting for ion concentration to improve ST. In accordance with phenotypic responses, QTL controlling Cl− accumulation differed entirely between hydroponics and field locations, and few were detected in two or more environments, demonstrating substantial QTL-by-environment interactions. The presence of several QTL for Cl− concentration indicated that uptake and accumulation was a polygenic trait. A major Cl− concentration QTL (5A; barc56/gwm186) was identified in three field environments, and accounted for 27–32% of the total genetic variance. Alignment between the 5A QTL interval and its corresponding physical genome regions in wheat and other grasses has enabled the search for candidate genes involved in Cl− transport, which is discussed. PMID:24893005

Genetic Basis of Body Color and Spotting Pattern in Redheaded Pine Sawfly Larvae (Neodiprion lecontei).

PubMed

Linnen, Catherine R; O'Quin, Claire T; Shackleford, Taylor; Sears, Connor R; Lindstedt, Carita

2018-05-01

Pigmentation has emerged as a premier model for understanding the genetic basis of phenotypic evolution, and a growing catalog of color loci is starting to reveal biases in the mutations, genes, and genetic architectures underlying color variation in the wild. However, existing studies have sampled a limited subset of taxa, color traits, and developmental stages. To expand the existing sample of color loci, we performed QTL mapping analyses on two types of larval pigmentation traits that vary among populations of the redheaded pine sawfly ( Neodiprion lecontei ): carotenoid-based yellow body color and melanin-based spotting pattern. For both traits, our QTL models explained a substantial proportion of phenotypic variation and suggested a genetic architecture that is neither monogenic nor highly polygenic. Additionally, we used our linkage map to anchor the current N. lecontei genome assembly. With these data, we identified promising candidate genes underlying (1) a loss of yellow pigmentation in populations in the mid-Atlantic/northeastern United States [C locus-associated membrane protein homologous to a mammalian HDL receptor-2 gene ( Cameo2 ) and lipid transfer particle apolipoproteins II and I gene ( apoLTP-II/I )], and (2) a pronounced reduction in black spotting in Great Lakes populations [members of the yellow gene family, tyrosine hydroxylase gene ( pale ), and dopamine N -acetyltransferase gene ( Dat )]. Several of these genes also contribute to color variation in other wild and domesticated taxa. Overall, our findings are consistent with the hypothesis that predictable genes of large effect contribute to color evolution in nature. Copyright © 2018 by the Genetics Society of America.

Current Status of Early Blight Resistance in Tomato: An Update

PubMed Central

Adhikari, Pragya; Oh, Yeonyee; Panthee, Dilip R.

2017-01-01

Early blight (EB) is one of the dreadful diseases of tomato caused by several species of Alternaria including Alternaria linariae (which includes A. solani and A. tomatophila), as well as A. alternata. In some instances, annual economic yield losses due to EB have been estimated at 79%. Alternaria are known only to reproduce asexually, but a highly-virulent isolate has the potential to overcome existing resistance genes. Currently, cultural practices and fungicide applications are employed for the management of EB due to the lack of strong resistant cultivars. Resistance sources have been identified in wild species of tomato; some breeding lines and cultivars with moderate resistance have been developed through conventional breeding methods. Polygenic inheritance of EB resistance, insufficient resistance in cultivated species and the association of EB resistance with undesirable horticultural traits have thwarted the effective breeding of EB resistance in tomato. Several quantitative trait loci (QTL) conferring EB resistance have been detected in the populations derived from different wild species including Solanum habrochaites, Solanum arcanum and S. pimpinellifolium, but none of them could be used in EB resistance breeding due to low individual QTL effects. Pyramiding of those QTLs would provide strong resistance. More research is needed to identify additional sources of useful resistance, to incorporate resistant QTLs into breeding lines through marker-assisted selection (MAS) and to develop resistant cultivars with desirable horticultural traits including high yielding potential and early maturity. This paper will review the current understanding of causal agents of EB of tomato, resistance genetics and breeding, problems associated with breeding and future prospects. PMID:28934121

An analysis of polygenes affecting wing shape on chromosome 2 in Drosophila melanogaster.

PubMed Central

Weber, K; Eisman, R; Higgins, S; Morey, L; Patty, A; Tausek, M; Zeng, Z B

2001-01-01

Genetic effects on an index of wing shape on chromosome 2 of Drosophila melanogaster were mapped using isogenic recombinants with transposable element markers. At least 10 genes with small additive effects are dispersed evenly along the chromosome. Many interactions exist, with only small net effects in homozygous recombinants and little effect on phenotypic variance. Heterozygous chromosome segments show almost no dominance. Pleiotropic effects on leg shape are only minor. At first view, wing shape genes form a rather homogeneous class, but certain complexities remain unresolved. PMID:11729152

Etiopathogenesis of Canine Hip Dysplasia, Prevalence, and Genetics.

PubMed

King, Michael D

2017-07-01

First identified in 1935, canine hip dysplasia is thought to be the most common orthopedic condition diagnosed in the dog. It is most prevalent in large and giant breed dogs, with a complex polygenic mode of inheritance, and relatively low heritability. External factors including caloric intake when growing have a significant effect on phenotypic expression. Initial joint laxity progresses to osteoarthritis due to subluxation and abnormal wearing. Selective breeding programs to attempt to decrease prevalence have shown modest results so far. Copyright © 2017 Elsevier Inc. All rights reserved.

Self-Fertilization and Genetic Population Structure in a Colonizing Land Snail

PubMed Central

Selander, Robert K.; Kaufman, Donald W.

1973-01-01

The pulmonate land snail Rumina decollata in its native Mediterranean range is a complex of monogenic or weakly polygenic strains generated by a breeding system of facultative self-fertilization. One strain colonized North America and now occupies much of the southern United States and northern Mexico. No genetic variation within or among populations in the United States was detected in an electrophoretic analysis of proteins encoded by 25 loci. These findings emphasize the potential for adaptive convergence in the genetic systems of hermaphroditic animals and plants. PMID:16592078

Genome-Wide Polygenic Scores Predict Reading Performance throughout the School Years

ERIC Educational Resources Information Center

Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O'Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

2017-01-01

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ("EduYears") to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample…

The polygenic risk for bipolar disorder influences brain regional function relating to visual and default state processing of emotional information.

PubMed

Dima, Danai; de Jong, Simone; Breen, Gerome; Frangou, Sophia

2016-01-01

Genome-wise association studies have identified a number of common single-nucleotide polymorphisms (SNPs), each of small effect, associated with risk to bipolar disorder (BD). Several risk-conferring SNPs have been individually shown to influence regional brain activation thus linking genetic risk for BD to altered brain function. The current study examined whether the polygenic risk score method, which models the cumulative load of all known risk-conferring SNPs, may be useful in the identification of brain regions whose function may be related to the polygenic architecture of BD. We calculated the individual polygenic risk score for BD (PGR-BD) in forty-one patients with the disorder, twenty-five unaffected first-degree relatives and forty-six unrelated healthy controls using the most recent Psychiatric Genomics Consortium data. Functional magnetic resonance imaging was used to define task-related brain activation patterns in response to facial affect and working memory processing. We found significant effects of the PGR-BD score on task-related activation irrespective of diagnostic group. There was a negative association between the PGR-BD score and activation in the visual association cortex during facial affect processing. In contrast, the PGR-BD score was associated with failure to deactivate the ventromedial prefrontal region of the default mode network during working memory processing. These results are consistent with the threshold-liability model of BD, and demonstrate the usefulness of the PGR-BD score in identifying brain functional alternations associated with vulnerability to BD. Additionally, our findings suggest that the polygenic architecture of BD is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions.

Genetic Predisposition to Obesity and Medicare Expenditures.

PubMed

Wehby, George L; Domingue, Benjamin W; Ullrich, Fred; Wolinsky, Fredric D

2017-12-12

The relationship between obesity and health expenditures is not well understood. We examined the relationship between genetic predisposition to obesity measured by a polygenic risk score for body mass index (BMI) and Medicare expenditures. Biennial interview data from the Health and Retirement Survey for a nationally representative sample of older adults enrolled in fee-for-service Medicare were obtained from 1991 through 2010 and linked to Medicare claims for the same period and to Genome-Wide Association Study (GWAS) data. The study included 6,628 Medicare beneficiaries who provided 68,627 complete person-year observations during the study period. Outcomes were total and service-specific Medicare expenditures and indicators for expenditures exceeding the 75th and 90th percentiles. The BMI polygenic risk score was derived from GWAS data. Regression models were used to examine how the BMI polygenic risk score was related to health expenditures adjusting for demographic factors and GWAS-derived ancestry. Greater genetic predisposition to obesity was associated with higher Medicare expenditures. Specifically, a 1 SD increase in the BMI polygenic risk score was associated with a $805 (p < .001) increase in annual Medicare expenditures per person in 2010 dollars (~15% increase), a $370 (p < .001) increase in inpatient expenses, and a $246 (p < .001) increase in outpatient services. A 1 SD increase in the polygenic risk score was also related to increased likelihood of expenditures exceeding the 75th percentile by 18% (95% CI: 10%-28%) and the 90th percentile by 27% (95% CI: 15%-40%). Greater genetic predisposition to obesity is associated with higher Medicare expenditures. © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Contributions of polygenic risk for obesity to PTSD-related metabolic syndrome and cortical thickness.

PubMed

Wolf, Erika J; Miller, Danielle R; Logue, Mark W; Sumner, Jennifer; Stoop, Tawni B; Leritz, Elizabeth C; Hayes, Jasmeet P; Stone, Annjanette; Schichman, Steven A; McGlinchey, Regina E; Milberg, William P; Miller, Mark W

2017-10-01

Research suggests that posttraumatic stress disorder (PTSD) is associated with metabolic syndrome (MetS) and that PTSD-associated MetS is related to decreased cortical thickness. However, the role of genetic factors in these associations is unclear. This study evaluated contributions of polygenic obesity risk and PTSD to MetS and of MetS and polygenic obesity risk to cortical thickness. 196 white, non-Hispanic veterans of the wars in Iraq and Afghanistan underwent clinical diagnostic interviews, physiological assessments, and genome-wide genotyping; 168 also completed magnetic resonance imaging scans. Polygenic risk scores (PRSs) for obesity were calculated from results of a prior genome-wide association study (Speliotes et al., 2010) and PTSD and MetS severity factor scores were obtained. Obesity PRS (β=0.15, p=0.009) and PTSD (β=0.17, p=0.005) predicted MetS and interacted such that the association between PTSD and MetS was stronger in individuals with greater polygenic obesity risk (β=0.13, p=0.02). Whole-brain vertex-wise analyses suggested that obesity PRS interacted with MetS to predict decreased cortical thickness in left rostral middle frontal gyrus (β=-0.40, p<0.001). Results suggest that PTSD, genetic variability, and MetS are related in a transactional fashion wherein obesity genetic risk increases stress-related metabolic pathology, and compounds the ill health effects of MetS on the brain. Genetic proclivity towards MetS should be considered in PTSD patients when prescribing psychotropic medications with adverse metabolic profiles. Results are consistent with a growing literature suggestive of PTSD-related accelerated aging. Published by Elsevier Inc.

Effects of aqueous extracts of dried calyx of sour tea (Hibiscus sabdariffa L.) on polygenic dyslipidemia: A randomized clinical trial.

PubMed

Hajifaraji, Majid; Matlabi, Mohammad; Ahmadzadeh-Sani, Farihe; Mehrabi, Yadollah; Rezaee, Mohammad Salem; Hajimehdipour, Homa; Hasanzadeh, Abbas; Roghani, Katayoun

2018-01-01

Dyslipidemia has been considered as a major risk factor for coronary heart disease. Alternative medicine has a significant role in treatment of dyslipidemia. There are controversial findings regarding the effects of sour tea on dyslipidemia. The aim of this study was to evaluate the impact of aqueous extract of dried calyx of sour tea on polygenic dyslipidemia. This clinical trial was done on 43 adults (30-60 years old) with polygenic dyslipidemia that were randomly assigned to the intervention and control groups. The control group was trained in lifestyle modifications at baseline. The intervention group was trained for lifestyle modifications at baseline and received two cups of sour tea daily, and both groups were followed up for 12 weeks. Lipid profile was evaluated at baseline, and six and 12 weeks following the intervention. In addition, dietary and physical activity assessed at baseline for twelve weeks. Mean concentration of total cholesterol, HDL-C and LDL-C significantly decreased by up to 9.46%, 8.33%, and 9.80%, respectively, after 12 weeks in the intervention group in comparison to their baseline values. However, LDL-C/HDL-C ratio significantly increased by up to 3.15%, following 12 weeks in the control group in comparison to their baseline values. This study showed no difference in lipid profiles between the two groups, except for HDL-C concentrations. sour tea may have significant positive effects on lipid profile of polygenic dyslipidemia subjects and these effect might be attributed to its anthocyanins and inflation factor content. Therefore, sour tea intake with recommended dietary patterns and physical activity can be useful in regulation of lipid profile in patients with polygenic dyslipidemia.

The associations between a polygenic score, reproductive and menstrual risk factors and breast cancer risk.

PubMed

Warren Andersen, Shaneda; Trentham-Dietz, Amy; Gangnon, Ronald E; Hampton, John M; Figueroa, Jonine D; Skinner, Halcyon G; Engelman, Corinne D; Klein, Barbara E; Titus, Linda J; Newcomb, Polly A

2013-07-01

We evaluated whether 13 single nucleotide polymorphisms (SNPs) identified in genome-wide association studies interact with one another and with reproductive and menstrual risk factors in association with breast cancer risk. DNA samples and information on parity, breastfeeding, age at menarche, age at first birth, and age at menopause were collected through structured interviews from 1,484 breast cancer cases and 1,307 controls who participated in a population-based case-control study conducted in three US states. A polygenic score was created as the sum of risk allele copies multiplied by the corresponding log odds estimate. Logistic regression was used to test the associations between SNPs, the score, reproductive and menstrual factors, and breast cancer risk. Nonlinearity of the score was assessed by the inclusion of a quadratic term for polygenic score. Interactions between the aforementioned variables were tested by including a cross-product term in models. We confirmed associations between rs13387042 (2q35), rs4973768 (SLC4A7), rs10941679 (5p12), rs2981582 (FGFR2), rs3817198 (LSP1), rs3803662 (TOX3), and rs6504950 (STXBP4) with breast cancer. Women in the score's highest quintile had 2.2-fold increased risk when compared to women in the lowest quintile (95 % confidence interval: 1.67-2.88). The quadratic polygenic score term was not significant in the model (p = 0.85), suggesting that the established breast cancer loci are not associated with increased risk more than the sum of risk alleles. Modifications of menstrual and reproductive risk factors associations with breast cancer risk by polygenic score were not observed. Our results suggest that the interactions between breast cancer susceptibility loci and reproductive factors are not strong contributors to breast cancer risk.

Investigating the genetic variation underlying episodicity in major depressive disorder: suggestive evidence for a bipolar contribution.

PubMed

Ferentinos, Panagiotis; Rivera, Margarita; Ising, Marcus; Spain, Sarah L; Cohen-Woods, Sarah; Butler, Amy W; Craddock, Nicholas; Owen, Michael J; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Mors, Ole; Rietschel, Marcella; Lucae, Susanne; Binder, Elisabeth B; Preisig, Martin; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Craig, Ian W; Farmer, Anne E; Müller-Myhsok, Bertram; McGuffin, Peter; Lewis, Cathryn M

2014-02-01

Highly recurrent major depressive disorder (MDD) has reportedly increased risk of shifting to bipolar disorder; high recurrence frequency has, therefore, featured as evidence of 'soft bipolarity'. We aimed to investigate the genetic underpinnings of total depressive episode count in recurrent MDD. Our primary sample included 1966 MDD cases with negative family history of bipolar disorder from the RADIANT studies. Total episode count was adjusted for gender, age, MDD duration, study and center before being tested for association with genotype in two separate genome-wide analyses (GWAS), in the full set and in a subset of 1364 cases with positive family history of MDD (FH+). We also calculated polygenic scores from the Psychiatric Genomics Consortium MDD and bipolar disorder studies. Episodicity (especially intermediate episode counts) was an independent index of MDD familial aggregation, replicating previous reports. The GWAS produced no genome-wide significant findings. The strongest signals were detected in the full set at MAGI1 (p=5.1×10(-7)), previously associated with bipolar disorder, and in the FH+ subset at STIM1 (p=3.9×10(-6) after imputation), a calcium channel signaling gene. However, these findings failed to replicate in an independent Munich cohort. In the full set polygenic profile analyses, MDD polygenes predicted episodicity better than bipolar polygenes; however, in the FH+ subset, both polygenic scores performed similarly. Episode count was self-reported and, therefore, subject to recall bias. Our findings lend preliminary support to the hypothesis that highly recurrent MDD with FH+ is part of a 'soft bipolar spectrum' but await replication in larger cohorts. © 2013 Published by Elsevier B.V.

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

PubMed

Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H; Bergen, Sarah E; Amdur, Richard L; Duan, Jubao; Sanders, Alan R; Shi, Jianxin; Mowry, Bryan J; Olincy, Ann; Amin, Farooq; Cloninger, C Robert; Silverman, Jeremy M; Buccola, Nancy G; Byerley, William F; Black, Donald W; Freedman, Robert; Dudbridge, Frank; Holmans, Peter A; Ripke, Stephan; Gejman, Pablo V; Kendler, Kenneth S; Levinson, Douglas F

2012-12-01

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia. Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor. No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples. The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

Genotyping by Sequencing for SNP-Based Linkage Analysis and Identification of QTLs Linked to Fruit Quality Traits in Japanese Plum (Prunus salicina Lindl.).

PubMed

Salazar, Juan A; Pacheco, Igor; Shinya, Paulina; Zapata, Patricio; Silva, Claudia; Aradhya, Mallikarjuna; Velasco, Dianne; Ruiz, David; Martínez-Gómez, Pedro; Infante, Rodrigo

2017-01-01

Marker-assisted selection (MAS) in stone fruit ( Prunus species) breeding is currently difficult to achieve due to the polygenic nature of the most relevant agronomic traits linked to fruit quality. Genotyping by sequencing (GBS), however, provides a large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from a reference genome. In this study, GBS was used to genotype 272 seedlings of three F1 Japanese plum ( Prunus salicina Lindl) progenies derived from crossing "98-99" (as a common female parent) with "Angeleno," "September King," and "September Queen" as male parents. Raw sequences were aligned to the Peach genome v1, and 42,909 filtered SNPs were obtained after sequence alignment. In addition, 153 seedlings from the "98-99" × "Angeleno" cross were used to develop a genetic map for each parent. A total of 981 SNPs were mapped (479 for "98-99" and 502 for "Angeleno"), covering a genetic distance of 688.8 and 647.03 cM, respectively. Fifty five seedlings from this progeny were phenotyped for different fruit quality traits including ripening time, fruit weight, fruit shape, chlorophyll index, skin color, flesh color, over color, firmness, and soluble solids content in the years 2015 and 2016. Linkage-based QTL analysis allowed the identification of genomic regions significantly associated with ripening time (LG4 of both parents and both phenotyping years), fruit skin color (LG3 and LG4 of both parents and both years), chlorophyll degradation index (LG3 of both parents in 2015) and fruit weight (LG7 of both parents in 2016). These results represent a promising situation for GBS in the identification of SNP variants associated to fruit quality traits, potentially applicable in breeding programs through MAS, in a highly heterozygous crop species such as Japanese plum.

The genetic basis of pectoralis major myopathies in modern broiler chicken lines

PubMed Central

Bailey, Richard A.; Watson, Kellie A.; Bilgili, S. F.; Avendano, Santiago

2015-01-01

This is the first report providing estimates of the genetic basis of breast muscle myopathies (BMM) and their relationship with growth and yield in broiler chickens. In addition, this paper addresses the hypothesis that genetic selection for increase breast yield has contributed to the onset of BMM. Data were analyzed from ongoing recording of BMM within the Aviagen breeding program. This study focused on three BMM: deep pectoral myopathy (DPM; binary trait), white striping (WS; 4 categories) and wooden breast (WB; 3 categories). Data from two purebred commercial broiler lines (A and B) were utilized providing greater than 40,000 meat quality records per line. The difference in selection history between these two lines has resulted in contrasting breast yield (BY): 29% for Line A and 21% for Line B. Data were analyzed to estimate genetic parameters using a multivariate animal model including six traits: body weight (BW), processing body weight (PW), BY, DPM, WB, and WS, in addition to the appropriate fixed effects and permanent environmental effect of the dam. Results indicate similar patterns of heritability and genetic correlations for the two lines. Heritabilities (h2) of BW, PW and BY ranged from 0.271–0.418; for DPM and WB h2 <0.1; and for WS h2 ≤0.338. Genetic correlations between the BMM and BW, PW, or BY were ≤0.132 in Line A and ≤0.248 in Line B. This paper demonstrates the polygenic nature of these traits and the low genetic relationships with BW, PW, and BY, which facilitates genetic improvement across all traits in a balanced breeding program. It also highlights the importance of understanding the environmental and/or management factors that contribute greater than 65% of the variance in the incidence of white striping of breast muscle and more than 90% of the variance of the incidence of wooden breast and deep pectoral myopathy in broiler chickens. PMID:26476091

Computer image analysis traits of cross-sectioned dry-cured hams: a genetic analysis.

PubMed

Bonfatti, V; Cecchinato, A; Sturaro, E; Gallo, L; Carnier, P

2011-08-01

The aims of this study were to estimate genetic parameters of image analysis traits of cross-sectioned dry-cured hams and carcass weight (CW) and to investigate effects of some nongenetic sources of variation on these traits. Computer image analysis (CIA) had been carried out for digital images of the cross-section of 1,319 San Daniele dry-cured hams. The cross-sectional area (SA, cm(2)); the average thickness of subcutaneous fat (FT, cm); and the proportions of lean (LA, %), fat-eye (FEA, %), and subcutaneous fat area (SCF, %) to SA, and of biceps femoris (BFA, %) and semitendinosus muscle area (STA, %) to LA were recorded. Bivariate analyses were carried out for pairs of traits for estimation of genetic parameters using Bayesian methodology and linear models. Linear models included the nongenetic effects of slaughter groups and sex and the additive genetic effects of pigs and their ancestors (1,888 animals). Variation of FEA was nearly 4-fold that of SA and LA. Variation of CIA traits due to sex effect was not large, whereas slaughter group effects were relevant sources of variation for all traits. For all traits, with the exception of FEA, the posterior probability for the true heritability being greater than 0.1, was greater than 0.95. Point estimates of heritabilities for FT and SCF were 0.42 and 0.51, respectively. Heritability estimates for FEA, LA, BFA, and STA were 0.13, 0.44, 0.44, and 0.36, respectively. The genetic correlations between CW and CIA traits were positive and large for SA (0.86), positive and moderate for FT, FEA, and STA (0.47, 0.40, and 0.45, respectively) and negative with LA (-0.28). Although FEA, FT, and SCF were all measures of the extent of fat deposition in the ham, the genetic correlations between FT or SCF and FEA were very low. A very large estimate (0.74) was obtained for the genetic relationship between SA and FEA, suggesting that reduction of ham roundness through selective breeding would be beneficial for decreasing FEA. On the basis of the estimated parameters, genetic selection is expected to be effective in changing size of fatty and lean areas of the cross-section of dry-cured hams. Causes related to the abnormal development of the fat-eye depot remain unknown, but this study provided evidence that influences of polygenic effects on phenotypic variation of FEA are limited. © 2011 American Society of Animal Science. All rights reserved.

Polygenic risk for psychiatric disorders correlates with executive function in typical development.

PubMed

Schork, A J; Brown, T T; Hagler, D J; Thompson, W K; Chen, C-H; Dale, A M; Jernigan, T L; Akshoomoff, N

2018-04-16

Executive functions are a diverse and critical suite of cognitive abilities that are often disrupted in individuals with psychiatric disorders. Despite their moderate to high heritability, little is known about the molecular genetic factors that contribute to variability in executive functions and how these factors may be related to those that predispose to psychiatric disorders. We examined the relationship between polygenic risk scores built from large genome-wide association studies of psychiatric disorders and executive functioning in typically developing children. In our discovery sample (N = 417), consistent with previous reports on general cognitive abilities, polygenic risk for autism spectrum disorder was associated with better performance on the Dimensional Change Card Sort test from the NIH Cognition Toolbox, with the largest effect in the youngest children. Polygenic risk for major depressive disorder was associated with poorer performance on the Flanker test in the same sample. This second association replicated for performance on the Penn Conditional Exclusion Test in an independent cohort (N = 3681). Our results suggest that the molecular genetic factors contributing to variability in executive function during typical development are at least partially overlapping with those associated with psychiatric disorders, although larger studies and further replication are needed. © 2018 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Individual and shared effects of social environment and polygenic risk scores on adolescent body mass index.

PubMed

Coleman, Jonathan R I; Krapohl, Eva; Eley, Thalia C; Breen, Gerome

2018-04-20

Juvenile obesity is associated with adverse health outcomes. Understanding genetic and environmental influences on body mass index (BMI) during adolescence could inform interventions. We investigated independent and interactive effects of parenting, socioeconomic status (SES) and polygenic risk on BMI pre-adolescence, and on the rate of change in BMI across adolescence. Genome-wide genotype data, BMI and child perceptions of parental warmth and punitive discipline were available at 11 years old, and parental SES was available from birth on 3,414 unrelated participants. Linear models were used to test the effects of social environment and polygenic risk on pre-adolescent BMI. Change in BMI across adolescence was assessed in a subset (N = 1943). Sex-specific effects were assessed. Higher genetic risk was associated with increased BMI pre-adolescence and across adolescence (p < 0.00417, corrected for multiple tests). Negative parenting was not significantly associated with either phenotype, but lower SES was associated with increased BMI pre-adolescence. No interactions passed correction for multiple testing. Polygenic risk scores from adult GWAS meta-analyses are associated with BMI in juveniles, suggesting a stable genetic component. Pre-adolescent BMI was associated with social environment, but parental style has, at most, a small effect.

Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions

Treesearch

Xiaoqing Yu; Guihua Bai; Shuwei Liu; Na Luo; Ying Wang; Douglas S. Richmond; Paula M. Pijut; Scott A. Jackson; Jianming Yu; Yiwei Jiang

2013-01-01

Drought is a major environmental stress limiting growth of perennial grasses in temperate regions. Plant drought tolerance is a complex trait that is controlled by multiple genes. Candidate gene association mapping provides a powerful tool for dissection of complex traits. Candidate gene association mapping of drought tolerance traits was conducted in 192 diverse...

Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences☆

PubMed Central

Hill, W.D.; Davies, G.; Liewald, D.C.; Payton, A.; McNeil, C.J.; Whalley, L.J.; Horan, M.; Ollier, W.; Starr, J.M.; Pendleton, N.; Hansel, N.K.; Montgomery, G.W.; Medland, S.E.; Martin, N.G.; Wright, M.J.; Bates, T.C.; Deary, I.J.

2016-01-01

Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences. PMID:26912939

Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

PubMed

Gauguier, Dominique; Behmoaras, Jacques; Argoud, Karène; Wilder, Steven P; Pradines, Christelle; Bihoreau, Marie Thérèse; Osborne-Pellegrin, Mary; Jacob, Marie Paule

2005-03-01

Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

Examining non-syndromic autosomal recessive intellectual disability (NS-ARID) genes for an enriched association with intelligence differences.

PubMed

Hill, W D; Davies, G; Liewald, D C; Payton, A; McNeil, C J; Whalley, L J; Horan, M; Ollier, W; Starr, J M; Pendleton, N; Hansel, N K; Montgomery, G W; Medland, S E; Martin, N G; Wright, M J; Bates, T C; Deary, I J

2016-01-01

Two themes are emerging regarding the molecular genetic aetiology of intelligence. The first is that intelligence is influenced by many variants and those that are tagged by common single nucleotide polymorphisms account for around 30% of the phenotypic variation. The second, in line with other polygenic traits such as height and schizophrenia, is that these variants are not randomly distributed across the genome but cluster in genes that work together. Less clear is whether the very low range of cognitive ability (intellectual disability) is simply one end of the normal distribution describing individual differences in cognitive ability across a population. Here, we examined 40 genes with a known association with non-syndromic autosomal recessive intellectual disability (NS-ARID) to determine if they are enriched for common variants associated with the normal range of intelligence differences. The current study used the 3511 individuals of the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium. In addition, a text mining analysis was used to identify gene sets biologically related to the NS-ARID set. Gene-based tests indicated that genes implicated in NS-ARID were not significantly enriched for quantitative trait loci (QTL) associated with intelligence. These findings suggest that genes in which mutations can have a large and deleterious effect on intelligence are not associated with variation across the range of intelligence differences.

Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder.

PubMed

de Moor, Marleen H M; van den Berg, Stéphanie M; Verweij, Karin J H; Krueger, Robert F; Luciano, Michelle; Arias Vasquez, Alejandro; Matteson, Lindsay K; Derringer, Jaime; Esko, Tõnu; Amin, Najaf; Gordon, Scott D; Hansell, Narelle K; Hart, Amy B; Seppälä, Ilkka; Huffman, Jennifer E; Konte, Bettina; Lahti, Jari; Lee, Minyoung; Miller, Mike; Nutile, Teresa; Tanaka, Toshiko; Teumer, Alexander; Viktorin, Alexander; Wedenoja, Juho; Abecasis, Goncalo R; Adkins, Daniel E; Agrawal, Arpana; Allik, Jüri; Appel, Katja; Bigdeli, Timothy B; Busonero, Fabio; Campbell, Harry; Costa, Paul T; Davey Smith, George; Davies, Gail; de Wit, Harriet; Ding, Jun; Engelhardt, Barbara E; Eriksson, Johan G; Fedko, Iryna O; Ferrucci, Luigi; Franke, Barbara; Giegling, Ina; Grucza, Richard; Hartmann, Annette M; Heath, Andrew C; Heinonen, Kati; Henders, Anjali K; Homuth, Georg; Hottenga, Jouke-Jan; Iacono, William G; Janzing, Joost; Jokela, Markus; Karlsson, Robert; Kemp, John P; Kirkpatrick, Matthew G; Latvala, Antti; Lehtimäki, Terho; Liewald, David C; Madden, Pamela A F; Magri, Chiara; Magnusson, Patrik K E; Marten, Jonathan; Maschio, Andrea; Medland, Sarah E; Mihailov, Evelin; Milaneschi, Yuri; Montgomery, Grant W; Nauck, Matthias; Ouwens, Klaasjan G; Palotie, Aarno; Pettersson, Erik; Polasek, Ozren; Qian, Yong; Pulkki-Råback, Laura; Raitakari, Olli T; Realo, Anu; Rose, Richard J; Ruggiero, Daniela; Schmidt, Carsten O; Slutske, Wendy S; Sorice, Rossella; Starr, John M; St Pourcain, Beate; Sutin, Angelina R; Timpson, Nicholas J; Trochet, Holly; Vermeulen, Sita; Vuoksimaa, Eero; Widen, Elisabeth; Wouda, Jasper; Wright, Margaret J; Zgaga, Lina; Porteous, David; Minelli, Alessandra; Palmer, Abraham A; Rujescu, Dan; Ciullo, Marina; Hayward, Caroline; Rudan, Igor; Metspalu, Andres; Kaprio, Jaakko; Deary, Ian J; Räikkönen, Katri; Wilson, James F; Keltikangas-Järvinen, Liisa; Bierut, Laura J; Hettema, John M; Grabe, Hans J; van Duijn, Cornelia M; Evans, David M; Schlessinger, David; Pedersen, Nancy L; Terracciano, Antonio; McGue, Matt; Penninx, Brenda W J H; Martin, Nicholas G; Boomsma, Dorret I

2015-07-01

Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases). To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.

ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties.

PubMed

St Pourcain, B; Robinson, E B; Anttila, V; Sullivan, B B; Maller, J; Golding, J; Skuse, D; Ring, S; Evans, D M; Zammit, S; Fisher, S E; Neale, B M; Anney, R J L; Ripke, S; Hollegaard, M V; Werge, T; Ronald, A; Grove, J; Hougaard, D M; Børglum, A D; Mortensen, P B; Daly, M J; Davey Smith, G

2018-02-01

Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic influences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children, N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic influences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors influencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic influences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptoms.

Joint effects of pleiotropic selection and stabilizing selection on the maintenance of quantitative genetic variation at mutation-selection balance.

PubMed Central

Zhang, Xu-Sheng; Hill, William G

2002-01-01

In quantitative genetics, there are two basic "conflicting" observations: abundant polygenic variation and strong stabilizing selection that should rapidly deplete that variation. This conflict, although having attracted much theoretical attention, still stands open. Two classes of model have been proposed: real stabilizing selection directly on the metric trait under study and apparent stabilizing selection caused solely by the deleterious pleiotropic side effects of mutations on fitness. Here these models are combined and the total stabilizing selection observed is assumed to derive simultaneously through these two different mechanisms. Mutations have effects on a metric trait and on fitness, and both effects vary continuously. The genetic variance (V(G)) and the observed strength of total stabilizing selection (V(s,t)) are analyzed with a rare-alleles model. Both kinds of selection reduce V(G) but their roles in depleting it are not independent: The magnitude of pleiotropic selection depends on real stabilizing selection and such dependence is subject to the shape of the distributions of mutational effects. The genetic variation maintained thus depends on the kurtosis as well as the variance of mutational effects: All else being equal, V(G) increases with increasing leptokurtosis of mutational effects on fitness, while for a given distribution of mutational effects on fitness, V(G) decreases with increasing leptokurtosis of mutational effects on the trait. The V(G) and V(s,t) are determined primarily by real stabilizing selection while pleiotropic effects, which can be large, have only a limited impact. This finding provides some promise that a high heritability can be explained under strong total stabilizing selection for what are regarded as typical values of mutation and selection parameters. PMID:12242254

Pseudomonas fluorescens F113 Mutant with Enhanced Competitive Colonization Ability and Improved Biocontrol Activity against Fungal Root Pathogens ▿

PubMed Central

Barahona, Emma; Navazo, Ana; Martínez-Granero, Francisco; Zea-Bonilla, Teresa; Pérez-Jiménez, Rosa María; Martín, Marta; Rivilla, Rafael

2011-01-01

Motility is one of the most important traits for efficient rhizosphere colonization by Pseudomonas fluorescens F113rif (F113). In this bacterium, motility is a polygenic trait that is repressed by at least three independent pathways, including the Gac posttranscriptional system, the Wsp chemotaxis-like pathway, and the SadB pathway. Here we show that the kinB gene, which encodes a signal transduction protein that together with AlgB has been implicated in alginate production, participates in swimming motility repression through the Gac pathway, acting downstream of the GacAS two-component system. Gac mutants are impaired in secondary metabolite production and are unsuitable as biocontrol agents. However, the kinB mutant and a triple mutant affected in kinB, sadB, and wspR (KSW) possess a wild-type phenotype for secondary metabolism. The KSW strain is hypermotile and more competitive for rhizosphere colonization than the wild-type strain. We have compared the biocontrol activity of KSW with those of the wild-type strain and a phenotypic variant (F113v35 [V35]) which is hypermotile and hypercompetitive but is affected in secondary metabolism since it harbors a gacS mutation. Biocontrol experiments in the Fusarium oxysporum f. sp. radicis-lycopersici/Lycopersicum esculentum (tomato) and Phytophthora cactorum/Fragaria vesca (strawberry) pathosystems have shown that the three strains possess biocontrol activity. Biocontrol activity was consistently lower for V35, indicating that the production of secondary metabolites was the most important trait for biocontrol. Strain KSW showed improved biocontrol compared with the wild-type strain, indicating that an increase in competitive colonization ability resulted in improved biocontrol and that the rational design of biocontrol agents by mutation is feasible. PMID:21685161

Pseudomonas fluorescens F113 mutant with enhanced competitive colonization ability and improved biocontrol activity against fungal root pathogens.

PubMed

Barahona, Emma; Navazo, Ana; Martínez-Granero, Francisco; Zea-Bonilla, Teresa; Pérez-Jiménez, Rosa María; Martín, Marta; Rivilla, Rafael

2011-08-01

Motility is one of the most important traits for efficient rhizosphere colonization by Pseudomonas fluorescens F113rif (F113). In this bacterium, motility is a polygenic trait that is repressed by at least three independent pathways, including the Gac posttranscriptional system, the Wsp chemotaxis-like pathway, and the SadB pathway. Here we show that the kinB gene, which encodes a signal transduction protein that together with AlgB has been implicated in alginate production, participates in swimming motility repression through the Gac pathway, acting downstream of the GacAS two-component system. Gac mutants are impaired in secondary metabolite production and are unsuitable as biocontrol agents. However, the kinB mutant and a triple mutant affected in kinB, sadB, and wspR (KSW) possess a wild-type phenotype for secondary metabolism. The KSW strain is hypermotile and more competitive for rhizosphere colonization than the wild-type strain. We have compared the biocontrol activity of KSW with those of the wild-type strain and a phenotypic variant (F113v35 [V35]) which is hypermotile and hypercompetitive but is affected in secondary metabolism since it harbors a gacS mutation. Biocontrol experiments in the Fusarium oxysporum f. sp. radicis-lycopersici/Lycopersicum esculentum (tomato) and Phytophthora cactorum/Fragaria vesca (strawberry) pathosystems have shown that the three strains possess biocontrol activity. Biocontrol activity was consistently lower for V35, indicating that the production of secondary metabolites was the most important trait for biocontrol. Strain KSW showed improved biocontrol compared with the wild-type strain, indicating that an increase in competitive colonization ability resulted in improved biocontrol and that the rational design of biocontrol agents by mutation is feasible.

Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents.

PubMed

Eskandari, Mehrzad; Cober, Elroy R; Rajcan, Istvan

2013-02-01

Soybean seed is a major source of oil for human consumption worldwide and the main renewable feedstock for biodiesel production in North America. Increasing seed oil concentration in soybean [Glycine max (L.) Merrill] with no or minimal impact on protein concentration could be accelerated by exploiting quantitative trait loci (QTL) or gene-specific markers. Oil concentration in soybean is a polygenic trait regulated by many genes with mostly small effects and which is negatively associated with protein concentration. The objectives of this study were to discover and validate oil QTL in two recombinant inbred line (RIL) populations derived from crosses between three moderately high-oil soybean cultivars, OAC Wallace, OAC Glencoe, and RCAT Angora. The RIL populations were grown across several environments over 2 years in Ontario, Canada. In a population of 203 F(3:6) RILs from a cross of OAC Wallace and OAC Glencoe, a total of 11 genomic regions on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping and single-factor ANOVA. The percentage of the phenotypic variation accounted for by each QTL ranged from 4 to 11 %. Of the five QTL that were tested in a population of 211 F(3:5) RILs from the cross RCAT Angora × OAC Wallace, a "trait-based" bidirectional selective genotyping analysis validated four QTL (80 %). In addition, a total of seven two-way epistatic interactions were identified for oil concentration in this study. The QTL and epistatic interactions identified in this study could be used in marker-assisted introgression aimed at pyramiding high-oil alleles in soybean cultivars to increase oil concentration for biodiesel as well as edible oil applications.

Chromosomal rearrangements, phenotypic variation and modularity: a case study from a contact zone between house mouse Robertsonian races in Central Italy.

PubMed

Franchini, Paolo; Colangelo, Paolo; Meyer, Axel; Fruciano, Carmelo

2016-03-01

The Western European house mouse, Mus musculus domesticus, is well-known for the high frequency of Robertsonian fusions that have rapidly produced more than 50 karyotipic races, making it an ideal model for studying the mechanisms of chromosomal speciation. The mouse mandible is one of the traits studied most intensively to investigate the effect of Robertsonian fusions on phenotypic variation within and between populations. This complex bone structure has also been widely used to study the level of integration between different morphogenetic units. Here, with the aim of testing the effect of different karyotypic assets on the morphology of the mouse mandible and on its level of modularity, we performed morphometric analyses of mice from a contact area between two highly metacentric races in Central Italy. We found no difference in size, while the mandible shape was found to be different between the two Robertsonian races, even after accounting for the genetic relationships among individuals and geographic proximity. Our results support the existence of two modules that indicate a certain degree of evolutionary independence, but no difference in the strength of modularity between chromosomal races. Moreover, the ascending ramus showed more pronounced interpopulation/race phenotypic differences than the alveolar region, an effect that could be associated to their different polygenic architecture. This study suggests that chromosomal rearrangements play a role in the house mouse phenotypic divergence, and that the two modules of the mouse mandible are differentially affected by environmental factors and genetic makeup.

Genetic potential of common bean progenies obtained by different breeding methods evaluated in various environments.

PubMed

Pontes Júnior, V A; Melo, P G S; Pereira, H S; Melo, L C

2016-09-02

Grain yield is strongly influenced by the environment, has polygenic and complex inheritance, and is a key trait in the selection and recommendation of cultivars. Breeding programs should efficiently explore the genetic variability resulting from crosses by selecting the most appropriate method for breeding in segregating populations. The goal of this study was to evaluate and compare the genetic potential of common bean progenies of carioca grain for grain yield, obtained by different breeding methods and evaluated in different environments. Progenies originating from crosses between lines and CNFC 7812 and CNFC 7829 were replanted up to the F 7 generation using three breeding methods in segregating populations: population (bulk), bulk within F 2 progenies, and single-seed descent (SSD). Fifteen F 8 progenies per method, two controls (BRS Estilo and Perola), and the parents were evaluated in a 7 x 7 simple lattice design, with plots of two 4-m rows. The tests were conducted in 10 environments in four States of Brazil and in three growing seasons in 2009 and 2010. Genetic parameters including genetic variance, heritability, variance of interaction, and expected selection gain were estimated. Genetic variability among progenies and the effect of progeny-environment interactions were determined for the three methods. The breeding methods differed significantly due to the effects of sampling procedures on the progenies and due to natural selection, which mainly affected the bulk method. The SSD and bulk methods provided populations with better estimates of genetic parameters and more stable progenies that were less affected by interaction with the environment.

Complementary Proteome and Transcriptome Profiling in Developing Grains of a Notched-Belly Rice Mutant Reveals Key Pathways Involved in Chalkiness Formation

PubMed Central

Lin, Zhaomiao; Wang, Zunxin; Zhang, Xincheng; Li, Ganghua; Wang, Shaohua; Ding, Yanfeng

2017-01-01

Rice grain chalkiness is a highly complex trait involved in multiple metabolic pathways and controlled by polygenes and growth conditions. To uncover novel aspects of chalkiness formation, we performed an integrated profiling of gene activity in the developing grains of a notched-belly rice mutant. Using exhaustive tandem mass spectrometry-based shotgun proteomics and whole-genome RNA sequencing to generate a nearly complete catalog of expressed mRNAs and proteins, we reliably identified 38,476 transcripts and 3,840 proteins. Comparison between the translucent part and chalky part of the notched-belly grains resulted in only a few differently express genes (240) and differently express proteins (363), thus making it possible to focus on ‘core’ genes or common pathways. Several novel key pathways were identified as of relevance to chalkiness formation, in particular the shift of C and N metabolism, the down-regulation of ribosomal proteins and the resulting low abundance of storage proteins especially the 13 kDa prolamin subunit, and the suppressed photosynthetic capacity in the pericarp of the chalky part. Further, genes and proteins as transporters for carbohydrates, amino acid/peptides, proteins, lipids and inorganic ions showed an increasing expression pattern in the chalky part of the notched-belly grains. Similarly, transcripts and proteins of receptors for auxin, ABA, ethylene and brassinosteroid were also up-regulated. In summary, this joint analysis of transcript and protein profiles provides a comprehensive reference map of gene activity regarding the physiological state in the chalky endosperm. PMID:28158863

The search for the genetic basis of hypertension.

PubMed

Yagil, Yoram; Yagil, Chana

2005-03-01

This review surveys the literature on the search for the genetic basis of hypertension during the 10 months since November 2003. The goals set forth by this search are defined and the highlights of the work accomplished are provided. The search for the genetic basis of hypertension is ongoing, generating an abundance of new data. These data consist of a large number of candidate genes, association of previously known and novel candidate genes with various facets of hypertension, detection of new quantitative trait loci and identification of genes that mediate susceptibility to hypertension. The renin-zangiotensin-aldosterone system continues to dominate the interest of investigators. Other gene systems are also emerging but a single-gene system cannot be singled out beyond the renin-angiotensin-aldosterone system and the data are mostly sporadic and do not reflect a guided or coordinated effort to resolve unanswered issues. The notion that hypertension is polygenic is reinforced, yet few data are provided as to the actual number of genes involved, gene-gene interaction or gene-environment interaction. Advanced biotechnological tools involving transcriptomics and proteomics are underused. Research on the genetic basis of hypertension has generated over the past year a large number of candidate genes and tied them to various aspects of hypertension. How these genes fit into the complex pathophysiological network that induces hypertension remains unclear. The task of putting together these genes into a cohesive framework still lies ahead, but promises to enlighten us as to the true nature of hypertension, the pathogenic mechanisms involved and improved therapeutic and preventive measures.

The vgll3 Locus Controls Age at Maturity in Wild and Domesticated Atlantic Salmon (Salmo salar L.) Males.

PubMed

Ayllon, Fernando; Kjærner-Semb, Erik; Furmanek, Tomasz; Wennevik, Vidar; Solberg, Monica F; Dahle, Geir; Taranger, Geir Lasse; Glover, Kevin A; Almén, Markus Sällman; Rubin, Carl J; Edvardsen, Rolf B; Wargelius, Anna

2015-11-01

Wild and domesticated Atlantic salmon males display large variation for sea age at sexual maturation, which varies between 1-5 years. Previous studies have uncovered a genetic predisposition for variation of age at maturity with moderate heritability, thus suggesting a polygenic or complex nature of this trait. The aim of this study was to identify associated genetic loci, genes and ultimately specific sequence variants conferring sea age at maturity in salmon. We performed a genome wide association study (GWAS) using a pool sequencing approach (20 individuals per river and phenotype) of male salmon returning to rivers as sexually mature either after one sea winter (2009) or three sea winters (2011) in six rivers in Norway. The study revealed one major selective sweep, which covered 76 significant SNPs in which 74 were found in a 370 kb region of chromosome 25. Genotyping other smolt year classes of wild and domesticated salmon confirmed this finding. Genotyping domesticated fish narrowed the haplotype region to four SNPs covering 2386 bp, containing the vgll3 gene, including two missense mutations explaining 33-36% phenotypic variation. A single locus was found to have a highly significant role in governing sea age at maturation in this species. The SNPs identified may be both used as markers to guide breeding for late maturity in salmon aquaculture and in monitoring programs of wild salmon. Interestingly, a SNP in proximity of the VGLL3 gene in humans (Homo sapiens), has previously been linked to age at puberty suggesting a conserved mechanism for timing of puberty in vertebrates.

High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model.

PubMed

Lo, Chiao-Ling; Lossie, Amy C; Liang, Tiebing; Liu, Yunlong; Xuei, Xiaoling; Lumeng, Lawrence; Zhou, Feng C; Muir, William M

2016-08-01

Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder) in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP). This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross) resulted in small haplotype blocks (HB) with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate) to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS), were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50%) of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284) and intronic regions (169) with the least in exon's (4), suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a), excitatory receptors (Grin2a, Gria3, Grip1), neurotransmitters (Pomc), and synapses (Snap29). This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits.

Incorporating genomics into breast and prostate cancer screening: assessing the implications

PubMed Central

Chowdhury, Susmita; Dent, Tom; Pashayan, Nora; Hall, Alison; Lyratzopoulos, Georgios; Hallowell, Nina; Hall, Per; Pharoah, Paul; Burton, Hilary

2013-01-01

Individual risk prediction and stratification based on polygenic profiling may be useful in disease prevention. Risk-stratified population screening based on multiple factors including a polygenic risk profile has the potential to be more efficient than age-stratified screening. In this article, we summarize the implications of personalized screening for breast and prostate cancers. We report the opinions of multidisciplinary international experts who have explored the scientific, ethical, and logistical aspects of stratified screening. We have identified (i) the need to recognize the benefits and harms of personalized screening as compared with existing screening methods, (ii) that the use of genetic data highlights complex ethical issues including discrimination against high-risk individuals by insurers and employers and patient autonomy in relation to genetic testing of minors, (iii) the need for transparency and clear communication about risk scores, about harms and benefits, and about reasons for inclusion and exclusion from the risk-based screening process, and (iv) the need to develop new professional competences and to assess cost-effectiveness and acceptability of stratified screening programs before implementation. We conclude that health professionals and stakeholders need to consider the implications of incorporating genetic information in intervention strategies for health-care planning in the future. Genet Med 2013:15(6):423–432 PMID:23412607

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

PubMed

Davies, Gail; Lam, Max; Harris, Sarah E; Trampush, Joey W; Luciano, Michelle; Hill, W David; Hagenaars, Saskia P; Ritchie, Stuart J; Marioni, Riccardo E; Fawns-Ritchie, Chloe; Liewald, David C M; Okely, Judith A; Ahola-Olli, Ari V; Barnes, Catriona L K; Bertram, Lars; Bis, Joshua C; Burdick, Katherine E; Christoforou, Andrea; DeRosse, Pamela; Djurovic, Srdjan; Espeseth, Thomas; Giakoumaki, Stella; Giddaluru, Sudheer; Gustavson, Daniel E; Hayward, Caroline; Hofer, Edith; Ikram, M Arfan; Karlsson, Robert; Knowles, Emma; Lahti, Jari; Leber, Markus; Li, Shuo; Mather, Karen A; Melle, Ingrid; Morris, Derek; Oldmeadow, Christopher; Palviainen, Teemu; Payton, Antony; Pazoki, Raha; Petrovic, Katja; Reynolds, Chandra A; Sargurupremraj, Muralidharan; Scholz, Markus; Smith, Jennifer A; Smith, Albert V; Terzikhan, Natalie; Thalamuthu, Anbupalam; Trompet, Stella; van der Lee, Sven J; Ware, Erin B; Windham, B Gwen; Wright, Margaret J; Yang, Jingyun; Yu, Jin; Ames, David; Amin, Najaf; Amouyel, Philippe; Andreassen, Ole A; Armstrong, Nicola J; Assareh, Amelia A; Attia, John R; Attix, Deborah; Avramopoulos, Dimitrios; Bennett, David A; Böhmer, Anne C; Boyle, Patricia A; Brodaty, Henry; Campbell, Harry; Cannon, Tyrone D; Cirulli, Elizabeth T; Congdon, Eliza; Conley, Emily Drabant; Corley, Janie; Cox, Simon R; Dale, Anders M; Dehghan, Abbas; Dick, Danielle; Dickinson, Dwight; Eriksson, Johan G; Evangelou, Evangelos; Faul, Jessica D; Ford, Ian; Freimer, Nelson A; Gao, He; Giegling, Ina; Gillespie, Nathan A; Gordon, Scott D; Gottesman, Rebecca F; Griswold, Michael E; Gudnason, Vilmundur; Harris, Tamara B; Hartmann, Annette M; Hatzimanolis, Alex; Heiss, Gerardo; Holliday, Elizabeth G; Joshi, Peter K; Kähönen, Mika; Kardia, Sharon L R; Karlsson, Ida; Kleineidam, Luca; Knopman, David S; Kochan, Nicole A; Konte, Bettina; Kwok, John B; Le Hellard, Stephanie; Lee, Teresa; Lehtimäki, Terho; Li, Shu-Chen; Liu, Tian; Koini, Marisa; London, Edythe; Longstreth, Will T; Lopez, Oscar L; Loukola, Anu; Luck, Tobias; Lundervold, Astri J; Lundquist, Anders; Lyytikäinen, Leo-Pekka; Martin, Nicholas G; Montgomery, Grant W; Murray, Alison D; Need, Anna C; Noordam, Raymond; Nyberg, Lars; Ollier, William; Papenberg, Goran; Pattie, Alison; Polasek, Ozren; Poldrack, Russell A; Psaty, Bruce M; Reppermund, Simone; Riedel-Heller, Steffi G; Rose, Richard J; Rotter, Jerome I; Roussos, Panos; Rovio, Suvi P; Saba, Yasaman; Sabb, Fred W; Sachdev, Perminder S; Satizabal, Claudia L; Schmid, Matthias; Scott, Rodney J; Scult, Matthew A; Simino, Jeannette; Slagboom, P Eline; Smyrnis, Nikolaos; Soumaré, Aïcha; Stefanis, Nikos C; Stott, David J; Straub, Richard E; Sundet, Kjetil; Taylor, Adele M; Taylor, Kent D; Tzoulaki, Ioanna; Tzourio, Christophe; Uitterlinden, André; Vitart, Veronique; Voineskos, Aristotle N; Kaprio, Jaakko; Wagner, Michael; Wagner, Holger; Weinhold, Leonie; Wen, K Hoyan; Widen, Elisabeth; Yang, Qiong; Zhao, Wei; Adams, Hieab H H; Arking, Dan E; Bilder, Robert M; Bitsios, Panos; Boerwinkle, Eric; Chiba-Falek, Ornit; Corvin, Aiden; De Jager, Philip L; Debette, Stéphanie; Donohoe, Gary; Elliott, Paul; Fitzpatrick, Annette L; Gill, Michael; Glahn, David C; Hägg, Sara; Hansell, Narelle K; Hariri, Ahmad R; Ikram, M Kamran; Jukema, J Wouter; Vuoksimaa, Eero; Keller, Matthew C; Kremen, William S; Launer, Lenore; Lindenberger, Ulman; Palotie, Aarno; Pedersen, Nancy L; Pendleton, Neil; Porteous, David J; Räikkönen, Katri; Raitakari, Olli T; Ramirez, Alfredo; Reinvang, Ivar; Rudan, Igor; Dan Rujescu; Schmidt, Reinhold; Schmidt, Helena; Schofield, Peter W; Schofield, Peter R; Starr, John M; Steen, Vidar M; Trollor, Julian N; Turner, Steven T; Van Duijn, Cornelia M; Villringer, Arno; Weinberger, Daniel R; Weir, David R; Wilson, James F; Malhotra, Anil; McIntosh, Andrew M; Gale, Catharine R; Seshadri, Sudha; Mosley, Thomas H; Bressler, Jan; Lencz, Todd; Deary, Ian J

2018-05-29

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10 -8 ) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Evolutionary diversity and turn-over of sex determination in teleost fishes.

PubMed

Mank, J E; Avise, J C

2009-01-01

Sex determination, due to the obvious association with reproduction and Darwinian fitness, has been traditionally assumed to be a relatively conserved trait. However, research on teleost fishes has shown that this need not be the case, as these animals display a remarkable diversity in the ways that they determine sex. These different mechanisms, which include constitutive genetic mechanisms on sex chromosomes, polygenic constitutive mechanisms, environmental influences, hermaphroditism, and unisexuality have each originated numerous independent times in the teleosts. The evolutionary lability of sex determination, and the corresponding rapid rate of turn-over among different modes, makes the teleost clade an excellent model with which to test theories regarding the evolution of sex determining adaptations. Much of the plasticity in sex determination likely results from the dynamic teleost genome, and recent advances in fish genetics and genomics have revealed the role of gene and genome duplication in fostering emergence and turn-over of sex determining mechanisms. 2009 S. Karger AG, Basel.

Complex segregation analysis of craniomandibular osteopathy in Deutsch Drahthaar dogs.

PubMed

Vagt, J; Distl, O

2018-01-01

This study investigated familial relationships among Deutsch Drahthaar dogs with craniomandibular osteopathy and examined the most likely mode of inheritance. Sixteen Deutsch Drahthaar dogs with craniomandibular osteopathy were diagnosed using clinical findings, radiography or computed tomography. All 16 dogs with craniomandibular osteopathy had one common ancestor. Complex segregation analyses rejected models explaining the segregation of craniomandibular osteopathy through random environmental variation, monogenic inheritance or an additive sex effect. Polygenic and mixed major gene models sufficiently explained the segregation of craniomandibular osteopathy in the pedigree analysis and offered the most likely hypotheses. The SLC37A2:c.1332C>T variant was not found in a sample of Deutsch Drahthaar dogs with craniomandibular osteopathy, nor in healthy controls. Craniomandibular osteopathy is an inherited condition in Deutsch Drahthaar dogs and the inheritance seems to be more complex than a simple Mendelian model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

PubMed

Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

2017-07-04

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years

PubMed Central

Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O’Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

2017-01-01

ABSTRACT It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education (EduYears) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education. PMID:28706435

Relationships between structural complexity, coral traits, and reef fish assemblages

NASA Astrophysics Data System (ADS)

Darling, Emily S.; Graham, Nicholas A. J.; Januchowski-Hartley, Fraser A.; Nash, Kirsty L.; Pratchett, Morgan S.; Wilson, Shaun K.

2017-06-01

With the ongoing loss of coral cover and the associated flattening of reef architecture, understanding the links between coral habitat and reef fishes is of critical importance. Here, we investigate whether considering coral traits and functional diversity provides new insights into the relationship between structural complexity and reef fish communities, and whether coral traits and community composition can predict structural complexity. Across 157 sites in Seychelles, Maldives, the Chagos Archipelago, and Australia's Great Barrier Reef, we find that structural complexity and reef zone are the strongest and most consistent predictors of reef fish abundance, biomass, species richness, and trophic structure. However, coral traits, diversity, and life histories provided additional predictive power for models of reef fish assemblages, and were key drivers of structural complexity. Our findings highlight that reef complexity relies on living corals—with different traits and life histories—continuing to build carbonate skeletons, and that these nuanced relationships between coral assemblages and habitat complexity can affect the structure of reef fish assemblages. Seascape-level estimates of structural complexity are rapid and cost effective with important implications for the structure and function of fish assemblages, and should be incorporated into monitoring programs.

Novel risk loci for rheumatoid arthritis in Han Chinese and congruence with risk variants in Europeans.

PubMed

Jiang, Lei; Yin, Jian; Ye, Lingying; Yang, Jian; Hemani, Gibran; Liu, Ai-Jun; Zou, Hejian; He, Dongyi; Sun, Lingyun; Zeng, Xiaofeng; Li, Zhanguo; Zheng, Yi; Lin, Yiping; Liu, Yi; Fang, Yongfei; Xu, Jianhua; Li, Yinong; Dai, Shengming; Guan, Jianlong; Jiang, Lindi; Wei, Qianghua; Wang, Yi; Li, Yang; Huang, Cibo; Zuo, Xiaoxia; Liu, Yu; Wu, Xin; Zhang, Libin; Zhou, Ling; Zhang, Qing; Li, Ting; Chen, Ling; Xu, Zhen; Yang, Xiaoping; Qian, Feng; Xie, Weilin; Liu, Wei; Guo, Qian; Huang, Shaolan; Zhao, Jing; Li, Mengmeng; Jin, Yanhua; Gao, Jie; Lv, Ying; Wang, Yiwen; Lin, Li; Guo, Aihua; Danoy, Patrick; Willner, Dana; Cremin, Catherine; Hadler, Johanna; Zhang, Fengchun; Zhao, Yan; Li, Mengtao; Yue, Tao; Fan, Xiaolei; Guo, Jianping; Mu, Rong; Li, Jingyi; Wu, Chao; Zeng, Ming; Wang, Jiucun; Li, Shilin; Jin, Li; Wang, Binbin; Wang, Jing; Ma, Xu; Sun, Liangdan; Zhang, Xuejun; Brown, Matthew A; Visscher, Peter M; Su, Ding-Feng; Xu, Huji

2014-05-01

To investigate differences in genetic risk factors for rheumatoid arthritis (RA) in Han Chinese as compared with Europeans. A genome-wide association study was conducted in China with 952 patients and 943 controls, and 32 variants were followed up in 2,132 patients and 2,553 controls. A transpopulation meta-analysis with results from a large European RA study was also performed to compare the genetic architecture across the 2 ethnic remote populations. Three non-major histocompatibility complex (non-MHC) loci were identified at the genome-wide significance level, the effect sizes of which were larger in anti-citrullinated protein antibody (ACPA)-positive patients than in ACPA-negative patients. These included 2 novel variants, rs12617656, located in an intron of DPP4 (odds ratio [OR] 1.56, P = 1.6 × 10(-21) ), and rs12379034, located in the coding region of CDK5RAP2 (OR 1.49, P = 1.1 × 10(-16) ), as well as a variant at the known CCR6 locus, rs1854853 (OR 0.71, P = 6.5 × 10(-15) ). The analysis of ACPA-positive patients versus ACPA-negative patients revealed that rs12617656 at the DPP4 locus showed a strong interaction effect with ACPAs (P = 5.3 × 10(-18) ), and such an interaction was also observed for rs7748270 at the MHC locus (P = 5.9 × 10(-8) ). The transpopulation meta-analysis showed genome-wide overlap and enrichment in association signals across the 2 populations, as confirmed by prediction analysis. This study has expanded the list of alleles that confer risk of RA, provided new insight into the pathogenesis of RA, and added empirical evidence to the emerging polygenic nature of complex trait variation driven by common genetic variants. Copyright © 2014 by the American College of Rheumatology.

Global genetic differentiation of complex traits shaped by natural selection in humans.

PubMed

Guo, Jing; Wu, Yang; Zhu, Zhihong; Zheng, Zhili; Trzaskowski, Maciej; Zeng, Jian; Robinson, Matthew R; Visscher, Peter M; Yang, Jian

2018-05-14

There are mean differences in complex traits among global human populations. We hypothesize that part of the phenotypic differentiation is due to natural selection. To address this hypothesis, we assess the differentiation in allele frequencies of trait-associated SNPs among African, Eastern Asian, and European populations for ten complex traits using data of large sample size (up to ~405,000). We show that SNPs associated with height ([Formula: see text]), waist-to-hip ratio ([Formula: see text]), and schizophrenia ([Formula: see text]) are significantly more differentiated among populations than matched "control" SNPs, suggesting that these trait-associated SNPs have undergone natural selection. We further find that SNPs associated with height ([Formula: see text]) and schizophrenia ([Formula: see text]) show significantly higher variance in linkage disequilibrium (LD) scores across populations than control SNPs. Our results support the hypothesis that natural selection has shaped the genetic differentiation of complex traits, such as height and schizophrenia, among worldwide populations.

A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure

PubMed Central

Tiezzi, Francesco; Parker-Gaddis, Kristen L.; Cole, John B.; Clay, John S.; Maltecca, Christian

2015-01-01

Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population. PMID:25658712

Directed evolution and synthetic biology applications to microbial systems.

PubMed

Bassalo, Marcelo C; Liu, Rongming; Gill, Ryan T

2016-06-01

Biotechnology applications require engineering complex multi-genic traits. The lack of knowledge on the genetic basis of complex phenotypes restricts our ability to rationally engineer them. However, complex phenotypes can be engineered at the systems level, utilizing directed evolution strategies that drive whole biological systems toward desired phenotypes without requiring prior knowledge of the genetic basis of the targeted trait. Recent developments in the synthetic biology field accelerates the directed evolution cycle, facilitating engineering of increasingly complex traits in biological systems. In this review, we summarize some of the most recent advances in directed evolution and synthetic biology that allows engineering of complex traits in microbial systems. Then, we discuss applications that can be achieved through engineering at the systems level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia.

PubMed

Ruderfer, Douglas M; Fanous, Ayman H; Ripke, Stephan; McQuillin, Andrew; Amdur, Richard L; Gejman, Pablo V; O'Donovan, Michael C; Andreassen, Ole A; Djurovic, Srdjan; Hultman, Christina M; Kelsoe, John R; Jamain, Stephane; Landén, Mikael; Leboyer, Marion; Nimgaonkar, Vishwajit; Nurnberger, John; Smoller, Jordan W; Craddock, Nick; Corvin, Aiden; Sullivan, Patrick F; Holmans, Peter; Sklar, Pamela; Kendler, Kenneth S

2014-09-01

Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

DOE PAGES

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; ...

2017-01-17

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We havemore » applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. Furthermore, a more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.« less

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing.

PubMed

Mizrachi, Eshchar; Verbeke, Lieven; Christie, Nanette; Fierro, Ana C; Mansfield, Shawn D; Davis, Mark F; Gjersing, Erica; Tuskan, Gerald A; Van Montagu, Marc; Van de Peer, Yves; Marchal, Kathleen; Myburg, Alexander A

2017-01-31

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

Dissecting the genetics of complex traits using summary association statistics.

PubMed

Pasaniuc, Bogdan; Price, Alkes L

2017-02-01

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

Dissecting the genetics of complex traits using summary association statistics

PubMed Central

Pasaniuc, Bogdan; Price, Alkes L.

2017-01-01

During the past decade, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyze summary association statistics. Here we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases. PMID:27840428

Genome-Wide Association Study Reveals Greater Polygenic Loading for Schizophrenia in Cases With a Family History of Illness

PubMed Central

Bigdeli, Tim B.; Ripke, Stephan; Bacanu, Silviu-Alin; Lee, Sang Hong; Wray, Naomi R.; Gejman, Pablo V.; Rietschel, Marcella; Cichon, Sven; St Clair, David; Corvin, Aiden; Kirov, George; McQuillin, Andrew; Gurling, Hugh; Rujescu, Dan; Andreassen, Ole A.; Werge, Thomas; Blackwood, Douglas H.R.; Pato, Carlos N.; Pato, Michele T.; Malhotra, Anil K.; O’Donovan, Michael C.; Kendler, Kenneth S.; Fanous, Ayman H.

2018-01-01

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke’s R2 = 0.0021; P = 0.00331; P-value threshold <0.4). Estimates of variability in disease liability attributable to the aggregate effect of genome-wide SNPs were significantly greater for family history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031).We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by previous epidemiological studies. PMID:26663532

Polygenic obesity in humans.

PubMed

Hinney, Anke; Hebebrand, Johannes

2008-01-01

The molecular genetic analysis of obesity has led to the identification of a limited number of confirmed major genes. While such major genes have a clear influence on the development of the phenotype, the underlying mutations are however (extremely) infrequent and thus of minor clinical importance only. The genetic predisposition to obesity must thus be polygenic; a number of such variants should be found in most obese subjects; however, these variants predisposing to obesity are also found in normal weight and even lean individuals. Therefore, a polygene can only be identified and validated by statistical analyses: the appropriate gene variant (allele) occurs more frequently in obese than in non-obese subjects. Each single polygene makes only a small contribution to the development of obesity. The 103Ile allele of the Val103Ile single nucleotide polymorphism (SNP) of the melanocortin-4 receptor gene (MC4R) was the first confirmed polygenetic variant with an influence on the body mass index (BMI); the more common Val103 allele is more frequent in obese individuals. As determined in a recent, large-scaled meta-analysis the effect size of this allele on mean BMI was approximately -0.5 kg/m(2). The first genome-wide association study (GWA) for obesity, based on approximately 100,000 SNPs analyzed in families of the Framingham study, revealed that a SNP in the proximity of the insulin-induced gene 2 (INSIG2) was associated with obesity. The positive result was replicated in independent samples; however, some other study groups detected no association. Currently, a meta-analysis is ongoing; its result will contribute to the evaluation of the importance of the INSIG2 polymorphism in body weight regulation. SNP alleles in intron 1 of the fat mass and obesity associated gene (FTO) confer the most relevant polygenic effect on obesity. In the first GWA for extreme early onset obesity we substantiated that variation in FTO strongly contributes to early onset obesity. Copyright 2008 S. Karger AG, Basel.

Evidence of a Major Gene From Bayesian Segregation Analyses of Liability to Osteochondral Diseases in Pigs

PubMed Central

Kadarmideen, Haja N.; Janss, Luc L. G.

2005-01-01

Bayesian segregation analyses were used to investigate the mode of inheritance of osteochondral lesions (osteochondrosis, OC) in pigs. Data consisted of 1163 animals with OC and their pedigrees included 2891 animals. Mixed-inheritance threshold models (MITM) and several variants of MITM, in conjunction with Markov chain Monte Carlo methods, were developed for the analysis of these (categorical) data. Results showed major genes with significant and substantially higher variances (range 1.384–37.81), compared to the polygenic variance (\\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\pagestyle{empty} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}{\\mathrm{{\\sigma}}}_{{\\mathrm{u}}}^{2}\\end{equation*}\\end{document}). Consequently, heritabilities for a mixed inheritance (range 0.65–0.90) were much higher than the heritabilities from the polygenes. Disease allele frequencies range was 0.38–0.88. Additional analyses estimating the transmission probabilities of the major gene showed clear evidence for Mendelian segregation of a major gene affecting osteochondrosis. The variants, MITM with informative prior on \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\pagestyle{empty} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}{\\mathrm{{\\sigma}}}_{{\\mathrm{u}}}^{2}\\end{equation*}\\end{document}, showed significant improvement in marginal distributions and accuracy of parameters. MITM with a “reduced polygenic model” for parameterization of polygenic effects avoided convergence problems and poor mixing encountered in an “individual polygenic model.” In all cases, “shrinkage estimators” for fixed effects avoided unidentifiability for these parameters. The mixed-inheritance linear model (MILM) was also applied to all OC lesions and compared with the MITM. This is the first study to report evidence of major genes for osteochondral lesions in pigs; these results may also form a basis for underpinning the genetic inheritance of this disease in other animals as well as in humans. PMID:16020792

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

Polygenic Control of Carotid Atherosclerosis in a BALB/cJ × SM/J Intercross and a Combined Cross Involving Multiple Mouse Strains.

PubMed

Grainger, Andrew T; Jones, Michael B; Chen, Mei-Hua; Shi, Weibin

2017-02-09

Atherosclerosis in the carotid arteries is a major cause of ischemic stroke, which accounts for 85% of all stroke cases. Genetic factors contributing to carotid atherosclerosis remain poorly understood. The aim of this study was to identify chromosomal regions harboring genes contributing to carotid atherosclerosis in mice. From an intercross between BALB/cJ (BALB) and SM/J (SM) apolipoprotein E-deficient ( Apoe -/- ) mice, 228 female F2 mice were generated and fed a "Western" diet for 12 wk. Atherosclerotic lesion sizes in the left carotid artery were quantified. Across the entire genome, 149 genetic markers were genotyped. Quantitative trait locus (QTL) analysis revealed eight loci for carotid lesion sizes, located on chromosomes 1, 5, 12, 13, 15, 16, and 18. Combined cross-linkage analysis using data from this cross, and two previous F2 crosses derived from BALB, C57BL/6J and C3H/HeJ strains, identified five significant QTL on chromosomes 5, 9, 12, and 13, and nine suggestive QTL for carotid atherosclerosis. Of them, the QTL on chromosome 12 had a high LOD score of 9.95. Bioinformatic analysis prioritized Arhgap5 , Akap6 , Mipol1 , Clec14a , Fancm , Nin , Dact1 , Rtn1 , and Slc38a6 as probable candidate genes for this QTL. Atherosclerotic lesion sizes were significantly correlated with non-HDL cholesterol levels ( r = 0.254; p = 0.00016) but inversely correlated with HDL cholesterol levels ( r = -0.134; p = 0.049) in the current cross. Thus, we demonstrated the polygenic control of carotid atherosclerosis in mice. The correlations of carotid lesion sizes with non-HDL and HDL suggest that genetic factors exert effects on carotid atherosclerosis partially through modulation of lipoprotein homeostasis. Copyright © 2017 Grainger et al.

Cross-Phenotype Polygenic Risk Score Analysis of Persistent Post-Concussive Symptoms in U.S. Army Soldiers with Deployment-Acquired Traumatic Brain Injury

PubMed Central

Polimanti, Renato; Chen, Chia-Yen; Ursano, Robert J.; Heeringa, Steven G.; Jain, Sonia; Kessler, Ronald C.; Nock, Matthew K.; Smoller, Jordan W.; Sun, Xiaoying; Gelernter, Joel

2017-01-01

Abstract Traumatic brain injury (TBI) contributes to the increased rates of suicide and post-traumatic stress disorder in military personnel and veterans, and it is also associated with the risk for neurodegenerative and psychiatric disorders. A cross-phenotype high-resolution polygenic risk score (PRS) analysis of persistent post-concussive symptoms (PCS) was conducted in 845 U.S. Army soldiers who sustained TBI during their deployment. We used a prospective longitudinal survey of three brigade combat teams to assess deployment-acquired TBI and persistent physical, cognitive, and emotional PCS. PRS was derived from summary statistics of large genome-wide association studies of Alzheimer's disease, Parkinson's disease, schizophrenia, bipolar disorder, and major depressive disorder (MDD); and for years of schooling, college completion, childhood intelligence, infant head circumference (IHC), and adult intracranial volume. Although our study had more than 95% of statistical power to detect moderate-to-large effect sizes, no association was observed with neurodegenerative and psychiatric disorders, suggesting that persistent PCS does not share genetic components with these traits to a moderate-to-large degree. We observed a significant finding: subjects with high IHC PRS recovered better from cognitive/emotional persistent PCS than the other individuals (R2 = 1.11%; p = 3.37 × 10−3). Enrichment analysis identified two significant Gene Ontology (GO) terms related to this result: GO:0050839∼Cell adhesion molecule binding (p = 8.9 × 10−6) and GO:0050905∼Neuromuscular process (p = 9.8 × 10−5). In summary, our study indicated that the genetic predisposition to persistent PCS after TBI does not have substantial overlap with neurodegenerative and psychiatric diseases, but mechanisms related to early brain growth may be involved. PMID:27439997

Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit Neighborhood Health Study.

PubMed

Meyers, J L; Cerdá, M; Galea, S; Keyes, K M; Aiello, A E; Uddin, M; Wildman, D E; Koenen, K C

2013-08-13

Cigarette smoking is influenced both by genetic and environmental factors. Until this year, all large-scale gene identification studies on smoking were conducted in populations of European ancestry. Consequently, the genetic architecture of smoking is not well described in other populations. Further, despite a rich epidemiologic literature focused on the social determinants of smoking, few studies have examined the moderation of genetic influences (for example, gene-environment interactions) on smoking in African Americans. In the Detroit Neighborhood Health Study (DNHS), a sample of randomly selected majority African American residents of Detroit, we constructed a genetic risk score (GRS), in which we combined top (P-value <5 × 10(-7)) genetic variants from a recent meta-analysis conducted in a large sample of African Americans. Using regression (effective n=399), we first tested for association between the GRS and cigarettes per day, attempting to replicate the findings from the meta-analysis. Second, we examined interactions with three social contexts that may moderate the genetic association with smoking: traumatic events, neighborhood social cohesion and neighborhood physical disorder. Among individuals who had ever smoked cigarettes, the GRS significantly predicted the number of cigarettes smoked per day and accounted for ~3% of the overall variance in the trait. Significant interactions were observed between the GRS and number of traumatic events experienced, as well as between the GRS and average neighborhood social cohesion; the association between genetic risk and smoking was greater among individuals who had experienced an increased number of traumatic events in their lifetimes, and diminished among individuals who lived in a neighborhood characterized by greater social cohesion. This study provides support for the utility of the GRS as an alternative approach to replication of common polygenic variation, and in gene-environment interaction, for smoking behaviors. In addition, this study indicates that environmental determinants have the potential to both exacerbate (traumatic events) and diminish (neighborhood social cohesion) genetic influences on smoking behaviors.

How Primary Care Providers Talk to Patients about Genome Sequencing Results: Risk, Rationale, and Recommendation.

PubMed

Vassy, Jason L; Davis, J Kelly; Kirby, Christine; Richardson, Ian J; Green, Robert C; McGuire, Amy L; Ubel, Peter A

2018-06-01

Genomics will play an increasingly prominent role in clinical medicine. To describe how primary care physicians (PCPs) discuss and make clinical recommendations about genome sequencing results. Qualitative analysis. PCPs and their generally healthy patients undergoing genome sequencing. Patients received clinical genome reports that included four categories of results: monogenic disease risk variants (if present), carrier status, five pharmacogenetics results, and polygenic risk estimates for eight cardiometabolic traits. Patients' office visits with their PCPs were audio-recorded, and summative content analysis was used to describe how PCPs discussed genomic results. For each genomic result discussed in 48 PCP-patient visits, we identified a "take-home" message (recommendation), categorized as continuing current management, further treatment, further evaluation, behavior change, remembering for future care, or sharing with family members. We analyzed how PCPs came to each recommendation by identifying 1) how they described the risk or importance of the given result and 2) the rationale they gave for translating that risk into a specific recommendation. Quantitative analysis showed that continuing current management was the most commonly coded recommendation across results overall (492/749, 66%) and for each individual result type except monogenic disease risk results. Pharmacogenetics was the most common result type to prompt a recommendation to remember for future care (94/119, 79%); carrier status was the most common type prompting a recommendation to share with family members (45/54, 83%); and polygenic results were the most common type prompting a behavior change recommendation (55/58, 95%). One-fifth of recommendation codes associated with monogenic results were for further evaluation (6/24, 25%). Rationales for these recommendations included patient context, family context, and scientific/clinical limitations of sequencing. PCPs distinguish substantive differences among categories of genome sequencing results and use clinical judgment to justify continuing current management in generally healthy patients with genomic results.

Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit neighborhood health study

PubMed Central

Meyers, J L; Cerdá, M; Galea, S; Keyes, K M; Aiello, A E; Uddin, M; Wildman, D E; Koenen, K C

2013-01-01

Cigarette smoking is influenced both by genetic and environmental factors. Until this year, all large-scale gene identification studies on smoking were conducted in populations of European ancestry. Consequently, the genetic architecture of smoking is not well described in other populations. Further, despite a rich epidemiologic literature focused on the social determinants of smoking, few studies have examined the moderation of genetic influences (for example, gene–environment interactions) on smoking in African Americans. In the Detroit Neighborhood Health Study (DNHS), a sample of randomly selected majority African American residents of Detroit, we constructed a genetic risk score (GRS), in which we combined top (P-value <5 × 10−7) genetic variants from a recent meta-analysis conducted in a large sample of African Americans. Using regression (effective n=399), we first tested for association between the GRS and cigarettes per day, attempting to replicate the findings from the meta-analysis. Second, we examined interactions with three social contexts that may moderate the genetic association with smoking: traumatic events, neighborhood social cohesion and neighborhood physical disorder. Among individuals who had ever smoked cigarettes, the GRS significantly predicted the number of cigarettes smoked per day and accounted for ∼3% of the overall variance in the trait. Significant interactions were observed between the GRS and number of traumatic events experienced, as well as between the GRS and average neighborhood social cohesion; the association between genetic risk and smoking was greater among individuals who had experienced an increased number of traumatic events in their lifetimes, and diminished among individuals who lived in a neighborhood characterized by greater social cohesion. This study provides support for the utility of the GRS as an alternative approach to replication of common polygenic variation, and in gene–environment interaction, for smoking behaviors. In addition, this study indicates that environmental determinants have the potential to both exacerbate (traumatic events) and diminish (neighborhood social cohesion) genetic influences on smoking behaviors. PMID:23942621

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle.

PubMed

Mateescu, Raluca G; Garrick, Dorian J; Reecy, James M

2017-01-01

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

Genetic variants linked to education predict longevity

PubMed Central

Marioni, Riccardo E.; Ritchie, Stuart J.; Joshi, Peter K.; Hagenaars, Saskia P.; Fischer, Krista; Adams, Mark J.; Hill, W. David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C.; Wilson, James F.; Hayward, Caroline; Esko, Tõnu; Porteous, David J.; Gale, Catharine R.; Deary, Ian J.

2016-01-01

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. PMID:27799538

Genetic variants linked to education predict longevity.

PubMed

Marioni, Riccardo E; Ritchie, Stuart J; Joshi, Peter K; Hagenaars, Saskia P; Okbay, Aysu; Fischer, Krista; Adams, Mark J; Hill, W David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C; Campbell, Archie; Wilson, James F; Hayward, Caroline; Esko, Tõnu; Porteous, David J; Gale, Catharine R; Deary, Ian J

2016-11-22

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n deaths = 79,702) and ∼2.4% lower risk for fathers (total n deaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

Genetics of Temporal Lobe Epilepsy: A Review

PubMed Central

Salzmann, Annick; Malafosse, Alain

2012-01-01

Temporal lobe epilepsy (TLE) is usually regarded as a polygenic and complex disorder. To understand its genetic component, numerous linkage analyses of familial forms and association studies of cases versus controls have been conducted since the middle of the nineties. The present paper lists genetic findings for TLE from the initial segregation analysis to the most recent results published in May 2011. To date, no genes have been clearly related to TLE despite many efforts to do so. However, it is vital to continue replication studies and collaborative attempts to find significant results and thus determine which gene variant combination plays a definitive role in the aetiology of TLE. PMID:22957248

A simple model clarifies the complicated relationships of complex networks

PubMed Central

Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

2014-01-01

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506

The genetics of fat distribution.

PubMed

Schleinitz, Dorit; Böttcher, Yvonne; Blüher, Matthias; Kovacs, Peter

2014-07-01

Fat stored in visceral depots makes obese individuals more prone to complications than subcutaneous fat. There is good evidence that body fat distribution (FD) is controlled by genetic factors. WHR, a surrogate measure of FD, shows significant heritability of up to ∼60%, even after adjusting for BMI. Genetic variants have been linked to various forms of altered FD such as lipodystrophies; however, the polygenic background of visceral obesity has only been sparsely investigated in the past. Recent genome-wide association studies (GWAS) for measures of FD revealed numerous loci harbouring genes potentially regulating FD. In addition, genes with fat depot-specific expression patterns (in particular subcutaneous vs visceral adipose tissue) provide plausible candidate genes involved in the regulation of FD. Many of these genes are differentially expressed in various fat compartments and correlate with obesity-related traits, thus further supporting their role as potential mediators of metabolic alterations associated with a distinct FD. Finally, developmental genes may at a very early stage determine specific FD in later life. Indeed, genes such as TBX15 not only manifest differential expression in various fat depots, but also correlate with obesity and related traits. Moreover, recent GWAS identified several polymorphisms in developmental genes (including TBX15, HOXC13, RSPO3 and CPEB4) strongly associated with FD. More accurate methods, including cardiometabolic imaging, for assessment of FD are needed to promote our understanding in this field, where the main focus is now to unravel the yet unknown biological function of these novel 'fat distribution genes'.

Privacy-preserving genomic testing in the clinic: a model using HIV treatment

PubMed Central

McLaren, Paul J.; Raisaro, Jean Louis; Aouri, Manel; Rotger, Margalida; Ayday, Erman; Bartha, István; Delgado, Maria B.; Vallet, Yannick; Günthard, Huldrych F.; Cavassini, Matthias; Furrer, Hansjakob; Doco-Lecompte, Thanh; Marzolini, Catia; Schmid, Patrick; Di Benedetto, Caroline; Decosterd, Laurent A.; Fellay, Jacques; Hubaux, Jean-Pierre; Telenti, Amalio

2016-01-01

Purpose: The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. Genet Med 18 8, 814–822. Methods: We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. Genet Med 18 8, 814–822. Results: A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. Genet Med 18 8, 814–822. Conclusions: The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine. Genet Med 18 8, 814–822. PMID:26765343

Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement.

PubMed

Carey, Caitlin E; Agrawal, Arpana; Bucholz, Kathleen K; Hartz, Sarah M; Lynskey, Michael T; Nelson, Elliot C; Bierut, Laura J; Bogdan, Ryan

2016-01-01

Despite evidence of substantial comorbidity between psychiatric disorders and substance involvement, the extent to which common genetic factors contribute to their co-occurrence remains understudied. In the current study, we tested for associations between polygenic risk for psychiatric disorders and substance involvement (i.e., ranging from ever-use to severe dependence) among 2573 non-Hispanic European-American participants from the Study of Addiction: Genetics and Environment. Polygenic risk scores (PRS) for cross-disorder psychopathology (CROSS) were generated based on the Psychiatric Genomics Consortium's Cross-Disorder meta-analysis and then tested for associations with a factor representing general liability to alcohol, cannabis, cocaine, nicotine, and opioid involvement (GENSUB). Follow-up analyses evaluated specific associations between each of the five psychiatric disorders which comprised CROSS-attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (AUT), bipolar disorder (BIP), major depressive disorder (MDD), and schizophrenia (SCZ)-and involvement with each component substance included in GENSUB. CROSS PRS explained 1.10% of variance in GENSUB in our sample (p < 0.001). After correction for multiple testing in our follow-up analyses of polygenic risk for each individual disorder predicting involvement with each component substance, associations remained between: (A) MDD PRS and non-problem cannabis use, (B) MDD PRS and severe cocaine dependence, (C) SCZ PRS and non-problem cannabis use and severe cannabis dependence, and (D) SCZ PRS and severe cocaine dependence. These results suggest that shared covariance from common genetic variation contributes to psychiatric and substance involvement comorbidity.

Common variants explain a large fraction of the variability in the liability to psoriasis in a Han Chinese population.

PubMed

Yin, Xianyong; Wineinger, Nathan E; Cheng, Hui; Cui, Yong; Zhou, Fusheng; Zuo, Xianbo; Zheng, Xiaodong; Yang, Sen; Schork, Nicholas J; Zhang, Xuejun

2014-01-30

Psoriasis is a common inflammatory skin disease with a known genetic component. Our previously published psoriasis genome-wide association study identified dozens of novel susceptibility loci in Han Chinese. However, these markers explained only a small fraction of the estimated heritable component of psoriasis. To better understand the unknown yet likely polygenic architecture in psoriasis, we applied a linear mixed model to quantify the variation in the liability to psoriasis explained by common genetic markers (minor allele frequency > 0.01) in a Han Chinese population. We explored the polygenic genetic architecture of psoriasis using genome-wide association data from 2,271 Han Chinese individuals. We estimated that 34.9% (s.e. = 6.0%, P = 9 × 10-9) of the variation in the liability to psoriasis is captured by common genotyped and imputed variants. We discuss these results in the context of the strong association between HLA variants and psoriasis. We also show that the variance explained by each chromosome is linearly correlated to its length (R2 = 0.27, P=0.01), and quantify the impact of a polygenic effect on the prediction and diagnosis of psoriasis. Our results suggest that psoriasis has a substantial polygenic component, which not only has implications for the development of genetic diagnostics and prognostics for psoriasis, but also suggests that more individual variants contributing to psoriasis may be detected if sample sizes in future association studies are increased.

Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease

PubMed Central

Won, Hong-Hee; Natarajan, Pradeep; Dobbyn, Amanda; Jordan, Daniel M.; Roussos, Panos; Lage, Kasper; Raychaudhuri, Soumya

2015-01-01

Large genome-wide association studies (GWAS) have identified many genetic loci associated with risk for myocardial infarction (MI) and coronary artery disease (CAD). Concurrently, efforts such as the National Institutes of Health (NIH) Roadmap Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE) Consortium have provided unprecedented data on functional elements of the human genome. In the present study, we systematically investigate the biological link between genetic variants associated with this complex disease and their impacts on gene function. First, we examined the heritability of MI/CAD according to genomic compartments. We observed that single nucleotide polymorphisms (SNPs) residing within nearby regulatory regions show significant polygenicity and contribute between 59–71% of the heritability for MI/CAD. Second, we showed that the polygenicity and heritability explained by these SNPs are enriched in histone modification marks in specific cell types. Third, we found that a statistically higher number of 45 MI/CAD-associated SNPs that have been identified from large-scale GWAS studies reside within certain functional elements of the genome, particularly in active enhancer and promoter regions. Finally, we observed significant heterogeneity of this signal across cell types, with strong signals observed within adipose nuclei, as well as brain and spleen cell types. These results suggest that the genetic etiology of MI/CAD is largely explained by tissue-specific regulatory perturbation within the human genome. PMID:26509271

Evaluation of polygenic risk scores for predicting breast and prostate cancer risk.

PubMed

Machiela, Mitchell J; Chen, Chia-Yen; Chen, Constance; Chanock, Stephen J; Hunter, David J; Kraft, Peter

2011-09-01

Recently, polygenic risk scores (PRS) have been shown to be associated with certain complex diseases. The approach has been based on the contribution of counting multiple alleles associated with disease across independent loci, without requiring compelling evidence that every locus had already achieved definitive genome-wide statistical significance. Whether PRS assist in the prediction of risk of common cancers is unknown. We built PRS from lists of genetic markers prioritized by their association with breast cancer (BCa) or prostate cancer (PCa) in a training data set and evaluated whether these scores could improve current genetic prediction of these specific cancers in independent test samples. We used genome-wide association data on 1,145 BCa cases and 1,142 controls from the Nurses' Health Study and 1,164 PCa cases and 1,113 controls from the Prostate Lung Colorectal and Ovarian Cancer Screening Trial. Ten-fold cross validation was used to build and evaluate PRS with 10 to 60,000 independent single nucleotide polymorphisms (SNPs). For both BCa and PCa, the models that included only published risk alleles maximized the cross-validation estimate of the area under the ROC curve (0.53 for breast and 0.57 for prostate). We found no significant evidence that PRS using common variants improved risk prediction for BCa and PCa over replicated SNP scores. © 2011 Wiley-Liss, Inc.

Integrating genome-wide association study summaries and element-gene interaction datasets identified multiple associations between elements and complex diseases.

PubMed

He, Awen; Wang, Wenyu; Prakash, N Tejo; Tinkov, Alexey A; Skalny, Anatoly V; Wen, Yan; Hao, Jingcan; Guo, Xiong; Zhang, Feng

2018-03-01

Chemical elements are closely related to human health. Extensive genomic profile data of complex diseases offer us a good opportunity to systemically investigate the relationships between elements and complex diseases/traits. In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element-gene interaction datasets and genome-wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element-gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits (all false discovery rate (FDR) < 0.05), including reported relationships such as aluminum vs. Alzheimer's disease (FDR = 0.042), calcium vs. bone mineral density (FDR = 0.031), magnesium vs. systemic lupus erythematosus (FDR = 0.012) as well as novel associations, such as nickel vs. hypertriglyceridemia (FDR = 0.002) and bipolar disorder (FDR = 0.027). Our study results are consistent with previous biological studies, supporting the good performance of GSEA. Our analyzing results based on GSEA framework provide novel clues for discovering causal relationships between elements and complex diseases. © 2017 WILEY PERIODICALS, INC.

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan

2017-03-02

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

PubMed Central

Deming, Yuetiva; Xia, Jian; Cai, Yefei; Lord, Jenny; Del-Aguila, Jorge L.; Fernandez, Maria Victoria; Carrell, David; Black, Kathleen; Budde, John; Ma, ShengMei; Saef, Benjamin; Howells, Bill; Bertelsen, Sarah; Bailey, Matthew; Ridge, Perry G.; Hefti, Franz; Fillit, Howard; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Carrillo, Maria; Fleisher, Adam; Reeder, Stephanie; Trncic, Nadira; Burke, Anna; Tariot, Pierre; Reiman, Eric M.; Chen, Kewei; Sabbagh, Marwan N.; Beiden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Green, Robert C.; Marshall, Gad; Johnson, Keith A.; Sperling, Reisa A.; Snyder, Peter; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Bernick, Charles; Munic, Donna; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Relkin, Norman; Chaing, Gloria; Ravdin, Lisa; Paul, Steven; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Friedl, Karl; Murali Doraiswamy, P.; Petrella, Jeffrey R.; Borges-Neto, Salvador; James, Olga; Wong, Terence; Coleman, Edward; Schwartz, Adam; Cellar, Janet S.; Levey, Allan L.; Lah, James J.; Behan, Kelly; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Farlow, Martin R.; Saykin, Andrew J.; Foroud, Tatiana M.; Shen, Li; Faber, Kelly; Kim, Sungeun; Nho, Kwangsik; Marie Hake, Ann; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Petersen, Ronald; Jack, Clifford R.; Bernstein, Matthew; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Chertkow, Howard; Hosein, Chris; Mintzer, Jacob; Spicer, Kenneth; Bachman, David; Grossman, Hillel; Mitsis, Effie; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Potter, William; Buckholtz, Neil; Hsiao, John; Kittur, Smita; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J; Glodzik, Lidia; De Santi, Susan; Johnson, Nancy; Chuang-Kuo; Kerwin, Diana; Bonakdarpour, Borna; Weintraub, Sandra; Grafman, Jordan; Lipowski, Kristine; Mesulam, Marek-Marsel; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Borrie, Michael; Lee, T-Y; Bartha, Rob; Martinez, Walter; Villena, Teresa; Sadowsky, Carl; Khachaturian, Zaven; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Frank, Richard; Fleischman, Debra; Arfanakis, Konstantinos; Shah, Raj C.; deToledo-Morrell, Leyla; Sorensen, Greg; Finger, Elizabeth; Pasternack, Stephen; Rachinsky, Irina; Drost, Dick; Rogers, John; Kertesz, Andrew; Furst, Ansgar J.; Chad, Stevan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Mudge, Benita; Assaly, Michele; Fox, Nick; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Ekstam Smith, Karen; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Natelson Love, Marissa; DeCarli, Charles; Carmichael, Owen; Olichney, John; Maillard, Pauline; Fletcher, Evan; Nguyen, Dana; Preda, Andrian; Potkin, Steven; Mulnard, Ruth A.; Thai, Gaby; McAdams-Ortiz, Catherine; Landau, Susan; Jagust, William; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Thompson, Paul; Donohue, Michael; Thomas, Ronald G.; Walter, Sarah; Gessert, Devon; Brewer, James; Vanderswag, Helen; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Aisen, Paul; Davis, Melissa; Morrison, Rosemary; Harvey, Danielle; Thal, Lean; Beckett, Laurel; Neylan, Thomas; Finley, Shannon; Weiner, Michael W.; Hayes, Jacqueline; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Massoglia, Dino; Brawman-Mentzer, Olga; Schuff, Norbert; Smith, Charles D.; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Koeppe, Robert A.; Lord, Joanne L.; Heidebrink, Judith L.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Trojanowki, John Q.; Shaw, Leslie M.; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Foster, Norm; Montine, Tom; Fruehling, J. Jay; Harding, Sandra; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Petrie, Eric C.; Peskind, Elaine; Li, Gail; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Smith, Amanda; Ashok Raj, Balebail; Fargher, Kristin; Kuller, Lew; Mathis, Chet; Ann Oakley, Mary; Lopez, Oscar L.; Simpson, Donna M.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Cairns, Nigel J.; Raichle, Marc; Morris, John C.; Householder, Erin; Taylor-Reinwald, Lisa; Holtzman, David; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Varma, Pradeep; MacAvoy, Martha G.; Carson, Richard E.; van Dyck, Christopher H.; Davies, Peter; Holtzman, David; Morris, John C.; Bales, Kelly; Pickering, Eve H.; Lee, Jin-Moo; Heitsch, Laura; Kauwe, John; Goate, Alison; Piccio, Laura; Cruchaga, Carlos

2016-01-01

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes, and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels, and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r, and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects, and complex disease associations in the same locus.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

The Molecular Genetic Architecture of Self-Employment

PubMed Central

van der Loos, Matthijs J. H. M.; Rietveld, Cornelius A.; Eklund, Niina; Koellinger, Philipp D.; Rivadeneira, Fernando; Abecasis, Gonçalo R.; Ankra-Badu, Georgina A.; Baumeister, Sebastian E.; Benjamin, Daniel J.; Biffar, Reiner; Blankenberg, Stefan; Boomsma, Dorret I.; Cesarini, David; Cucca, Francesco; de Geus, Eco J. C.; Dedoussis, George; Deloukas, Panos; Dimitriou, Maria; Eiriksdottir, Guðny; Eriksson, Johan; Gieger, Christian; Gudnason, Vilmundur; Höhne, Birgit; Holle, Rolf; Hottenga, Jouke-Jan; Isaacs, Aaron; Järvelin, Marjo-Riitta; Johannesson, Magnus; Kaakinen, Marika; Kähönen, Mika; Kanoni, Stavroula; Laaksonen, Maarit A.; Lahti, Jari; Launer, Lenore J.; Lehtimäki, Terho; Loitfelder, Marisa; Magnusson, Patrik K. E.; Naitza, Silvia; Oostra, Ben A.; Perola, Markus; Petrovic, Katja; Quaye, Lydia; Raitakari, Olli; Ripatti, Samuli; Scheet, Paul; Schlessinger, David; Schmidt, Carsten O.; Schmidt, Helena; Schmidt, Reinhold; Senft, Andrea; Smith, Albert V.; Spector, Timothy D.; Surakka, Ida; Svento, Rauli; Terracciano, Antonio; Tikkanen, Emmi; van Duijn, Cornelia M.; Viikari, Jorma; Völzke, Henry; Wichmann, H. -Erich; Wild, Philipp S.; Willems, Sara M.; Willemsen, Gonneke; van Rooij, Frank J. A.; Groenen, Patrick J. F.; Uitterlinden, André G.; Hofman, Albert; Thurik, A. Roy

2013-01-01

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg 2/σP 2 = 25%, h 2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases. PMID:23593239

Impact of a cis-associated gene expression SNP in 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance

PubMed Central

Li, Ming; Luo, Xiong-jian; Landén, Mikael; Bergen, Sarah E.; Hultman, Christina M.; Li, Xiao; Zhang, Wen; Yao, Yong-Gang; Zhang, Chen; Liu, Jiewei; Mattheisen, Manuel; Cichon, Sven; Mühleisen, Thomas W.; Degenhardt, Franziska A.; Nöthen, Markus M.; Schulze, Thomas G.; Grigoroiu-Serbanescu, Maria; Li, Hao; Fuller, Chris K.; Chen, Chunhui; Dong, Qi; Chen, Chuansheng; Jamain, Stéphane; Leboyer, Marion; Bellivier, Frank; Etain, Bruno; Kahn, Jean-Pierre; Henry, Chantal; Preisig, Martin; Kutalik, Zoltán; Castelao, Enrique; Wright, Adam; Mitchell, Philip B.; Fullerton, Janice M.; Schofield, Peter R.; Montgomery, Grant W.; Medland, Sarah E.; Gordon, Scott D.; Martin, Nicholas G.; Rietschel, Marcella; Liu, Chunyu; Kleinman, Joel E.; Hyde, Thomas M.; Weinberger, Daniel R.; Su, Bing

2016-01-01

Summary Bipolar disorder (BPD) is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for BPD among the expression quantitative trait loci (eQTL) in the brain. Aims We sought to assess the impact of eQTL variants on BPD risk by combining data from both BPD genome-wide association study (GWAS) and brain eQTL. Method To detect single-nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with BPD, we jointly analyzed data from a BPD GWAS (7,481 cases and 9,250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (N=5,775) and cognitive performance (N=342) among healthy subjects. Results Integrative analysis revealed a significant association between a brain eQTL rs6088662 in 20q11.22 and BPD (Log Bayes Factor=5.48; BPD p-val=5.85×10−5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and BPD susceptibility (p-val=3.54×10−8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy subjects. Conclusions Our findings suggest that 20q11.22 is likely a risk region for BPD, highlighting the informativeness of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex diseases such as BPD. PMID:26338991

Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

PubMed

Li, Ming; Luo, Xiong-jian; Landén, Mikael; Bergen, Sarah E; Hultman, Christina M; Li, Xiao; Zhang, Wen; Yao, Yong-Gang; Zhang, Chen; Liu, Jiewei; Mattheisen, Manuel; Cichon, Sven; Mühleisen, Thomas W; Degenhardt, Franziska A; Nöthen, Markus M; Schulze, Thomas G; Grigoroiu-Serbanescu, Maria; Li, Hao; Fuller, Chris K; Chen, Chunhui; Dong, Qi; Chen, Chuansheng; Jamain, Stéphane; Leboyer, Marion; Bellivier, Frank; Etain, Bruno; Kahn, Jean-Pierre; Henry, Chantal; Preisig, Martin; Kutalik, Zoltán; Castelao, Enrique; Wright, Adam; Mitchell, Philip B; Fullerton, Janice M; Schofield, Peter R; Montgomery, Grant W; Medland, Sarah E; Gordon, Scott D; Martin, Nicholas G; Rietschel, Marcella; Liu, Chunyu; Kleinman, Joel E; Hyde, Thomas M; Weinberger, Daniel R; Su, Bing

2016-02-01

Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain. We sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL. To detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals. Integrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85 × 10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54 × 10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals. Our findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder. © The Royal College of Psychiatrists 2016.

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Genetic constraints on wing pattern variation in Lycaeides butterflies: A case study on mapping complex, multifaceted traits in structured populations.

PubMed

Lucas, Lauren K; Nice, Chris C; Gompert, Zachariah

2018-03-13

Patterns of phenotypic variation within and among species can be shaped and constrained by trait genetic architecture. This is particularly true for complex traits, such as butterfly wing patterns, that consist of multiple elements. Understanding the genetics of complex trait variation across species boundaries is difficult, as it necessitates mapping in structured populations and can involve many loci with small or variable phenotypic effects. Here, we investigate the genetic architecture of complex wing pattern variation in Lycaeides butterflies as a case study of mapping multivariate traits in wild populations that include multiple nominal species or groups. We identify conserved modules of integrated wing pattern elements within populations and species. We show that trait covariances within modules have a genetic basis and thus represent genetic constraints that can channel evolution. Consistent with this, we find evidence that evolutionary changes in wing patterns among populations and species occur in the directions of genetic covariances within these groups. Thus, we show that genetic constraints affect patterns of biological diversity (wing pattern) in Lycaeides, and we provide an analytical template for similar work in other systems. © 2018 John Wiley & Sons Ltd.

Polygenic risk score analysis of pathologically confirmed Alzheimer disease.

PubMed

Escott-Price, Valentina; Myers, Amanda J; Huentelman, Matt; Hardy, John

2017-08-01

Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case-control series. Here, we apply the same analytic approaches to a pathological case-control series and show a predictive AUC of 84%. We suggest that this analysis has clinical utility and that there is limited room for further improvement using genetic data. Ann Neurol 2017;82:311-314. © 2017 American Neurological Association.

[Diabetes and predictive medicine--parallax of the present time].

PubMed

Rybka, J

2010-04-01

Predictive genetics uses genetic testing to estimate the risk in asymptomatic persons. Since in the case of multifactorial diseases predictive genetic analysis deals with findings which allow wider interpretation, it has a higher predictive value in expressly qualified diseases (monogenous) with high penetration compared to multifactorial (polygenous) diseases with high participation of environmental factors. In most "civilisation" (multifactorial) diseases including diabetes, heredity and environmental factors do not play two separate, independent roles. Instead, their interactions play a principal role. The new classification of diabetes is based on the implementation of not only ethiopathogenetic, but also genetic research. Diabetes mellitus type 1 (DM1T) is a polygenous multifactorial disease with the genetic component carrying about one half of the risk, the non-genetic one the other half. The study of the autoimmune nature of DM1T in connection with genetic analysis is going to bring about new insights in DM1T prediction. The author presents new pieces of knowledge on molecular genetics concerning certain specific types of diabetes. Issues relating to heredity in diabetes mellitus type 2 (DM2T) are even more complex. The disease has a polygenous nature, and the phenotype of a patient with DM2T, in addition to environmental factors, involves at least three, perhaps even tens of different genetic variations. At present, results at the genom-wide level appear to be most promising. The current concept of prediabetes is a realistic foundation for our prediction and prevention of DM2T. A multifactorial, multimarker approach based on our understanding of new pathophysiological factors of DM2T, tries to outline a "map" of prediabetes physiology, and if these tests are combined with sophisticated methods of genetic forecasting of DM2T, this may represent a significant step in our methodology of diabetes prediction. So far however, predictive genetics is limited by the interpretation of genetic predisposition and individualisation of the level of risk. There is no doubt that interpretation calls for co-operation with clinicians, while results of genetic analyses should presently be not uncritically overestimated. Predictive medicine, however, unquestionably fulfills the preventive focus of modern medicine, and genetic analysis is a perspective diagnostic method.

Mendelian randomisation analysis provides no evidence for a relationship between adult height and testicular cancer risk.

PubMed

Levy, M; Hall, D; Sud, A; Law, P; Litchfield, K; Dudakia, D; Haugen, T B; Karlsson, R; Reid, A; Huddart, R A; Grotmol, T; Wiklund, F; Houlston, R S; Turnbull, C

2017-09-01

Observational studies have suggested anthropometric traits, particularly increased height are associated with an elevated risk of testicular cancer (testicular germ cell tumour). However, there is an inconsistency between study findings, suggesting the possibility of the influence of confounding factors. To examine the association between anthropometric traits and testicular germ cell tumour using an unbiased approach, we performed a Mendelian randomisation study. We used genotype data from genome wide association studies of testicular germ cell tumour totalling 5518 cases and 19,055 controls. Externally weighted polygenic risk scores were created and used to evaluate associations with testicular germ cell tumour risk per one standard deviation (s.d) increase in genetically-defined adult height, adult BMI, adult waist hip ratio adjusted for BMI (WHRadjBMI), adult hip circumference adjusted for BMI (HIPadjBMI), adult waist circumference adjusted for BMI (WCadjBMI), birth weight (BW) and childhood obesity. Mendelian randomisation analysis did not demonstrate an association between any anthropometric trait and testicular germ cell tumour risk. In particular, despite good power, there was no global evidence for association between height and testicular germ cell tumour. However, three SNPs for adult height individually showed association with testicular germ cell tumour (rs4624820: OR = 1.47, 95% CI: 1.41-1.55, p = 2.7 × 10 -57 ; rs12228415: OR = 1.17, 95% CI: 1.11-1.22, p = 3.1 × 10 -10 ; rs7568069: OR = 1.13, 95% CI: 1.07-1.18, p = 1.1 × 10 -6 ). This Mendelian randomisation analysis, based on the largest testicular germ cell tumour genome wide association dataset to date, does not support a causal etiological association between anthropometric traits and testicular germ cell tumour aetiology. Our findings are more compatible with confounding by shared environmental factors, possibly related to prenatal growth with exposure to these risk factors occurring in utero. © 2017 American Society of Andrology and European Academy of Andrology.

The genetic basis of pectoralis major myopathies in modern broiler chicken lines.

PubMed

Bailey, Richard A; Watson, Kellie A; Bilgili, S F; Avendano, Santiago

2015-12-01

This is the first report providing estimates of the genetic basis of breast muscle myopathies (BMM) and their relationship with growth and yield in broiler chickens. In addition, this paper addresses the hypothesis that genetic selection for increase breast yield has contributed to the onset of BMM. Data were analyzed from ongoing recording of BMM within the Aviagen breeding program. This study focused on three BMM: deep pectoral myopathy (DPM; binary trait), white striping (WS; 4 categories) and wooden breast (WB; 3 categories). Data from two purebred commercial broiler lines (A and B) were utilized providing greater than 40,000 meat quality records per line. The difference in selection history between these two lines has resulted in contrasting breast yield (BY): 29% for Line A and 21% for Line B. Data were analyzed to estimate genetic parameters using a multivariate animal model including six traits: body weight (BW), processing body weight (PW), BY, DPM, WB, and WS, in addition to the appropriate fixed effects and permanent environmental effect of the dam. Results indicate similar patterns of heritability and genetic correlations for the two lines. Heritabilities (h2) of BW, PW and BY ranged from 0.271-0.418; for DPM and WB h2<0.1; and for WS h2≤0.338. Genetic correlations between the BMM and BW, PW, or BY were ≤0.132 in Line A and ≤0.248 in Line B. This paper demonstrates the polygenic nature of these traits and the low genetic relationships with BW, PW, and BY, which facilitates genetic improvement across all traits in a balanced breeding program. It also highlights the importance of understanding the environmental and/or management factors that contribute greater than 65% of the variance in the incidence of white striping of breast muscle and more than 90% of the variance of the incidence of wooden breast and deep pectoral myopathy in broiler chickens. © The Author 2015. Published by Oxford University Press on behalf of Poultry Science Association.

Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity

PubMed Central

Wang, Hui; Drake, Thomas A; Lusis, Aldons J

2006-01-01

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE−/−) background. This BXH.ApoE−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits. PMID:16462940

Progress of genome wide association study in domestic animals

PubMed Central

2012-01-01

Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described. PMID:22958308

Genetic variations associated with six-white-point coat pigmentation in Diannan small-ear pigs

PubMed Central

Lü, Meng-Die; Han, Xu-Man; Ma, Yun-Fei; Irwin, David M.; Gao, Yun; Deng, Jia-Kun; Adeola, Adeniyi C.; Xie, Hai-Bing; Zhang, Ya-Ping

2016-01-01

A common phenotypic difference among domestic animals is variation in coat color. Six-white-point is a pigmentation pattern observed in varying pig breeds, which seems to have evolved through several different mechanistic pathways. Herein, we re-sequenced whole genomes of 31 Diannan small-ear pigs from China and found that the six-white-point coat color in Diannan small-ear pigs is likely regulated by polygenic loci, rather than by the MC1R locus. Strong associations were observed at three loci (EDNRB, CNTLN, and PINK1), which explain about 20 percent of the total coat color variance in the Diannan small-ear pigs. We found a mutation that is highly differentiated between six-white-point and black Diannan small-ear pigs, which is located in a conserved noncoding sequence upstream of the EDNRB gene and is a putative binding site of the CEBPB protein. This study advances our understanding of coat color evolution in Diannan small-ear pigs and expands our traditional knowledge of coat color being a monogenic trait. PMID:27270507

Characteristics of human infection with avian influenza viruses and development of new antiviral agents

PubMed Central

Liu, Qiang; Liu, Dong-ying; Yang, Zhan-qiu

2013-01-01

Since 1997, several epizootic avian influenza viruses (AIVs) have been transmitted to humans, causing diseases and even deaths. The recent emergence of severe human infections with AIV (H7N9) in China has raised concerns about efficient interpersonal viral transmission, polygenic traits in viral pathogenicity and the management of newly emerging strains. The symptoms associated with viral infection are different in various AI strains: H5N1 and newly emerged H7N9 induce severe pneumonia and related complications in patients, while some H7 and H9 subtypes cause only conjunctivitis or mild respiratory symptoms. The virulence and tissue tropism of viruses as well as the host responses contribute to the pathogenesis of human AIV infection. Several preventive and therapeutic approaches have been proposed to combat AIV infection, including antiviral drugs such as M2 inhibitors, neuraminidase inhibitors, RNA polymerase inhibitors, attachment inhibitors and signal-transduction inhibitors etc. In this article, we summarize the recent progress in researches on the epidemiology, clinical features, pathogenicity determinants, and available or potential antivirals of AIV. PMID:24096642

Mate choice theory and the mode of selection in sexual populations.

PubMed

Carson, Hampton L

2003-05-27

Indirect new data imply that mate and/or gamete choice are major selective forces driving genetic change in sexual populations. The system dictates nonrandom mating, an evolutionary process requiring both revised genetic theory and new data on heritability of characters underlying Darwinian fitness. Successfully reproducing individuals represent rare selections from among vigorous, competing survivors of preadult natural selection. Nonrandom mating has correlated demographic effects: reduced effective population size, inbreeding, low gene flow, and emphasis on deme structure. Characters involved in choice behavior at reproduction appear based on quantitative trait loci. This variability serves selection for fitness within the population, having only an incidental relationship to the origin of genetically based reproductive isolation between populations. The claim that extensive hybridization experiments with Drosophila indicate that selection favors a gradual progression of "isolating mechanisms" is flawed, because intra-group random mating is assumed. Over deep time, local sexual populations are strong, independent genetic systems that use rich fields of variable polygenic components of fitness. The sexual reproduction system thus particularizes, in small subspecific populations, the genetic basis of the grand adaptive sweep of selective evolutionary change, much as Darwin proposed.

Minor Allele Frequency Changes the Nature of Genotype by Environment Interactions.

PubMed

Verhulst, Brad; Neale, Michael C

2016-09-01

In the classical twin study, phenotypic variation is often partitioned into additive genetic (A), common (C) and specific environment (E) components. From genetical theory, the outcome of genotype by environment interaction is expected to inflate A when the interacting factor is shared (i.e., C) between the members of a twin pair. We show that estimates of both A and C can be inflated. When the shared interacting factor changes the size of the difference between homozygotes' means, the expected sibling or DZ twin correlation is .5 if and only if the minor allele frequency (MAF) is .5; otherwise the expected DZ correlation is greater than this value, consistent (and confounded) with some additional effect of C. This result is considered in the light of the distribution of minor allele frequencies for polygenic traits. Also discussed is whether such interactions take place at the locus level or affect an aggregated biological structure or system. Interactions with structures or endophenotypes that result from the aggregated effects of many loci will generally emerge as part of the A estimate.

Interplay between Schizophrenia Polygenic Risk Score and Childhood Adversity in First-Presentation Psychotic Disorder: A Pilot Study

PubMed Central

Trotta, Antonella; Iyegbe, Conrad; Di Forti, Marta; Sham, Pak C.; Campbell, Desmond D.; Cherny, Stacey S.; Mondelli, Valeria; Aitchison, Katherine J.; Murray, Robin M.

2016-01-01

A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to number or severity of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing genetic vulnerability. Research on gene-environment interaction in psychosis has primarily focused on candidate genes, although the genetic effects are now known to be polygenic. This pilot study investigated whether the effect of childhood adversity on psychosis is moderated by the polygenic risk score for schizophrenia (PRS). Data were utilised from the Genes and Psychosis (GAP) study set in South London, UK. The GAP sample comprises 285 first-presentation psychosis cases and 256 unaffected controls with information on childhood adversity. We studied only white subjects (80 cases and 110 controls) with PRS data, as the PRS has limited predictive ability in patients of African ancestry. The occurrence of childhood adversity was assessed with the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) and the PRS was based on genome-wide meta-analysis results for schizophrenia from the Psychiatric Genomics Consortium. Higher schizophrenia PRS and childhood adversities each predicted psychosis status. Nevertheless, no evidence was found for interaction as departure from additivity, indicating that the effect of polygenic risk scores on psychosis was not increased in the presence of a history of childhood adversity. These findings are compatible with a multifactorial threshold model in which both genetic liability and exposure to environmental risk contribute independently to the etiology of psychosis. PMID:27648571

Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity.

PubMed

Harrisson, Katherine A; Amish, Stephen J; Pavlova, Alexandra; Narum, Shawn R; Telonis-Scott, Marina; Rourke, Meaghan L; Lyon, Jarod; Tonkin, Zeb; Gilligan, Dean M; Ingram, Brett A; Lintermans, Mark; Gan, Han Ming; Austin, Christopher M; Luikart, Gordon; Sunnucks, Paul

2017-11-01

Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene-environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired-end restriction site-associated DNA sequencing data (6,605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene-association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature- and precipitation-related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies. © 2017 John Wiley & Sons Ltd.

Association Between Substance Use Disorder and Polygenic Liability to Schizophrenia.

PubMed

Hartz, Sarah M; Horton, Amy C; Oehlert, Mary; Carey, Caitlin E; Agrawal, Arpana; Bogdan, Ryan; Chen, Li-Shiun; Hancock, Dana B; Johnson, Eric O; Pato, Carlos N; Pato, Michele T; Rice, John P; Bierut, Laura J

2017-11-15

There are high levels of comorbidity between schizophrenia and substance use disorder, but little is known about the genetic etiology of this comorbidity. We tested the hypothesis that shared genetic liability contributes to the high rates of comorbidity between schizophrenia and substance use disorder. To do this, polygenic risk scores for schizophrenia derived from a large meta-analysis by the Psychiatric Genomics Consortium were computed in three substance use disorder datasets: the Collaborative Genetic Study of Nicotine Dependence (ascertained for tobacco use disorder; n = 918 cases; 988 control subjects), the Collaborative Study on the Genetics of Alcoholism (ascertained for alcohol use disorder; n = 643 cases; 384 control subjects), and the Family Study of Cocaine Dependence (ascertained for cocaine use disorder; n = 210 cases; 317 control subjects). Phenotypes were harmonized across the three datasets and standardized analyses were performed. Genome-wide genotypes were imputed to the 1000 Genomes reference panel. In each individual dataset and in the mega-analysis, strong associations were observed between any substance use disorder diagnosis and the polygenic risk score for schizophrenia (mega-analysis pseudo-R 2 range 0.8-3.7%; minimum p = 4 × 10 -23 ). These results suggest that comorbidity between schizophrenia and substance use disorder is partially attributable to shared polygenic liability. This shared liability is most consistent with a general risk for substance use disorder rather than specific risks for individual substance use disorders and adds to increasing evidence of a blurred boundary between schizophrenia and substance use disorder. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

PubMed

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

E-Index for Differentiating Complex Dynamic Traits

PubMed Central

Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

2016-01-01

While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait.

PubMed

Maurer, Matthew J; Sutardja, Lawrence; Pinel, Dominic; Bauer, Stefan; Muehlbauer, Amanda L; Ames, Tyler D; Skerker, Jeffrey M; Arkin, Adam P

2017-03-17

Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

Epigenetic Modifications in Essential Hypertension

PubMed Central

Wise, Ingrid A.; Charchar, Fadi J.

2016-01-01

Essential hypertension (EH) is a complex, polygenic condition with no single causative agent. Despite advances in our understanding of the pathophysiology of EH, hypertension remains one of the world’s leading public health problems. Furthermore, there is increasing evidence that epigenetic modifications are as important as genetic predisposition in the development of EH. Indeed, a complex and interactive genetic and environmental system exists to determine an individual’s risk of EH. Epigenetics refers to all heritable changes to the regulation of gene expression as well as chromatin remodelling, without involvement of nucleotide sequence changes. Epigenetic modification is recognized as an essential process in biology, but is now being investigated for its role in the development of specific pathologic conditions, including EH. Epigenetic research will provide insights into the pathogenesis of blood pressure regulation that cannot be explained by classic Mendelian inheritance. This review concentrates on epigenetic modifications to DNA structure, including the influence of non-coding RNAs on hypertension development. PMID:27023534

Effects of Schizophrenia Polygenic Risk Scores on Brain Activity and Performance During Working Memory Subprocesses in Healthy Young Adults.

PubMed

Miller, Jacob A; Scult, Matthew A; Conley, Emily Drabant; Chen, Qiang; Weinberger, Daniel R; Hariri, Ahmad R

2018-06-06

Recent work has begun to shed light on the neural correlates and possible mechanisms of polygenic risk for schizophrenia. Here, we map a schizophrenia polygenic risk profile score (PRS) based on genome-wide association study significant loci onto variability in the activity and functional connectivity of a frontoparietal network supporting the manipulation versus maintenance of information during a numerical working memory (WM) task in healthy young adults (n = 99, mean age = 19.8). Our analyses revealed that higher PRS was associated with hypoactivity of the dorsolateral prefrontal cortex (dlPFC) during the manipulation but not maintenance of information in WM (r2 = .0576, P = .018). Post hoc analyses revealed that PRS-modulated dlPFC hypoactivity correlated with faster reaction times during WM manipulation (r2 = .0967, P = .002), and faster processing speed (r2 = .0967, P = .003) on a separate behavioral task. These PRS-associated patterns recapitulate dlPFC hypoactivity observed in patients with schizophrenia during central executive manipulation of information in WM on this task.

Multilocus genetic profile in dopaminergic pathway modulates the striatum and working memory.

PubMed

Wang, Chao; Liu, Bing; Zhang, Xiaolong; Cui, Yue; Yu, Chunshui; Jiang, Tianzi

2018-03-29

Dopamine is critical in pathophysiology and therapy of schizophrenia. Many studies have reported altered dopaminergic activity in the dorsal but not ventral striatum in schizophrenia. Based on the largest genome-wide association study of schizophrenia to date, we calculated the polygenic risk score (PGRS) of each subject in a healthy general group, including all variations in the set of functionally related genes involved in dopamine neurotransmitter system. We aimed to test whether the genetic variations in the dopaminergic pathway that have been identified as associated with schizophrenia are related to the function of the striatum and to working memory. We found that a higher PGRS was significantly associated with impairment in working memory. Moreover, resting-state functional connectivity analysis revealed that as the polygenic risk score increased, the connections between left putamen and caudate and the default mode network grew stronger, while the connections with the fronto-parietal network grew weaker. Our findings may shed light on the biological mechanism underlying the "dopamine hypothesis" of schizophrenia and provide some implications regarding the polygenic effects on the dopaminergic activity in the risk for schizophrenia.

The transformative potential of an integrative approach to pregnancy.

PubMed

Eidem, Haley R; McGary, Kriston L; Capra, John A; Abbot, Patrick; Rokas, Antonis

2017-09-01

Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies. We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy. We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions. We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate Qst–Fst Comparisons: A Neutrality Test for the Evolution of the G Matrix in Structured Populations

PubMed Central

Martin, Guillaume; Chapuis, Elodie; Goudet, Jérôme

2008-01-01

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Qst–Fst) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2Fst/(1 − Fst)G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2Fst/(1 − Fst)] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Qst–Fst comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions. PMID:18245845

Identification of Promising Mutants Associated with Egg Production Traits Revealed by Genome-Wide Association Study.

PubMed

Yuan, Jingwei; Sun, Congjiao; Dou, Taocun; Yi, Guoqiang; Qu, LuJiang; Qu, Liang; Wang, Kehua; Yang, Ning

2015-01-01

Egg number (EN), egg laying rate (LR) and age at first egg (AFE) are important production traits related to egg production in poultry industry. To better understand the knowledge of genetic architecture of dynamic EN during the whole laying cycle and provide the precise positions of associated variants for EN, LR and AFE, laying records from 21 to 72 weeks of age were collected individually for 1,534 F2 hens produced by reciprocal crosses between White Leghorn and Dongxiang Blue-shelled chicken, and their genotypes were assayed by chicken 600 K Affymetrix high density genotyping arrays. Subsequently, pedigree and SNP-based genetic parameters were estimated and a genome-wide association study (GWAS) was conducted on EN, LR and AFE. The heritability estimates were similar between pedigree and SNP-based estimates varying from 0.17 to 0.36. In the GWA analysis, we identified nine genome-wide significant loci associated with EN of the laying periods from 21 to 26 weeks, 27 to 36 weeks and 37 to 72 weeks. Analysis of GTF2A1 and CLSPN suggested that they influenced the function of ovary and uterus, and may be considered as relevant candidates. The identified SNP rs314448799 for accumulative EN from 21 to 40 weeks on chromosome 5 created phenotypic differences of 6.86 eggs between two homozygous genotypes, which could be potentially applied to the molecular breeding for EN selection. Moreover, our finding showed that LR was a moderate polygenic trait. The suggestive significant region on chromosome 16 for AFE suggested the relationship between sex maturity and immune in the current population. The present study comprehensively evaluates the role of genetic variants in the development of egg laying. The findings will be helpful to investigation of causative genes function and future marker-assisted selection and genomic selection in chickens.

Genomic Trajectories to Desiccation Resistance: Convergence and Divergence Among Replicate Selected Drosophila Lines

PubMed Central

Griffin, Philippa C.; Hangartner, Sandra B.; Fournier-Level, Alexandre; Hoffmann, Ary A.

2017-01-01

Adaptation to environmental stress is critical for long-term species persistence. With climate change and other anthropogenic stressors compounding natural selective pressures, understanding the nature of adaptation is as important as ever in evolutionary biology. In particular, the number of alternative molecular trajectories available for an organism to reach the same adaptive phenotype remains poorly understood. Here, we investigate this issue in a set of replicated Drosophila melanogaster lines selected for increased desiccation resistance—a classical physiological trait that has been closely linked to Drosophila species distributions. We used pooled whole-genome sequencing (Pool-Seq) to compare the genetic basis of their selection responses, using a matching set of replicated control lines for characterizing laboratory (lab-)adaptation, as well as the original base population. The ratio of effective population size to census size was high over the 21 generations of the experiment at 0.52–0.88 for all selected and control lines. While selected SNPs in replicates of the same treatment (desiccation-selection or lab-adaptation) tended to change frequency in the same direction, suggesting some commonality in the selection response, candidate SNP and gene lists often differed among replicates. Three of the five desiccation-selection replicates showed significant overlap at the gene and network level. All five replicates showed enrichment for ovary-expressed genes, suggesting maternal effects on the selected trait. Divergence between pairs of replicate lines for desiccation-candidate SNPs was greater than between pairs of control lines. This difference also far exceeded the divergence between pairs of replicate lines for neutral SNPs. Overall, while there was overlap in the direction of allele frequency changes and the network and functional categories affected by desiccation selection, replicates showed unique responses at all levels, likely reflecting hitchhiking effects, and highlighting the challenges in identifying candidate genes from these types of experiments when traits are likely to be polygenic. PMID:28007884

Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes.

PubMed

Correa, Katharina; Lhorente, Jean P; López, María E; Bassini, Liane; Naswa, Sudhir; Deeb, Nader; Di Genova, Alex; Maass, Alejandro; Davidson, William S; Yáñez, José M

2015-10-24

Pisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon. 2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested. Genome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen. Due to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array.

[Genome-wide association study for adolescent idiopathic scoliosis].

PubMed

Ogura, Yoji; Kou, Ikuyo; Scoliosis, Japan; Matsumoto, Morio; Watanabe, Kota; Ikegawa, Shiro

2016-04-01

Adolescent idiopathic scoliosis(AIS)is a polygenic disease. Genome-wide association studies(GWASs)have been performed for a lot of polygenic diseases. For AIS, we conducted GWAS and identified the first AIS locus near LBX1. After the discovery, we have extended our study by increasing the numbers of subjects and SNPs. In total, our Japanese GWAS has identified four susceptibility genes. GWASs for AIS have also been performed in the USA and China, which identified one and three susceptibility genes, respectively. Here we review GWASs in Japan and abroad and functional analysis to clarify the pathomechanism of AIS.

Histocompatibility antigens and genetic control of the immune response in guinea-pigs. V. Evidence from further breeding studies for the polygenic control of the cellular immune response to structurally unrelated antigens in the guinea-pig.

PubMed

Geczy, A F; de Weck, A L

1977-10-01

Further breeding studies were carried out to investigate the polygenic control of the cellular immune response in the guinea-pig to low doses of aspirin anhydride (ASAN), penicilloylated bovine immunoglobulin (BPO-BGG) and to the multi-chain copolymer (T, G)-A-L. Although responsiveness to these three antigens is controlled by three independently segregating loci, at least one gene required for these responses is linked to the strain 13 haplotype.

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle.

PubMed

Fang, Lingzhao; Sørensen, Peter; Sahana, Goutam; Panitz, Frank; Su, Guosheng; Zhang, Shengli; Yu, Ying; Li, Bingjie; Ma, Li; Liu, George; Lund, Mogens Sandø; Thomsen, Bo

2018-06-19

MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15 million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P < 0.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

High-resolution genetic mapping of allelic variants associated with cell wall chemistry in Populus.

PubMed

Muchero, Wellington; Guo, Jianjun; DiFazio, Stephen P; Chen, Jin-Gui; Ranjan, Priya; Slavov, Gancho T; Gunter, Lee E; Jawdy, Sara; Bryan, Anthony C; Sykes, Robert; Ziebell, Angela; Klápště, Jaroslav; Porth, Ilga; Skyba, Oleksandr; Unda, Faride; El-Kassaby, Yousry A; Douglas, Carl J; Mansfield, Shawn D; Martin, Joel; Schackwitz, Wendy; Evans, Luke M; Czarnecki, Olaf; Tuskan, Gerald A

2015-01-23

QTL cloning for the discovery of genes underlying polygenic traits has historically been cumbersome in long-lived perennial plants like Populus. Linkage disequilibrium-based association mapping has been proposed as a cloning tool, and recent advances in high-throughput genotyping and whole-genome resequencing enable marker saturation to levels sufficient for association mapping with no a priori candidate gene selection. Here, multiyear and multienvironment evaluation of cell wall phenotypes was conducted in an interspecific P. trichocarpa x P. deltoides pseudo-backcross mapping pedigree and two partially overlapping populations of unrelated P. trichocarpa genotypes using pyrolysis molecular beam mass spectrometry, saccharification, and/ or traditional wet chemistry. QTL mapping was conducted using a high-density genetic map with 3,568 SNP markers. As a fine-mapping approach, chromosome-wide association mapping targeting a QTL hot-spot on linkage group XIV was performed in the two P. trichocarpa populations. Both populations were genotyped using the 34 K Populus Infinium SNP array and whole-genome resequencing of one of the populations facilitated marker-saturation of candidate intervals for gene identification. Five QTLs ranging in size from 0.6 to 1.8 Mb were mapped on linkage group XIV for lignin content, syringyl to guaiacyl (S/G) ratio, 5- and 6-carbon sugars using the mapping pedigree. Six candidate loci exhibiting significant associations with phenotypes were identified within QTL intervals. These associations were reproducible across multiple environments, two independent genotyping platforms, and different plant growth stages. cDNA sequencing for allelic variants of three of the six loci identified polymorphisms leading to variable length poly glutamine (PolyQ) stretch in a transcription factor annotated as an ANGUSTIFOLIA C-terminus Binding Protein (CtBP) and premature stop codons in a KANADI transcription factor as well as a protein kinase. Results from protoplast transient expression assays suggested that each of the polymorphisms conferred allelic differences in the activation of cellulose, hemicelluloses, and lignin pathway marker genes. This study illustrates the utility of complementary QTL and association mapping as tools for gene discovery with no a priori candidate gene selection. This proof of concept in a perennial organism opens up opportunities for discovery of novel genetic determinants of economically important but complex traits in plants.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

A Meta-Assembly of Selection Signatures in Cattle

PubMed Central

Randhawa, Imtiaz A. S.; Khatkar, Mehar S.; Thomson, Peter C.; Raadsma, Herman W.

2016-01-01

Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species. PMID:27045296

PLASMA LIPIDOMIC PROFILE SIGNATURE OF HYPERTENSION IN MEXICAN AMERICAN FAMILIES: SPECIFIC ROLE OF DIACYLGLYCEROLS

PubMed Central

Kulkarni, Hemant; Meikle, Peter J.; Mamtani, Manju; Weir, Jacquelyn M.; Barlow, Christopher K.; Jowett, Jeremy B.; Bellis, Claire; Dyer, Thomas D.; Johnson, Matthew P.; Rainwater, David L.; Almasy, Laura; Mahaney, Michael C.; Commuzzie, Anthony G.; Blangero, John; Curran, Joanne E.

2013-01-01

Both as a component of metabolic syndrome and as an independent entity, hypertension poses a continued challenge with regard to its diagnosis, pathogenesis and treatment. Previous studies have documented connections between hypertension and indicators of lipid metabolism. Novel technologies like plasma lipidomic profiling promise a better understanding of disorders in which there is a derangement of the lipid metabolism. However, association of plasma lipidomic profiles with hypertension in a high-risk population, like Mexican Americans, has not been evaluated before. Using the rich data and sample resource from the ongoing San Antonio Family Heart Study, we conducted plasma lipidomic profiling by combining high performance liquid chromatography with tandem mass spectroscopy to characterize 319 lipid species in 1192 individuals from 42 large and extended Mexican American families. Robust statistical analyses employing polygenic regression models, liability threshold models and bivariate trait analyses implemented in the SOLAR software were conducted after accounting for obesity, insulin resistance and relative abundance of various lipoprotein fractions. Diacylglycerols in general and the DG 16:0/22:5 and DG 16:0/22:6 lipid species in particular were significantly associated with systolic, diastolic and mean arterial pressures as well as liability of incident hypertension measured during 7767.42 person-years of follow-up. Four lipid species, including the DG 16:0/22:5 and DG 16:0/22:6 species, showed significant genetic correlations with the liability of hypertension in bivariate trait analyses. Our results demonstrate the value of plasma lipidomic profiling in the context of hypertension and identify disturbance of diacyglycerol metabolism as an independent biomarker of hypertension. PMID:23798346

Integrative approaches for large-scale transcriptome-wide association studies

PubMed Central

Gusev, Alexander; Ko, Arthur; Shi, Huwenbo; Bhatia, Gaurav; Chung, Wonil; Penninx, Brenda W J H; Jansen, Rick; de Geus, Eco JC; Boomsma, Dorret I; Wright, Fred A; Sullivan, Patrick F; Nikkola, Elina; Alvarez, Marcus; Civelek, Mete; Lusis, Aldons J.; Lehtimäki, Terho; Raitoharju, Emma; Kähönen, Mika; Seppälä, Ilkka; Raitakari, Olli T.; Kuusisto, Johanna; Laakso, Markku; Price, Alkes L.; Pajukanta, Päivi; Pasaniuc, Bogdan

2016-01-01

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. Here, we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated to complex traits. We leverage expression imputation to perform a transcriptome wide association scan (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits. PMID:26854917

Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data

PubMed Central

Gibson, J; Russ, T C; Adams, M J; Clarke, T-K; Howard, D M; Hall, L S; Fernandez-Pujals, A M; Wigmore, E M; Hayward, C; Davies, G; Murray, A D; Smith, B H; Porteous, D J; Deary, I J; McIntosh, A M

2017-01-01

Major depressive disorder (MDD) and Alzheimer's disease (AD) are both common in older age and frequently co-occur. Numerous phenotypic studies based on clinical diagnoses suggest that a history of depression increases risk of subsequent AD, although the basis of this relationship is uncertain. Both illnesses are polygenic, and shared genetic risk factors could explain some of the observed association. We used genotype data to test whether MDD and AD have an overlapping polygenic architecture in two large population-based cohorts, Generation Scotland's Scottish Family Health Study (GS:SFHS; N=19 889) and UK Biobank (N=25 118), and whether age of depression onset influences any relationship. Using two complementary techniques, we found no evidence that the disorders are influenced by common genetic variants. Using linkage disequilibrium score regression with genome-wide association study (GWAS) summary statistics from the International Genomics of Alzheimer's Project, we report no significant genetic correlation between AD and MDD (rG=−0.103, P=0.59). Polygenic risk scores (PRS) generated using summary data from International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium were used to assess potential pleiotropy between the disorders. PRS for MDD were nominally associated with participant-recalled AD family history in GS:SFHS, although this association did not survive multiple comparison testing. AD PRS were not associated with depression status or late-onset depression, and a survival analysis showed no association between age of depression onset and genetic risk for AD. This study found no evidence to support a common polygenic structure for AD and MDD, suggesting that the comorbidity of these disorders is not explained by common genetic variants. PMID:28418403

Is Multifactorial Sex Determination in the House Fly, Musca domestica (L.), Stable Over Time?

PubMed

Meisel, Richard P; Davey, Taira; Son, Jae Hak; Gerry, Alec C; Shono, Toshio; Scott, Jeffrey G

2016-01-01

Sex determination pathways evolve rapidly, usually because of turnover of master regulatory genes at the top of the developmental pathway. Polygenic sex determination is expected to be a transient state between ancestral and derived conditions. However, polygenic sex determination has been observed in numerous animal species, including the house fly, Musca domestica House fly males carry a male-determining factor (M) that can be located on any chromosome, and an individual male may have multiple M factors. Females lack M and/or have a dominant allele of the Md-tra gene (Md-tra D ) that acts as a female-determining locus even in the presence of multiple copies of M. We found the frequency and linkage of M in house flies collected in Chino, CA (USA) was relatively unchanged between 1982 and 2014. The frequency of females with Md-tra D in the 2014 collection was 33.6% (n = 140). Analysis of these results, plus previously published data, revealed a strong correlation between the frequencies of Md-tra D and multiple M males, and we find that these populations are expected to have balanced sex ratios. We also find that fitness values that allow for the invasion and maintenance of multiple sex determining loci suggest that sexually antagonistic selection could be responsible for maintaining polygenic sex determination in house fly populations. The stability over time and equilibrium frequencies within populations suggest the house fly polygenic sex determination system is not in transition, and provide guidance for future investigations on the factors responsible for the polymorphism. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

MiR-137-derived polygenic risk: effects on cognitive performance in patients with schizophrenia and controls.

PubMed

Cosgrove, D; Harold, D; Mothersill, O; Anney, R; Hill, M J; Bray, N J; Blokland, G; Petryshen, T; Richards, A; Mantripragada, K; Owen, M; O'Donovan, M C; Gill, M; Corvin, A; Morris, D W; Donohoe, G

2017-01-24

Variants at microRNA-137 (MIR137), one of the most strongly associated schizophrenia risk loci identified to date, have been associated with poorer cognitive performance. As microRNA-137 is known to regulate the expression of ~1900 other genes, including several that are independently associated with schizophrenia, we tested whether this gene set was also associated with variation in cognitive performance. Our analysis was based on an empirically derived list of genes whose expression was altered by manipulation of MIR137 expression. This list was cross-referenced with genome-wide schizophrenia association data to construct individual polygenic scores. We then tested, in a sample of 808 patients and 192 controls, whether these risk scores were associated with altered performance on cognitive functions known to be affected in schizophrenia. A subgroup of healthy participants also underwent functional imaging during memory (n=108) and face processing tasks (n=83). Increased polygenic risk within the empirically derived miR-137 regulated gene score was associated with significantly lower performance on intelligence quotient, working memory and episodic memory. These effects were observed most clearly at a polygenic threshold of P=0.05, although significant results were observed at all three thresholds analyzed. This association was found independently for the gene set as a whole, excluding the schizophrenia-associated MIR137 SNP itself. Analysis of the spatial working memory fMRI task further suggested that increased risk score (thresholded at P=10 -5 ) was significantly associated with increased activation of the right inferior occipital gyrus. In conclusion, these data are consistent with emerging evidence that MIR137 associated risk for schizophrenia may relate to its broader downstream genetic effects.

Polygenic Risk Score for Alzheimer's Disease: Implications for Memory Performance and Hippocampal Volumes in Early Life.

PubMed

Axelrud, Luiza K; Santoro, Marcos L; Pine, Daniel S; Talarico, Fernanda; Gadelha, Ary; Manfro, Gisele G; Pan, Pedro M; Jackowski, Andrea; Picon, Felipe; Brietzke, Elisa; Grassi-Oliveira, Rodrigo; Bressan, Rodrigo A; Miguel, Eurípedes C; Rohde, Luis A; Hakonarson, Hakon; Pausova, Zdenka; Belangero, Sintia; Paus, Tomas; Salum, Giovanni A

2018-06-01

Alzheimer's disease is a heritable neurodegenerative disorder in which early-life precursors may manifest in cognition and brain structure. The authors evaluate this possibility by examining, in youths, associations among polygenic risk score for Alzheimer's disease, cognitive abilities, and hippocampal volume. Participants were children 6-14 years of age in two Brazilian cities, constituting the discovery (N=364) and replication samples (N=352). As an additional replication, data from a Canadian sample (N=1,029), with distinct tasks, MRI protocol, and genetic risk, were included. Cognitive tests quantified memory and executive function. Reading and writing abilities were assessed by standardized tests. Hippocampal volumes were derived from the Multiple Automatically Generated Templates (MAGeT) multi-atlas segmentation brain algorithm. Genetic risk for Alzheimer's disease was quantified using summary statistics from the International Genomics of Alzheimer's Project. Analyses showed that for the Brazilian discovery sample, each one-unit increase in z-score for Alzheimer's polygenic risk score significantly predicted a 0.185 decrement in z-score for immediate recall and a 0.282 decrement for delayed recall. Findings were similar for the Brazilian replication sample (immediate and delayed recall, β=-0.259 and β=-0.232, both significant). Quantile regressions showed lower hippocampal volumes bilaterally for individuals with high polygenic risk scores. Associations fell short of significance for the Canadian sample. Genetic risk for Alzheimer's disease may affect early-life cognition and hippocampal volumes, as shown in two independent samples. These data support previous evidence that some forms of late-life dementia may represent developmental conditions with roots in childhood. This result may vary depending on a sample's genetic risk and may be specific to some types of memory tasks.

A Polygenic Risk Score of glutamatergic SNPs associated with schizophrenia predicts attentional behavior and related brain activity in healthy humans.

PubMed

Rampino, Antonio; Taurisano, Paolo; Fanelli, Giuseppe; Attrotto, Mariateresa; Torretta, Silvia; Antonucci, Linda Antonella; Miccolis, Grazia; Pergola, Giulio; Ursini, Gianluca; Maddalena, Giancarlo; Romano, Raffaella; Masellis, Rita; Di Carlo, Pasquale; Pignataro, Patrizia; Blasi, Giuseppe; Bertolino, Alessandro

2017-09-01

Multiple genetic variations impact on risk for schizophrenia. Recent analyses by the Psychiatric Genomics Consortium (PGC2) identified 128 SNPs genome-wide associated with the disorder. Furthermore, attention and working memory deficits are core features of schizophrenia, are heritable and have been associated with variation in glutamatergic neurotransmission. Based on this evidence, in a sample of healthy volunteers, we used SNPs associated with schizophrenia in PGC2 to construct a Polygenic-Risk-Score (PRS) reflecting the cumulative risk for schizophrenia, along with a Polygenic-Risk-Score including only SNPs related to genes implicated in glutamatergic signaling (Glu-PRS). We performed Factor Analysis for dimension reduction of indices of cognitive performance. Furthermore, both PRS and Glu-PRS were used as predictors of cognitive functioning in the domains of Attention, Speed of Processing and Working Memory. The association of the Glu-PRS on brain activity during the Variable Attention Control (VAC) task was also explored. Finally, in a second independent sample of healthy volunteers we sought to confirm the association between the Glu-PRS and both performance in the domain of Attention and brain activity during the VAC.We found that performance in Speed of Processing and Working Memory was not associated with any of the Polygenic-Risk-Scores. The Glu-PRS, but not the PRS was associated with Attention and brain activity during the VAC. The specific effects of Glu-PRS on Attention and brain activity during the VAC were also confirmed in the replication sample.Our results suggest a pathway specificity in the relationship between genetic risk for schizophrenia, the associated cognitive dysfunction and related brain processing. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Genetic liability for schizophrenia predicts risk of immune disorders.

PubMed

Stringer, Sven; Kahn, René S; de Witte, Lot D; Ophoff, Roel A; Derks, Eske M

2014-11-01

Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between schizophrenia and three immune disorders and to compare with the overlap between schizophrenia and two disorders not primarily characterized by immune dysregulation: bipolar disorder and type 2 diabetes. We performed a polygenic risk score analysis using results from the schizophrenia Psychiatric GWAS consortium (PGC) (8922 cases and 9528 controls) and five Wellcome Trust Case Control Consortium (WTCCC) case samples as target cases: bipolar disorder (n=1998), type 1 diabetes (n=2000), Crohn's diseases (n=2005), rheumatoid arthritis (n=1999), and type 2 diabetes (n=1999). The WTCCC British Birth Cohort and National Blood Service samples (n=3004) were used as target controls. Additionally, we tested whether schizophrenia polygenic risk scores significantly differed between patients with immune disorder, bipolar disorder, and type 2 diabetes respectively. Polygenic risk scores for schizophrenia significantly predicted disease status in all three immune disorder samples (Nagelkerke-R(2) 1.1%-1.3%; p<0.05). The polygenic risk of schizophrenia in patients with immune disorders was significantly lower than in patients with bipolar disorder (Nagelkerke-R(2) 6.0%; p<0.05), but higher than in type 2 diabetes patients (Nagelkerke-R(2) 0.5%; p<0.05). Our results suggest that genetic factors are shared between schizophrenia and immune disorders. This contributes to an accumulating body of evidence that immune processes may play a role in the etiology of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Traumatic Stress Interacts With Bipolar Disorder Genetic Risk to Increase Risk for Suicide Attempts

PubMed Central

Wilcox, Holly C.; Fullerton, Janice M.; Glowinski, Anne L.; Benke, Kelly; Kamali, Masoud; Hulvershorn, Leslie A.; Stapp, Emma K.; Edenberg, Howard J.; Roberts, Gloria M.P.; Ghaziuddin, Neera; Fisher, Carrie; Brucksch, Christine; Frankland, Andrew; Toma, Claudio; Shaw, Alex D.; Kastelic, Elizabeth; Miller, Leslie; McInnis, Melvin G.; Mitchell, Philip B.; Nurnberger, John I.

2018-01-01

Objective Bipolar disorder (BD) is one of the most heritable psychiatric conditions and is associated with high suicide risk. To explore the reasons for this link, this study examined the interaction between traumatic stress and BD polygenic risk score in relation to suicidal ideation, suicide attempt, and nonsuicidal self-injury (NSSI) in adolescent and young adult offspring and relatives of persons with BD (BD-relatives) compared with adolescent and young adult offspring of individuals without psychiatric disorders (controls). Method Data were collected from 4 sites in the United States and 1 site in Australia from 2006 through 2012. Generalized estimating equation models were used to compare rates of ideation, attempts, and NSSI between BD-relatives (n = 307) and controls (n = 166) and to determine the contribution of demographic factors, traumatic stress exposure, lifetime mood or substance (alcohol/drug) use disorders, and BD polygenic risk score. Results After adjusting for demographic characteristics and mood and substance use disorders, BD-relatives were at increased risk for suicidal ideation and attempts but not for NSSI. Independent of BD-relative versus control status, demographic factors, or mood and substance use disorders, exposure to trauma within the past year (including bullying, sexual abuse, and domestic violence) was associated with suicide attempts (p = .014), and BD polygenic risk score was marginally associated with attempts (p = .061). Importantly, the interaction between BD polygenic risk score and traumatic event exposures was significantly associated with attempts, independent of demographics, relative versus control status, and mood and substance use disorders (p = .041). Conclusion BD-relatives are at increased risk for suicide attempts and ideation, especially if they are exposed to trauma and have evidence of increased genetic vulnerability. PMID:29173741

Polygenic Risk, Personality Dimensions, and Adolescent Alcohol Use Problems: A Longitudinal Study

PubMed Central

Li, James J.; Savage, Jeanne E.; Kendler, Kenneth S.; Hickman, Matthew; Mahedy, Liam; Macleod, John; Kaprio, Jaakko; Rose, Richard J.; Dick, Danielle M.

2017-01-01

Objective: Alcohol use problems are common during adolescence and can predict serious negative outcomes in adulthood, including substance dependence and psychopathology. The current study examines the notion that alcohol use problems are driven by polygenic influences and that genetic influences may indirectly affect alcohol use problems through multiple pathways of risk, including variations in personality. Method: We used a genome-wide approach to examine associations between genetic risk for alcohol use problems, personality dimensions, and adolescent alcohol use problems in two separate longitudinal population-based samples, the Finnish Twin Cohort (FinnTwin12) and the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants were 1,035 young adults from FinnTwin12 and 3,160 adolescents from ALSPAC. Polygenic risk scores (PRS) were calculated for ALSPAC using genome-wide association results (on alcohol dependence symptoms as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) from FinnTwin12. A parallel multiple mediator model was tested to examine whether the association between PRS and alcohol use problems assessed at age 16 could be explained by variations in personality dimensions assessed at age 13, including sensation seeking and negative emotionality. Results: PRS were marginally predictive of age 16 alcohol use problems; this association was partially mediated by sensation seeking. Polygenic variation underlying risk for alcohol use problems may directly influence the effects of sensation seeking, which in turn influence the development of alcohol use problems in later adolescence. Conclusions: These findings contribute to the increasing evidence regarding the salience of sensation seeking during early adolescence as a potential constituent in the risk pathway underlying the development of alcohol use problems. PMID:28499112

Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data.

PubMed

Gibson, J; Russ, T C; Adams, M J; Clarke, T-K; Howard, D M; Hall, L S; Fernandez-Pujals, A M; Wigmore, E M; Hayward, C; Davies, G; Murray, A D; Smith, B H; Porteous, D J; Deary, I J; McIntosh, A M

2017-04-18

Major depressive disorder (MDD) and Alzheimer's disease (AD) are both common in older age and frequently co-occur. Numerous phenotypic studies based on clinical diagnoses suggest that a history of depression increases risk of subsequent AD, although the basis of this relationship is uncertain. Both illnesses are polygenic, and shared genetic risk factors could explain some of the observed association. We used genotype data to test whether MDD and AD have an overlapping polygenic architecture in two large population-based cohorts, Generation Scotland's Scottish Family Health Study (GS:SFHS; N=19 889) and UK Biobank (N=25 118), and whether age of depression onset influences any relationship. Using two complementary techniques, we found no evidence that the disorders are influenced by common genetic variants. Using linkage disequilibrium score regression with genome-wide association study (GWAS) summary statistics from the International Genomics of Alzheimer's Project, we report no significant genetic correlation between AD and MDD (r G =-0.103, P=0.59). Polygenic risk scores (PRS) generated using summary data from International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium were used to assess potential pleiotropy between the disorders. PRS for MDD were nominally associated with participant-recalled AD family history in GS:SFHS, although this association did not survive multiple comparison testing. AD PRS were not associated with depression status or late-onset depression, and a survival analysis showed no association between age of depression onset and genetic risk for AD. This study found no evidence to support a common polygenic structure for AD and MDD, suggesting that the comorbidity of these disorders is not explained by common genetic variants.

Evaluation of polygenic cause in Korean patients with familial hypercholesterolemia - A study supported by Korean Society of Lipidology and Atherosclerosis.

PubMed

Kwon, Manjae; Han, Soo Min; Kim, Do-Il; Rhee, Moo-Yong; Lee, Byoung-Kwon; Ahn, Young Keun; Cho, Byung Ryul; Woo, Jeongtaek; Hur, Seung-Ho; Jeong, Jin-Ok; Jang, Yangsoo; Lee, Sang-Hak; Lee, Ji Hyun

2015-09-01

Familial hypercholesterolemia (FH) is an autosomal dominant disorder caused by mutations in LDLR, APOB, or PCSK9. Polygenicity is a plausible cause in mutation-negative FH patients based on LDL cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs) identified by the Global Lipids Genetics Consortium (GLGC). However, there are limited data regarding the polygenic cause of FH in Asians. We gathered data from 66 mutation-negative and 31 mutation-positive Korean FH patients, as well as from 2274 controls who participated in the Korean Health Examinee (HEXA) shared control study. We genotyped the patients for six GLGC SNPs and four East Asian LDL-C-associated SNPs and compared SNP scores among patient groups and controls. Weighted mean 6- and 4-SNP scores (0.67 [SD = 0.07] and 0.46 [0.11], respectively) were both significantly associated with LDL-C levels in controls (p = 2.1 × 10(-4), R(2) = 0.01 and p = 5.0 × 10(-12), R(2) = 0.02, respectively). Mutation-negative FH patients had higher 6-SNP (0.72 [0.07]) and 4-SNP (0.49 [0.08]) scores than controls (p = 1.8 × 10(-8) and p = 3.6 × 10(-3), respectively). We also observed higher scores in mutation-positive FH patients compared with controls, but the difference did not reach statistical significance. The present study demonstrates the utility of SNP score analysis for identifying polygenic FH in Korean patients by showing that small-effect common SNPs may cumulatively elevate LDL-C levels. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Sensitivity assessment of freshwater macroinvertebrates to pesticides using biological traits.

PubMed

Ippolito, A; Todeschini, R; Vighi, M

2012-03-01

Assessing the sensitivity of different species to chemicals is one of the key points in predicting the effects of toxic compounds in the environment. Trait-based predicting methods have proved to be extremely efficient for assessing the sensitivity of macroinvertebrates toward compounds with non specific toxicity (narcotics). Nevertheless, predicting the sensitivity of organisms toward compounds with specific toxicity is much more complex, since it depends on the mode of action of the chemical. The aim of this work was to predict the sensitivity of several freshwater macroinvertebrates toward three classes of plant protection products: organophosphates, carbamates and pyrethroids. Two databases were built: one with sensitivity data (retrieved, evaluated and selected from the U.S. Environmental Protection Agency ECOTOX database) and the other with biological traits. Aside from the "traditional" traits usually considered in ecological analysis (i.e. body size, respiration technique, feeding habits, etc.), multivariate analysis was used to relate the sensitivity of organisms to some other characteristics which may be involved in the process of intoxication. Results confirmed that, besides traditional biological traits, related to uptake capability (e.g. body size and body shape) some traits more related to particular metabolic characteristics or patterns have a good predictive capacity on the sensitivity to these kinds of toxic substances. For example, behavioral complexity, assumed as an indicator of nervous system complexity, proved to be an important predictor of sensitivity towards these compounds. These results confirm the need for more complex traits to predict effects of highly specific substances. One key point for achieving a complete mechanistic understanding of the process is the choice of traits, whose role in the discrimination of sensitivity should be clearly interpretable, and not only statistically significant.

Advanced complex trait analysis.

PubMed

Gray, A; Stewart, I; Tenesa, A

2012-12-01

The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance. We restructure the genetic relationship matrix (GRM) estimation phase of the code and introduce the highly optimized parallel Basic Linear Algebra Subprograms (BLAS) library combined with manual parallelization and optimization. We introduce the Linear Algebra PACKage (LAPACK) library into the restricted maximum likelihood (REML) analysis stage. For a test case with 8999 individuals and 279,435 single nucleotide polymorphisms (SNPs), we reduce the total runtime, using a compute node with two multi-core Intel Nehalem CPUs, from ∼17 h to ∼11 min. The source code is fully available under the GNU Public License, along with Linux binaries. For more information see http://www.epcc.ed.ac.uk/software-products/acta. a.gray@ed.ac.uk Supplementary data are available at Bioinformatics online.

Constitutional mechanisms of vulnerability and resilience to nicotine dependence

PubMed Central

Hiroi, N; Scott, D

2017-01-01

The core nature of nicotine dependence is evident in wide variations in how individuals become and remain smokers. Individuals with pre-existing behavioral traits are more likely to develop nicotine dependence and experience difficulty when attempting to quit. Many molecular factors likely contribute to individual variations in the development of nicotine dependence and behavioral traits in complex manners. However, the identification of such molecules has been hampered by the phenotypic complexity of nicotine dependence and the complex ways molecules affect elements of nicotine dependence. We hypothesize that nicotine dependence is, in part, a result of interactions between nicotine and pre-existing behavioral traits. This perspective suggests that the identification of the molecular bases of such pre-existing behavioral traits will contribute to the development of effective methods for reducing smoking dependence and for helping smokers to quit. PMID:19238150

The Nature of Nurture: Using a Virtual-Parent Design to Test Parenting Effects on Children's Educational Attainment in Genotyped Families.

PubMed

Bates, Timothy C; Maher, Brion S; Medland, Sarah E; McAloney, Kerrie; Wright, Margaret J; Hansell, Narelle K; Kendler, Kenneth S; Martin, Nicholas G; Gillespie, Nathan A

2018-04-01

Research on environmental and genetic pathways to complex traits such as educational attainment (EA) is confounded by uncertainty over whether correlations reflect effects of transmitted parental genes, causal family environments, or some, possibly interactive, mixture of both. Thus, an aggregate of thousands of alleles associated with EA (a polygenic risk score; PRS) may tap parental behaviors and home environments promoting EA in the offspring. New methods for unpicking and determining these causal pathways are required. Here, we utilize the fact that parents pass, at random, 50% of their genome to a given offspring to create independent scores for the transmitted alleles (conventional EA PRS) and a parental score based on alleles not transmitted to the offspring (EA VP_PRS). The formal effect of non-transmitted alleles on offspring attainment was tested in 2,333 genotyped twins for whom high-quality measures of EA, assessed at age 17 years, were available, and whose parents were also genotyped. Four key findings were observed. First, the EA PRS and EA VP_PRS were empirically independent, validating the virtual-parent design. Second, in this family-based design, children's own EA PRS significantly predicted their EA (β = 0.15), ruling out stratification confounds as a cause of the association of attainment with the EA PRS. Third, parental EA PRS predicted the SES environment parents provided to offspring (β = 0.20), and parental SES and offspring EA were significantly associated (β = 0.33). This would suggest that the EA PRS is at least as strongly linked to social competence as it is to EA, leading to higher attained SES in parents and, therefore, a higher experienced SES for children. In a full structural equation model taking account of family genetic relatedness across multiple siblings the non-transmitted allele effects were estimated at similar values; but, in this more complex model, confidence intervals included zero. A test using the forthcoming EA3 PRS may clarify this outcome. The virtual-parent method may be applied to clarify causality in other phenotypes where observational evidence suggests parenting may moderate expression of other outcomes, for instance in psychiatry.

Polygenic Risk, Appetite Traits, and Weight Gain in Middle Childhood: A Longitudinal Study.

PubMed

Steinsbekk, Silje; Belsky, Daniel; Guzey, Ismail Cuneyt; Wardle, Jane; Wichstrøm, Lars

2016-02-01

Genome-wide association studies have identified genetic risks for obesity. These genetic risks influence development of obesity partly by accelerating weight gain in childhood. Research is needed to identify mechanisms to inform intervention. Cross-sectional studies suggest appetite traits as a candidate mechanism. Longitudinal studies are needed to test whether appetite traits mediate genetic influences on children's weight gain. To test whether genetic risk for obesity predicts accelerated weight gain in middle childhood (ages 4-8 years) and whether genetic association with accelerated weight gain is mediated by appetite traits. Longitudinal study of a representative birth cohort at the Trondheim Early Secure Study, Trondheim, Norway, enrolled at age 4 years during 2007 to 2008, with follow-ups at ages 6 and 8 years. Participants were sampled from all children born in 2003 or 2004 who attended regular community health checkups for 4-year-olds (97.2% attendance; 82.0% consent rate, n = 2475). Nine hundred ninety-five children participated at age 4 years, 795 at age 6 years, and 699 at age 8 years. Analyses included 652 children with genotype, adiposity, and appetite data. Outcomes were body mass index and body-fat phenotypes measured from anthropometry (ages 4, 6, and 8 years) and bioelectrical impedance (ages 6 and 8 years). Genetic risk for obesity was measured using a genetic risk score composed of 32 single-nucleotide polymorphisms previously discovered in genome-wide association studies of adult body mass index. Appetite traits were measured at age 6 years with the Children's Eating Behavior Questionnaire. Of the 652 genotyped child participants, 323 (49.5%) were female, 58 (8.9%) were overweight, and 1 (0.2%) was obese. Children at higher genetic risk for obesity had higher baseline body mass index and fat mass compared with lower genetic risk peers, and they gained weight and fat mass more rapidly during follow-up. Each SD increase in genetic risk score was associated with a 0.22-point increase in BMI at age-4 baseline (for the intercept, unstandardized path coefficient B = 0.22 [95% CI, 0.06-0.38]; P = .008. Children with higher genetic risk scores also gained BMI points more rapidly from ages 4 to 6 years (B = 0.11 [95% CI, 0.03-0.20]; P = .01 ; β = 0.12) and from 6 to 8 years (B = 0.09 [95% CI, 0.00-0.19]; P = .05; β = 0.10), compared with their lower genetic risk peers. Children at higher genetic risk had higher levels of alleged obesogenic appetite traits than peers with lower genetic risk at age 6 years, but appetite traits did not mediate genetic associations with weight gain. The sum of the 5 indirect effects was B = -0.001 (95% CI, -0.02 -0.01); P = .86; β = 0.00. Genetic risk for obesity is associated with accelerated childhood weight gain. Interventions targeting childhood weight gain may provide one path to mitigating genetic risk. However, middle childhood appetite traits may not be a promising target for such interventions. Studies of early-childhood samples are needed to test whether appetite traits explain how genetic risks accelerate growth earlier in development.

Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

PubMed Central

Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

2012-01-01

Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

Enhancing genomic prediction with genome-wide association studies in multiparental maize populations

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits which have been validated with fine-mapping and functional analysis. Many sequence variants associated with complex traits in maize have small effects and low repeatability, howev...

New insights from monogenic diabetes for “common” type 2 diabetes

PubMed Central

Tallapragada, Divya Sri Priyanka; Bhaskar, Seema; Chandak, Giriraj R.

2015-01-01

Boundaries between monogenic and complex genetic diseases are becoming increasingly blurred, as a result of better understanding of phenotypes and their genetic determinants. This had a large impact on the way complex disease genetics is now being investigated. Starting with conventional approaches like familial linkage, positional cloning and candidate genes strategies, the scope of complex disease genetics has grown exponentially with scientific and technological advances in recent times. Despite identification of multiple loci harboring common and rare variants associated with complex diseases, interpreting and evaluating their functional role has proven to be difficult. Information from monogenic diseases, especially related to the intermediate traits associated with complex diseases comes handy. The significant overlap between traits and phenotypes of monogenic diseases with related complex diseases provides a platform to understand the disease biology better. In this review, we would discuss about one such complex disease, type 2 diabetes, which shares marked similarity of intermediate traits with different forms of monogenic diabetes. PMID:26300908

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. III

Treesearch

Kathleen D. Jermstad; Daniel L. Bassoni; Keith S. Jech; Gary A. Ritchie; Nicholas C. Wheeler; David B. Neale

2003-01-01

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring...

The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

PubMed Central

Lohmueller, Kirk E.

2014-01-01

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation's effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation's effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits. PMID:24875776

Joint Analysis of Strain and Parent-of-Origin Effects for Recombinant Inbred Intercrosses Generated from Multiparent Populations with the Collaborative Cross as an Example.

PubMed

Liu, Yanyan; Xiong, Sican; Sun, Wei; Zou, Fei

2018-02-02

Multiparent populations (MPP) have become popular resources for complex trait mapping because of their wider allelic diversity and larger population size compared with traditional two-way recombinant inbred (RI) strains. In mice, the collaborative cross (CC) is one of the most popular MPP and is derived from eight genetically diverse inbred founder strains. The strategy of generating RI intercrosses (RIX) from MPP in general and from the CC in particular can produce a large number of completely reproducible heterozygote genomes that better represent the (outbred) human population. Since both maternal and paternal haplotypes of each RIX are readily available, RIX is a powerful resource for studying both standing genetic and epigenetic variations of complex traits, in particular, the parent-of-origin (PoO) effects, which are important contributors to many complex traits. Furthermore, most complex traits are affected by >1 genes, where multiple quantitative trait locus mapping could be more advantageous. In this paper, for MPP-RIX data but taking CC-RIX as a working example, we propose a general Bayesian variable selection procedure to simultaneously search for multiple genes with founder allelic effects and PoO effects. The proposed model respects the complex relationship among RIX samples, and the performance of the proposed method is examined by extensive simulations. Copyright © 2018 Liu et al.

Comparison of Two New Mouse Models of Polygenic Type 2 Diabetes at the Jackson Laboratory, NONcNZO10Lt/J and TALLYHO/JngJ

PubMed Central

Leiter, Edward H.; Strobel, Marjorie; Schultz, David; Schile, Andrew; Reifsnyder, Peter C.

2013-01-01

This review compares two novel polygenic mouse models of type 2 diabetes (T2D), TALLYHO/JngJ and NONcNZO10/LtJ, and contrasts both with the well-known C57BLKS/J-Leprdb (db/db) monogenic diabesity model. We posit that the new polygenic models are more representative of the “garden variety” obesity underlying human T2D in terms of their polygenetic rather than monogenic etiology. Moreover, the clinical phenotypes in these new models are less extreme, for example, more moderated development of obesity coupled with less extreme endocrine disturbances. The more progressive development of obesity produces a maturity-onset development of hyperglycemia in contrast to the juvenile-onset diabetes observed in the morbidly obese db/db model. Unlike the leptin receptor-deficient db/db models with central leptin resistance, the new models develop a progressive peripheral leptin resistance and are able to maintain reproductive function. Although the T2D pathophysiology in both TALLYHO/JngJ and NONcNZO10/LtJ is remarkably similar, their genetic etiologies are clearly different, underscoring the genetic heterogeneity underlying T2D in humans. PMID:23671854

Comparison of Two New Mouse Models of Polygenic Type 2 Diabetes at the Jackson Laboratory, NONcNZO10Lt/J and TALLYHO/JngJ.

PubMed

Leiter, Edward H; Strobel, Marjorie; O'Neill, Adam; Schultz, David; Schile, Andrew; Reifsnyder, Peter C

2013-01-01

This review compares two novel polygenic mouse models of type 2 diabetes (T2D), TALLYHO/JngJ and NONcNZO10/LtJ, and contrasts both with the well-known C57BLKS/J-Lepr(db) (db/db) monogenic diabesity model. We posit that the new polygenic models are more representative of the "garden variety" obesity underlying human T2D in terms of their polygenetic rather than monogenic etiology. Moreover, the clinical phenotypes in these new models are less extreme, for example, more moderated development of obesity coupled with less extreme endocrine disturbances. The more progressive development of obesity produces a maturity-onset development of hyperglycemia in contrast to the juvenile-onset diabetes observed in the morbidly obese db/db model. Unlike the leptin receptor-deficient db/db models with central leptin resistance, the new models develop a progressive peripheral leptin resistance and are able to maintain reproductive function. Although the T2D pathophysiology in both TALLYHO/JngJ and NONcNZO10/LtJ is remarkably similar, their genetic etiologies are clearly different, underscoring the genetic heterogeneity underlying T2D in humans.

The Geographic Distribution of Genetic Risk as Compared to Social Risk for Chronic Diseases in the United States.

PubMed

Rehkopf, David H; Domingue, Benjamin W; Cullen, Mark R

2016-01-01

There is an association between chronic disease and geography, and there is evidence that the environment plays a critical role in this relationship. Yet at the same time, there is known to be substantial geographic variation by ancestry across the United States. Resulting geographic genetic variation-that is, the extent to which single nucleotide polymorphisms (SNPs) related to chronic disease vary spatially-could thus drive some part of the association between geography and disease. We describe the variation in chronic disease genetic risk by state of birth by taking risk SNPs from genome-wide association study meta-analyses for coronary artery disease, diabetes, and ischemic stroke and creating polygenic risk scores. We compare the amount of variability across state of birth in these polygenic scores to the variability in parental education, own education, earnings, and wealth. Our primary finding is that the polygenic risk scores are only weakly differentially distributed across U.S. states. The magnitude of the differences in geographic distribution is very small in comparison to the distribution of social and economic factors and thus is not likely sufficient to have a meaningful effect on geographic disease differences by U.S. state.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

PubMed

Seibert, Tyler M; Fan, Chun Chieh; Wang, Yunpeng; Zuber, Verena; Karunamuni, Roshan; Parsons, J Kellogg; Eeles, Rosalind A; Easton, Douglas F; Kote-Jarai, ZSofia; Al Olama, Ali Amin; Garcia, Sara Benlloch; Muir, Kenneth; Grönberg, Henrik; Wiklund, Fredrik; Aly, Markus; Schleutker, Johanna; Sipeky, Csilla; Tammela, Teuvo Lj; Nordestgaard, Børge G; Nielsen, Sune F; Weischer, Maren; Bisbjerg, Rasmus; Røder, M Andreas; Iversen, Peter; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokolorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Cuk, Katarina; Saum, Kai-Uwe; Park, Jong Y; Sellers, Thomas A; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Karow, David S; Mills, Ian G; Andreassen, Ole A; Dale, Anders M

2018-01-10

To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. Multiple institutions that were members of international PRACTICAL consortium. All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. Prediction with hazard score of age of onset of aggressive cancer in validation set. In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10 -16 ). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

PubMed Central

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris

2016-01-01

Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding – especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5) – Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0–5 cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars. PMID:27999587

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees

Treesearch

Glenn T. Howe; Sally N. Aitken; David B. Neale; Kathleen D. Jermstad; Nicholas C. Wheeler; Tony H.H Chen

2003-01-01

Adaptation to winter cold in temperate and boreal trees involves complex genetic, physiological, and developmental processes. Genecological studies demonstrate the existence of steep genetic clines for cold adaptation traits in relation to environmental (mostly temperature related) gradients. Population differentiation is generally stronger for cold adaptation traits...

Genetic Analysis and QTL Mapping of Fruit Peduncle Length in Cucumber (Cucumis sativus L.)

PubMed Central

Zhang, Song; Wang, Ye; Zhang, Sheng-Ping; Gu, Xing-Fang

2016-01-01

Mechanized harvesting of cucumbers offers significant advantages compared to manual labor as both shortages and costs of labor increase. However the efficient use of machines depends on breeding plants with longer peduncles, but the genetic and molecular basis of fruit peduncle development in cucumber is not well understood. In this study, F2 populations were developed from a cross between two inbred lines, 1101 with a long peduncle and 1694 with a short peduncle. These were grown at two field sites, Hainan, with a tropical marine climate, in December 2014, and Beijing, with a warm temperate climate, in May 2015. Electron microscope examination of the pith cells in the peduncles of the two parental lines showed that line 1101 had significantly greater numbers of smaller cells compared to line 1694. The inheritance of cucumber fruit peduncle length (FPL) was investigated by the mixed major gene and polygene inheritance model. Genetic analysis indicated that FPL in cucumber is quantitatively inherited and controlled by one additive major gene and additive-dominant polygenes (D-2 model). A total of 1460 pairs of SSR (simple sequence repeat) primers were analyzed to identify quantitative trait loci (QTLs). Two similar genetic maps with 78 SSR markers which covered 720.6 cM in seven linkage groups were constructed based on two F2 populations. QTL analysis from the data collected at the two field sites showed that there are two minor QTLs on chromosome 1, named qfpl1.1 and qfpl1.2, and one major QTL on chromosome 6, named qfpl6.1. The marker UW021226, which was the closest one to qfpl6.1, had an accuracy rate of 79.0% when tested against plants selected from populations of the two parents. The results from this study provide insights into the inheritance and molecular mechanism of the variation of FPL in cucumber, and further research will be carried out to fine map qfpl6.1 to develop more accurate markers for MAS breeding. PMID:27936210

Molecular genetics of alopecias.

PubMed

Ramot, Yuval; Zlotogorski, Abraham

2015-01-01

Recent developments in research methods and techniques, such as whole-exome and -genome sequencing, have substantially improved our understanding of genetic conditions. Special progress has been made in the field of genotrichoses, or hereditary hair diseases, a field that has been obscure for many years. The underlying genes for many of the monogenic hair diseases are now known. Additionally, complex analyses of large cohorts of patients have given us the first clues to the genes associated with polygenic hair disorders, such as androgenetic alopecia and alopecia areata. Thanks to these major findings, the sophisticated regulation of the morphogenesis, development and growth of hair follicles has begun to be revealed, and new players in this delicate molecular interplay have been exposed. © 2015 S. Karger AG, Basel.

Identification of genotyping-by-sequencing sequence tags associated with milling performance and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat quality is defined by culinary end-uses and processing characteristics. Wheat breeders are interested to identify quantitative trait loci for grain, milling, and end-use quality traits because it is imperative to understand the genetic complexity underlying quantitatively inherited traits to ...

Does structural complexity determine the morphology of assemblages? An experimental test on three continents.

PubMed

Gibb, Heloise; Parr, Catherine L

2013-01-01

Understanding how species will respond to global change depends on our ability to distinguish generalities from idiosyncrasies. For diverse, but poorly known taxa, such as insects, species traits may provide a short-cut to predicting species turnover. We tested whether ant traits respond consistently to habitat complexity across geographically independent ant assemblages, using an experimental approach and baits. We repeated our study in six paired simple and complex habitats on three continents with distinct ant faunas. We also compared traits amongst ants with different foraging strategies. We hypothesised that ants would be larger, broader, have longer legs and more dorsally positioned eyes in simpler habitats. In agreement with predictions, ants had longer femurs and dorsally positioned eyes in simple habitats. This pattern was most pronounced for ants that discovered resources. Body size and pronotum width responded as predicted for experimental treatments, but were inconsistent across continents. Monopolising ants were smaller, with shorter femurs than those that occupied or discovered resources. Consistent responses for several traits suggest that many, but not all, aspects of morphology respond predictably to habitat complexity, and that foraging strategy is linked with morphology. Some traits thus have the potential to be used to predict the direction of species turnover, changes in foraging strategy and, potentially, evolution in response to changes in habitat structure.

Biodiversity in a complex world: consolidation and progress in functional biodiversity research.

PubMed

Hillebrand, Helmut; Matthiessen, Birte

2009-12-01

The global decline of biodiversity caused by human domination of ecosystems worldwide is supposed to alter important process rates and state variables in these ecosystems. However, there is considerable debate on the prevalence and importance of biodiversity effects on ecosystem function (BDEF). Here, we argue that much of the debate stems from two major shortcomings. First, most studies do not directly link the traits leading to increased or decreased function to the traits needed for species coexistence and dominance. We argue that implementing a trait-based approach and broadening the perception of diversity to include trait dissimilarity or trait divergence will result in more realistic predictions on the consequences of altered biodiversity. Second, the empirical and theoretical studies do not reflect the complexity of natural ecosystems, which makes it difficult to transfer the results to natural situations of species loss. We review how different aspects of complexity (trophic structure, multifunctionality, spatial or temporal heterogeneity, and spatial population dynamics) alter our perception of BDEF. We propose future research avenues concisely testing whether acknowledging this complexity will strengthen the observed biodiversity effects. Finally, we propose that a major future task is to disentangle biodiversity effects on ecosystem function from direct changes in function due to human alterations of abiotic constraints.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits. PMID:29387071

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

PubMed

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Ensemble learning of QTL models improves prediction of complex traits

USDA-ARS?s Scientific Manuscript database

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability, but are less useful for genetic prediction due to difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage ...

Nested association mapping for dissecting complex traits using Peanut 58K SNP array

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWAS) and linkage mapping have been the two most predominant strategies to dissect complex traits, but are limited by the occurrence of false positives reported for GWAS, and low resolution in the case of linkage analysis. This has led to the development of a joint a...

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, HELIOTHIS SUBFLEXA

USDA-ARS?s Scientific Manuscript database

The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...

The Genetic Architecture of Complex Traits in Teosinte (Zea mays ssp. parviglumis): New Evidence from Association Mapping

USDA-ARS?s Scientific Manuscript database

Our previous association analyses showed that variation at major regulatory genes contributes to standing variation for complex traits in Balsas teosinte, the progenitor of maize. This study expands our previous association mapping effort in teosinte by testing 123 markers in 52 candidate genes for ...

Association analysis of three diverse rice (Oryza sativa L.) germplasm collections for loci regulating grain quality traits

USDA-ARS?s Scientific Manuscript database

In rice (Oryza sativa L.), end-use/cooking quality is vital for producers and millions of consumers worldwide. Grain quality is a complex trait with interacting genetic and environmental factors. Deciphering the complex genetic architecture associated with grain quality, will provide vital informati...

Handling Complexity in Animal and Plant Science Research-From Single to Functional Traits: Are We There Yet?

PubMed

Roberts, Jessica; Power, Aoife; Chandra, Shaneel; Chapman, James; Cozzolino, Daniel

2018-05-28

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

PubMed

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Empirical verification of evolutionary theories of aging.

PubMed

Kyryakov, Pavlo; Gomez-Perez, Alejandra; Glebov, Anastasia; Asbah, Nimara; Bruno, Luigi; Meunier, Carolynne; Iouk, Tatiana; Titorenko, Vladimir I

2016-10-25

We recently selected 3 long-lived mutant strains of Saccharomyces cerevisiae by a lasting exposure to exogenous lithocholic acid. Each mutant strain can maintain the extended chronological lifespan after numerous passages in medium without lithocholic acid. In this study, we used these long-lived yeast mutants for empirical verification of evolutionary theories of aging. We provide evidence that the dominant polygenic trait extending longevity of each of these mutants 1) does not affect such key features of early-life fitness as the exponential growth rate, efficacy of post-exponential growth and fecundity; and 2) enhances such features of early-life fitness as susceptibility to chronic exogenous stresses, and the resistance to apoptotic and liponecrotic forms of programmed cell death. These findings validate evolutionary theories of programmed aging. We also demonstrate that under laboratory conditions that imitate the process of natural selection within an ecosystem, each of these long-lived mutant strains is forced out of the ecosystem by the parental wild-type strain exhibiting shorter lifespan. We therefore concluded that yeast cells have evolved some mechanisms for limiting their lifespan upon reaching a certain chronological age. These mechanisms drive the evolution of yeast longevity towards maintaining a finite yeast chronological lifespan within ecosystems.

Comparative assessment of genetic and epigenetic variation among regenerants of potato (Solanum tuberosum) derived from long-term nodal tissue-culture and cell selection.

PubMed

Dann, Alison L; Wilson, Calum R

2011-04-01

Three long-term nodal tissued cultured Russet Burbank potato clones and nine thaxtomin A-treated regenerant lines, derived from the nodal lines, were assessed for genetic and epigenetic (in the form of DNA methylation) differences by AFLP and MSAP. The treated regenerant lines were originally selected for superior resistance to common scab disease and acceptable tuber yield in pot and field trials. The long-term, tissue culture clone lines exhibited genetic (8.75-15.63% polymorphisms) and epigenetic (12.56-26.13% polymorphisms) differences between them and may represent a stress response induced by normal plant growth disruption. The thaxtomin A-treated regenerant lines exhibited much higher significant (p < 0.05) genetic (2-29.38%) and epigenetic (45.22-51.76%) polymorphisms than the nodal cultured parent clones. Methylation-sensitive mutations accumulated within the regenerant lines are significantly correlated (p < 0.05) to disease resistance. However, linking phenotypic differences that could be of benefit to potato growers, to single gene sequence polymorphisms in a tetraploid plant such as the potato would be extremely difficult since it is assumed many desirable traits are under polygenic control.

Studies on the genetic control of murine humoral response to immunization with a peptidoglycan-containing fraction extracted from Brucella melitensis.

PubMed

Cannat, A; Feingold, N; Caffin, J C; Serre, A

1979-01-01

A peptidoglycan containing fraction (fraction "5") extracted from Brucella melitensis has been injected in low infra-vaccinating doses into inbred mice. The genetic control of the resulting anti-Brucella humoral response has been studied in the C57BL/6 "good responder" X DBA2 "low responder" model. The results observed in F1, F2 and reciprocal backcrosses show that the "good responder" character, although transmitted as a dominant trait, is under polygenic control and independent of H2 haplotype, Ig allotype, sexual chromosoms or the "d" coat color gene. On the other hand, the phenotypic expression of at least one of the genes involved is sex-limited and influenced by hormonal environmental factors. Moreover the expression in females of one of these sex-dependent genes is associated with the "b" coat color gene. These results are discussed in terms of their possible relevance in spontaneous or vaccinal resistance to experimental brucellosis, of the relative role of the peptidoglycan and lipoprotein moieties in fraction "5" and of the possible importance of sex-dependent and chromosome 4-linked genetic factors for B-cell functions.

Common polymorphic variation in the genetically diverse African insulin gene and its association with size at birth.

PubMed

Petry, Clive J; Rayco-Solon, Pura; Fulford, Anthony J C; Stead, John D H; Wingate, Dianne L; Ong, Ken K; Sirugo, Giorgio; Prentice, Andrew M; Dunger, David B

2009-09-01

The insulin variable number of tandem repeats (INS VNTR) has been variably associated with size at birth in non-African populations. Small size at birth is a major determinant of neonatal mortality, so the INS VNTR may influence survival. We tested the hypothesis, therefore, that genetic variation around the INS VNTR in a rural Gambian population, who experience seasonal variation in nutrition and subsequently birth weight, may be associated with foetal and early growth. Six polymorphisms flanking the INS VNTR were genotyped in over 2,500 people. Significant associations were detected between the maternally inherited SNP 27 (rs689) allele and birth length [effect size 17.5 (5.2-29.8) mm; P = 0.004; n = 361]. Significant associations were also found between the maternally inherited African-specific SNP 28 (rs5506) allele and post-natal weight gain [effect size 0.19 (0.05-0.32) z score points/year; P = 0.005; n = 728). These results suggest that in the Gambian population studied there are associations between polymorphic variation in the genetically diverse INS gene and foetal and early growth characteristics, which contribute to overall polygenic associations with these traits.

Predicting educational achievement from DNA

PubMed Central

Selzam, S; Krapohl, E; von Stumm, S; O'Reilly, P F; Rimfeld, K; Kovas, Y; Dale, P S; Lee, J J; Plomin, R

2017-01-01

A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences. PMID:27431296

Review and meta-analysis of genetic polymorphisms associated with exceptional human longevity.

PubMed

Revelas, Mary; Thalamuthu, Anbupalam; Oldmeadow, Christopher; Evans, Tiffany-Jane; Armstrong, Nicola J; Kwok, John B; Brodaty, Henry; Schofield, Peter R; Scott, Rodney J; Sachdev, Perminder S; Attia, John R; Mather, Karen A

2018-06-08

Many factors contribute to exceptional longevity, with genetics playing a significant role. However, to date, genetic studies examining exceptional longevity have been inconclusive. This comprehensive review seeks to determine the genetic variants associated with exceptional longevity by undertaking meta-analyses. Meta-analyses of genetic polymorphisms previously associated with exceptional longevity (85+) were undertaken. For each variant, meta-analyses were performed if there were data from at least three independent studies available, including two unpublished additional cohorts. Five polymorphisms, ACE rs4340, APOE ε2/3/4, FOXO3A rs2802292, KLOTHO KL-VS and IL6 rs1800795 were significantly associated with exceptional longevity, with the pooled effect sizes (odds ratios) ranging from 0.42 (APOE ε4) to 1.45 (FOXO3A males). In general, the observed modest effect sizes of the significant variants suggest many genes of small influence play a role in exceptional longevity, which is consistent with results for other polygenic traits. Our results also suggest that genes related to cardiovascular health may be implicated in exceptional longevity. Future studies should examine the roles of gender and ethnicity and carefully consider study design, including the selection of appropriate controls. Copyright © 2018. Published by Elsevier B.V.