Causes and Consequences of Genetic Background Effects Illuminated by Integrative Genomic Analysis

PubMed Central

Chandler, Christopher H.; Chari, Sudarshan; Dworkin, Ian

2014-01-01

The phenotypic consequences of individual mutations are modulated by the wild-type genetic background in which they occur. Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist or about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome-level datasets from a mapping-by-introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome resequencing of the parental lines—two commonly used laboratory strains—to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background-dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative noncomplementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well. PMID:24504186

Will genomic selection be a practical method for plant breeding?

PubMed Central

Nakaya, Akihiro; Isobe, Sachiko N.

2012-01-01

Background Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. Scope In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Conclusions Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory. PMID:22645117

Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Akgöl, Batuhan; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2017-02-01

Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.

Coalescence with Background and Balancing Selection in Systems with Bi- and Uniparental Reproduction: Contrasting Partial Asexuality and Selfing

PubMed Central

Agrawal, Aneil F.; Hartfield, Matthew

2016-01-01

Uniparental reproduction in diploids, via asexual reproduction or selfing, reduces the independence with which separate loci are transmitted across generations. This is expected to increase the extent to which a neutral marker is affected by selection elsewhere in the genome. Such effects have previously been quantified in coalescent models involving selfing. Here we examine the effects of background selection and balancing selection in diploids capable of both sexual and asexual reproduction (i.e., partial asexuality). We find that the effect of background selection on reducing coalescent time (and effective population size) can be orders of magnitude greater when rates of sex are low than when sex is common. This is because asexuality enhances the effects of background selection through both a recombination effect and a segregation effect. We show that there are several reasons that the strength of background selection differs between systems with partial asexuality and those with comparable levels of uniparental reproduction via selfing. Expectations for reductions in Ne via background selection have been verified using stochastic simulations. In contrast to background selection, balancing selection increases the coalescence time for a linked neutral site. With partial asexuality, the effect of balancing selection is somewhat dependent upon the mode of selection (e.g., heterozygote advantage vs. negative frequency-dependent selection) in a manner that does not apply to selfing. This is because the frequency of heterozygotes, which are required for recombination onto alternative genetic backgrounds, is more dependent on the pattern of selection with partial asexuality than with selfing. PMID:26584901

Coalescence with Background and Balancing Selection in Systems with Bi- and Uniparental Reproduction: Contrasting Partial Asexuality and Selfing.

PubMed

Agrawal, Aneil F; Hartfield, Matthew

2016-01-01

Uniparental reproduction in diploids, via asexual reproduction or selfing, reduces the independence with which separate loci are transmitted across generations. This is expected to increase the extent to which a neutral marker is affected by selection elsewhere in the genome. Such effects have previously been quantified in coalescent models involving selfing. Here we examine the effects of background selection and balancing selection in diploids capable of both sexual and asexual reproduction (i.e., partial asexuality). We find that the effect of background selection on reducing coalescent time (and effective population size) can be orders of magnitude greater when rates of sex are low than when sex is common. This is because asexuality enhances the effects of background selection through both a recombination effect and a segregation effect. We show that there are several reasons that the strength of background selection differs between systems with partial asexuality and those with comparable levels of uniparental reproduction via selfing. Expectations for reductions in Ne via background selection have been verified using stochastic simulations. In contrast to background selection, balancing selection increases the coalescence time for a linked neutral site. With partial asexuality, the effect of balancing selection is somewhat dependent upon the mode of selection (e.g., heterozygote advantage vs. negative frequency-dependent selection) in a manner that does not apply to selfing. This is because the frequency of heterozygotes, which are required for recombination onto alternative genetic backgrounds, is more dependent on the pattern of selection with partial asexuality than with selfing. Copyright © 2016 by the Genetics Society of America.

Advances and Challenges in Genomic Selection for Disease Resistance.

PubMed

Poland, Jesse; Rutkoski, Jessica

2016-08-04

Breeding for disease resistance is a central focus of plant breeding programs, as any successful variety must have the complete package of high yield, disease resistance, agronomic performance, and end-use quality. With the need to accelerate the development of improved varieties, genomics-assisted breeding is becoming an important tool in breeding programs. With marker-assisted selection, there has been success in breeding for disease resistance; however, much of this work and research has focused on identifying, mapping, and selecting for major resistance genes that tend to be highly effective but vulnerable to breakdown with rapid changes in pathogen races. In contrast, breeding for minor-gene quantitative resistance tends to produce more durable varieties but is a more challenging breeding objective. As the genetic architecture of resistance shifts from single major R genes to a diffused architecture of many minor genes, the best approach for molecular breeding will shift from marker-assisted selection to genomic selection. Genomics-assisted breeding for quantitative resistance will therefore necessitate whole-genome prediction models and selection methodology as implemented for classical complex traits such as yield. Here, we examine multiple case studies testing whole-genome prediction models and genomic selection for disease resistance. In general, whole-genome models for disease resistance can produce prediction accuracy suitable for application in breeding. These models also largely outperform multiple linear regression as would be applied in marker-assisted selection. With the implementation of genomic selection for yield and other agronomic traits, whole-genome marker profiles will be available for the entire set of breeding lines, enabling genomic selection for disease at no additional direct cost. In this context, the scope of implementing genomics selection for disease resistance, and specifically for quantitative resistance and quarantined pathogens

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

PubMed Central

2010-01-01

Background The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved. Results This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. Conclusions emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time. PMID:20969788

The nucleotide composition of microbial genomes indicates differential patterns of selection on core and accessory genomes.

PubMed

Bohlin, Jon; Eldholm, Vegard; Pettersson, John H O; Brynildsrud, Ola; Snipen, Lars

2017-02-10

The core genome consists of genes shared by the vast majority of a species and is therefore assumed to have been subjected to substantially stronger purifying selection than the more mobile elements of the genome, also known as the accessory genome. Here we examine intragenic base composition differences in core genomes and corresponding accessory genomes in 36 species, represented by the genomes of 731 bacterial strains, to assess the impact of selective forces on base composition in microbes. We also explore, in turn, how these results compare with findings for whole genome intragenic regions. We found that GC content in coding regions is significantly higher in core genomes than accessory genomes and whole genomes. Likewise, GC content variation within coding regions was significantly lower in core genomes than in accessory genomes and whole genomes. Relative entropy in coding regions, measured as the difference between observed and expected trinucleotide frequencies estimated from mononucleotide frequencies, was significantly higher in the core genomes than in accessory and whole genomes. Relative entropy was positively associated with coding region GC content within the accessory genomes, but not within the corresponding coding regions of core or whole genomes. The higher intragenic GC content and relative entropy, as well as the lower GC content variation, observed in the core genomes is most likely associated with selective constraints. It is unclear whether the positive association between GC content and relative entropy in the more mobile accessory genomes constitutes signatures of selection or selective neutral processes.

Selections that isolate recombinant mitochondrial genomes in animals

PubMed Central

Ma, Hansong; O'Farrell, Patrick H

2015-01-01

Homologous recombination is widespread and catalyzes evolution. Nonetheless, its existence in animal mitochondrial DNA is questioned. We designed selections for recombination between co-resident mitochondrial genomes in various heteroplasmic Drosophila lines. In four experimental settings, recombinant genomes became the sole or dominant genome in the progeny. Thus, selection uncovers occurrence of homologous recombination in Drosophila mtDNA and documents its functional benefit. Double-strand breaks enhanced recombination in the germline and revealed somatic recombination. When the recombination partner was a diverged Drosophila melanogaster genome or a genome from a different species such as Drosophila yakuba, sequencing revealed long continuous stretches of exchange. In addition, the distribution of sequence polymorphisms in recombinants allowed us to map a selected trait to a particular region in the Drosophila mitochondrial genome. Thus, recombination can be harnessed to dissect function and evolution of mitochondrial genome. DOI: http://dx.doi.org/10.7554/eLife.07247.001 PMID:26237110

Revealing the selection history of adaptive loci using genome-wide scans for selection: an example from domestic sheep.

PubMed

Rochus, Christina Marie; Tortereau, Flavie; Plisson-Petit, Florence; Restoux, Gwendal; Moreno-Romieux, Carole; Tosser-Klopp, Gwenola; Servin, Bertrand

2018-01-23

One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs. Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species ("selection hotspots") including ABCG2, LCORL/NCAPG, MSTN, and coat colour genes such as ASIP, MC1R, MITF, and TYRP1. For one of these regions (ABCG2, LCORL/NCAPG), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds. Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

Genome-wide signatures of population bottlenecks and diversifying selection in European wolves

PubMed Central

Pilot, M; Greco, C; vonHoldt, B M; Jędrzejewska, B; Randi, E; Jędrzejewski, W; Sidorovich, V E; Ostrander, E A; Wayne, R K

2014-01-01

Genomic resources developed for domesticated species provide powerful tools for studying the evolutionary history of their wild relatives. Here we use 61K single-nucleotide polymorphisms (SNPs) evenly spaced throughout the canine nuclear genome to analyse evolutionary relationships among the three largest European populations of grey wolves in comparison with other populations worldwide, and investigate genome-wide effects of demographic bottlenecks and signatures of selection. European wolves have a discontinuous range, with large and connected populations in Eastern Europe and relatively smaller, isolated populations in Italy and the Iberian Peninsula. Our results suggest a continuous decline in wolf numbers in Europe since the Late Pleistocene, and long-term isolation and bottlenecks in the Italian and Iberian populations following their divergence from the Eastern European population. The Italian and Iberian populations have low genetic variability and high linkage disequilibrium, but relatively few autozygous segments across the genome. This last characteristic clearly distinguishes them from populations that underwent recent drastic demographic declines or founder events, and implies long-term bottlenecks in these two populations. Although genetic drift due to spatial isolation and bottlenecks seems to be a major evolutionary force diversifying the European populations, we detected 35 loci that are putatively under diversifying selection. Two of these loci flank the canine platelet-derived growth factor gene, which affects bone growth and may influence differences in body size between wolf populations. This study demonstrates the power of population genomics for identifying genetic signals of demographic bottlenecks and detecting signatures of directional selection in bottlenecked populations, despite their low background variability. PMID:24346500

The scope and strength of sex-specific selection in genome evolution

PubMed Central

Wright, A E; Mank, J E

2013-01-01

Males and females share the vast majority of their genomes and yet are often subject to different, even conflicting, selection. Genomic and transcriptomic developments have made it possible to assess sex-specific selection at the molecular level, and it is clear that sex-specific selection shapes the evolutionary properties of several genomic characteristics, including transcription, post-transcriptional regulation, imprinting, genome structure and gene sequence. Sex-specific selection is strongly influenced by mating system, which also causes neutral evolutionary changes that affect different regions of the genome in different ways. Here, we synthesize theoretical and molecular work in order to provide a cohesive view of the role of sex-specific selection and mating system in genome evolution. We also highlight the need for a combined approach, incorporating both genomic data and experimental phenotypic studies, in order to understand precisely how sex-specific selection drives evolutionary change across the genome. PMID:23848139

The scope and strength of sex-specific selection in genome evolution.

PubMed

Wright, A E; Mank, J E

2013-09-01

Males and females share the vast majority of their genomes and yet are often subject to different, even conflicting, selection. Genomic and transcriptomic developments have made it possible to assess sex-specific selection at the molecular level, and it is clear that sex-specific selection shapes the evolutionary properties of several genomic characteristics, including transcription, post-transcriptional regulation, imprinting, genome structure and gene sequence. Sex-specific selection is strongly influenced by mating system, which also causes neutral evolutionary changes that affect different regions of the genome in different ways. Here, we synthesize theoretical and molecular work in order to provide a cohesive view of the role of sex-specific selection and mating system in genome evolution. We also highlight the need for a combined approach, incorporating both genomic data and experimental phenotypic studies, in order to understand precisely how sex-specific selection drives evolutionary change across the genome. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Genome-wide diversity and selective pressure in the human rhinovirus

PubMed Central

Kistler, Amy L; Webster, Dale R; Rouskin, Silvi; Magrini, Vince; Credle, Joel J; Schnurr, David P; Boushey, Homer A; Mardis, Elaine R; Li, Hao; DeRisi, Joseph L

2007-01-01

Background The human rhinoviruses (HRV) are one of the most common and diverse respiratory pathogens of humans. Over 100 distinct HRV serotypes are known, yet only 6 genomes are available. Due to the paucity of HRV genome sequence, little is known about the genetic diversity within HRV or the forces driving this diversity. Previous comparative genome sequence analyses indicate that recombination drives diversification in multiple genera of the picornavirus family, yet it remains unclear if this holds for HRV. Results To resolve this and gain insight into the forces driving diversification in HRV, we generated a representative set of 34 fully sequenced HRVs. Analysis of these genomes shows consistent phylogenies across the genome, conserved non-coding elements, and only limited recombination. However, spikes of genetic diversity at both the nucleotide and amino acid level are detectable within every locus of the genome. Despite this, the HRV genome as a whole is under purifying selective pressure, with islands of diversifying pressure in the VP1, VP2, and VP3 structural genes and two non-structural genes, the 3C protease and 3D polymerase. Mapping diversifying residues in these factors onto available 3-dimensional structures revealed the diversifying capsid residues partition to the external surface of the viral particle in statistically significant proximity to antigenic sites. Diversifying pressure in the pleconaril binding site is confined to a single residue known to confer drug resistance (VP1 191). In contrast, diversifying pressure in the non-structural genes is less clear, mapping both nearby and beyond characterized functional domains of these factors. Conclusion This work provides a foundation for understanding HRV genetic diversity and insight into the underlying biology driving evolution in HRV. It expands our knowledge of the genome sequence space that HRV reference serotypes occupy and how the pattern of genetic diversity across HRV genomes differs

Genomic resources and their influence on the detection of the signal of positive selection in genome scans.

PubMed

Manel, S; Perrier, C; Pratlong, M; Abi-Rached, L; Paganini, J; Pontarotti, P; Aurelle, D

2016-01-01

Genome scans represent powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful, for example, in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non-model species. Thousands of SNPs called using Reduced Representation Sequencing are increasingly used in genome scans. Besides, genome sequences are also becoming increasingly available, allowing better processing of short-read data, offering physical localization of variants, and improving haplotype reconstruction and data imputation. Ultimately, genome sequences are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genome sequences, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by (i) improving the overall quality of the data, (ii) helping the reconstruction of demographic history for the population studied to decrease false-positive rates and (iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high-quality reference genome can improve the detection of the signal of selection by (i) allowing matching the potential candidate loci to linked coding regions under selection, (ii) rapidly moving the investigation to the gene and function and (iii) ensuring that the highly variable regions of the genomes that include functional genes are also investigated. For all those reasons, using reference genomes in genome scan analyses is highly recommended. © 2015 John Wiley & Sons Ltd.

Integrating genomic selection into dairy cattle breeding programmes: a review.

PubMed

Bouquet, A; Juga, J

2013-05-01

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However

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

Detecting signatures of positive selection associated with musical aptitude in the human genome

PubMed Central

Liu, Xuanyao; Kanduri, Chakravarthi; Oikkonen, Jaana; Karma, Kai; Raijas, Pirre; Ukkola-Vuoti, Liisa; Teo, Yik-Ying; Järvelä, Irma

2016-01-01

Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and FST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude. PMID:26879527

Detecting signatures of positive selection associated with musical aptitude in the human genome.

PubMed

Liu, Xuanyao; Kanduri, Chakravarthi; Oikkonen, Jaana; Karma, Kai; Raijas, Pirre; Ukkola-Vuoti, Liisa; Teo, Yik-Ying; Järvelä, Irma

2016-02-16

Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and FST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude.

Signatures of selection in tilapia revealed by whole genome resequencing

PubMed Central

Hong Xia, Jun; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Yi Wan, Zi; Li, Jiale; Lin, Haoran; Hua Yue, Gen

2015-01-01

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10–100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia. PMID:26373374

Signatures of selection in tilapia revealed by whole genome resequencing.

PubMed

Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

Detection of selective sweeps in cattle using genome-wide SNP data

PubMed Central

2013-01-01

Background The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps. Results Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour. Conclusions The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra

Genome size variation affects song attractiveness in grasshoppers: evidence for sexual selection against large genomes.

PubMed

Schielzeth, Holger; Streitner, Corinna; Lampe, Ulrike; Franzke, Alexandra; Reinhold, Klaus

2014-12-01

Genome size is largely uncorrelated to organismal complexity and adaptive scenarios. Genetic drift as well as intragenomic conflict have been put forward to explain this observation. We here study the impact of genome size on sexual attractiveness in the bow-winged grasshopper Chorthippus biguttulus. Grasshoppers show particularly large variation in genome size due to the high prevalence of supernumerary chromosomes that are considered (mildly) selfish, as evidenced by non-Mendelian inheritance and fitness costs if present in high numbers. We ranked male grasshoppers by song characteristics that are known to affect female preferences in this species and scored genome sizes of attractive and unattractive individuals from the extremes of this distribution. We find that attractive singers have significantly smaller genomes, demonstrating that genome size is reflected in male courtship songs and that females prefer songs of males with small genomes. Such a genome size dependent mate preference effectively selects against selfish genetic elements that tend to increase genome size. The data therefore provide a novel example of how sexual selection can reinforce natural selection and can act as an agent in an intragenomic arms race. Furthermore, our findings indicate an underappreciated route of how choosy females could gain indirect benefits. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Genome-wide selection components analysis in a fish with male pregnancy.

PubMed

Flanagan, Sarah P; Jones, Adam G

2017-04-01

A major goal of evolutionary biology is to identify the genome-level targets of natural and sexual selection. With the advent of next-generation sequencing, whole-genome selection components analysis provides a promising avenue in the search for loci affected by selection in nature. Here, we implement a genome-wide selection components analysis in the sex role reversed Gulf pipefish, Syngnathus scovelli. Our approach involves a double-digest restriction-site associated DNA sequencing (ddRAD-seq) technique, applied to adult females, nonpregnant males, pregnant males, and their offspring. An F ST comparison of allele frequencies among these groups reveals 47 genomic regions putatively experiencing sexual selection, as well as 468 regions showing a signature of differential viability selection between males and females. A complementary likelihood ratio test identifies similar patterns in the data as the F ST analysis. Sexual selection and viability selection both tend to favor the rare alleles in the population. Ultimately, we conclude that genome-wide selection components analysis can be a useful tool to complement other approaches in the effort to pinpoint genome-level targets of selection in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

A Primer on High-Throughput Computing for Genomic Selection

PubMed Central

Wu, Xiao-Lin; Beissinger, Timothy M.; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J. M.; Weigel, Kent A.; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

Genomic selection using beef commercial carcass phenotypes.

PubMed

Todd, D L; Roughsedge, T; Woolliams, J A

2014-03-01

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype-environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρX). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρX. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρX of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρX; however, the effect of varying ρX was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρX=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes

Measuring genomic pre-selection in theory and in practice

USDA-ARS?s Scientific Manuscript database

Potential biases from genomic pre-selection were estimated from actual selection and mating patterns of US Holsteins. Traditional models using only phenotypes and pedigrees do not adjust for average genomic merit of an animal’s parents, progeny, mates, or contemporaries. Positive assortative mating ...

A genome-wide scan for signatures of selection in Chinese indigenous and commercial pig breeds

PubMed Central

2014-01-01

Background Modern breeding and artificial selection play critical roles in pig domestication and shape the genetic variation of different breeds. China has many indigenous pig breeds with various characteristics in morphology and production performance that differ from those of foreign commercial pig breeds. However, the signatures of selection on genes implying for economic traits between Chinese indigenous and commercial pigs have been poorly understood. Results We identified footprints of positive selection at the whole genome level, comprising 44,652 SNPs genotyped in six Chinese indigenous pig breeds, one developed breed and two commercial breeds. An empirical genome-wide distribution of Fst (F-statistics) was constructed based on estimations of Fst for each SNP across these nine breeds. We detected selection at the genome level using the High-Fst outlier method and found that 81 candidate genes show high evidence of positive selection. Furthermore, the results of network analyses showed that the genes that displayed evidence of positive selection were mainly involved in the development of tissues and organs, and the immune response. In addition, we calculated the pairwise Fst between Chinese indigenous and commercial breeds (CHN VS EURO) and between Northern and Southern Chinese indigenous breeds (Northern VS Southern). The IGF1R and ESR1 genes showed evidence of positive selection in the CHN VS EURO and Northern VS Southern groups, respectively. Conclusions In this study, we first identified the genomic regions that showed evidences of selection between Chinese indigenous and commercial pig breeds using the High-Fst outlier method. These regions were found to be involved in the development of tissues and organs, the immune response, growth and litter size. The results of this study provide new insights into understanding the genetic variation and domestication in pigs. PMID:24422716

Genome-wide scans for loci under selection in humans

PubMed Central

2005-01-01

Natural selection, which can be defined as the differential contribution of genetic variants to future generations, is the driving force of Darwinian evolution. Identifying regions of the human genome that have been targets of natural selection is an important step in clarifying human evolutionary history and understanding how genetic variation results in phenotypic diversity, it may also facilitate the search for complex disease genes. Technological advances in high-throughput DNA sequencing and single nucleotide polymorphism genotyping have enabled several genome-wide scans of natural selection to be undertaken. Here, some of the observations that are beginning to emerge from these studies will be reviewed, including evidence for geographically restricted selective pressures (ie local adaptation) and a relationship between genes subject to natural selection and human disease. In addition, the paper will highlight several important problems that need to be addressed in future genome-wide studies of natural selection. PMID:16004726

Does genomic selection have a future in plant breeding?

PubMed

Jonas, Elisabeth; de Koning, Dirk-Jan

2013-09-01

Plant breeding largely depends on phenotypic selection in plots and only for some, often disease-resistance-related traits, uses genetic markers. The more recently developed concept of genomic selection, using a black box approach with no need of prior knowledge about the effect or function of individual markers, has also been proposed as a great opportunity for plant breeding. Several empirical and theoretical studies have focused on the possibility to implement this as a novel molecular method across various species. Although we do not question the potential of genomic selection in general, in this Opinion, we emphasize that genomic selection approaches from dairy cattle breeding cannot be easily applied to complex plant breeding. Copyright © 2013 Elsevier Ltd. All rights reserved.

Signatures of natural selection and ecological differentiation in microbial genomes.

PubMed

Shapiro, B Jesse

2014-01-01

We live in a microbial world. Most of the genetic and metabolic diversity that exists on earth - and has existed for billions of years - is microbial. Making sense of this vast diversity is a daunting task, but one that can be approached systematically by analyzing microbial genome sequences. This chapter explores how the evolutionary forces of recombination and selection act to shape microbial genome sequences, leaving signatures that can be detected using comparative genomics and population-genetic tests for selection. I describe the major classes of tests, paying special attention to their relative strengths and weaknesses when applied to microbes. Specifically, I apply a suite of tests for selection to a set of closely-related bacterial genomes with different microhabitat preferences within the marine water column, shedding light on the genomic mechanisms of ecological differentiation in the wild. I will focus on the joint problem of simultaneously inferring the boundaries between microbial populations, and the selective forces operating within and between populations.

An experimental validation of genomic selection in octoploid strawberry

PubMed Central

Gezan, Salvador A; Osorio, Luis F; Verma, Sujeet; Whitaker, Vance M

2017-01-01

The primary goal of genomic selection is to increase genetic gains for complex traits by predicting performance of individuals for which phenotypic data are not available. The objective of this study was to experimentally evaluate the potential of genomic selection in strawberry breeding and to define a strategy for its implementation. Four clonally replicated field trials, two in each of 2 years comprised of a total of 1628 individuals, were established in 2013–2014 and 2014–2015. Five complex yield and fruit quality traits with moderate to low heritability were assessed in each trial. High-density genotyping was performed with the Affymetrix Axiom IStraw90 single-nucleotide polymorphism array, and 17 479 polymorphic markers were chosen for analysis. Several methods were compared, including Genomic BLUP, Bayes B, Bayes C, Bayesian LASSO Regression, Bayesian Ridge Regression and Reproducing Kernel Hilbert Spaces. Cross-validation within training populations resulted in higher values than for true validations across trials. For true validations, Bayes B gave the highest predictive abilities on average and also the highest selection efficiencies, particularly for yield traits that were the lowest heritability traits. Selection efficiencies using Bayes B for parent selection ranged from 74% for average fruit weight to 34% for early marketable yield. A breeding strategy is proposed in which advanced selection trials are utilized as training populations and in which genomic selection can reduce the breeding cycle from 3 to 2 years for a subset of untested parents based on their predicted genomic breeding values. PMID:28090334

Genomic Selection in Dairy Cattle: The USDA Experience.

PubMed

Wiggans, George R; Cole, John B; Hubbard, Suzanne M; Sonstegard, Tad S

2017-02-08

Genomic selection has revolutionized dairy cattle breeding. Since 2000, assays have been developed to genotype large numbers of single-nucleotide polymorphisms (SNPs) at relatively low cost. The first commercial SNP genotyping chip was released with a set of 54,001 SNPs in December 2007. Over 15,000 genotypes were used to determine which SNPs should be used in genomic evaluation of US dairy cattle. Official USDA genomic evaluations were first released in January 2009 for Holsteins and Jerseys, in August 2009 for Brown Swiss, in April 2013 for Ayrshires, and in April 2016 for Guernseys. Producers have accepted genomic evaluations as accurate indications of a bull's eventual daughter-based evaluation. The integration of DNA marker technology and genomics into the traditional evaluation system has doubled the rate of genetic progress for traits of economic importance, decreased generation interval, increased selection accuracy, reduced previous costs of progeny testing, and allowed identification of recessive lethals.

Genomic Selection in Multi-environment Crop Trials.

PubMed

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Switches in Genomic GC Content Drive Shifts of Optimal Codons under Sustained Selection on Synonymous Sites

PubMed Central

Sun, Yu; Tamarit, Daniel

2017-01-01

Abstract The major codon preference model suggests that codons read by tRNAs in high concentrations are preferentially utilized in highly expressed genes. However, the identity of the optimal codons differs between species although the forces driving such changes are poorly understood. We suggest that these questions can be tackled by placing codon usage studies in a phylogenetic framework and that bacterial genomes with extreme nucleotide composition biases provide informative model systems. Switches in the background substitution biases from GC to AT have occurred in Gardnerella vaginalis (GC = 32%), and from AT to GC in Lactobacillus delbrueckii (GC = 62%) and Lactobacillus fermentum (GC = 63%). We show that despite the large effects on codon usage patterns by these switches, all three species evolve under selection on synonymous sites. In G. vaginalis, the dramatic codon frequency changes coincide with shifts of optimal codons. In contrast, the optimal codons have not shifted in the two Lactobacillus genomes despite an increased fraction of GC-ending codons. We suggest that all three species are in different phases of an on-going shift of optimal codons, and attribute the difference to a stronger background substitution bias and/or longer time since the switch in G. vaginalis. We show that comparative and correlative methods for optimal codon identification yield conflicting results for genomes in flux and discuss possible reasons for the mispredictions. We conclude that switches in the direction of the background substitution biases can drive major shifts in codon preference patterns even under sustained selection on synonymous codon sites. PMID:27540085

Complex interplay between neutral and adaptive evolution shaped differential genomic background and disease susceptibility along the Italian peninsula.

PubMed

Sazzini, Marco; Gnecchi Ruscone, Guido Alberto; Giuliani, Cristina; Sarno, Stefania; Quagliariello, Andrea; De Fanti, Sara; Boattini, Alessio; Gentilini, Davide; Fiorito, Giovanni; Catanoso, Mariagrazia; Boiardi, Luigi; Croci, Stefania; Macchioni, Pierluigi; Mantovani, Vilma; Di Blasio, Anna Maria; Matullo, Giuseppe; Salvarani, Carlo; Franceschi, Claudio; Pettener, Davide; Garagnani, Paolo; Luiselli, Donata

2016-09-01

The Italian peninsula has long represented a natural hub for human migrations across the Mediterranean area, being involved in several prehistoric and historical population movements. Coupled with a patchy environmental landscape entailing different ecological/cultural selective pressures, this might have produced peculiar patterns of population structure and local adaptations responsible for heterogeneous genomic background of present-day Italians. To disentangle this complex scenario, genome-wide data from 780 Italian individuals were generated and set into the context of European/Mediterranean genomic diversity by comparison with genotypes from 50 populations. To maximize possibility of pinpointing functional genomic regions that have played adaptive roles during Italian natural history, our survey included also ~250,000 exomic markers and ~20,000 coding/regulatory variants with well-established clinical relevance. This enabled fine-grained dissection of Italian population structure through the identification of clusters of genetically homogeneous provinces and of genomic regions underlying their local adaptations. Description of such patterns disclosed crucial implications for understanding differential susceptibility to some inflammatory/autoimmune disorders, coronary artery disease and type 2 diabetes of diverse Italian subpopulations, suggesting the evolutionary causes that made some of them particularly exposed to the metabolic and immune challenges imposed by dietary and lifestyle shifts that involved western societies in the last centuries.

Assessing Predictive Properties of Genome-Wide Selection in Soybeans

PubMed Central

Xavier, Alencar; Muir, William M.; Rainey, Katy Martin

2016-01-01

Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. PMID:27317786

Optimization of Swine Breeding Programs Using Genomic Selection with ZPLAN+

PubMed Central

Lopez, B. M.; Kang, H. S.; Kim, T. H.; Viterbo, V. S.; Kim, H. S.; Na, C. S.; Seo, K. S.

2016-01-01

The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (GEBV) as the selection criteria. The ZPLAN+ software was employed to calculate and compare the genetic gain, total cost, return and profit of each selection strategy. The first strategy reflected the current conventional breeding program, which was a progeny test system (CS). The second strategy was a selection scheme based strictly on genomic information (GS1). The third scenario was the same as GS1, but the selection by GEBV was further supplemented by the performance test (GS2). The last scenario was a mixture of genomic information and progeny tests (GS3). The results showed that the accuracy of the selection index of young boars of GS1 was 26% higher than that of CS. On the other hand, both GS2 and GS3 gave 31% higher accuracy than CS for young boars. The annual monetary genetic gain of GS1, GS2 and GS3 was 10%, 12%, and 11% higher, respectively, than that of CS. As expected, the discounted costs of genomic selection strategies were higher than those of CS. The costs of GS1, GS2 and GS3 were 35%, 73%, and 89% higher than those of CS, respectively, assuming a genotyping cost of $120. As a result, the discounted profit per animal of GS1 and GS2 was 8% and 2% higher, respectively, than that of CS while GS3 was 6% lower. Comparison among genomic breeding scenarios revealed that GS1 was more profitable than GS2 and GS3. The genomic selection schemes, especially GS1 and GS2, were clearly superior to the conventional scheme in terms of monetary genetic gain and profit. PMID:26954222

Practical Approaches for Detecting Selection in Microbial Genomes.

PubMed

Hedge, Jessica; Wilson, Daniel J

2016-02-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

Electron transfer to nitrogenase in different genomic and metabolic backgrounds.

PubMed

Poudel, Saroj; Colman, Daniel R; Fixen, Kathryn R; Ledbetter, Rhesa N; Zheng, Yanning; Pence, Natasha; Seefeldt, Lance C; Peters, John W; Harwood, Caroline S; Boyd, Eric S

2018-02-26

Nitrogenase catalyzes the reduction of dinitrogen (N 2 ) using low potential electrons from ferredoxin (Fd) or flavodoxin (Fld) through an ATP dependent process. Since its emergence in an anaerobic chemoautotroph, this oxygen (O 2 ) sensitive enzyme complex has evolved to operate in a variety of genomic and metabolic backgrounds including those of aerobes, anaerobes, chemotrophs, and phototrophs. However, whether pathways of electron delivery to nitrogenase are influenced by these different metabolic backgrounds is not well understood. Here, we report the distribution of homologs of Fds, Flds, and Fd/Fld-reducing enzymes in 359 genomes of putative N 2 fixers (diazotrophs). Six distinct lineages of nitrogenase were identified and their distributions largely corresponded to differences in the host cells' ability to integrate O 2 or light into energy metabolism. Predicted pathways of electron transfer to nitrogenase in aerobes, facultative anaerobes, and phototrophs varied from those in anaerobes at the level of Fds/Flds used to reduce nitrogenase, the enzymes that generate reduced Fds/Flds, and the putative substrates of these enzymes. Proteins that putatively reduce Fd with hydrogen or pyruvate were enriched in anaerobes, while those that reduce Fd with NADH/NADPH were enriched in aerobes, facultative anaerobes, and anoxygenic phototrophs. The energy metabolism of aerobic, facultatively anaerobic, and anoxygenic phototrophic diazotrophs often yields reduced NADH/NADPH that is not sufficiently reduced to drive N 2 reduction. At least two mechanisms have been acquired by these taxa to overcome this limitation and to generate electrons with potentials capable of reducing Fd. These include the bifurcation of electrons or the coupling of Fd reduction to reverse ion translocation. IMPORTANCE Nitrogen fixation supplies fixed nitrogen to cells from a variety of genomic and metabolic backgrounds including those of aerobes, facultative anaerobes, chemotrophs, and phototrophs

Dynamics of Dark-Fly Genome Under Environmental Selections

PubMed Central

Izutsu, Minako; Toyoda, Atsushi; Fujiyama, Asao; Agata, Kiyokazu; Fuse, Naoyuki

2015-01-01

Environmental adaptation is one of the most fundamental features of organisms. Modern genome science has identified some genes associated with adaptive traits of organisms, and has provided insights into environmental adaptation and evolution. However, how genes contribute to adaptive traits and how traits are selected under an environment in the course of evolution remain mostly unclear. To approach these issues, we utilize “Dark-fly”, a Drosophila melanogaster line maintained in constant dark conditions for more than 60 years. Our previous analysis identified 220,000 single nucleotide polymorphisms (SNPs) in the Dark-fly genome, but did not clarify which SNPs of Dark-fly are truly adaptive for living in the dark. We found here that Dark-fly dominated over the wild-type fly in a mixed population under dark conditions, and based on this domination we designed an experiment for genome reselection to identify adaptive genes of Dark-fly. For this experiment, large mixed populations of Dark-fly and the wild-type fly were maintained in light conditions or in dark conditions, and the frequencies of Dark-fly SNPs were compared between these populations across the whole genome. We thereby detected condition-dependent selections toward approximately 6% of the genome. In addition, we observed the time-course trajectory of SNP frequency in the mixed populations through generations 0, 22, and 49, which resulted in notable categorization of the selected SNPs into three types with different combinations of positive and negative selections. Our data provided a list of about 100 strong candidate genes associated with the adaptive traits of Dark-fly. PMID:26637434

Assessing genomic selection prediction accuracy in a dynamic barley breeding

USDA-ARS?s Scientific Manuscript database

Genomic selection is a method to improve quantitative traits in crops and livestock by estimating breeding values of selection candidates using phenotype and genome-wide marker data sets. Prediction accuracy has been evaluated through simulation and cross-validation, however validation based on prog...

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

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

Dynamics of Dark-Fly Genome Under Environmental Selections.

PubMed

Izutsu, Minako; Toyoda, Atsushi; Fujiyama, Asao; Agata, Kiyokazu; Fuse, Naoyuki

2015-12-04

Environmental adaptation is one of the most fundamental features of organisms. Modern genome science has identified some genes associated with adaptive traits of organisms, and has provided insights into environmental adaptation and evolution. However, how genes contribute to adaptive traits and how traits are selected under an environment in the course of evolution remain mostly unclear. To approach these issues, we utilize "Dark-fly", a Drosophila melanogaster line maintained in constant dark conditions for more than 60 years. Our previous analysis identified 220,000 single nucleotide polymorphisms (SNPs) in the Dark-fly genome, but did not clarify which SNPs of Dark-fly are truly adaptive for living in the dark. We found here that Dark-fly dominated over the wild-type fly in a mixed population under dark conditions, and based on this domination we designed an experiment for genome reselection to identify adaptive genes of Dark-fly. For this experiment, large mixed populations of Dark-fly and the wild-type fly were maintained in light conditions or in dark conditions, and the frequencies of Dark-fly SNPs were compared between these populations across the whole genome. We thereby detected condition-dependent selections toward approximately 6% of the genome. In addition, we observed the time-course trajectory of SNP frequency in the mixed populations through generations 0, 22, and 49, which resulted in notable categorization of the selected SNPs into three types with different combinations of positive and negative selections. Our data provided a list of about 100 strong candidate genes associated with the adaptive traits of Dark-fly. Copyright © 2016 Izutsu et al.

Accuracy of genomic selection in European maize elite breeding populations.

PubMed

Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C

2012-03-01

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

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

The locus of sexual selection: moving sexual selection studies into the post-genomics era.

PubMed

Wilkinson, G S; Breden, F; Mank, J E; Ritchie, M G; Higginson, A D; Radwan, J; Jaquiery, J; Salzburger, W; Arriero, E; Barribeau, S M; Phillips, P C; Renn, S C P; Rowe, L

2015-04-01

Sexual selection drives fundamental evolutionary processes such as trait elaboration and speciation. Despite this importance, there are surprisingly few examples of genes unequivocally responsible for variation in sexually selected phenotypes. This lack of information inhibits our ability to predict phenotypic change due to universal behaviours, such as fighting over mates and mate choice. Here, we discuss reasons for this apparent gap and provide recommendations for how it can be overcome by adopting contemporary genomic methods, exploiting underutilized taxa that may be ideal for detecting the effects of sexual selection and adopting appropriate experimental paradigms. Identifying genes that determine variation in sexually selected traits has the potential to improve theoretical models and reveal whether the genetic changes underlying phenotypic novelty utilize common or unique molecular mechanisms. Such a genomic approach to sexual selection will help answer questions in the evolution of sexually selected phenotypes that were first asked by Darwin and can furthermore serve as a model for the application of genomics in all areas of evolutionary biology. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

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.

Genome-wide association analysis of bacterial cold water disease resistance in rainbow trout reveals the potential of a hybrid approach between genomic selection and marker assisted selection

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) simultaneously incorporates dense SNP marker genotypes with phenotypic data from related animals to predict animal-specific genomic breeding value (GEBV), which circumvents the need to measure the disease phenotype in potential breeders. Marker assisted selection (MAS) involv...

Genomic Selection Improves Heat Tolerance in Dairy Cattle

PubMed Central

Garner, J. B.; Douglas, M. L.; Williams, S. R. O; Wales, W. J.; Marett, L. C.; Nguyen, T. T. T.; Reich, C. M.; Hayes, B. J.

2016-01-01

Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events. PMID:27682591

Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops.

PubMed

Jonas, Elisabeth; de Koning, Dirk Jan

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.

Changes in Malaria Parasite Drug Resistance in an Endemic Population Over a 25-Year Period With Resulting Genomic Evidence of Selection

PubMed Central

Nwakanma, Davis C.; Duffy, Craig W.; Amambua-Ngwa, Alfred; Oriero, Eniyou C.; Bojang, Kalifa A.; Pinder, Margaret; Drakeley, Chris J.; Sutherland, Colin J.; Milligan, Paul J.; MacInnis, Bronwyn; Kwiatkowski, Dominic P.; Clark, Taane G.; Greenwood, Brian M.; Conway, David J.

2014-01-01

Background. Analysis of genome-wide polymorphism in many organisms has potential to identify genes under recent selection. However, data on historical allele frequency changes are rarely available for direct confirmation. Methods. We genotyped single nucleotide polymorphisms (SNPs) in 4 Plasmodium falciparum drug resistance genes in 668 archived parasite-positive blood samples of a Gambian population between 1984 and 2008. This covered a period before antimalarial resistance was detected locally, through subsequent failure of multiple drugs until introduction of artemisinin combination therapy. We separately performed genome-wide sequence analysis of 52 clinical isolates from 2008 to prospect for loci under recent directional selection. Results. Resistance alleles increased from very low frequencies, peaking in 2000 for chloroquine resistance-associated crt and mdr1 genes and at the end of the survey period for dhfr and dhps genes respectively associated with pyrimethamine and sulfadoxine resistance. Temporal changes fit a model incorporating likely selection coefficients over the period. Three of the drug resistance loci were in the top 4 regions under strong selection implicated by the genome-wide analysis. Conclusions. Genome-wide polymorphism analysis of an endemic population sample robustly identifies loci with detailed documentation of recent selection, demonstrating power to prospectively detect emerging drug resistance genes. PMID:24265439

A Genomic Selection Index Applied to Simulated and Real Data

PubMed Central

Ceron-Rojas, J. Jesus; Crossa, José; Arief, Vivi N.; Basford, Kaye; Rutkoski, Jessica; Jarquín, Diego; Alvarado, Gregorio; Beyene, Yoseph; Semagn, Kassa; DeLacy, Ian

2015-01-01

A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to estimate the GSI selection response and the GSI expected genetic gain per selection cycle for the unobserved traits after the first selection cycle to obtain information about the genetic gains in each subsequent selection cycle. In this paper, we develop the theory of a GSI and apply it to two simulated and four real data sets with four traits. Also, we numerically compare its efficiency with that of the phenotypic selection index (PSI) by using the ratio of the GSI response over the PSI response, and the PSI and GSI expected genetic gain per selection cycle for observed and unobserved traits, respectively. In addition, we used the Technow inequality to compare GSI vs. PSI efficiency. Results from the simulated data were confirmed by the real data, indicating that GSI was more efficient than PSI per unit of time. PMID:26290571

solGS: a web-based tool for genomic selection

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, ana...

Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

PubMed

Muley, Vijaykumar Yogesh; Ranjan, Akash

2012-01-01

Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. Higher performance for predicting protein-protein interactions was achievable even with 100-150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling allows for selecting 50-100 genomes for comparable

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Lemarié, S; Fugeray-Scarbel, A; Elsen, J M

2016-06-01

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous

Genomic selection for quantitative adult plant stem rust resistance in wheat

USDA-ARS?s Scientific Manuscript database

Quantitative adult plant resistance (APR) to stem rust (Puccinia graminis f. sp. tritici) is an important breeding target in wheat (Triticum aestivum L.) and a potential target for genomic selection (GS). To evaluate the relative importance of known APR loci in applying genomic selection, we charact...

Genomic signatures of positive selection in humans and the limits of outlier approaches.

PubMed

Kelley, Joanna L; Madeoy, Jennifer; Calhoun, John C; Swanson, Willie; Akey, Joshua M

2006-08-01

Identifying regions of the human genome that have been targets of positive selection will provide important insights into recent human evolutionary history and may facilitate the search for complex disease genes. However, the confounding effects of population demographic history and selection on patterns of genetic variation complicate inferences of selection when a small number of loci are studied. To this end, identifying outlier loci from empirical genome-wide distributions of genetic variation is a promising strategy to detect targets of selection. Here, we evaluate the power and efficiency of a simple outlier approach and describe a genome-wide scan for positive selection using a dense catalog of 1.58 million SNPs that were genotyped in three human populations. In total, we analyzed 14,589 genes, 385 of which possess patterns of genetic variation consistent with the hypothesis of positive selection. Furthermore, several extended genomic regions were found, spanning >500 kb, that contained multiple contiguous candidate selection genes. More generally, these data provide important practical insights into the limits of outlier approaches in genome-wide scans for selection, provide strong candidate selection genes to study in greater detail, and may have important implications for disease related research.

Reproductive technologies combine well with genomic selection in dairy breeding programs.

PubMed

Thomasen, J R; Willam, A; Egger-Danner, C; Sørensen, A C

2016-02-01

The objective of the present study was to examine whether genomic selection of females interacts with the use of reproductive technologies (RT) to increase annual monetary genetic gain (AMGG). This was tested using a factorial design with 3 factors: genomic selection of females (0 or 2,000 genotyped heifers per year), RT (0 or 50 donors selected at 14 mo of age for producing 10 offspring), and 2 reliabilities of genomic prediction. In addition, different strategies for use of RT and how strategies interact with the reliability of genomic prediction were investigated using stochastic simulation by varying (1) number of donors (25, 50, 100, 200), (2) number of calves born per donor (10 or 20), (3) age of donor (2 or 14 mo), and (4) number of sires (25, 50, 100, 200). In total, 72 different breeding schemes were investigated. The profitability of the different breeding strategies was evaluated by deterministic simulation by varying the costs of a born calf with reproductive technologies at levels of €500, €1,000, and €1,500. The results confirm our hypothesis that combining genomic selection of females with use of RT increases AMGG more than in a reference scheme without genomic selection in females. When the reliability of genomic prediction is high, the effect on rate of inbreeding (ΔF) is small. The study also demonstrates favorable interaction effects between the components of the breeder's equation (selection intensity, selection accuracy, generation interval) for the bull dam donor path, leading to higher AMGG. Increasing the donor program and number of born calves to achieve higher AMGG is associated with the undesirable effect of increased ΔF. This can be alleviated, however, by increasing the numbers of sires without compromising AMGG remarkably. For the major part of the investigated donor schemes, the investment in RT is profitable in dairy cattle populations, even at high levels of costs for RT. Copyright © 2016 American Dairy Science Association

Application of selection index calculations to determine selection strategies in genomic breeding programs.

PubMed

König, S; Swalve, H H

2009-10-01

The availability of genomic estimated breeding values (GEBV) allows for possible modifications to existing dairy cattle breeding programs. Selection index calculations including genomic and phenotypic observations as index sources were used to determine the optimal number of offspring per genotyped sire with a focus on functional traits and the design of cooperator herds, and to evaluate the importance of a central station test for genotyped bull dams. Evaluation criteria to compare different breeding strategies were correlations between index and aggregate genotype (r(TI)), and the relative selection response percentage (RSR) of an index without single nucleotide polymorphism information in relation to a single nucleotide polymorphism-based index. The number of required daughter records per sire to achieve a predefined r(TI) strongly depends on the accuracy of GEBV (r(mg)) and the heritability of the trait. For a desired r(TI) of 0.8, h(2) = 0.10, and r(mg) = 0.5, at least 57 additional daughters have to be included in the genetic evaluation. Daughter records of genotyped sires are not necessary for optimal scenarios where r(mg) is greater than or equal to r(TI). There still is a substantial need for phenotypic daughter records, especially for low-heritability functional traits and r(mg) < 0.7. Phenotypic records from genotyped potential bull dams have no relevance for increasing r(TI), even with a low value for r(mg) of 0.5. Hence, genomic breeding programs should focus on recording functional traits within progeny groups, preferably in cooperator herds. For low-heritability traits and with r(mg) > 0.7, the RSR of conventional breeding programs was only 10% of RSR from genomic breeding strategies. As shown in scenarios including 2 traits in the index as well as in the aggregate genotype, the availability of highly accurate GEBV for production traits and low-accuracy GEBV for functional traits increased the risk of widening the gap between selection responses in

Application of genomic selection in farm animal breeding.

PubMed

Tan, Cheng; Bian, Cheng; Yang, Da; Li, Ning; Wu, Zhen-Fang; Hu, Xiao-Xiang

2017-11-20

Genomic selection (GS) has become a widely accepted method in animal breeding to genetically improve economic traits. With the declining costs of high-density SNP chips and next-generation sequencing, GS has been applied in dairy cattle, swine, poultry and other animals and gained varying degrees of success. Currently, major challenges in GS studies include further reducing the cost of genome-wide SNP genotyping and improving the predictive accuracy of genomic estimated breeding value (GEBV). In this review, we summarize various methods for genome-wide SNP genotyping and GEBV prediction, and give a brief introduction of GS in livestock and poultry breeding. This review will provide a reference for further implementation of GS in farm animal breeding.

Genome-wide evidence for divergent selection between populations of a major agricultural pathogen.

PubMed

Hartmann, Fanny E; McDonald, Bruce A; Croll, Daniel

2018-06-01

The genetic and environmental homogeneity in agricultural ecosystems is thought to impose strong and uniform selection pressures. However, the impact of this selection on plant pathogen genomes remains largely unknown. We aimed to identify the proportion of the genome and the specific gene functions under positive selection in populations of the fungal wheat pathogen Zymoseptoria tritici. First, we performed genome scans in four field populations that were sampled from different continents and on distinct wheat cultivars to test which genomic regions are under recent selection. Based on extended haplotype homozygosity and composite likelihood ratio tests, we identified 384 and 81 selective sweeps affecting 4% and 0.5% of the 35 Mb core genome, respectively. We found differences both in the number and the position of selective sweeps across the genome between populations. Using a XtX-based outlier detection approach, we identified 51 extremely divergent genomic regions between the allopatric populations, suggesting that divergent selection led to locally adapted pathogen populations. We performed an outlier detection analysis between two sympatric populations infecting two different wheat cultivars to identify evidence for host-driven selection. Selective sweep regions harboured genes that are likely to play a role in successfully establishing host infections. We also identified secondary metabolite gene clusters and an enrichment in genes encoding transporter and protein localization functions. The latter gene functions mediate responses to environmental stress, including interactions with the host. The distinct gene functions under selection indicate that both local host genotypes and abiotic factors contributed to local adaptation. © 2018 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Perspectives for genomic selection applications and research in plants

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) has created a lot of excitement and expectations in the animal and plant breeding research communities. In this review, we briefly describe how genomic prediction can be integrated into breeding efforts and point out achievements and areas where more research is needed. GS pro...

Genomic selection signatures in sheep from the Western Pyrenees.

PubMed

Ruiz-Larrañaga, Otsanda; Langa, Jorge; Rendo, Fernando; Manzano, Carmen; Iriondo, Mikel; Estonba, Andone

2018-03-22

The current large spectrum of sheep phenotypic diversity results from the combined product of sheep selection for different production traits such as wool, milk and meat, and its natural adaptation to new environments. In this study, we scanned the genome of 25 Sasi Ardi and 75 Latxa sheep from the Western Pyrenees for three types of regions under selection: (1) regions underlying local adaptation of Sasi Ardi semi-feral sheep, (2) regions related to a long traditional dairy selection pressure in Latxa sheep, and (3) regions experiencing the specific effect of the modern genetic improvement program established for the Latxa breed during the last three decades. Thirty-two selected candidate regions including 147 annotated genes were detected by using three statistical parameters: pooled heterozygosity H, Tajima's D, and Wright's fixation index F st . For Sasi Ardi sheep, chromosomes Ovis aries (OAR)4, 6, and 22 showed the strongest signals and harbored several candidate genes related to energy metabolism and morphology (BBS9, ELOVL3 and LDB1), immunity (NFKB2), and reproduction (H2AFZ). The major genomic difference between Sasi Ardi and Latxa sheep was on OAR6, which is known to affect milk production, with highly selected regions around the ABCG2, SPP1, LAP3, NCAPG, LCORL, and MEPE genes in Latxa sheep. The effect of the modern genetic improvement program on Latxa sheep was also evident on OAR15, on which several olfactory genes are located. We also detected several genes involved in reproduction such as ESR1 and ZNF366 that were affected by this selection program. Natural and artificial selection have shaped the genome of both Sasi Ardi and Latxa sheep. Our results suggest that Sasi Ardi traits related to energy metabolism, morphological, reproductive, and immunological features have been under positive selection to adapt this semi-feral sheep to its particular environment. The highly selected Latxa sheep for dairy production showed clear signatures of selection

Combining genomic selection and gene identification for crop improvement

USDA-ARS?s Scientific Manuscript database

The use of genetic information to predict the value of individuals in plant breeding populations began about 40 years ago. The original paradigm was to identify genomic regions with outsize influence on a trait of economic value, then to use markers in that genomic region to select individuals carry...

Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia

PubMed Central

Iwata, Hiroyoshi; Hayashi, Takeshi; Terakami, Shingo; Takada, Norio; Sawamura, Yutaka; Yamamoto, Toshiya

2013-01-01

Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding with 76 Japanese pear cultivars to detect significant associations of 162 markers with nine agronomic traits. We applied multilocus Bayesian models accounting for ordinal categorical phenotypes for GWAS and GS model training. Significant associations were detected at harvest time, black spot resistance and the number of spurs and two of the associations were closely linked to known loci. Genome-wide predictions for GS were accurate at the highest level (0.75) in harvest time, at medium levels (0.38–0.61) in resistance to black spot, firmness of flesh, fruit shape in longitudinal section, fruit size, acid content and number of spurs and at low levels (<0.2) in all soluble solid content and vigor of tree. Results suggest the potential of GWAS and GS for use in future breeding programs in Japanese pear. PMID:23641189

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Genomic signatures of selection at linked sites: unifying the disparity among species

PubMed Central

Cutter, Asher D.; Payseur, Bret A.

2014-01-01

Population genetics theory supplies powerful predictions about how natural selection interacts with genetic linkage to sculpt the genomic landscape of nucleotide polymorphism. Both the spread of beneficial mutations and removal of deleterious mutations act to depress polymorphism levels, especially in low-recombination regions. However, empiricists have documented extreme disparities among species. Here we characterize the dominant features that could drive variation in linked selection among species, including roles for selective sweeps being ‘hard’ or ‘soft’, and concealing by demography and genomic confounds. We advocate targeted studies of close relatives to unify our understanding of how selection and linkage interact to shape genome evolution. PMID:23478346

Genomic Signature of Kin Selection in an Ant with Obligately Sterile Workers

PubMed Central

Warner, Michael R.; Mikheyev, Alexander S.

2017-01-01

Abstract Kin selection is thought to drive the evolution of cooperation and conflict, but the specific genes and genome-wide patterns shaped by kin selection are unknown. We identified thousands of genes associated with the sterile ant worker caste, the archetype of an altruistic phenotype shaped by kin selection, and then used population and comparative genomic approaches to study patterns of molecular evolution at these genes. Consistent with population genetic theoretical predictions, worker-upregulated genes experienced reduced selection compared with genes upregulated in reproductive castes. Worker-upregulated genes included more taxonomically restricted genes, indicating that the worker caste has recruited more novel genes, yet these genes also experienced reduced selection. Our study identifies a putative genomic signature of kin selection and helps to integrate emerging sociogenomic data with longstanding social evolution theory. PMID:28419349

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

PubMed

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

PubMed Central

Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

2015-01-01

The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

Identifying artificial selection signals in the chicken genome.

PubMed

Ma, Yunlong; Gu, Lantao; Yang, Liubin; Sun, Chenghao; Xie, Shengsong; Fang, Chengchi; Gong, Yangzhang; Li, Shijun

2018-01-01

Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF), Jinghong (JH), Araucanas (AR), White Leghorn (WL), Pekin-Bantam (PB), Shamo (SH), Gallus-Gallus-Spadiceus (GA), Rheinlander (RH) and Vorwerkhuhn (VO). Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a 'two-step' strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study.

Detection of genomic signatures of recent selection in commercial broiler chickens.

PubMed

Fu, Weixuan; Lee, William R; Abasht, Behnam

2016-08-26

Identification of the genomic signatures of recent selection may help uncover causal polymorphisms controlling traits relevant to recent decades of selective breeding in livestock. In this study, we aimed at detecting signatures of recent selection in commercial broiler chickens using genotype information from single nucleotide polymorphisms (SNPs). A total of 565 chickens from five commercial purebred lines, including three broiler sire (male) lines and two broiler dam (female) lines, were genotyped using the 60K SNP Illumina iSelect chicken array. To detect genomic signatures of recent selection, we applied two methods based on population comparison, cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio (XP-CLR), and further analyzed the results to find genomic regions under recent selection in multiple purebred lines. A total of 321 candidate selection regions spanning approximately 1.45 % of the chicken genome in each line were detected by consensus of results of both XP-EHH and XP-CLR methods. To minimize false discovery due to genetic drift, only 42 of the candidate selection regions that were shared by 2 or more purebred lines were considered as high-confidence selection regions in the study. Of these 42 regions, 20 were 50 kb or less while 4 regions were larger than 0.5 Mb. In total, 91 genes could be found in the 42 regions, among which 19 regions contained only 1 or 2 genes, and 9 regions were located at gene deserts. Our results provide a genome-wide scan of recent selection signatures in five purebred lines of commercial broiler chickens. We found several candidate genes for recent selection in multiple lines, such as SOX6 (Sex Determining Region Y-Box 6) and cTR (Thyroid hormone receptor beta). These genes may have been under recent selection due to their essential roles in growth, development and reproduction in chickens. Furthermore, our results suggest that in some candidate regions, the same or

Imputation of unordered markers and the impact on genomic selection accuracy

USDA-ARS?s Scientific Manuscript database

Genomic selection, a breeding method that promises to accelerate rates of genetic gain, requires dense, genome-wide marker data. Genotyping-by-sequencing can generate a large number of de novo markers. However, without a reference genome, these markers are unordered and typically have a large propo...

Tracking footprints of artificial selection in the dog genome.

PubMed

Akey, Joshua M; Ruhe, Alison L; Akey, Dayna T; Wong, Aaron K; Connelly, Caitlin F; Madeoy, Jennifer; Nicholas, Thomas J; Neff, Mark W

2010-01-19

The size, shape, and behavior of the modern domesticated dog has been sculpted by artificial selection for at least 14,000 years. The genetic substrates of selective breeding, however, remain largely unknown. Here, we describe a genome-wide scan for selection in 275 dogs from 10 phenotypically diverse breeds that were genotyped for over 21,000 autosomal SNPs. We identified 155 genomic regions that possess strong signatures of recent selection and contain candidate genes for phenotypes that vary most conspicuously among breeds, including size, coat color and texture, behavior, skeletal morphology, and physiology. In addition, we demonstrate a significant association between HAS2 and skin wrinkling in the Shar-Pei, and provide evidence that regulatory evolution has played a prominent role in the phenotypic diversification of modern dog breeds. Our results provide a first-generation map of selection in the dog, illustrate how such maps can rapidly inform the genetic basis of canine phenotypic variation, and provide a framework for delineating the mechanistic basis of how artificial selection promotes rapid and pronounced phenotypic evolution.

Prospects for genomic selection in cassava breeding

USDA-ARS?s Scientific Manuscript database

Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa in order to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on p...

Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones

USGS Publications Warehouse

Kovach, Ryan P.; Hand, Brian K.; Hohenlohe, Paul A.; Cosart, Ted F.; Boyer, Matthew C.; Neville, Helen H.; Muhlfeld, Clint C.; Amish, Stephen J.; Carim, Kellie; Narum, Shawn R.; Lowe, Winsor H.; Allendorf, Fred W.; Luikart, Gordon

2016-01-01

Evolutionary and ecological consequences of hybridization between native and invasive species are notoriously complicated because patterns of selection acting on non-native alleles can vary throughout the genome and across environments. Rapid advances in genomics now make it feasible to assess locus-specific and genome-wide patterns of natural selection acting on invasive introgression within and among natural populations occupying diverse environments. We quantified genome-wide patterns of admixture across multiple independent hybrid zones of native westslope cutthroat trout and invasive rainbow trout, the world's most widely introduced fish, by genotyping 339 individuals from 21 populations using 9380 species-diagnostic loci. A significantly greater proportion of the genome appeared to be under selection favouring native cutthroat trout (rather than rainbow trout), and this pattern was pervasive across the genome (detected on most chromosomes). Furthermore, selection against invasive alleles was consistent across populations and environments, even in those where rainbow trout were predicted to have a selective advantage (warm environments). These data corroborate field studies showing that hybrids between these species have lower fitness than the native taxa, and show that these fitness differences are due to selection favouring many native genes distributed widely throughout the genome.

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs

PubMed Central

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios. PMID

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.

PubMed

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios.

Resolving the Conflict Between Associative Overdominance and Background Selection

PubMed Central

Zhao, Lei; Charlesworth, Brian

2016-01-01

In small populations, genetic linkage between a polymorphic neutral locus and loci subject to selection, either against partially recessive mutations or in favor of heterozygotes, may result in an apparent selective advantage to heterozygotes at the neutral locus (associative overdominance) and a retardation of the rate of loss of variability by genetic drift at this locus. In large populations, selection against deleterious mutations has previously been shown to reduce variability at linked neutral loci (background selection). We describe analytical, numerical, and simulation studies that shed light on the conditions under which retardation vs. acceleration of loss of variability occurs at a neutral locus linked to a locus under selection. We consider a finite, randomly mating population initiated from an infinite population in equilibrium at a locus under selection. With mutation and selection, retardation occurs only when S, the product of twice the effective population size and the selection coefficient, is of order 1. With S >> 1, background selection always causes an acceleration of loss of variability. Apparent heterozygote advantage at the neutral locus is, however, always observed when mutations are partially recessive, even if there is an accelerated rate of loss of variability. With heterozygote advantage at the selected locus, loss of variability is nearly always retarded. The results shed light on experiments on the loss of variability at marker loci in laboratory populations and on the results of computer simulations of the effects of multiple selected loci on neutral variability. PMID:27182952

Genomic Signatures Reveal New Evidences for Selection of Important Traits in Domestic Cattle

PubMed Central

Xu, Lingyang; Bickhart, Derek M.; Cole, John B.; Schroeder, Steven G.; Song, Jiuzhou; Tassell, Curtis P. Van; Sonstegard, Tad S.; Liu, George E.

2015-01-01

We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health. PMID:25431480

Genomic selection in forage breeding: designing an estimation population

USDA-ARS?s Scientific Manuscript database

The benefits of genomic selection to livestock, crops and forest tree breeding can be extended to forage grasses and legumes. The main benefits expected are increased selection accuracy and reduced costs per unit of genotype evaluated and breeding cycle length. Aiming at designing a training populat...

Genome-wide patterns of selection in 230 ancient Eurasians

PubMed Central

Mathieson, Iain; Lazaridis, Iosif; Rohland, Nadin; Mallick, Swapan; Patterson, Nick; Roodenberg, Songül Alpaslan; Harney, Eadaoin; Stewardson, Kristin; Fernandes, Daniel; Novak, Mario; Sirak, Kendra; Gamba, Cristina; Jones, Eppie R.; Llamas, Bastien; Dryomov, Stanislav; Pickrel, Joseph; Arsuaga, Juan Luís; de Castro, José María Bermúdez; Carbonell, Eudald; Gerritsen, Fokke; Khokhlov, Aleksandr; Kuznetsov, Pavel; Lozano, Marina; Meller, Harald; Mochalov, Oleg; Moiseyev, Vayacheslav; Rojo Guerra, Manuel A.; Roodenberg, Jacob; Vergès, Josep Maria; Krause, Johannes; Cooper, Alan; Alt, Kurt W.; Brown, Dorcas; Anthony, David; Lalueza-Fox, Carles; Haak, Wolfgang; Pinhasi, Ron; Reich, David

2016-01-01

Ancient DNA makes it possible to directly witness natural selection by analyzing samples from populations before, during and after adaptation events. Here we report the first scan for selection using ancient DNA, capitalizing on the largest genome-wide dataset yet assembled: 230 West Eurasians dating to between 6500 and 1000 BCE, including 163 with newly reported data. The new samples include the first genome-wide data from the Anatolian Neolithic culture whose genetic material we extracted from the DNA-rich petrous bone and who we show were members of the population that was the source of Europe’s first farmers. We also report a complete transect of the steppe region in Samara between 5500 and 1200 BCE that allows us to recognize admixture from at least two external sources into steppe populations during this period. We detect selection at loci associated with diet, pigmentation and immunity, and two independent episodes of selection on height. PMID:26595274

Improving the baking quality of bread wheat by genomic selection in early generations.

PubMed

Michel, Sebastian; Kummer, Christian; Gallee, Martin; Hellinger, Jakob; Ametz, Christian; Akgöl, Batuhan; Epure, Doru; Güngör, Huseyin; Löschenberger, Franziska; Buerstmayr, Hermann

2018-02-01

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

Positive Selection Driving Cytoplasmic Genome Evolution of the Medicinally Important Ginseng Plant Genus Panax.

PubMed

Jiang, Peng; Shi, Feng-Xue; Li, Ming-Rui; Liu, Bao; Wen, Jun; Xiao, Hong-Xing; Li, Lin-Feng

2018-01-01

Panax L. (the ginseng genus) is a shade-demanding group within the family Araliaceae and all of its species are of crucial significance in traditional Chinese medicine. Phylogenetic and biogeographic analyses demonstrated that two rounds of whole genome duplications accompanying with geographic and ecological isolations promoted the diversification of Panax species. However, contributions of the cytoplasmic genomes to the adaptive evolution of Panax species remained largely uninvestigated. In this study, we sequenced the chloroplast and mitochondrial genomes of 11 accessions belonging to seven Panax species. Our results show that heterogeneity in nucleotide substitution rate is abundant in both of the two cytoplasmic genomes, with the mitochondrial genome possessing more variants at the total level but the chloroplast showing higher sequence polymorphisms at the genic regions. Genome-wide scanning of positive selection identified five and 12 genes from the chloroplast and mitochondrial genomes, respectively. Functional analyses further revealed that these selected genes play important roles in plant development, cellular metabolism and adaptation. We therefore conclude that positive selection might be one of the potential evolutionary forces that shaped nucleotide variation pattern of these Panax species. In particular, the mitochondrial genes evolved under stronger selective pressure compared to the chloroplast genes.

Accuracy of genomic selection for BCWD resistance in rainbow trout

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant economic losses in salmonids. In this study, we aimed to (1) predict genomic breeding values (GEBV) by genotyping training (n=583) and validation samples (n=53) with a SNP50K chip; and (2) assess the accuracy of genomic selection (GS) for BCWD r...

Trait variation and genetic diversity in a banana genomic selection training population

PubMed Central

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents. PMID:28586365

Trait variation and genetic diversity in a banana genomic selection training population.

PubMed

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim; Doležel, Jaroslav

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31-35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

Signatures of Long-Term Balancing Selection in Human Genomes

PubMed Central

de Filippo, Cesare; Teixeira, João C; Schmidt, Joshua M; Kleinert, Philip; Meyer, Diogo; Andrés, Aida M

2018-01-01

Abstract Balancing selection maintains advantageous diversity in populations through various mechanisms. Although extensively explored from a theoretical perspective, an empirical understanding of its prevalence and targets lags behind our knowledge of positive selection. Here, we describe the Non-central Deviation (NCD), a simple yet powerful statistic to detect long-term balancing selection (LTBS) that quantifies how close frequencies are to expectations under LTBS, and provides the basis for a neutrality test. NCD can be applied to a single locus or genomic data, and can be implemented considering only polymorphisms (NCD1) or also considering fixed differences with respect to an outgroup (NCD2) species. Incorporating fixed differences improves power, and NCD2 has higher power to detect LTBS in humans under different frequencies of the balanced allele(s) than other available methods. Applied to genome-wide data from African and European human populations, in both cases using chimpanzee as an outgroup, NCD2 shows that, albeit not prevalent, LTBS affects a sizable portion of the genome: ∼0.6% of analyzed genomic windows and 0.8% of analyzed positions. Significant windows (P < 0.0001) contain 1.6% of SNPs in the genome, which disproportionally fall within exons and change protein sequence, but are not enriched in putatively regulatory sites. These windows overlap ∼8% of the protein-coding genes, and these have larger number of transcripts than expected by chance even after controlling for gene length. Our catalog includes known targets of LTBS but a majority of them (90%) are novel. As expected, immune-related genes are among those with the strongest signatures, although most candidates are involved in other biological functions, suggesting that LTBS potentially influences diverse human phenotypes. PMID:29608730

A Ranking Approach to Genomic Selection.

PubMed

Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

PubMed

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Genomic selection for fruit quality traits in apple (Malus×domestica Borkh.).

PubMed

Kumar, Satish; Chagné, David; Bink, Marco C A M; Volz, Richard K; Whitworth, Claire; Carlisle, Charmaine

2012-01-01

The genome sequence of apple (Malus×domestica Borkh.) was published more than a year ago, which helped develop an 8K SNP chip to assist in implementing genomic selection (GS). In apple breeding programmes, GS can be used to obtain genomic breeding values (GEBV) for choosing next-generation parents or selections for further testing as potential commercial cultivars at a very early stage. Thus GS has the potential to accelerate breeding efficiency significantly because of decreased generation interval or increased selection intensity. We evaluated the accuracy of GS in a population of 1120 seedlings generated from a factorial mating design of four females and two male parents. All seedlings were genotyped using an Illumina Infinium chip comprising 8,000 single nucleotide polymorphisms (SNPs), and were phenotyped for various fruit quality traits. Random-regression best liner unbiased prediction (RR-BLUP) and the Bayesian LASSO method were used to obtain GEBV, and compared using a cross-validation approach for their accuracy to predict unobserved BLUP-BV. Accuracies were very similar for both methods, varying from 0.70 to 0.90 for various fruit quality traits. The selection response per unit time using GS compared with the traditional BLUP-based selection were very high (>100%) especially for low-heritability traits. Genome-wide average estimated linkage disequilibrium (LD) between adjacent SNPs was 0.32, with a relatively slow decay of LD in the long range (r(2) = 0.33 and 0.19 at 100 kb and 1,000 kb respectively), contributing to the higher accuracy of GS. Distribution of estimated SNP effects revealed involvement of large effect genes with likely pleiotropic effects. These results demonstrated that genomic selection is a credible alternative to conventional selection for fruit quality traits.

Positive Selection Driving Cytoplasmic Genome Evolution of the Medicinally Important Ginseng Plant Genus Panax

PubMed Central

Jiang, Peng; Shi, Feng-Xue; Li, Ming-Rui; Liu, Bao; Wen, Jun; Xiao, Hong-Xing; Li, Lin-Feng

2018-01-01

Panax L. (the ginseng genus) is a shade-demanding group within the family Araliaceae and all of its species are of crucial significance in traditional Chinese medicine. Phylogenetic and biogeographic analyses demonstrated that two rounds of whole genome duplications accompanying with geographic and ecological isolations promoted the diversification of Panax species. However, contributions of the cytoplasmic genomes to the adaptive evolution of Panax species remained largely uninvestigated. In this study, we sequenced the chloroplast and mitochondrial genomes of 11 accessions belonging to seven Panax species. Our results show that heterogeneity in nucleotide substitution rate is abundant in both of the two cytoplasmic genomes, with the mitochondrial genome possessing more variants at the total level but the chloroplast showing higher sequence polymorphisms at the genic regions. Genome-wide scanning of positive selection identified five and 12 genes from the chloroplast and mitochondrial genomes, respectively. Functional analyses further revealed that these selected genes play important roles in plant development, cellular metabolism and adaptation. We therefore conclude that positive selection might be one of the potential evolutionary forces that shaped nucleotide variation pattern of these Panax species. In particular, the mitochondrial genes evolved under stronger selective pressure compared to the chloroplast genes. PMID:29670636

Impairment of organ-specific T cell negative selection by diabetes susceptibility genes: genomic analysis by mRNA profiling

PubMed Central

Liston, Adrian; Hardy, Kristine; Pittelkow, Yvonne; Wilson, Susan R; Makaroff, Lydia E; Fahrer, Aude M; Goodnow, Christopher C

2007-01-01

Background T cells in the thymus undergo opposing positive and negative selection processes so that the only T cells entering circulation are those bearing a T cell receptor (TCR) with a low affinity for self. The mechanism differentiating negative from positive selection is poorly understood, despite the fact that inherited defects in negative selection underlie organ-specific autoimmune disease in AIRE-deficient people and the non-obese diabetic (NOD) mouse strain Results Here we use homogeneous populations of T cells undergoing either positive or negative selection in vivo together with genome-wide transcription profiling on microarrays to identify the gene expression differences underlying negative selection to an Aire-dependent organ-specific antigen, including the upregulation of a genomic cluster in the cytogenetic band 2F. Analysis of defective negative selection in the autoimmune-prone NOD strain demonstrates a global impairment in the induction of the negative selection response gene set, but little difference in positive selection response genes. Combining expression differences with genetic linkage data, we identify differentially expressed candidate genes, including Bim, Bnip3, Smox, Pdrg1, Id1, Pdcd1, Ly6c, Pdia3, Trim30 and Trim12. Conclusion The data provide a molecular map of the negative selection response in vivo and, by analysis of deviations from this pathway in the autoimmune susceptible NOD strain, suggest that susceptibility arises from small expression differences in genes acting at multiple points in the pathway between the TCR and cell death. PMID:17239257

Overview of genomic selection in dairy cattle populations

USDA-ARS?s Scientific Manuscript database

Genomic selection is most successful for traits recorded over many years in large populations. Holstein breeders have reference populations >10,000 proven bulls via cooperation among major countries, and countries with smaller Holstein populations can contribute additional bulls. Scandinavian red da...

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

PubMed

Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

2017-08-14

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.

Genomic variation in Plasmodium vivax malaria reveals regions under selective pressure

PubMed Central

Diez Benavente, Ernest; Ward, Zoe; Chan, Wilson; Mohareb, Fady R.; Sutherland, Colin J.; Roper, Cally; Campino, Susana

2017-01-01

Background Although Plasmodium vivax contributes to almost half of all malaria cases outside Africa, it has been relatively neglected compared to the more deadly P. falciparum. It is known that P. vivax populations possess high genetic diversity, differing geographically potentially due to different vector species, host genetics and environmental factors. Results We analysed the high-quality genomic data for 46 P. vivax isolates spanning 10 countries across 4 continents. Using population genetic methods we identified hotspots of selection pressure, including the previously reported MRP1 and DHPS genes, both putative drug resistance loci. Extra copies and deletions in the promoter region of another drug resistance candidate, MDR1 gene, and duplications in the Duffy binding protein gene (PvDBP) potentially involved in erythrocyte invasion, were also identified. For surveillance applications, continental-informative markers were found in putative drug resistance loci, and we show that organellar polymorphisms could classify P. vivax populations across continents and differentiate between Plasmodia spp. Conclusions This study has shown that genomic diversity that lies within and between P. vivax populations can be used to elucidate potential drug resistance and invasion mechanisms, as well as facilitate the molecular barcoding of the parasite for surveillance applications. PMID:28493919

Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition

PubMed Central

2012-01-01

Background Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds. Results Two independent experiments using either Iranian or Ovine HapMap genotyping data contrasted thin and fat tail breeds. Population differentiation using FST in Iranian thin and fat tail breeds revealed seven genomic regions. Almost all of these regions overlapped with QTLs that had previously been identified as affecting fat and carcass yield traits in beef and dairy cattle. Study of selection sweep signatures using FST in thin and fat tail breeds sampled from the Ovine HapMap project confirmed three of these regions located on Chromosomes 5, 7 and X. We found increased homozygosity in these regions in favour of fat tail breeds on chromosome 5 and X and in favour of thin tail breeds on chromosome 7. Conclusions In this study, we were able to identify three novel regions associated with fat deposition in thin and fat tail sheep breeds. Two of these were associated with an increase of homozygosity in the fat tail breeds which would be consistent with selection for mutations affecting fat tail size several thousand years after domestication. PMID:22364287

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

PubMed Central

2013-01-01

Background Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation. Results When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives

Genomic background-related activation of microglia and reduced β-amyloidosis in a mouse model of Alzheimer's disease.

PubMed

Fröhlich, Christina; Paarmann, Kristin; Steffen, Johannes; Stenzel, Jan; Krohn, Markus; Heinze, Hans-Jochen; Pahnke, Jens

2013-03-01

Alzheimer's disease (AD) is by far the most common neurodegenerative disease. AD is histologically characterized not only by extracellular senile plaques and vascular deposits consisting of β-amyloid (Aβ) but also by accompanying neuroinflammatory processes involving the brain's microglia. The importance of the microglia is still in controversial discussion, which currently favors a protective function in disease progression. Recent findings by different research groups highlighted the importance of strain-specific and mitochondria-specific genomic variations in mouse models of cerebral β-amyloidosis. Here, we want to summarize our previously presented data and add new results that draw attention towards the consideration of strain-specific genomic alterations in the setting of APP transgenes. We present data from APP-transgenic mice in commonly used C57Bl/6J and FVB/N genomic backgrounds and show a direct influence on the kinetics of Aβ deposition and the activity of resident microglia. Plaque size, plaque deposition rate and the total amount of Aβ are highest in C57Bl/6J mice as compared to the FVB/N genomic background, which can be explained at least partially by a reduced microglia activity towards amyloid deposits in the C57BL/6J strain.

Interpopulation hybridization results in widespread viability selection across the genome in Tigriopus californicus

PubMed Central

2011-01-01

Background Genetic interactions within hybrids influence their overall fitness. Understanding the details of these interactions can improve our understanding of speciation. One experimental approach is to investigate deviations from Mendelian expectations (segregation distortion) in the inheritance of mapped genetic markers. In this study, we used the copepod Tigriopus californicus, a species which exhibits high genetic divergence between populations and a general pattern of reduced fitness in F2 interpopulation hybrids. Previous studies have implicated both nuclear-cytoplasmic and nuclear-nuclear interactions in causing this fitness reduction. We identified and mapped population-diagnostic single nucleotide polymorphisms (SNPs) and used these to examine segregation distortion across the genome within F2 hybrids. Results We generated a linkage map which included 45 newly elucidated SNPs and 8 population-diagnostic microsatellites used in previous studies. The map, the first available for the Copepoda, was estimated to cover 75% of the genome and included markers on all 12 T. californicus chromosomes. We observed little segregation distortion in newly hatched F2 hybrid larvae (fewer than 10% of markers at p < 0.05), but strikingly higher distortion in F2 hybrid adult males (45% of markers at p < 0.05). Hence, segregation distortion was primarily caused by selection against particular genetic combinations which acted between hatching and maturity. Distorted markers were not distributed randomly across the genome but clustered on particular chromosomes. In contrast to other studies in this species we found little evidence for cytonuclear coadaptation. Instead, different linkage groups exhibited markedly different patterns of distortion, which appear to have been influenced by nuclear-nuclear epistatic interactions and may also reflect genetic load carried within the parental lines. Conclusion Adult male F2 hybrids between two populations of T. californius exhibit

Experimental evidence supports a sex-specific selective sieve in mitochondrial genome evolution.

PubMed

Innocenti, Paolo; Morrow, Edward H; Dowling, Damian K

2011-05-13

Mitochondria are maternally transmitted; hence, their genome can only make a direct and adaptive response to selection through females, whereas males represent an evolutionary dead end. In theory, this creates a sex-specific selective sieve, enabling deleterious mutations to accumulate in mitochondrial genomes if they exert male-specific effects. We tested this hypothesis, expressing five mitochondrial variants alongside a standard nuclear genome in Drosophila melanogaster, and found striking sexual asymmetry in patterns of nuclear gene expression. Mitochondrial polymorphism had few effects on nuclear gene expression in females but major effects in males, modifying nearly 10% of transcripts. These were mostly male-biased in expression, with enrichment hotspots in the testes and accessory glands. Our results suggest an evolutionary mechanism that results in mitochondrial genomes harboring male-specific mutation loads.

SweeD: likelihood-based detection of selective sweeps in thousands of genomes.

PubMed

Pavlidis, Pavlos; Živkovic, Daniel; Stamatakis, Alexandros; Alachiotis, Nikolaos

2013-09-01

The advent of modern DNA sequencing technology is the driving force in obtaining complete intra-specific genomes that can be used to detect loci that have been subject to positive selection in the recent past. Based on selective sweep theory, beneficial loci can be detected by examining the single nucleotide polymorphism patterns in intraspecific genome alignments. In the last decade, a plethora of algorithms for identifying selective sweeps have been developed. However, the majority of these algorithms have not been designed for analyzing whole-genome data. We present SweeD (Sweep Detector), an open-source tool for the rapid detection of selective sweeps in whole genomes. It analyzes site frequency spectra and represents a substantial extension of the widely used SweepFinder program. The sequential version of SweeD is up to 22 times faster than SweepFinder and, more importantly, is able to analyze thousands of sequences. We also provide a parallel implementation of SweeD for multi-core processors. Furthermore, we implemented a checkpointing mechanism that allows to deploy SweeD on cluster systems with queue execution time restrictions, as well as to resume long-running analyses after processor failures. In addition, the user can specify various demographic models via the command-line to calculate their theoretically expected site frequency spectra. Therefore, (in contrast to SweepFinder) the neutral site frequencies can optionally be directly calculated from a given demographic model. We show that an increase of sample size results in more precise detection of positive selection. Thus, the ability to analyze substantially larger sample sizes by using SweeD leads to more accurate sweep detection. We validate SweeD via simulations and by scanning the first chromosome from the 1000 human Genomes project for selective sweeps. We compare SweeD results with results from a linkage-disequilibrium-based approach and identify common outliers.

Selective significance of genome size in a plant community with heavy metal pollution.

PubMed

Vidic, T; Greilhuber, J; Vilhar, B; Dermastia, M

2009-09-01

In eukaryotes, nuclear genome sizes vary by more than five orders of magnitude. This variation is not related to organismal complexity, and its origin and biological significance are still disputed. One of the open questions is whether genome size has an adaptive role. We tested the hypothesis that genome size has selective significance, using five grassland communities occurring on a gradient of metal pollution of the soil as a model. We detected a negative correlation between the concentration of contaminating metals in the soil and the number of vascular plant species. Analysis of genome sizes of 70 herbaceous dicot perennial species occurring on the investigated plots revealed a negative correlation between the concentration of contaminating metals in the soil and the proportion of species with large genomes in plant communities. Consistent with the hypothesis, these results show that species with large genomes are at selective disadvantage in extreme environmental conditions.

Performance comparison of two efficient genomic selection methods (gsbay & MixP) applied in aquacultural organisms

NASA Astrophysics Data System (ADS)

Su, Hailin; Li, Hengde; Wang, Shi; Wang, Yangfan; Bao, Zhenmin

2017-02-01

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools MixP and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop ( Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction (GBLUP) method which has been applied widely. Our results showed that both MixP and gsbay could accurately estimate single-nucleotide polymorphism (SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values (GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by MixP; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by MixP and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with MixP the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by MixP and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data

PubMed Central

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S.; Molyneaux, Adam; Xu, Zhenyu; Hubaux, Jean-Pierre

2016-01-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients’ complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. PMID:27789525

Genomic Hypomethylation in the Human Germline Associates with Selective Structural Mutability in the Human Genome

PubMed Central

Li, Jian; Harris, R. Alan; Cheung, Sau Wai; Coarfa, Cristian; Jeong, Mira; Goodell, Margaret A.; White, Lisa D.; Patel, Ankita; Kang, Sung-Hae; Shaw, Chad; Chinault, A. Craig; Gambin, Tomasz; Gambin, Anna; Lupski, James R.; Milosavljevic, Aleksandar

2012-01-01

The hotspots of structural polymorphisms and structural mutability in the human genome remain to be explained mechanistically. We examine associations of structural mutability with germline DNA methylation and with non-allelic homologous recombination (NAHR) mediated by low-copy repeats (LCRs). Combined evidence from four human sperm methylome maps, human genome evolution, structural polymorphisms in the human population, and previous genomic and disease studies consistently points to a strong association of germline hypomethylation and genomic instability. Specifically, methylation deserts, the ∼1% fraction of the human genome with the lowest methylation in the germline, show a tenfold enrichment for structural rearrangements that occurred in the human genome since the branching of chimpanzee and are highly enriched for fast-evolving loci that regulate tissue-specific gene expression. Analysis of copy number variants (CNVs) from 400 human samples identified using a custom-designed array comparative genomic hybridization (aCGH) chip, combined with publicly available structural variation data, indicates that association of structural mutability with germline hypomethylation is comparable in magnitude to the association of structural mutability with LCR–mediated NAHR. Moreover, rare CNVs occurring in the genomes of individuals diagnosed with schizophrenia, bipolar disorder, and developmental delay and de novo CNVs occurring in those diagnosed with autism are significantly more concentrated within hypomethylated regions. These findings suggest a new connection between the epigenome, selective mutability, evolution, and human disease. PMID:22615578

Rapid cycling genomic selection in a multiparental tropical maize population

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) increases genetic gain by reducing the length of the selection cycle, as has been exemplified in maize using rapid cycling recombination of biparental populations. However, no results of GS applied to maize multi-parental populations have been reported so far. This study is th...

Will genomic selection be a practical method for plant breeding?

PubMed

Nakaya, Akihiro; Isobe, Sachiko N

2012-11-01

Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

Genomic selection in dairy cattle: the USDA experience

USDA-ARS?s Scientific Manuscript database

Genomic selection has revolutionized dairy cattle breeding. Since 2000, assays have been developed to genotype large numbers of single nucleotide polymorphisms (SNP) at relatively low cost. The first commercial SNP genotyping chip was released with a set of 54,001 SNP in December 2007. Over 15,000 ...

Accuracy of genomic prediction for BCWD resistance in rainbow trout using different genotyping platforms and genomic selection models

USDA-ARS?s Scientific Manuscript database

In this study, we aimed to (1) predict genomic estimated breeding value (GEBV) for bacterial cold water disease (BCWD) resistance by genotyping training (n=583) and validation samples (n=53) with two genotyping platforms (24K RAD-SNP and 49K SNP) and using different genomic selection (GS) models (Ba...

Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection.

PubMed

García-Ruiz, Adriana; Cole, John B; VanRaden, Paul M; Wiggans, George R; Ruiz-López, Felipe J; Van Tassell, Curtis P

2016-07-12

Seven years after the introduction of genomic selection in the United States, it is now possible to evaluate the impact of this technology on the population. Selection differential(s) (SD) and generation interval(s) (GI) were characterized in a four-path selection model that included sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). Changes in SD over time were estimated for milk, fat, and protein yield; somatic cell score (SCS); productive life (PL); and daughter pregnancy rate (DPR) for the Holstein breed. In the period following implementation of genomic selection, dramatic reductions were seen in GI, especially the SB and SC paths. The SB GI reduced from ∼7 y to less than 2.5 y, and the DB GI fell from about 4 y to nearly 2.5 y. SD were relatively stable for yield traits, although modest gains were noted in recent years. The most dramatic response to genomic selection was observed for the lowly heritable traits DPR, PL, and SCS. Genetic trends changed from close to zero to large and favorable, resulting in rapid genetic improvement in fertility, lifespan, and health in a breed where these traits eroded over time. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. Based on the four-path selection model, rates of genetic gain per year increased from ∼50-100% for yield traits and from threefold to fourfold for lowly heritable traits.

Comparative genomics of wild type yeast strains unveils important genome diversity

PubMed Central

Carreto, Laura; Eiriz, Maria F; Gomes, Ana C; Pereira, Patrícia M; Schuller, Dorit; Santos, Manuel AS

2008-01-01

Background Genome variability generates phenotypic heterogeneity and is of relevance for adaptation to environmental change, but the extent of such variability in natural populations is still poorly understood. For example, selected Saccharomyces cerevisiae strains are variable at the ploidy level, have gene amplifications, changes in chromosome copy number, and gross chromosomal rearrangements. This suggests that genome plasticity provides important genetic diversity upon which natural selection mechanisms can operate. Results In this study, we have used wild-type S. cerevisiae (yeast) strains to investigate genome variation in natural and artificial environments. We have used comparative genome hybridization on array (aCGH) to characterize the genome variability of 16 yeast strains, of laboratory and commercial origin, isolated from vineyards and wine cellars, and from opportunistic human infections. Interestingly, sub-telomeric instability was associated with the clinical phenotype, while Ty element insertion regions determined genomic differences of natural wine fermentation strains. Copy number depletion of ASP3 and YRF1 genes was found in all wild-type strains. Other gene families involved in transmembrane transport, sugar and alcohol metabolism or drug resistance had copy number changes, which also distinguished wine from clinical isolates. Conclusion We have isolated and genotyped more than 1000 yeast strains from natural environments and carried out an aCGH analysis of 16 strains representative of distinct genotype clusters. Important genomic variability was identified between these strains, in particular in sub-telomeric regions and in Ty-element insertion sites, suggesting that this type of genome variability is the main source of genetic diversity in natural populations of yeast. The data highlights the usefulness of yeast as a model system to unravel intraspecific natural genome diversity and to elucidate how natural selection shapes the yeast genome

PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

PubMed

Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

2013-12-27

With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data.

PubMed

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S; Molyneaux, Adam; Xu, Zhenyu; Fellay, Jacques; Steinmetz, Lars M; Hubaux, Jean-Pierre

2016-12-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. © 2016 Huang et al.; Published by Cold Spring Harbor Laboratory Press.

Sex-linked genomic variation and its relationship to avian plumage dichromatism and sexual selection.

PubMed

Huang, Huateng; Rabosky, Daniel L

2015-09-16

Sexual dichromatism is the tendency for sexes to differ in color pattern and represents a striking form of within-species morphological variation. Conspicuous intersexual differences in avian plumage are generally thought to result from Darwinian sexual selection, to the extent that dichromatism is often treated as a surrogate for the intensity of sexual selection in phylogenetic comparative studies. Intense sexual selection is predicted to leave a footprint on genetic evolution by reducing the relative genetic diversity on sex chromosome to that on the autosomes. In this study, we test the association between plumage dichromatism and sex-linked genetic diversity using eight species pairs with contrasting levels of dichromatism. We estimated Z-linked and autosomal genetic diversity for these non-model avian species using restriction-site associated (RAD) loci that covered ~3 % of the genome. We find that monochromatic birds consistently have reduced sex-linked genomic variation relative to phylogenetically-paired dichromatic species and this pattern is robust to mutational biases. Our results are consistent with several interpretations. If present-day sexual selection is stronger in dichromatic birds, our results suggest that its impact on sex-linked genomic variation is offset by other processes that lead to proportionately lower Z-linked variation in monochromatic species. We discuss possible factors that may contribute to this discrepancy between phenotypes and genomic variation. Conversely, it is possible that present-day sexual selection -- as measured by the variance in male reproductive success -- is stronger in the set of monochromatic taxa we have examined, potentially reflecting the importance of song, behavior and other non-plumage associated traits as targets of sexual selection. This counterintuitive finding suggests that the relationship between genomic variation and sexual selection is complex and highlights the need for a more comprehensive survey

Diversifying selection and host adaptation in two endosymbiont genomes

PubMed Central

Brownlie, Jeremy C; Adamski, Marcin; Slatko, Barton; McGraw, Elizabeth A

2007-01-01

Background The endosymbiont Wolbachia pipientis infects a broad range of arthropod and filarial nematode hosts. These diverse associations form an attractive model for understanding host:symbiont coevolution. Wolbachia's ubiquity and ability to dramatically alter host reproductive biology also form the foundation of research strategies aimed at controlling insect pests and vector-borne disease. The Wolbachia strains that infect nematodes are phylogenetically distinct, strictly vertically transmitted, and required by their hosts for growth and reproduction. Insects in contrast form more fluid associations with Wolbachia. In these taxa, host populations are most often polymorphic for infection, horizontal transmission occurs between distantly related hosts, and direct fitness effects on hosts are mild. Despite extensive interest in the Wolbachia system for many years, relatively little is known about the molecular mechanisms that mediate its varied interactions with different hosts. We have compared the genomes of the Wolbachia that infect Drosophila melanogaster, wMel and the nematode Brugia malayi, wBm to that of an outgroup Anaplasma marginale to identify genes that have experienced diversifying selection in the Wolbachia lineages. The goal of the study was to identify likely molecular mechanisms of the symbiosis and to understand the nature of the diverse association across different hosts. Results The prevalence of selection was far greater in wMel than wBm. Genes contributing to DNA metabolism, cofactor biosynthesis, and secretion were positively selected in both lineages. In wMel there was a greater emphasis on DNA repair, cell division, protein stability, and cell envelope synthesis. Conclusion Secretion pathways and outer surface protein encoding genes are highly affected by selection in keeping with host:parasite theory. If evidence of selection on various cofactor molecules reflects possible provisioning, then both insect as well as nematode Wolbachia may

Detecting and Characterizing Genomic Signatures of Positive Selection in Global Populations

PubMed Central

Liu, Xuanyao; Ong, Rick Twee-Hee; Pillai, Esakimuthu Nisha; Elzein, Abier M.; Small, Kerrin S.; Clark, Taane G.; Kwiatkowski, Dominic P.; Teo, Yik-Ying

2013-01-01

Natural selection is a significant force that shapes the architecture of the human genome and introduces diversity across global populations. The question of whether advantageous mutations have arisen in the human genome as a result of single or multiple mutation events remains unanswered except for the fact that there exist a handful of genes such as those that confer lactase persistence, affect skin pigmentation, or cause sickle cell anemia. We have developed a long-range-haplotype method for identifying genomic signatures of positive selection to complement existing methods, such as the integrated haplotype score (iHS) or cross-population extended haplotype homozygosity (XP-EHH), for locating signals across the entire allele frequency spectrum. Our method also locates the founder haplotypes that carry the advantageous variants and infers their corresponding population frequencies. This presents an opportunity to systematically interrogate the whole human genome whether a selection signal shared across different populations is the consequence of a single mutation process followed subsequently by gene flow between populations or of convergent evolution due to the occurrence of multiple independent mutation events either at the same variant or within the same gene. The application of our method to data from 14 populations across the world revealed that positive-selection events tend to cluster in populations of the same ancestry. Comparing the founder haplotypes for events that are present across different populations revealed that convergent evolution is a rare occurrence and that the majority of shared signals stem from the same evolutionary event. PMID:23731540

The Evolution of Genome Structure by Natural and Sexual Selection.

PubMed

Kirkpatrick, Mark

2017-01-01

Progress on understanding how genome structure evolves is accelerating with the arrival of new genomic, comparative, and theoretical approaches. This article reviews progress in understanding how chromosome inversions and sex chromosomes evolve, and how their evolution affects species' ecology. Analyses of clines in inversion frequencies in flies and mosquitoes imply strong local adaptation, and roles for both over- and under dominant selection. Those results are consistent with the hypothesis that inversions become established when they capture locally adapted alleles. Inversions can carry alleles that are beneficial to closely related species, causing them to introgress following hybridization. Models show that this "adaptive cassette" scenario can trigger large range expansions, as recently happened in malaria mosquitoes. Sex chromosomes are the most rapidly evolving genome regions of some taxa. Sexually antagonistic selection may be the key force driving transitions of sex determination between different pairs of chromosomes and between XY and ZW systems. Fusions between sex-chromosomes and autosomes most often involve the Y chromosome, a pattern that can be explained if fusions are mildly deleterious and fix by drift. Sexually antagonistic selection is one of several hypotheses to explain the recent discovery that the sex determination system has strong effects on the adult sex ratios of tetrapods. The emerging view of how genome structure evolves invokes a much richer constellation of forces than was envisioned during the Golden Age of research on Drosophila karyotypes. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A selective sweep of >8 Mb on chromosome 26 in the Boxer genome.

PubMed

Quilez, Javier; Short, Andrea D; Martínez, Verónica; Kennedy, Lorna J; Ollier, William; Sanchez, Armand; Altet, Laura; Francino, Olga

2011-07-01

Modern dog breeds display traits that are either breed-specific or shared by a few breeds as a result of genetic bottlenecks during the breed creation process and artificial selection for breed standards. Selective sweeps in the genome result from strong selection and can be detected as a reduction or elimination of polymorphism in a given region of the genome. Extended regions of homozygosity, indicative of selective sweeps, were identified in a genome-wide scan dataset of 25 Boxers from the United Kingdom genotyped at ~20,000 single-nucleotide polymorphisms (SNPs). These regions were further examined in a second dataset of Boxers collected from a different geographical location and genotyped using higher density SNP arrays (~170,000 SNPs). A selective sweep previously associated with canine brachycephaly was detected on chromosome 1. A novel selective sweep of over 8 Mb was observed on chromosome 26 in Boxer and for a shorter region in English and French bulldogs. It was absent in 171 samples from eight other dog breeds and 7 Iberian wolf samples. A region of extended increased heterozygosity on chromosome 9 overlapped with a previously reported copy number variant (CNV) which was polymorphic in multiple dog breeds. A selective sweep of more than 8 Mb on chromosome 26 was identified in the Boxer genome. This sweep is likely caused by strong artificial selection for a trait of interest and could have inadvertently led to undesired health implications for this breed. Furthermore, we provide supporting evidence for two previously described regions: a selective sweep on chromosome 1 associated with canine brachycephaly and a CNV on chromosome 9 polymorphic in multiple dog breeds.

Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection

PubMed Central

García-Ruiz, Adriana; Cole, John B.; VanRaden, Paul M.; Wiggans, George R.; Ruiz-López, Felipe J.; Van Tassell, Curtis P.

2016-01-01

Seven years after the introduction of genomic selection in the United States, it is now possible to evaluate the impact of this technology on the population. Selection differential(s) (SD) and generation interval(s) (GI) were characterized in a four-path selection model that included sire(s) of bulls (SB), sire(s) of cows (SC), dam(s) of bulls (DB), and dam(s) of cows (DC). Changes in SD over time were estimated for milk, fat, and protein yield; somatic cell score (SCS); productive life (PL); and daughter pregnancy rate (DPR) for the Holstein breed. In the period following implementation of genomic selection, dramatic reductions were seen in GI, especially the SB and SC paths. The SB GI reduced from ∼7 y to less than 2.5 y, and the DB GI fell from about 4 y to nearly 2.5 y. SD were relatively stable for yield traits, although modest gains were noted in recent years. The most dramatic response to genomic selection was observed for the lowly heritable traits DPR, PL, and SCS. Genetic trends changed from close to zero to large and favorable, resulting in rapid genetic improvement in fertility, lifespan, and health in a breed where these traits eroded over time. These results clearly demonstrate the positive impact of genomic selection in US dairy cattle, even though this technology has only been in use for a short time. Based on the four-path selection model, rates of genetic gain per year increased from ∼50–100% for yield traits and from threefold to fourfold for lowly heritable traits. PMID:27354521

Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

PubMed Central

2013-01-01

Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

Different selective pressures lead to different genomic outcomes as newly-formed hybrid yeasts evolve.

PubMed

Piotrowski, Jeff S; Nagarajan, Saisubramanian; Kroll, Evgueny; Stanbery, Alison; Chiotti, Kami E; Kruckeberg, Arthur L; Dunn, Barbara; Sherlock, Gavin; Rosenzweig, Frank

2012-04-02

Interspecific hybridization occurs in every eukaryotic kingdom. While hybrid progeny are frequently at a selective disadvantage, in some instances their increased genome size and complexity may result in greater stress resistance than their ancestors, which can be adaptively advantageous at the edges of their ancestors' ranges. While this phenomenon has been repeatedly documented in the field, the response of hybrid populations to long-term selection has not often been explored in the lab. To fill this knowledge gap we crossed the two most distantly related members of the Saccharomyces sensu stricto group, S. cerevisiae and S. uvarum, and established a mixed population of homoploid and aneuploid hybrids to study how different types of selection impact hybrid genome structure. As temperature was raised incrementally from 31°C to 46.5°C over 500 generations of continuous culture, selection favored loss of the S. uvarum genome, although the kinetics of genome loss differed among independent replicates. Temperature-selected isolates exhibited greater inherent and induced thermal tolerance than parental species and founding hybrids, and also exhibited ethanol resistance. In contrast, as exogenous ethanol was increased from 0% to 14% over 500 generations of continuous culture, selection favored euploid S. cerevisiae x S. uvarum hybrids. Ethanol-selected isolates were more ethanol tolerant than S. uvarum and one of the founding hybrids, but did not exhibit resistance to temperature stress. Relative to parental and founding hybrids, temperature-selected strains showed heritable differences in cell wall structure in the forms of increased resistance to zymolyase digestion and Micafungin, which targets cell wall biosynthesis. This is the first study to show experimentally that the genomic fate of newly-formed interspecific hybrids depends on the type of selection they encounter during the course of evolution, underscoring the importance of the ecological theatre in

Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs

PubMed Central

Freedman, Adam H.; Schweizer, Rena M.; Ortega-Del Vecchyo, Diego; Han, Eunjung; Davis, Brian W.; Gronau, Ilan; Silva, Pedro M.; Galaverni, Marco; Fan, Zhenxin; Marx, Peter; Lorente-Galdos, Belen; Ramirez, Oscar; Hormozdiari, Farhad; Alkan, Can; Vilà, Carles; Squire, Kevin; Geffen, Eli; Kusak, Josip; Boyko, Adam R.; Parker, Heidi G.; Lee, Clarence; Tadigotla, Vasisht; Siepel, Adam; Bustamante, Carlos D.; Harkins, Timothy T.; Nelson, Stanley F.; Marques-Bonet, Tomas; Ostrander, Elaine A.; Wayne, Robert K.; Novembre, John

2016-01-01

Controlling for background demographic effects is important for accurately identifying loci that have recently undergone positive selection. To date, the effects of demography have not yet been explicitly considered when identifying loci under selection during dog domestication. To investigate positive selection on the dog lineage early in the domestication, we examined patterns of polymorphism in six canid genomes that were previously used to infer a demographic model of dog domestication. Using an inferred demographic model, we computed false discovery rates (FDR) and identified 349 outlier regions consistent with positive selection at a low FDR. The signals in the top 100 regions were frequently centered on candidate genes related to brain function and behavior, including LHFPL3, CADM2, GRIK3, SH3GL2, MBP, PDE7B, NTAN1, and GLRA1. These regions contained significant enrichments in behavioral ontology categories. The 3rd top hit, CCRN4L, plays a major role in lipid metabolism, that is supported by additional metabolism related candidates revealed in our scan, including SCP2D1 and PDXC1. Comparing our method to an empirical outlier approach that does not directly account for demography, we found only modest overlaps between the two methods, with 60% of empirical outliers having no overlap with our demography-based outlier detection approach. Demography-aware approaches have lower-rates of false discovery. Our top candidates for selection, in addition to expanding the set of neurobehavioral candidate genes, include genes related to lipid metabolism, suggesting a dietary target of selection that was important during the period when proto-dogs hunted and fed alongside hunter-gatherers. PMID:26943675

Demographic history, selection and functional diversity of the canine genome.

PubMed

Ostrander, Elaine A; Wayne, Robert K; Freedman, Adam H; Davis, Brian W

2017-12-01

The domestic dog represents one of the most dramatic long-term evolutionary experiments undertaken by humans. From a large wolf-like progenitor, unparalleled diversity in phenotype and behaviour has developed in dogs, providing a model for understanding the developmental and genomic mechanisms of diversification. We discuss pattern and process in domestication, beginning with general findings about early domestication and problems in documenting selection at the genomic level. Furthermore, we summarize genotype-phenotype studies based first on single nucleotide polymorphism (SNP) genotyping and then with whole-genome data and show how an understanding of evolution informs topics as different as human history, adaptive and deleterious variation, morphological development, ageing, cancer and behaviour.

Selective Amplification of the Genome Surrounding Key Placental Genes in Trophoblast Giant Cells.

PubMed

Hannibal, Roberta L; Baker, Julie C

2016-01-25

While most cells maintain a diploid state, polyploid cells exist in many organisms and are particularly prevalent within the mammalian placenta [1], where they can generate more than 900 copies of the genome [2]. Polyploidy is thought to be an efficient method of increasing the content of the genome by avoiding the costly and slow process of cytokinesis [1, 3, 4]. Polyploidy can also affect gene regulation by amplifying a subset of genomic regions required for specific cellular function [1, 3, 4]. This mechanism is found in the fruit fly Drosophila melanogaster, where polyploid ovarian follicle cells amplify genomic regions containing chorion genes, which facilitate secretion of eggshell proteins [5]. Here, we report that genomic amplification also occurs in mammals at selective regions of the genome in parietal trophoblast giant cells (p-TGCs) of the mouse placenta. Using whole-genome sequencing (WGS) and digital droplet PCR (ddPCR) of mouse p-TGCs, we identified five amplified regions, each containing a gene family known to be involved in mammalian placentation: the prolactins (two clusters), serpins, cathepsins, and the natural killer (NK)/C-type lectin (CLEC) complex [6-12]. We report here the first description of amplification at selective genomic regions in mammals and present evidence that this is an important mode of genome regulation in placental TGCs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Potential benefits of genomic selection on genetic gain of small ruminant breeding programs.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Elsen, J M

2013-08-01

In conventional small ruminant breeding programs, only pedigree and phenotype records are used to make selection decisions but prospects of including genomic information are now under consideration. The objective of this study was to assess the potential benefits of genomic selection on the genetic gain in French sheep and goat breeding designs of today. Traditional and genomic scenarios were modeled with deterministic methods for 3 breeding programs. The models included decisional variables related to male selection candidates, progeny testing capacity, and economic weights that were optimized to maximize annual genetic gain (AGG) of i) a meat sheep breeding program that improved a meat trait of heritability (h(2)) = 0.30 and a maternal trait of h(2) = 0.09 and ii) dairy sheep and goat breeding programs that improved a milk trait of h(2) = 0.30. Values of ±0.20 of genetic correlation between meat and maternal traits were considered to study their effects on AGG. The Bulmer effect was accounted for and the results presented here are the averages of AGG after 10 generations of selection. Results showed that current traditional breeding programs provide an AGG of 0.095 genetic standard deviation (σa) for meat and 0.061 σa for maternal trait in meat breed and 0.147 σa and 0.120 σa in sheep and goat dairy breeds, respectively. By optimizing decisional variables, the AGG with traditional selection methods increased to 0.139 σa for meat and 0.096 σa for maternal traits in meat breeding programs and to 0.174 σa and 0.183 σa in dairy sheep and goat breeding programs, respectively. With a medium-sized reference population (nref) of 2,000 individuals, the best genomic scenarios gave an AGG that was 17.9% greater than with traditional selection methods with optimized values of decisional variables for combined meat and maternal traits in meat sheep, 51.7% in dairy sheep, and 26.2% in dairy goats. The superiority of genomic schemes increased with the size of the

The efficiency of genome-wide selection for genetic improvement of net merit.

PubMed

Togashi, K; Lin, C Y; Yamazaki, T

2011-10-01

Four methods of selection for net merit comprising 2 correlated traits were compared in this study: 1) EBV-only index (I₁), which consists of the EBV of both traits (i.e., traditional 2-trait BLUP selection); 2) GEBV-only index (I₂), which comprises the genomic EBV (GEBV) of both traits; 3) GEBV-assisted index (I₃), which combines both the EBV and the GEBV of both traits; and 4) GBV-assisted index (I₄), which combines both the EBV and the true genomic breeding value (GBV) of both traits. Comparisons of these indices were based on 3 evaluation criteria [selection accuracy, genetic response (ΔH), and relative efficiency] under 64 scenarios that arise from combining 2 levels of genetic correlation (r(G)), 2 ratios of genetic variances between traits, 2 ratios of the genomic variance to total genetic variances for trait 1, 4 accuracies of EBV, and 2 proportions of r(G) explained by the GBV. Both selection accuracy and genetic responses of the indices I₁, I₃, and I₄ increased as the accuracy of EBV increased, but the efficiency of the indices I₃ and I₄ relative to I₁ decreased as the accuracy of EBV increased. The relative efficiency of both I₃ and I₄ was generally greater when the accuracy of EBV was 0.6 than when it was 0.9, suggesting that the genomic markers are most useful to assist selection when the accuracy of EBV is low. The GBV-assisted index I₄ was superior to the GEBV-assisted I₃ in all 64 cases examined, indicating the importance of improving the accuracy of prediction of genomic breeding values. Other parameters being identical, increasing the genetic variance of a high heritability trait would increase the genetic response of the genomic indices (I₂, I₃, and I₄). The genetic responses to I₂, I₃, and I(4) was greater when the genetic correlation between traits was positive (r(G) = 0.5) than when it was negative (r(G) = -0.5). The results of this study indicate that the effectiveness of the GEBV-assisted index I₃ is

Identification of genomic variants putatively targeted by selection during dog domestication.

PubMed

Cagan, Alex; Blass, Torsten

2016-01-12

Dogs [Canis lupus familiaris] were the first animal species to be domesticated and continue to occupy an important place in human societies. Recent studies have begun to reveal when and where dog domestication occurred. While much progress has been made in identifying the genetic basis of phenotypic differences between dog breeds we still know relatively little about the genetic changes underlying the phenotypes that differentiate all dogs from their wild progenitors, wolves [Canis lupus]. In particular, dogs generally show reduced aggression and fear towards humans compared to wolves. Therefore, selection for tameness was likely a necessary prerequisite for dog domestication. With the increasing availability of whole-genome sequence data it is possible to try and directly identify the genetic variants contributing to the phenotypic differences between dogs and wolves. We analyse the largest available database of genome-wide polymorphism data in a global sample of dogs 69 and wolves 7. We perform a scan to identify regions of the genome that are highly differentiated between dogs and wolves. We identify putatively functional genomic variants that are segregating or at high frequency [> = 0.75 Fst] for alternative alleles between dogs and wolves. A biological pathways analysis of the genes containing these variants suggests that there has been selection on the 'adrenaline and noradrenaline biosynthesis pathway', well known for its involvement in the fight-or-flight response. We identify 11 genes with putatively functional variants fixed for alternative alleles between dogs and wolves. The segregating variants in these genes are strong candidates for having been targets of selection during early dog domestication. We present the first genome-wide analysis of the different categories of putatively functional variants that are fixed or segregating at high frequency between a global sampling of dogs and wolves. We find evidence that selection has been strongest

Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity

PubMed Central

Andersen, Erik C.; Gerke, Justin P.; Shapiro, Joshua A.; Crissman, Jonathan R.; Ghosh, Rajarshi; Bloom, Joshua S.; Félix, Marie-Anne; Kruglyak, Leonid

2011-01-01

The nematode Caenorhabditis elegans is central to research in molecular, cell, and developmental biology, but nearly all of this research has been conducted on a single strain. Comparatively little is known about the population genomic and evolutionary history of this species. We characterized C. elegans genetic variation by high-throughput selective sequencing of a worldwide collection of 200 wild strains, identifying 41,188 single nucleotide polymorphisms. Unexpectedly, C. elegans genome variation is dominated by a set of commonly shared haplotypes on four of the six chromosomes, each spanning many megabases. Population-genetic modeling shows that this pattern was generated by chromosome-scale selective sweeps that have reduced variation worldwide; at least one of these sweeps likely occurred in the past few hundred years. These sweeps, which we hypothesize to be a result of human activity, have dramatically reshaped the global C. elegans population in the recent past. PMID:22286215

Detecting and characterizing genomic signatures of positive selection in global populations.

PubMed

Liu, Xuanyao; Ong, Rick Twee-Hee; Pillai, Esakimuthu Nisha; Elzein, Abier M; Small, Kerrin S; Clark, Taane G; Kwiatkowski, Dominic P; Teo, Yik-Ying

2013-06-06

Natural selection is a significant force that shapes the architecture of the human genome and introduces diversity across global populations. The question of whether advantageous mutations have arisen in the human genome as a result of single or multiple mutation events remains unanswered except for the fact that there exist a handful of genes such as those that confer lactase persistence, affect skin pigmentation, or cause sickle cell anemia. We have developed a long-range-haplotype method for identifying genomic signatures of positive selection to complement existing methods, such as the integrated haplotype score (iHS) or cross-population extended haplotype homozygosity (XP-EHH), for locating signals across the entire allele frequency spectrum. Our method also locates the founder haplotypes that carry the advantageous variants and infers their corresponding population frequencies. This presents an opportunity to systematically interrogate the whole human genome whether a selection signal shared across different populations is the consequence of a single mutation process followed subsequently by gene flow between populations or of convergent evolution due to the occurrence of multiple independent mutation events either at the same variant or within the same gene. The application of our method to data from 14 populations across the world revealed that positive-selection events tend to cluster in populations of the same ancestry. Comparing the founder haplotypes for events that are present across different populations revealed that convergent evolution is a rare occurrence and that the majority of shared signals stem from the same evolutionary event. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Landscape genomics: natural selection drives the evolution of mitogenome in penguins.

PubMed

Ramos, Barbara; González-Acuña, Daniel; Loyola, David E; Johnson, Warren E; Parker, Patricia G; Massaro, Melanie; Dantas, Gisele P M; Miranda, Marcelo D; Vianna, Juliana A

2018-01-16

Mitochondria play a key role in the balance of energy and heat production, and therefore the mitochondrial genome is under natural selection by environmental temperature and food availability, since starvation can generate more efficient coupling of energy production. However, selection over mitochondrial DNA (mtDNA) genes has usually been evaluated at the population level. We sequenced by NGS 12 mitogenomes and with four published genomes, assessed genetic variation in ten penguin species distributed from the equator to Antarctica. Signatures of selection of 13 mitochondrial protein-coding genes were evaluated by comparing among species within and among genera (Spheniscus, Pygoscelis, Eudyptula, Eudyptes and Aptenodytes). The genetic data were correlated with environmental data obtained through remote sensing (sea surface temperature [SST], chlorophyll levels [Chl] and a combination of SST and Chl [COM]) through the distribution of these species. We identified the complete mtDNA genomes of several penguin species, including ND6 and 8 tRNAs on the light strand and 12 protein coding genes, 14 tRNAs and two rRNAs positioned on the heavy strand. The highest diversity was found in NADH dehydrogenase genes and the lowest in COX genes. The lowest evolutionary divergence among species was between Humboldt (Spheniscus humboldti) and Galapagos (S. mendiculus) penguins (0.004), while the highest was observed between little penguin (Eudyptula minor) and Adélie penguin (Pygoscelis adeliae) (0.097). We identified a signature of purifying selection (Ka/Ks < 1) across the mitochondrial genome, which is consistent with the hypothesis that purifying selection is constraining mitogenome evolution to maintain Oxidative phosphorylation (OXPHOS) proteins and functionality. Pairwise species maximum-likelihood analyses of selection at codon sites suggest positive selection has occurred on ATP8 (Fixed-Effects Likelihood, FEL) and ND4 (Single Likelihood Ancestral Counting, SLAC) in

Comparing genomic selection and marker-assisted selection for Fusarium head blight resistance in wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) and marker-assisted selection (MAS) rely on marker-trait associations and are both routinely used for breeding purposes. Although similar, these two approaches differ in their applications and how markers are used to estimate breeding values. In this study, GS and MAS were com...

The Genomic Impacts of Drift and Selection for Hybrid Performance in Maize

PubMed Central

Gerke, Justin P.; Edwards, Jode W.; Guill, Katherine E.; Ross-Ibarra, Jeffrey; McMullen, Michael D.

2015-01-01

Although maize is naturally an outcrossing organism, modern breeding utilizes highly inbred lines in controlled crosses to produce hybrids. The U.S. Department of Agriculture’s reciprocal recurrent selection experiment between the Iowa Stiff Stalk Synthetic (BSSS) and the Iowa Corn Borer Synthetic No. 1 (BSCB1) populations represents one of the longest running experiments to understand the response to selection for hybrid performance. To investigate the genomic impact of this selection program, we genotyped the progenitor lines and >600 individuals across multiple cycles of selection using a genome-wide panel of ∼40,000 SNPs. We confirmed previous results showing a steady temporal decrease in genetic diversity within populations and a corresponding increase in differentiation between populations. Thanks to detailed historical information on experimental design, we were able to perform extensive simulations using founder haplotypes to replicate the experiment in the absence of selection. These simulations demonstrate that while most of the observed reduction in genetic diversity can be attributed to genetic drift, heterozygosity in each population has fallen more than expected. We then took advantage of our high-density genotype data to identify extensive regions of haplotype fixation and trace haplotype ancestry to single founder inbred lines. The vast majority of regions showing such evidence of selection differ between the two populations, providing evidence for the dominance model of heterosis. We discuss how this pattern is likely to occur during selection for hybrid performance and how it poses challenges for dissecting the impacts of modern breeding and selection on the maize genome. PMID:26385980

Integrating marker-assisted background analysis with foreground selection for pyramiding bacterial blight resistance genes into Basmati rice.

PubMed

Baliyan, Nikita; Malik, Rekha; Rani, Reema; Mehta, Kirti; Vashisth, Urvashi; Dhillon, Santosh; Boora, Khazan Singh

2018-01-01

Bacterial leaf blight (BB), caused by the bacterium Xanthomonas oryzae pv. Oryzae (Xoo), is the major constraint amongst rice diseases in India. CSR-30 is a very popular high-yielding, salt-tolerant Basmati variety widely grown in Haryana, India, but highly susceptible to BB. In the present study, we have successfully introgressed three BB resistance genes (Xa21, xa13 and xa5) from BB-resistant donor variety IRBB-60 into the BB-susceptible Basmati variety CSR-30 through marker-assisted selection (MAS) exercised with stringent phenotypic selection without compromising the Basmati traits. Background analysis using 131 polymorphic SSR markers revealed that recurrent parent genome (RPG) recovery ranged up to 97.1% among 15 BC 3 F 1 three-gene-pyramided genotypes. Based on agronomic evaluation, BB reaction, aroma, percentage recovery of RPG, and grain quality evaluation, four genotypes, viz., IC-R28, IC-R68, IC-R32, and IC-R42, were found promising and advanced to BC 3 F 2 generation. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Selective Gene Delivery for Integrating Exogenous DNA into Plastid and Mitochondrial Genomes Using Peptide-DNA Complexes.

PubMed

Yoshizumi, Takeshi; Oikawa, Kazusato; Chuah, Jo-Ann; Kodama, Yutaka; Numata, Keiji

2018-05-14

Selective gene delivery into organellar genomes (mitochondrial and plastid genomes) has been limited because of a lack of appropriate platform technology, even though these organelles are essential for metabolite and energy production. Techniques for selective organellar modification are needed to functionally improve organelles and produce transplastomic/transmitochondrial plants. However, no method for mitochondrial genome modification has yet been established for multicellular organisms including plants. Likewise, modification of plastid genomes has been limited to a few plant species and algae. In the present study, we developed ionic complexes of fusion peptides containing organellar targeting signal and plasmid DNA for selective delivery of exogenous DNA into the plastid and mitochondrial genomes of intact plants. This is the first report of exogenous DNA being integrated into the mitochondrial genomes of not only plants, but also multicellular organisms in general. This fusion peptide-mediated gene delivery system is a breakthrough platform for both plant organellar biotechnology and gene therapy for mitochondrial diseases in animals.

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites.

PubMed

Amambua-Ngwa, Alfred; Tetteh, Kevin K A; Manske, Magnus; Gomez-Escobar, Natalia; Stewart, Lindsay B; Deerhake, M Elizabeth; Cheeseman, Ian H; Newbold, Christopher I; Holder, Anthony A; Knuepfer, Ellen; Janha, Omar; Jallow, Muminatou; Campino, Susana; Macinnis, Bronwyn; Kwiatkowski, Dominic P; Conway, David J

2012-01-01

Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now

Complete plastid genome sequences suggest strong selection for retention of photosynthetic genes in the parasitic plant genus Cuscuta

PubMed Central

McNeal, Joel R; Kuehl, Jennifer V; Boore, Jeffrey L; de Pamphilis, Claude W

2007-01-01

Background Plastid genome content and protein sequence are highly conserved across land plants and their closest algal relatives. Parasitic plants, which obtain some or all of their nutrition through an attachment to a host plant, are often a striking exception. Heterotrophy can lead to relaxed constraint on some plastid genes or even total gene loss. We sequenced plastid genomes of two species in the parasitic genus Cuscuta along with a non-parasitic relative, Ipomoea purpurea, to investigate changes in the plastid genome that may result from transition to the parasitic lifestyle. Results Aside from loss of all ndh genes, Cuscuta exaltata retains photosynthetic and photorespiratory genes that evolve under strong selective constraint. Cuscuta obtusiflora has incurred substantially more change to its plastid genome, including loss of all genes for the plastid-encoded RNA polymerase. Despite extensive change in gene content and greatly increased rate of overall nucleotide substitution, C. obtusiflora also retains all photosynthetic and photorespiratory genes with only one minor exception. Conclusion Although Epifagus virginiana, the only other parasitic plant with its plastid genome sequenced to date, has lost a largely overlapping set of transfer-RNA and ribosomal genes as Cuscuta, it has lost all genes related to photosynthesis and maintains a set of genes which are among the most divergent in Cuscuta. Analyses demonstrate photosynthetic genes are under the highest constraint of any genes within the plastid genomes of Cuscuta, indicating a function involving RuBisCo and electron transport through photosystems is still the primary reason for retention of the plastid genome in these species. PMID:17956636

Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection.

PubMed

McElroy, Michel S; Navarro, Alberto J R; Mustiga, Guiliana; Stack, Conrad; Gezan, Salvador; Peña, Geover; Sarabia, Widem; Saquicela, Diego; Sotomayor, Ignacio; Douglas, Gavin M; Migicovsky, Zoë; Amores, Freddy; Tarqui, Omar; Myles, Sean; Motamayor, Juan C

2018-01-01

Cacao ( Theobroma cacao ) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches' broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri , respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds

Genomic selection & association mapping in rice: effect of trait genetic architecture, training population composition, marker number & statistical model on accuracy of rice genomic selection in elite, tropical rice breeding

USDA-ARS?s Scientific Manuscript database

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its ef...

Increased prediction accuracy in wheat breeding trials using a marker x environment interaction genomic selection model

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates for selection. Originally these models were developed without considering genotype ' environment interaction (GE). Several authors have proposed extensions of the cannonical GS model that accomm...

Strategies for implementing genomic selection for feed efficiency in dairy cattle breeding schemes.

PubMed

Wallén, S E; Lillehammer, M; Meuwissen, T H E

2017-08-01

Alternative genomic selection and traditional BLUP breeding schemes were compared for the genetic improvement of feed efficiency in simulated Norwegian Red dairy cattle populations. The change in genetic gain over time and achievable selection accuracy were studied for milk yield and residual feed intake, as a measure of feed efficiency. When including feed efficiency in genomic BLUP schemes, it was possible to achieve high selection accuracies for genomic selection, and all genomic BLUP schemes gave better genetic gain for feed efficiency than BLUP using a pedigree relationship matrix. However, introducing a second trait in the breeding goal caused a reduction in the genetic gain for milk yield. When using contracted test herds with genotyped and feed efficiency recorded cows as a reference population, adding an additional 4,000 new heifers per year to the reference population gave accuracies that were comparable to a male reference population that used progeny testing with 250 daughters per sire. When the test herd consisted of 500 or 1,000 cows, lower genetic gain was found than using progeny test records to update the reference population. It was concluded that to improve difficult to record traits, the use of contracted test herds that had additional recording (e.g., measurements required to calculate feed efficiency) is a viable option, possibly through international collaborations. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Training set optimization under population structure in genomic selection

USDA-ARS?s Scientific Manuscript database

The optimization of the training set (TRS) in genomic selection (GS) has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the Coefficient of D...

Using genomics to enhance selection of novel traits in North American dairy cattle

USDA-ARS?s Scientific Manuscript database

Genomics offers new opportunities for the effective selection of novel traits. For traits such as mastitis resistance, hoof health, or the prediction of milk composition from mid-infrared (MIR) data, for example, enough records are usually available to carry out genomic evaluations using sire genoty...

Inference of Gorilla Demographic and Selective History from Whole-Genome Sequence Data

PubMed Central

McManus, Kimberly F.; Kelley, Joanna L.; Song, Shiya; Veeramah, Krishna R.; Woerner, August E.; Stevison, Laurie S.; Ryder, Oliver A.; Ape Genome Project, Great; Kidd, Jeffrey M.; Wall, Jeffrey D.; Bustamante, Carlos D.; Hammer, Michael F.

2015-01-01

Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection. PMID:25534031

Whole genome detection of signature of positive selection in African cattle reveals selection for thermotolerance.

PubMed

Taye, Mengistie; Lee, Wonseok; Caetano-Anolles, Kelsey; Dessie, Tadelle; Hanotte, Olivier; Mwai, Okeyo Ally; Kemp, Stephen; Cho, Seoae; Oh, Sung Jong; Lee, Hak-Kyo; Kim, Heebal

2017-12-01

As African indigenous cattle evolved in a hot tropical climate, they have developed an inherent thermotolerance; survival mechanisms include a light-colored and shiny coat, increased sweating, and cellular and molecular mechanisms to cope with high environmental temperature. Here, we report the positive selection signature of genes in African cattle breeds which contribute for their heat tolerance mechanisms. We compared the genomes of five indigenous African cattle breeds with the genomes of four commercial cattle breeds using cross-population composite likelihood ratio (XP-CLR) and cross-population extended haplotype homozygosity (XP-EHH) statistical methods. We identified 296 (XP-EHH) and 327 (XP-CLR) positively selected genes. Gene ontology analysis resulted in 41 biological process terms and six Kyoto Encyclopedia of Genes and Genomes pathways. Several genes and pathways were found to be involved in oxidative stress response, osmotic stress response, heat shock response, hair and skin properties, sweat gland development and sweating, feed intake and metabolism, and reproduction functions. The genes and pathways identified directly or indirectly contribute to the superior heat tolerance mechanisms in African cattle populations. The result will improve our understanding of the biological mechanisms of heat tolerance in African cattle breeds and opens an avenue for further study. © 2017 Japanese Society of Animal Science.

Genome-Wide Variation Patterns Uncover the Origin and Selection in Cultivated Ginseng (Panax ginseng Meyer)

PubMed Central

Li, Ming-Rui; Shi, Feng-Xue; Li, Ya-Ling; Jiang, Peng; Jiao, Lili

2017-01-01

Abstract Chinese ginseng (Panax ginseng Meyer) is a medicinally important herb and plays crucial roles in traditional Chinese medicine. Pharmacological analyses identified diverse bioactive components from Chinese ginseng. However, basic biological attributes including domestication and selection of the ginseng plant remain under-investigated. Here, we presented a genome-wide view of the domestication and selection of cultivated ginseng based on the whole genome data. A total of 8,660 protein-coding genes were selected for genome-wide scanning of the 30 wild and cultivated ginseng accessions. In complement, the 45s rDNA, chloroplast and mitochondrial genomes were included to perform phylogenetic and population genetic analyses. The observed spatial genetic structure between northern cultivated ginseng (NCG) and southern cultivated ginseng (SCG) accessions suggested multiple independent origins of cultivated ginseng. Genome-wide scanning further demonstrated that NCG and SCG have undergone distinct selection pressures during the domestication process, with more genes identified in the NCG (97 genes) than in the SCG group (5 genes). Functional analyses revealed that these genes are involved in diverse pathways, including DNA methylation, lignin biosynthesis, and cell differentiation. These findings suggested that the SCG and NCG groups have distinct demographic histories. Candidate genes identified are useful for future molecular breeding of cultivated ginseng. PMID:28922794

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.

Inferring Selective Constraint from Population Genomic Data Suggests Recent Regulatory Turnover in the Human Brain

PubMed Central

Schrider, Daniel R.; Kern, Andrew D.

2015-01-01

The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely missed by searching for sequence conservation across species. Here we present an analysis based on variation data among human genomes that utilizes a supervised machine learning approach for the identification of human-specific purifying selection in the genome. Using only allele frequency information from the complete low-coverage 1000 Genomes Project data set in conjunction with a support vector machine trained from known functional and nonfunctional portions of the genome, we are able to accurately identify portions of the genome constrained by purifying selection. Our method identifies previously known human-specific gains or losses of function and uncovers many novel candidates. Candidate targets for gain and loss of function along the human lineage include numerous putative regulatory regions of genes essential for normal development of the central nervous system, including a significant enrichment of gain of function events near neurotransmitter receptor genes. These results are consistent with regulatory turnover being a key mechanism in the evolution of human-specific characteristics of brain development. Finally, we show that the majority of the genome is unconstrained by natural selection currently, in agreement with what has been estimated from phylogenetic methods but in sharp contrast to estimates based on transcriptomics or other high-throughput functional methods. PMID:26590212

Signatures of positive selection in East African Shorthorn Zebu: A genome-wide single nucleotide polymorphism analysis

PubMed Central

Bahbahani, Hussain; Clifford, Harry; Wragg, David; Mbole-Kariuki, Mary N; Van Tassell, Curtis; Sonstegard, Tad; Woolhouse, Mark; Hanotte, Olivier

2015-01-01

The small East African Shorthorn Zebu (EASZ) is the main indigenous cattle across East Africa. A recent genome wide SNP analysis revealed an ancient stable African taurine x Asian zebu admixture. Here, we assess the presence of candidate signatures of positive selection in their genome, with the aim to provide qualitative insights about the corresponding selective pressures. Four hundred and twenty-five EASZ and four reference populations (Holstein-Friesian, Jersey, N’Dama and Nellore) were analysed using 46,171 SNPs covering all autosomes and the X chromosome. Following FST and two extended haplotype homozygosity-based (iHS and Rsb) analyses 24 candidate genome regions within 14 autosomes and the X chromosome were revealed, in which 18 and 4 were previously identified in tropical-adapted and commercial breeds, respectively. These regions overlap with 340 bovine QTL. They include 409 annotated genes, in which 37 were considered as candidates. These genes are involved in various biological pathways (e.g. immunity, reproduction, development and heat tolerance). Our results support that different selection pressures (e.g. environmental constraints, human selection, genome admixture constrains) have shaped the genome of EASZ. We argue that these candidate regions represent genome landmarks to be maintained in breeding programs aiming to improve sustainable livestock productivity in the tropics. PMID:26130263

Genomic data as the “hitchhiker's guide” to cattle adaptation: tracking the milestones of past selection in the bovine genome

PubMed Central

Utsunomiya, Yuri T.; Pérez O'Brien, Ana M.; Sonstegard, Tad S.; Sölkner, Johann; Garcia, José F.

2015-01-01

The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle “hitchhiked” on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field. PMID:25713583

Comparing Patterns of Natural Selection across Species Using Selective Signatures

PubMed Central

Shapiro, B. Jesse; Alm, Eric J

2008-01-01

Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 γ-proteobacterial species. We describe the pattern of fast or slow evolution across species as the “selective signature” of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in Idiomarina loihiensis, mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell. PMID:18266472

Atlantic salmon populations reveal adaptive divergence of immune related genes - a duplicated genome under selection.

PubMed

Kjærner-Semb, Erik; Ayllon, Fernando; Furmanek, Tomasz; Wennevik, Vidar; Dahle, Geir; Niemelä, Eero; Ozerov, Mikhail; Vähä, Juha-Pekka; Glover, Kevin A; Rubin, Carl J; Wargelius, Anna; Edvardsen, Rolf B

2016-08-11

Populations of Atlantic salmon display highly significant genetic differences with unresolved molecular basis. These differences may result from separate postglacial colonization patterns, diversifying natural selection and adaptation, or a combination. Adaptation could be influenced or even facilitated by the recent whole genome duplication in the salmonid lineage which resulted in a partly tetraploid species with duplicated genes and regions. In order to elucidate the genes and genomic regions underlying the genetic differences, we conducted a genome wide association study using whole genome resequencing data from eight populations from Northern and Southern Norway. From a total of ~4.5 million sequencing-derived SNPs, more than 10 % showed significant differentiation between populations from these two regions and ten selective sweeps on chromosomes 5, 10, 11, 13-15, 21, 24 and 25 were identified. These comprised 59 genes, of which 15 had one or more differentiated missense mutation. Our analysis showed that most sweeps have paralogous regions in the partially tetraploid genome, each lacking the high number of significant SNPs found in the sweeps. The most significant sweep was found on Chr 25 and carried several missense mutations in the antiviral mx genes, suggesting that these populations have experienced differing viral pressures. Interestingly the second most significant sweep, found on Chr 5, contains two genes involved in the NF-KB pathway (nkap and nkrf), which is also a known pathogen target that controls a large number of processes in animals. Our results show that natural selection acting on immune related genes has contributed to genetic divergence between salmon populations in Norway. The differences between populations may have been facilitated by the plasticity of the salmon genome. The observed signatures of selection in duplicated genomic regions suggest that the recently duplicated genome has provided raw material for evolutionary adaptation.

Whole-genome resequencing reveals signatures of selection and timing of duck domestication.

PubMed

Zhang, Zebin; Jia, Yaxiong; Almeida, Pedro; Mank, Judith E; van Tuinen, Marcel; Wang, Qiong; Jiang, Zhihua; Chen, Yu; Zhan, Kai; Hou, Shuisheng; Zhou, Zhengkui; Li, Huifang; Yang, Fangxi; He, Yong; Ning, Zhonghua; Yang, Ning; Qu, Lujiang

2018-04-01

The genetic basis of animal domestication remains poorly understood, and systems with substantial phenotypic differences between wild and domestic populations are useful for elucidating the genetic basis of adaptation to new environments as well as the genetic basis of rapid phenotypic change. Here, we sequenced the whole genome of 78 individual ducks, from two wild and seven domesticated populations, with an average sequencing depth of 6.42X per individual. Our population and demographic analyses indicate a complex history of domestication, with early selection for separate meat and egg lineages. Genomic comparison of wild to domesticated populations suggests that genes that affect brain and neuronal development have undergone strong positive selection during domestication. Our FST analysis also indicates that the duck white plumage is the result of selection at the melanogenesis-associated transcription factor locus. Our results advance the understanding of animal domestication and selection for complex phenotypic traits.

Genome-wide distribution of genetic diversity and linkage disequilibrium in a mass-selected population of maritime pine

PubMed Central

2014-01-01

Background The accessibility of high-throughput genotyping technologies has contributed greatly to the development of genomic resources in non-model organisms. High-density genotyping arrays have only recently been developed for some economically important species such as conifers. The potential for using genomic technologies in association mapping and breeding depends largely on the genome wide patterns of diversity and linkage disequilibrium in current breeding populations. This study aims to deepen our knowledge regarding these issues in maritime pine, the first species used for reforestation in south western Europe. Results Using a new map merging algorithm, we first established a 1,712 cM composite linkage map (comprising 1,838 SNP markers in 12 linkage groups) by bringing together three already available genetic maps. Using rigorous statistical testing based on kernel density estimation and resampling we identified cold and hot spots of recombination. In parallel, 186 unrelated trees of a mass-selected population were genotyped using a 12k-SNP array. A total of 2,600 informative SNPs allowed to describe historical recombination, genetic diversity and genetic structure of this recently domesticated breeding pool that forms the basis of much of the current and future breeding of this species. We observe very low levels of population genetic structure and find no evidence that artificial selection has caused a reduction in genetic diversity. By combining these two pieces of information, we provided the map position of 1,671 SNPs corresponding to 1,192 different loci. This made it possible to analyze the spatial pattern of genetic diversity (H e ) and long distance linkage disequilibrium (LD) along the chromosomes. We found no particular pattern in the empirical variogram of H e across the 12 linkage groups and, as expected for an outcrossing species with large effective population size, we observed an almost complete lack of long distance LD. Conclusions These

Hybrid selection for sequencing pathogen genomes from clinical samples

PubMed Central

2011-01-01

We have adapted a solution hybrid selection protocol to enrich pathogen DNA in clinical samples dominated by human genetic material. Using mock mixtures of human and Plasmodium falciparum malaria parasite DNA as well as clinical samples from infected patients, we demonstrate an average of approximately 40-fold enrichment of parasite DNA after hybrid selection. This approach will enable efficient genome sequencing of pathogens from clinical samples, as well as sequencing of endosymbiotic organisms such as Wolbachia that live inside diverse metazoan phyla. PMID:21835008

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

PubMed Central

Wichgers Schreur, Paul J.; Kortekaas, Jeroen

2016-01-01

The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH), the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV) genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process. PMID:27548280

Sequencing of a QTL-rich region of the Theobroma cacao genome using pooled BACs and the identification of trait specific candidate genes

USDA-ARS?s Scientific Manuscript database

Background: BAC-based physical maps provide for sequencing across an entire genome or selected sub-genome regions of biological interest. Using the minimum tiling path as a guide, it is possible to select specific BAC clones from prioritized genome sections such as a genetically defined QTL interv...

Genomic selection for the improvement of meat quality in beef.

PubMed

Pimentel, E C G; König, S

2012-10-01

Selection index theory was used to compare different selection strategies aiming at the improvement of meat quality in beef cattle. Alternative strategies were compared with a reference scenario with three basic traits in the selection index: BW at 200 d (W200) and 400 d (W400) and muscling score (MUSC). These traits resemble the combination currently used in the German national beef genetic evaluation system. Traits in the breeding goal were defined as the 3 basic traits plus marbling score (MARB), to depict a situation where an established breeding program currently selecting for growth and carcass yield intends to incorporate meat quality in its selection program. Economic weights were either the same for all 4 traits, or doubled or tripled for MARB. Two additional selection criteria for improving MARB were considered: Live animal intramuscular fat content measured by ultrasound (UIMF) as an indicator trait and a genomic breeding value (GEBV) for the target trait directly (gMARB). Results were used to estimate the required number of genotyped animals in an own calibration set for implementing genomic selection focusing on meat quality. Adding UIMF to the basic index increased the overall genetic gain per generation by 15% when the economic weight on MARB was doubled and by 44% when it was tripled. When a genomic breeding value for marbling could be estimated with an accuracy of 0.5, adding gMARB to the index provided larger genetic gain than adding UIMF. Greatest genetic gain per generation was obtained with the scenario containing GEBV for 4 traits (gW200, gW400, gMUSC, and gMARB) when the accuracies of these GEBV were ≥0.7. Adding UIMF to the index substantially improved response to selection for MARB, which switched from negative to positive when the economic weight on MARB was doubled or tripled. For all scenarios that contained gMARB in the selection index, the response to selection in MARB was positive for all relative economic weights on MARB, when the

Genome-wide scan for selection signatures in six cattle breeds in South Africa.

PubMed

Makina, Sithembile O; Muchadeyi, Farai C; van Marle-Köster, Este; Taylor, Jerry F; Makgahlela, Mahlako L; Maiwashe, Azwihangwisi

2015-11-26

The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (F ST). Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.

Inference of gorilla demographic and selective history from whole-genome sequence data.

PubMed

McManus, Kimberly F; Kelley, Joanna L; Song, Shiya; Veeramah, Krishna R; Woerner, August E; Stevison, Laurie S; Ryder, Oliver A; Ape Genome Project, Great; Kidd, Jeffrey M; Wall, Jeffrey D; Bustamante, Carlos D; Hammer, Michael F

2015-03-01

Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Identification of Genomic Regions Associated with Phenotypic Variation between Dog Breeds using Selection Mapping

PubMed Central

Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H.; Hansen, Mark S. T.; Lawley, Cindy T.; Karlsson, Elinor K.; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Åke; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T.

2011-01-01

The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease. PMID:22022279

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

PubMed

Vaysse, Amaury; Ratnakumar, Abhirami; Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H; Hansen, Mark S T; Lawley, Cindy T; Karlsson, Elinor K; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Ake; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T

2011-10-01

The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

A genome-wide scan for selection signatures in Nelore cattle

USDA-ARS?s Scientific Manuscript database

Brazilian Nelore cattle have been selected for growth traits over more than four decades. In recent years, reproductive and meat quality traits have become more important because of increasing consumption, exports and consumer demand. The identification of genomic regions altered by artificial selec...

Selecting sequence variants to improve genomic predictions for dairy cattle

USDA-ARS?s Scientific Manuscript database

Millions of genetic variants have been identified by population-scale sequencing projects, but subsets are needed for routine genomic predictions or to include on genotyping arrays. Methods of selecting sequence variants were compared using both simulated sequence genotypes and actual data from run ...

Accuracy and training population design for genomic selection in elite north american oats

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) is a method to estimate the breeding values of individuals by using markers throughout the genome. We evaluated the accuracies of GS using data from five traits on 446 oat lines genotyped with 1005 Diversity Array Technology (DArT) markers and two GS methods (RR-BLUP and Bayes...

Genome-Wide Variation Patterns Uncover the Origin and Selection in Cultivated Ginseng (Panax ginseng Meyer).

PubMed

Li, Ming-Rui; Shi, Feng-Xue; Li, Ya-Ling; Jiang, Peng; Jiao, Lili; Liu, Bao; Li, Lin-Feng

2017-09-01

Chinese ginseng (Panax ginseng Meyer) is a medicinally important herb and plays crucial roles in traditional Chinese medicine. Pharmacological analyses identified diverse bioactive components from Chinese ginseng. However, basic biological attributes including domestication and selection of the ginseng plant remain under-investigated. Here, we presented a genome-wide view of the domestication and selection of cultivated ginseng based on the whole genome data. A total of 8,660 protein-coding genes were selected for genome-wide scanning of the 30 wild and cultivated ginseng accessions. In complement, the 45s rDNA, chloroplast and mitochondrial genomes were included to perform phylogenetic and population genetic analyses. The observed spatial genetic structure between northern cultivated ginseng (NCG) and southern cultivated ginseng (SCG) accessions suggested multiple independent origins of cultivated ginseng. Genome-wide scanning further demonstrated that NCG and SCG have undergone distinct selection pressures during the domestication process, with more genes identified in the NCG (97 genes) than in the SCG group (5 genes). Functional analyses revealed that these genes are involved in diverse pathways, including DNA methylation, lignin biosynthesis, and cell differentiation. These findings suggested that the SCG and NCG groups have distinct demographic histories. Candidate genes identified are useful for future molecular breeding of cultivated ginseng. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A genome-wide scan for signatures of directional selection in domesticated pigs.

PubMed

Moon, Sunjin; Kim, Tae-Hun; Lee, Kyung-Tai; Kwak, Woori; Lee, Taeheon; Lee, Si-Woo; Kim, Myung-Jick; Cho, Kyuho; Kim, Namshin; Chung, Won-Hyong; Sung, Samsun; Park, Taesung; Cho, Seoae; Groenen, Martien Am; Nielsen, Rasmus; Kim, Yuseob; Kim, Heebal

2015-02-25

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication. Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness. We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

Genomic selection in domestic animals: Principles, applications and perspectives.

PubMed

Boichard, Didier; Ducrocq, Vincent; Croiseau, Pascal; Fritz, Sébastien

2016-01-01

The principles of genomic selection are described, with the main factors affecting its efficiency and the assumptions underlying the different models proposed. The reasons of its fast adoption in dairy cattle are explained and the conditions of its application to other species are discussed. Perspectives of development include: selection for new traits and new breeding objectives; adoption of more robust approaches based on information on causal variants; predictions of genotype×environment interactions. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection.

PubMed

Haberland, A M; König von Borstel, U; Simianer, H; König, S

2012-09-01

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r(TI) ) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (= accuracy of GEBV) was fixed to a relatively low value of r(mg) = 0.5. For a low heritability trait (h(2) = 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r(TI) from 0.27 to 0.54. Including the conventional information source 'own performance' into the before mentioned index, additional SNP information increases r(TI) by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.

Evaluation of artificial selection in Standard Poodles using whole-genome sequencing.

PubMed

Friedenberg, Steven G; Meurs, Kathryn M; Mackay, Trudy F C

2016-12-01

Identifying regions of artificial selection within dog breeds may provide insights into genetic variation that underlies breed-specific traits or diseases-particularly if these traits or disease predispositions are fixed within a breed. In this study, we searched for runs of homozygosity (ROH) and calculated the d i statistic (which is based upon F ST ) to identify regions of artificial selection in Standard Poodles using high-coverage, whole-genome sequencing data of 15 Standard Poodles and 49 dogs across seven other breeds. We identified consensus ROH regions ≥1 Mb in length and common to at least ten Standard Poodles covering 0.6 % of the genome, and d i regions that most distinguish Standard Poodles from other breeds covering 3.7 % of the genome. Within these regions, we identified enriched gene pathways related to olfaction, digestion, and taste, as well as pathways related to adrenal hormone biosynthesis, T cell function, and protein ubiquitination that could contribute to the pathogenesis of some Poodle-prevalent autoimmune diseases. We also validated variants related to hair coat and skull morphology that have previously been identified as being under selective pressure in Poodles, and flagged additional polymorphisms in genes such as ITGA2B, CBX4, and TNXB that may represent strong candidates for other common Poodle disorders.

Development of selective attention in preschool-age children from lower socioeconomic status backgrounds.

PubMed

Hampton Wray, Amanda; Stevens, Courtney; Pakulak, Eric; Isbell, Elif; Bell, Theodore; Neville, Helen

2017-08-01

Although differences in selective attention skills have been identified in children from lower compared to higher socioeconomic status (SES) backgrounds, little is known about these differences in early childhood, a time of rapid attention development. The current study evaluated the development of neural systems for selective attention in children from lower SES backgrounds. Event-related potentials (ERPs) were acquired from 33 children from lower SES and 14 children from higher SES backgrounds during a dichotic listening task. The lower SES group was followed longitudinally for one year. At age four, the higher SES group exhibited a significant attention effect (larger ERP response to attended compared to unattended condition), an effect not observed in the lower SES group. At age five, the lower SES group exhibited a significant attention effect comparable in overall magnitude to that observed in the 4-year-old higher SES group, but with poorer distractor suppression (larger response to the unattended condition). Together, these findings suggest both a maturational delay and divergent developmental pattern in neural mechanisms for selective attention in young children from lower compared to higher SES backgrounds. Furthermore, these findings highlight the importance of studying neurodevelopment within narrow age ranges and in children from diverse backgrounds. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Positive and purifying selection in mitochondrial genomes of a bird with mitonuclear discordance.

PubMed

Morales, Hernán E; Pavlova, Alexandra; Joseph, Leo; Sunnucks, Paul

2015-06-01

Diversifying selection on metabolic pathways can reduce intraspecific gene flow and promote population divergence. An opportunity to explore this arises from mitonuclear discordance observed in an Australian bird Eopsaltria australis. Across >1500 km, nuclear differentiation is low and latitudinally structured by isolation by distance, whereas two highly divergent, parapatric mitochondrial lineages (>6.6% in ND2) show a discordant longitudinal geographic pattern and experience different climates. Vicariance, incomplete lineage sorting and sex-biased dispersal were shown earlier to be unlikely drivers of the mitonuclear discordance; instead, natural selection on a female-linked trait was the preferred hypothesis. Accordingly, here we tested for signals of positive, divergent selection on mitochondrial genes in E. australis. We used codon models and physicochemical profiles of amino acid replacements to analyse complete mitochondrial genomes of the two mitochondrial lineages in E. australis, its sister species Eopsaltria griseogularis, and outgroups. We found evidence of positive selection on at least five amino acids, encoded by genes of two oxidative phosphorylation pathway complexes NADH dehydrogenase (ND4 and ND4L) and cytochrome bc1 (cyt-b) against a background of widespread purifying selection on all mitochondrial genes. Three of these amino acid replacements were fixed in ND4 of the geographically most widespread E. australis lineage. The other two replacements were fixed in ND4L and cyt-b of the geographically more restricted E. australis lineage. We discuss whether this selection may reflect local environmental adaptation, a by-product of other selective processes, or genetic incompatibilities, and propose how these hypotheses can be tested in future. © 2015 John Wiley & Sons Ltd.

flyDIVaS: A Comparative Genomics Resource for Drosophila Divergence and Selection

PubMed Central

Stanley, Craig E.; Kulathinal, Rob J.

2016-01-01

With arguably the best finished and expertly annotated genome assembly, Drosophila melanogaster is a formidable genetics model to study all aspects of biology. Nearly a decade ago, the 12 Drosophila genomes project expanded D. melanogaster’s breadth as a comparative model through the community-development of an unprecedented genus- and genome-wide comparative resource. However, since its inception, these datasets for evolutionary inference and biological discovery have become increasingly outdated, outmoded, and inaccessible. Here, we provide an updated and upgradable comparative genomics resource of Drosophila divergence and selection, flyDIVaS, based on the latest genomic assemblies, curated FlyBase annotations, and recent OrthoDB orthology calls. flyDIVaS is an online database containing D. melanogaster-centric orthologous gene sets, CDS and protein alignments, divergence statistics (% gaps, dN, dS, dN/dS), and codon-based tests of positive Darwinian selection. Out of 13,920 protein-coding D. melanogaster genes, ∼80% have one aligned ortholog in the closely related species, D. simulans, and ∼50% have 1–1 12-way alignments in the original 12 sequenced species that span over 80 million yr of divergence. Genes and their orthologs can be chosen from four different taxonomic datasets differing in phylogenetic depth and coverage density, and visualized via interactive alignments and phylogenetic trees. Users can also batch download entire comparative datasets. A functional survey finds conserved mitotic and neural genes, highly diverged immune and reproduction-related genes, more conspicuous signals of divergence across tissue-specific genes, and an enrichment of positive selection among highly diverged genes. flyDIVaS will be regularly updated and can be freely accessed at www.flydivas.info. We encourage researchers to regularly use this resource as a tool for biological inference and discovery, and in their classrooms to help train the next generation of

flyDIVaS: A Comparative Genomics Resource for Drosophila Divergence and Selection.

PubMed

Stanley, Craig E; Kulathinal, Rob J

2016-08-09

With arguably the best finished and expertly annotated genome assembly, Drosophila melanogaster is a formidable genetics model to study all aspects of biology. Nearly a decade ago, the 12 Drosophila genomes project expanded D. melanogaster's breadth as a comparative model through the community-development of an unprecedented genus- and genome-wide comparative resource. However, since its inception, these datasets for evolutionary inference and biological discovery have become increasingly outdated, outmoded, and inaccessible. Here, we provide an updated and upgradable comparative genomics resource of Drosophila divergence and selection, flyDIVaS, based on the latest genomic assemblies, curated FlyBase annotations, and recent OrthoDB orthology calls. flyDIVaS is an online database containing D. melanogaster-centric orthologous gene sets, CDS and protein alignments, divergence statistics (% gaps, dN, dS, dN/dS), and codon-based tests of positive Darwinian selection. Out of 13,920 protein-coding D. melanogaster genes, ∼80% have one aligned ortholog in the closely related species, D. simulans, and ∼50% have 1-1 12-way alignments in the original 12 sequenced species that span over 80 million yr of divergence. Genes and their orthologs can be chosen from four different taxonomic datasets differing in phylogenetic depth and coverage density, and visualized via interactive alignments and phylogenetic trees. Users can also batch download entire comparative datasets. A functional survey finds conserved mitotic and neural genes, highly diverged immune and reproduction-related genes, more conspicuous signals of divergence across tissue-specific genes, and an enrichment of positive selection among highly diverged genes. flyDIVaS will be regularly updated and can be freely accessed at www.flydivas.info We encourage researchers to regularly use this resource as a tool for biological inference and discovery, and in their classrooms to help train the next generation of

The Jujube Genome Provides Insights into Genome Evolution and the Domestication of Sweetness/Acidity Taste in Fruit Trees.

PubMed

Huang, Jian; Zhang, Chunmei; Zhao, Xing; Fei, Zhangjun; Wan, KangKang; Zhang, Zhong; Pang, Xiaoming; Yin, Xiao; Bai, Yang; Sun, Xiaoqing; Gao, Lizhi; Li, Ruiqiang; Zhang, Jinbo; Li, Xingang

2016-12-01

Jujube (Ziziphus jujuba Mill.) belongs to the Rhamnaceae family and is a popular fruit tree species with immense economic and nutritional value. Here, we report a draft genome of the dry jujube cultivar 'Junzao' and the genome resequencing of 31 geographically diverse accessions of cultivated and wild jujubes (Ziziphus jujuba var. spinosa). Comparative analysis revealed that the genome of 'Dongzao', a fresh jujube, was ~86.5 Mb larger than that of the 'Junzao', partially due to the recent insertions of transposable elements in the 'Dongzao' genome. We constructed eight proto-chromosomes of the common ancestor of Rhamnaceae and Rosaceae, two sister families in the order Rosales, and elucidated the evolutionary processes that have shaped the genome structures of modern jujubes. Population structure analysis revealed the complex genetic background of jujubes resulting from extensive hybridizations between jujube and its wild relatives. Notably, several key genes that control fruit organic acid metabolism and sugar content were identified in the selective sweep regions. We also identified S-locus genes controlling gametophytic self-incompatibility and investigated haplotype patterns of the S locus in the jujube genomes, which would provide a guideline for parent selection for jujube crossbreeding. This study provides valuable genomic resources for jujube improvement, and offers insights into jujube genome evolution and its population structure and domestication.

Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle.

PubMed

Rolf, Megan M; Taylor, Jeremy F; Schnabel, Robert D; McKay, Stephanie D; McClure, Matthew C; Northcutt, Sally L; Kerley, Monty S; Weaber, Robert L

2010-04-19

Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain) recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population. Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle. This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix.

The genomic landscape shaped by selection on transposable elements across 18 mouse strains.

PubMed

Nellåker, Christoffer; Keane, Thomas M; Yalcin, Binnaz; Wong, Kim; Agam, Avigail; Belgard, T Grant; Flint, Jonathan; Adams, David J; Frankel, Wayne N; Ponting, Chris P

2012-06-15

Transposable element (TE)-derived sequence dominates the landscape of mammalian genomes and can modulate gene function by dysregulating transcription and translation. Our current knowledge of TEs in laboratory mouse strains is limited primarily to those present in the C57BL/6J reference genome, with most mouse TEs being drawn from three distinct classes, namely short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs) and the endogenous retrovirus (ERV) superfamily. Despite their high prevalence, the different genomic and gene properties controlling whether TEs are preferentially purged from, or are retained by, genetic drift or positive selection in mammalian genomes remain poorly defined. Using whole genome sequencing data from 13 classical laboratory and 4 wild-derived mouse inbred strains, we developed a comprehensive catalogue of 103,798 polymorphic TE variants. We employ this extensive data set to characterize TE variants across the Mus lineage, and to infer neutral and selective processes that have acted over 2 million years. Our results indicate that the majority of TE variants are introduced though the male germline and that only a minority of TE variants exert detectable changes in gene expression. However, among genes with differential expression across the strains there are twice as many TE variants identified as being putative causal variants as expected. Most TE variants that cause gene expression changes appear to be purged rapidly by purifying selection. Our findings demonstrate that past TE insertions have often been highly deleterious, and help to prioritize TE variants according to their likely contribution to gene expression or phenotype variation.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

PubMed

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-06-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

Genomic data for 78 chickens from 14 populations

PubMed Central

Li, Diyan; Che, Tiandong; Chen, Binlong; Tian, Shilin; Zhou, Xuming; Zhang, Guolong; Li, Miao; Gaur, Uma; Li, Yan; Luo, Majing; Zhang, Long; Xu, Zhongxian; Zhao, Xiaoling; Yin, Huadong; Wang, Yan; Jin, Long; Tang, Qianzi; Xu, Huailiang; Yang, Mingyao; Zhou, Rongjia; Li, Ruiqiang

2017-01-01

Abstract Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to ∼10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ∼21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ∼6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens. PMID:28431039

Function-selective domain architecture plasticity potentials in eukaryotic genome evolution

PubMed Central

Linkeviciute, Viktorija; Rackham, Owen J.L.; Gough, Julian; Oates, Matt E.; Fang, Hai

2015-01-01

To help evaluate how protein function impacts on genome evolution, we introduce a new concept of ‘architecture plasticity potential’ – the capacity to form distinct domain architectures – both for an individual domain, or more generally for a set of domains grouped by shared function. We devise a scoring metric to measure the plasticity potential for these domain sets, and evaluate how function has changed over time for different species. Applying this metric to a phylogenetic tree of eukaryotic genomes, we find that the involvement of each function is not random but highly selective. For certain lineages there is strong bias for evolution to involve domains related to certain functions. In general eukaryotic genomes, particularly animals, expand complex functional activities such as signalling and regulation, but at the cost of reducing metabolic processes. We also observe differential evolution of transcriptional regulation and a unique evolutionary role of channel regulators; crucially this is only observable in terms of the architecture plasticity potential. Our findings provide a new layer of information to understand the significance of function in eukaryotic genome evolution. A web search tool, available at http://supfam.org/Pevo, offers a wide spectrum of options for exploring functional importance in eukaryotic genome evolution. PMID:25980317

Can we use genetic and genomic approaches to identify candidate animals for targeted selective treatment.

PubMed

Laurenson, Yan C S M; Kyriazakis, Ilias; Bishop, Stephen C

2013-10-18

Estimated breeding values (EBV) for faecal egg count (FEC) and genetic markers for host resistance to nematodes may be used to identify resistant animals for selective breeding programmes. Similarly, targeted selective treatment (TST) requires the ability to identify the animals that will benefit most from anthelmintic treatment. A mathematical model was used to combine the concepts and evaluate the potential of using genetic-based methods to identify animals for a TST regime. EBVs obtained by genomic prediction were predicted to be the best determinant criterion for TST in terms of the impact on average empty body weight and average FEC, whereas pedigree-based EBVs for FEC were predicted to be marginally worse than using phenotypic FEC as a determinant criterion. Whilst each method has financial implications, if the identification of host resistance is incorporated into a wider genomic selection indices or selective breeding programmes, then genetic or genomic information may be plausibly included in TST regimes. Copyright © 2013 Elsevier B.V. All rights reserved.

Genomic selection across multiple breeding cycles in applied bread wheat breeding.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2016-06-01

We evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Genomic and environmental selection patterns in two distinct lettuce crop–wild hybrid crosses

PubMed Central

Hartman, Yorike; Uwimana, Brigitte; Hooftman, Danny A P; Schranz, Michael E; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2013-01-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop–wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop–wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar–wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability. PMID:23789025

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses.

PubMed

Hartman, Yorike; Uwimana, Brigitte; Hooftman, Danny A P; Schranz, Michael E; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2013-06-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop-wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop-wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar-wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability.

Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers.

PubMed

Brito, Luiz F; Kijas, James W; Ventura, Ricardo V; Sargolzaei, Mehdi; Porto-Neto, Laercio R; Cánovas, Angela; Feng, Zeny; Jafarikia, Mohsen; Schenkel, Flávio S

2017-03-14

The detection of signatures of selection has the potential to elucidate the identities of genes and mutations associated with phenotypic traits important for livestock species. It is also very relevant to investigate the levels of genetic diversity of a population, as genetic diversity represents the raw material essential for breeding and has practical implications for implementation of genomic selection. A total of 1151 animals from nine goat populations selected for different breeding goals and genotyped with the Illumina Goat 50K single nucleotide polymorphisms (SNP) Beadchip were included in this investigation. The proportion of polymorphic SNPs ranged from 0.902 (Nubian) to 0.995 (Rangeland). The overall mean H O and H E was 0.374 ± 0.021 and 0.369 ± 0.023, respectively. The average pairwise genetic distance (D) ranged from 0.263 (Toggenburg) to 0.323 (Rangeland). The overall average for the inbreeding measures F EH , F VR , F LEUT , F ROH and F PED was 0.129, -0.012, -0.010, 0.038 and 0.030, respectively. Several regions located on 19 chromosomes were potentially under selection in at least one of the goat breeds. The genomic population tree constructed using all SNPs differentiated breeds based on selection purpose, while genomic population tree built using only SNPs in the most significant region showed a great differentiation between LaMancha and the other breeds. We hypothesized that this region is related to ear morphogenesis. Furthermore, we identified genes potentially related to reproduction traits, adult body mass, efficiency of food conversion, abdominal fat deposition, conformation traits, liver fat metabolism, milk fatty acids, somatic cells score, milk protein, thermo-tolerance and ear morphogenesis. In general, moderate to high levels of genetic variability were observed for all the breeds and a characterization of runs of homozygosity gave insights into the breeds' development history. The information reported here will be useful for

A systems approach defining constraints of the genome architecture on lineage selection and evolvability during somatic cancer evolution

PubMed Central

Rübben, Albert; Nordhoff, Ole

2013-01-01

Summary Most clinically distinguishable malignant tumors are characterized by specific mutations, specific patterns of chromosomal rearrangements and a predominant mechanism of genetic instability but it remains unsolved whether modifications of cancer genomes can be explained solely by mutations and selection through the cancer microenvironment. It has been suggested that internal dynamics of genomic modifications as opposed to the external evolutionary forces have a significant and complex impact on Darwinian species evolution. A similar situation can be expected for somatic cancer evolution as molecular key mechanisms encountered in species evolution also constitute prevalent mutation mechanisms in human cancers. This assumption is developed into a systems approach of carcinogenesis which focuses on possible inner constraints of the genome architecture on lineage selection during somatic cancer evolution. The proposed systems approach can be considered an analogy to the concept of evolvability in species evolution. The principal hypothesis is that permissive or restrictive effects of the genome architecture on lineage selection during somatic cancer evolution exist and have a measurable impact. The systems approach postulates three classes of lineage selection effects of the genome architecture on somatic cancer evolution: i) effects mediated by changes of fitness of cells of cancer lineage, ii) effects mediated by changes of mutation probabilities and iii) effects mediated by changes of gene designation and physical and functional genome redundancy. Physical genome redundancy is the copy number of identical genetic sequences. Functional genome redundancy of a gene or a regulatory element is defined as the number of different genetic elements, regardless of copy number, coding for the same specific biological function within a cancer cell. Complex interactions of the genome architecture on lineage selection may be expected when modifications of the genome

Genomic Signatures of Selective Pressures and Introgression from Archaic Hominins at Human Innate Immunity Genes

PubMed Central

Deschamps, Matthieu; Laval, Guillaume; Fagny, Maud; Itan, Yuval; Abel, Laurent; Casanova, Jean-Laurent; Patin, Etienne; Quintana-Murci, Lluis

2016-01-01

Human genes governing innate immunity provide a valuable tool for the study of the selective pressure imposed by microorganisms on host genomes. A comprehensive, genome-wide study of how selective constraints and adaptations have driven the evolution of innate immunity genes is missing. Using full-genome sequence variation from the 1000 Genomes Project, we first show that innate immunity genes have globally evolved under stronger purifying selection than the remainder of protein-coding genes. We identify a gene set under the strongest selective constraints, mutations in which are likely to predispose individuals to life-threatening disease, as illustrated by STAT1 and TRAF3. We then evaluate the occurrence of local adaptation and detect 57 high-scoring signals of positive selection at innate immunity genes, variation in which has been associated with susceptibility to common infectious or autoimmune diseases. Furthermore, we show that most adaptations targeting coding variation have occurred in the last 6,000–13,000 years, the period at which populations shifted from hunting and gathering to farming. Finally, we show that innate immunity genes present higher Neandertal introgression than the remainder of the coding genome. Notably, among the genes presenting the highest Neandertal ancestry, we find the TLR6-TLR1-TLR10 cluster, which also contains functional adaptive variation in Europeans. This study identifies highly constrained genes that fulfill essential, non-redundant functions in host survival and reveals others that are more permissive to change—containing variation acquired from archaic hominins or adaptive variants in specific populations—improving our understanding of the relative biological importance of innate immunity pathways in natural conditions. PMID:26748513

Genome characterization of the selected long- and short-sleep mouse lines.

PubMed

Dowell, Robin; Odell, Aaron; Richmond, Phillip; Malmer, Daniel; Halper-Stromberg, Eitan; Bennett, Beth; Larson, Colin; Leach, Sonia; Radcliffe, Richard A

2016-12-01

The Inbred Long- and Short-Sleep (ILS, ISS) mouse lines were selected for differences in acute ethanol sensitivity using the loss of righting response (LORR) as the selection trait. The lines show an over tenfold difference in LORR and, along with a recombinant inbred panel derived from them (the LXS), have been widely used to dissect the genetic underpinnings of acute ethanol sensitivity. Here we have sequenced the genomes of the ILS and ISS to investigate the DNA variants that contribute to their sensitivity difference. We identified ~2.7 million high-confidence SNPs and small indels and ~7000 structural variants between the lines; variants were found to occur in 6382 annotated genes. Using a hidden Markov model, we were able to reconstruct the genome-wide ancestry patterns of the eight inbred progenitor strains from which the ILS and ISS were derived, and found that quantitative trait loci that have been mapped for LORR were slightly enriched for DNA variants. Finally, by mapping and quantifying RNA-seq reads from the ILS and ISS to their strain-specific genomes rather than to the reference genome, we found a substantial improvement in a differential expression analysis between the lines. This work will help in identifying and characterizing the DNA sequence variants that contribute to the difference in ethanol sensitivity between the ILS and ISS and will also aid in accurate quantification of RNA-seq data generated from the LXS RIs.

Signatures of positive selection in East African Shorthorn Zebu: a genome-wide SNP analysis

USDA-ARS?s Scientific Manuscript database

The small East African Shorthorn Zebu is the main indigenous cattle across East Africa. A recent genome wide SNPs analysis has revealed their ancient stable African taurine x Asian zebu admixture. Here, we assess the presence of candidate signature of positive selection in their genome, with the aim...

Genetic diversity, molecular phylogeny and selection evidence of the silkworm mitochondria implicated by complete resequencing of 41 genomes

PubMed Central

2010-01-01

Background Mitochondria are a valuable resource for studying the evolutionary process and deducing phylogeny. A few mitochondria genomes have been sequenced, but a comprehensive picture of the domestication event for silkworm mitochondria remains to be established. In this study, we integrate the extant data, and perform a whole genome resequencing of Japanese wild silkworm to obtain breakthrough results in silkworm mitochondrial (mt) population, and finally use these to deduce a more comprehensive phylogeny of the Bombycidae. Results We identified 347 single nucleotide polymorphisms (SNPs) in the mt genome, but found no past recombination event to have occurred in the silkworm progenitor. A phylogeny inferred from these whole genome SNPs resulted in a well-classified tree, confirming that the domesticated silkworm, Bombyx mori, most recently diverged from the Chinese wild silkworm, rather than from the Japanese wild silkworm. We showed that the population sizes of the domesticated and Chinese wild silkworms both experience neither expansion nor contraction. We also discovered that one mt gene, named cytochrome b, shows a strong signal of positive selection in the domesticated clade. This gene is related to energy metabolism, and may have played an important role during silkworm domestication. Conclusions We present a comparative analysis on 41 mt genomes of B. mori and B. mandarina from China and Japan. With these, we obtain a much clearer picture of the evolution history of the silkworm. The data and analyses presented here aid our understanding of the silkworm in general, and provide a crucial insight into silkworm phylogeny. PMID:20334646

Patterns of population differentiation and natural selection on the celiac disease background risk network.

PubMed

Sams, Aaron; Hawks, John

2013-01-01

Celiac disease is a common small intestinal inflammatory condition induced by wheat gluten and related proteins from rye and barley. Left untreated, the clinical presentation of CD can include failure to thrive, malnutrition, and distension in juveniles. The disease can additionally lead to vitamin deficiencies, anemia, and osteoporosis. Therefore, CD potentially negatively affected fitness in past populations utilizing wheat, barley, and rye. Previous analyses of CD risk variants have uncovered evidence for positive selection on some of these loci. These studies also suggest the possibility that risk for common autoimmune conditions such as CD may be the result of positive selection on immune related loci in the genome to fight infection. Under this evolutionary scenario, disease phenotypes may be a trade-off from positive selection on immunity. If this hypothesis is generally true, we can expect to find a signal of natural selection when we survey across the network of loci known to influence CD risk. This study examines the non-HLA autosomal network of gene loci associated with CD risk in Europe. We reject the null hypothesis of neutrality on this network of CD risk loci. Additionally, we can localize evidence of selection in time and space by adding information from the genome of the Tyrolean Iceman. While we can show significant differentiation between continental regions across the CD network, the pattern of evidence is not consistent with primarily recent (Holocene) selection across this network in Europe. Further localization of ancient selection on this network may illuminate the ecological pressures acting on the immune system during this critically interesting phase of our evolution.

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

PubMed

Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

A genome-wide scan for signatures of selection in Chinese indigenous and commercial pig breeds.

PubMed

Yang, Songbai; Li, Xiuling; Li, Kui; Fan, Bin; Tang, Zhonglin

2014-01-15

Modern breeding and artificial selection play critical roles in pig domestication and shape the genetic variation of different breeds. China has many indigenous pig breeds with various characteristics in morphology and production performance that differ from those of foreign commercial pig breeds. However, the signatures of selection on genes implying for economic traits between Chinese indigenous and commercial pigs have been poorly understood. We identified footprints of positive selection at the whole genome level, comprising 44,652 SNPs genotyped in six Chinese indigenous pig breeds, one developed breed and two commercial breeds. An empirical genome-wide distribution of Fst (F-statistics) was constructed based on estimations of Fst for each SNP across these nine breeds. We detected selection at the genome level using the High-Fst outlier method and found that 81 candidate genes show high evidence of positive selection. Furthermore, the results of network analyses showed that the genes that displayed evidence of positive selection were mainly involved in the development of tissues and organs, and the immune response. In addition, we calculated the pairwise Fst between Chinese indigenous and commercial breeds (CHN VS EURO) and between Northern and Southern Chinese indigenous breeds (Northern VS Southern). The IGF1R and ESR1 genes showed evidence of positive selection in the CHN VS EURO and Northern VS Southern groups, respectively. In this study, we first identified the genomic regions that showed evidences of selection between Chinese indigenous and commercial pig breeds using the High-Fst outlier method. These regions were found to be involved in the development of tissues and organs, the immune response, growth and litter size. The results of this study provide new insights into understanding the genetic variation and domestication in pigs.

Genomic regions with a history of divergent selection affect fitness of hybrids between two butterfly species.

PubMed

Gompert, Zachariah; Lucas, Lauren K; Nice, Chris C; Fordyce, James A; Forister, Matthew L; Buerkle, C Alex

2012-07-01

Speciation is the process by which reproductively isolated lineages arise, and is one of the fundamental means by which the diversity of life increases. Whereas numerous studies have documented an association between ecological divergence and reproductive isolation, relatively little is known about the role of natural selection in genome divergence during the process of speciation. Here, we use genome-wide DNA sequences and Bayesian models to test the hypothesis that loci under divergent selection between two butterfly species (Lycaeides idas and L. melissa) also affect fitness in an admixed population. Locus-specific measures of genetic differentiation between L. idas and L. melissa and genomic introgression in hybrids varied across the genome. The most differentiated genetic regions were characterized by elevated L. idas ancestry in the admixed population, which occurs in L. idas-like habitat, consistent with the hypothesis that local adaptation contributes to speciation. Moreover, locus-specific measures of genetic differentiation (a metric of divergent selection) were positively associated with extreme genomic introgression (a metric of hybrid fitness). Interestingly, concordance of differentiation and introgression was only partial. We discuss multiple, complementary explanations for this partial concordance. © 2012 The Author(s).

Natural Selection and Recombination Rate Variation Shape Nucleotide Polymorphism Across the Genomes of Three Related Populus Species

PubMed Central

Wang, Jing; Street, Nathaniel R.; Scofield, Douglas G.; Ingvarsson, Pär K.

2016-01-01

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome resequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum, and population-scaled recombination rates in three species of Populus: Populus tremula, P. tremuloides, and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies, and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, due to both purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination largely explain the disparate magnitudes and signatures of linked selection that we observe among species. The present work provides the first phylogenetic comparative study on a genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species. PMID:26721855

Natural Selection and Recombination Rate Variation Shape Nucleotide Polymorphism Across the Genomes of Three Related Populus Species.

PubMed

Wang, Jing; Street, Nathaniel R; Scofield, Douglas G; Ingvarsson, Pär K

2016-03-01

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome resequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum, and population-scaled recombination rates in three species of Populus: Populus tremula, P. tremuloides, and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies, and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, due to both purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination largely explain the disparate magnitudes and signatures of linked selection that we observe among species. The present work provides the first phylogenetic comparative study on a genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species. Copyright © 2016 by the Genetics Society of America.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat

PubMed Central

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-01-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection. PMID:24518889

The Jujube Genome Provides Insights into Genome Evolution and the Domestication of Sweetness/Acidity Taste in Fruit Trees

PubMed Central

Wan, KangKang; Zhang, Zhong; Pang, Xiaoming; Yin, Xiao; Bai, Yang; Sun, Xiaoqing; Gao, Lizhi; Li, Ruiqiang; Zhang, Jinbo

2016-01-01

Jujube (Ziziphus jujuba Mill.) belongs to the Rhamnaceae family and is a popular fruit tree species with immense economic and nutritional value. Here, we report a draft genome of the dry jujube cultivar ‘Junzao’ and the genome resequencing of 31 geographically diverse accessions of cultivated and wild jujubes (Ziziphus jujuba var. spinosa). Comparative analysis revealed that the genome of ‘Dongzao’, a fresh jujube, was ~86.5 Mb larger than that of the ‘Junzao’, partially due to the recent insertions of transposable elements in the ‘Dongzao’ genome. We constructed eight proto-chromosomes of the common ancestor of Rhamnaceae and Rosaceae, two sister families in the order Rosales, and elucidated the evolutionary processes that have shaped the genome structures of modern jujubes. Population structure analysis revealed the complex genetic background of jujubes resulting from extensive hybridizations between jujube and its wild relatives. Notably, several key genes that control fruit organic acid metabolism and sugar content were identified in the selective sweep regions. We also identified S-locus genes controlling gametophytic self-incompatibility and investigated haplotype patterns of the S locus in the jujube genomes, which would provide a guideline for parent selection for jujube crossbreeding. This study provides valuable genomic resources for jujube improvement, and offers insights into jujube genome evolution and its population structure and domestication. PMID:28005948

Genomic signatures of parasite-driven natural selection in north European Atlantic salmon (Salmo salar).

PubMed

Zueva, Ksenia J; Lumme, Jaakko; Veselov, Alexey E; Kent, Matthew P; Primmer, Craig R

2018-06-01

Understanding the genomic basis of host-parasite adaptation is important for predicting the long-term viability of species and developing successful management practices. However, in wild populations, identifying specific signatures of parasite-driven selection often presents a challenge, as it is difficult to unravel the molecular signatures of selection driven by different, but correlated, environmental factors. Furthermore, separating parasite-mediated selection from similar signatures due to genetic drift and population history can also be difficult. Populations of Atlantic salmon (Salmo salar L.) from northern Europe have pronounced differences in their reactions to the parasitic flatworm Gyrodactylus salaris Malmberg 1957 and are therefore a good model to search for specific genomic regions underlying inter-population differences in pathogen response. We used a dense Atlantic salmon SNP array, along with extensive sampling of 43 salmon populations representing the two G. salaris response extremes (extreme susceptibility vs resistant), to screen the salmon genome for signatures of directional selection while attempting to separate the parasite effect from other factors. After combining the results from two independent genome scan analyses, 57 candidate genes potentially under positive selection were identified, out of which 50 were functionally annotated. This candidate gene set was shown to be functionally enriched for lymph node development, focal adhesion genes and anti-viral response, which suggests that the regulation of both innate and acquired immunity might be an important mechanism for salmon response to G. salaris. Overall, our results offer insights into the apparently complex genetic basis of pathogen susceptibility in salmon and highlight methodological challenges for separating the effects of various environmental factors. Copyright © 2018 Elsevier B.V. All rights reserved.

Upweighting rare favourable alleles increases long-term genetic gain in genomic selection programs.

PubMed

Liu, Huiming; Meuwissen, Theo H E; Sørensen, Anders C; Berg, Peer

2015-03-21

The short-term impact of using different genomic prediction (GP) models in genomic selection has been intensively studied, but their long-term impact is poorly understood. Furthermore, long-term genetic gain of genomic selection is expected to improve by using Jannink's weighting (JW) method, in which rare favourable marker alleles are upweighted in the selection criterion. In this paper, we extend the JW method by including an additional parameter to decrease the emphasis on rare favourable alleles over the time horizon, with the purpose of further improving the long-term genetic gain. We call this new method dynamic weighting (DW). The paper explores the long-term impact of different GP models with or without weighting methods. Different selection criteria were tested by simulating a population of 500 animals with truncation selection of five males and 50 females. Selection criteria included unweighted and weighted genomic estimated breeding values using the JW or DW methods, for which ridge regression (RR) and Bayesian lasso (BL) were used to estimate marker effects. The impacts of these selection criteria were compared under three genetic architectures, i.e. varying numbers of QTL for the trait and for two time horizons of 15 (TH15) or 40 (TH40) generations. For unweighted GP, BL resulted in up to 21.4% higher long-term genetic gain and 23.5% lower rate of inbreeding under TH40 than RR. For weighted GP, DW resulted in 1.3 to 5.5% higher long-term gain compared to unweighted GP. JW, however, showed a 6.8% lower long-term genetic gain relative to unweighted GP when BL was used to estimate the marker effects. Under TH40, both DW and JW obtained significantly higher genetic gain than unweighted GP. With DW, the long-term genetic gain was increased by up to 30.8% relative to unweighted GP, and also increased by 8% relative to JW, although at the expense of a lower short-term gain. Irrespective of the number of QTL simulated, BL is superior to RR in maintaining

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.

PubMed

Mariani, Luca; Weinand, Kathryn; Vedenko, Anastasia; Barrera, Luis A; Bulyk, Martha L

2017-09-27

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs. Copyright © 2017 Elsevier Inc. All rights reserved.

A genome-wide scan for signatures of differential artificial selection in ten cattle breeds.

PubMed

Rothammer, Sophie; Seichter, Doris; Förster, Martin; Medugorac, Ivica

2013-12-21

Since the times of domestication, cattle have been continually shaped by the influence of humans. Relatively recent history, including breed formation and the still enduring enormous improvement of economically important traits, is expected to have left distinctive footprints of selection within the genome. The purpose of this study was to map genome-wide selection signatures in ten cattle breeds and thus improve the understanding of the genome response to strong artificial selection and support the identification of the underlying genetic variants of favoured phenotypes. We analysed 47,651 single nucleotide polymorphisms (SNP) using Cross Population Extended Haplotype Homozygosity (XP-EHH). We set the significance thresholds using the maximum XP-EHH values of two essentially artificially unselected breeds and found up to 229 selection signatures per breed. Through a confirmation process we verified selection for three distinct phenotypes typical for one breed (polledness in Galloway, double muscling in Blanc-Bleu Belge and red coat colour in Red Holstein cattle). Moreover, we detected six genes strongly associated with known QTL for beef or dairy traits (TG, ABCG2, DGAT1, GH1, GHR and the Casein Cluster) within selection signatures of at least one breed. A literature search for genes lying in outstanding signatures revealed further promising candidate genes. However, in concordance with previous genome-wide studies, we also detected a substantial number of signatures without any yet known gene content. These results show the power of XP-EHH analyses in cattle to discover promising candidate genes and raise the hope of identifying phenotypically important variants in the near future. The finding of plausible functional candidates in some short signatures supports this hope. For instance, MAP2K6 is the only annotated gene of two signatures detected in Galloway and Gelbvieh cattle and is already known to be associated with carcass weight, back fat thickness and

Nuclease Target Site Selection for Maximizing On-target Activity and Minimizing Off-target Effects in Genome Editing

PubMed Central

Lee, Ciaran M; Cradick, Thomas J; Fine, Eli J; Bao, Gang

2016-01-01

The rapid advancement in targeted genome editing using engineered nucleases such as ZFNs, TALENs, and CRISPR/Cas9 systems has resulted in a suite of powerful methods that allows researchers to target any genomic locus of interest. A complementary set of design tools has been developed to aid researchers with nuclease design, target site selection, and experimental validation. Here, we review the various tools available for target selection in designing engineered nucleases, and for quantifying nuclease activity and specificity, including web-based search tools and experimental methods. We also elucidate challenges in target selection, especially in predicting off-target effects, and discuss future directions in precision genome editing and its applications. PMID:26750397

Analysis of adaptive evolution in Lyssavirus genomes reveals pervasive diversifying selection during species diversification.

PubMed

Voloch, Carolina M; Capellão, Renata T; Mello, Beatriz; Schrago, Carlos G

2014-11-19

Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G), RNA-dependent RNA polymerase (L) and polymerase (P) genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups.

Analysis of Adaptive Evolution in Lyssavirus Genomes Reveals Pervasive Diversifying Selection during Species Diversification

PubMed Central

Voloch, Carolina M.; Capellão, Renata T.; Mello, Beatriz; Schrago, Carlos G.

2014-01-01

Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G), RNA-dependent RNA polymerase (L) and polymerase (P) genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups. PMID:25415197

The genomics of selection in dogs and the parallel evolution between dogs and humans.

PubMed

Wang, Guo-dong; Zhai, Weiwei; Yang, He-chuan; Fan, Ruo-xi; Cao, Xue; Zhong, Li; Wang, Lu; Liu, Fei; Wu, Hong; Cheng, Lu-guang; Poyarkov, Andrei D; Poyarkov, Nikolai A; Tang, Shu-sheng; Zhao, Wen-ming; Gao, Yun; Lv, Xue-mei; Irwin, David M; Savolainen, Peter; Wu, Chung-I; Zhang, Ya-ping

2013-01-01

The genetic bases of demographic changes and artificial selection underlying domestication are of great interest in evolutionary biology. Here we perform whole-genome sequencing of multiple grey wolves, Chinese indigenous dogs and dogs of diverse breeds. Demographic analysis show that the split between wolves and Chinese indigenous dogs occurred 32,000 years ago and that the subsequent bottlenecks were mild. Therefore, dogs may have been under human selection over a much longer time than previously concluded, based on molecular data, perhaps by initially scavenging with humans. Population genetic analysis identifies a list of genes under positive selection during domestication, which overlaps extensively with the corresponding list of positively selected genes in humans. Parallel evolution is most apparent in genes for digestion and metabolism, neurological process and cancer. Our study, for the first time, draws together humans and dogs in their recent genomic evolution.

Genomic selection of agronomic traits in hybrid rice using an NCII population.

PubMed

Xu, Yang; Wang, Xin; Ding, Xiaowen; Zheng, Xingfei; Yang, Zefeng; Xu, Chenwu; Hu, Zhongli

2018-05-10

Hybrid breeding is an effective tool to improve yield in rice, while parental selection remains the key and difficult issue. Genomic selection (GS) provides opportunities to predict the performance of hybrids before phenotypes are measured. However, the application of GS is influenced by several genetic and statistical factors. Here, we used a rice North Carolina II (NC II) population constructed by crossing 115 rice varieties with five male sterile lines as a model to evaluate effects of statistical methods, heritability, marker density and training population size on prediction for hybrid performance. From the comparison of six GS methods, we found that predictabilities for different methods are significantly different, with genomic best linear unbiased prediction (GBLUP) and least absolute shrinkage and selection operation (LASSO) being the best, support vector machine (SVM) and partial least square (PLS) being the worst. The marker density has lower influence on predicting rice hybrid performance compared with the size of training population. Additionally, we used the 575 (115 × 5) hybrid rice as a training population to predict eight agronomic traits of all hybrids derived from 120 (115 + 5) rice varieties each mating with 3023 rice accessions from the 3000 rice genomes project (3 K RGP). Of the 362,760 potential hybrids, selection of the top 100 predicted hybrids would lead to 35.5%, 23.25%, 30.21%, 42.87%, 61.80%, 75.83%, 19.24% and 36.12% increase in grain yield per plant, thousand-grain weight, panicle number per plant, plant height, secondary branch number, grain number per panicle, panicle length and primary branch number, respectively. This study evaluated the factors affecting predictabilities for hybrid prediction and demonstrated the implementation of GS to predict hybrid performance of rice. Our results suggest that GS could enable the rapid selection of superior hybrids, thus increasing the efficiency of rice hybrid breeding.

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars.

PubMed

Cavanagh, Colin R; Chao, Shiaoman; Wang, Shichen; Huang, Bevan Emma; Stephen, Stuart; Kiani, Seifollah; Forrest, Kerrie; Saintenac, Cyrille; Brown-Guedira, Gina L; Akhunova, Alina; See, Deven; Bai, Guihua; Pumphrey, Michael; Tomar, Luxmi; Wong, Debbie; Kong, Stephan; Reynolds, Matthew; da Silva, Marta Lopez; Bockelman, Harold; Talbert, Luther; Anderson, James A; Dreisigacker, Susanne; Baenziger, Stephen; Carter, Arron; Korzun, Viktor; Morrell, Peter Laurent; Dubcovsky, Jorge; Morell, Matthew K; Sorrells, Mark E; Hayden, Matthew J; Akhunov, Eduard

2013-05-14

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars

PubMed Central

Cavanagh, Colin R.; Chao, Shiaoman; Wang, Shichen; Huang, Bevan Emma; Stephen, Stuart; Kiani, Seifollah; Forrest, Kerrie; Saintenac, Cyrille; Brown-Guedira, Gina L.; Akhunova, Alina; See, Deven; Bai, Guihua; Pumphrey, Michael; Tomar, Luxmi; Wong, Debbie; Kong, Stephan; Reynolds, Matthew; da Silva, Marta Lopez; Bockelman, Harold; Talbert, Luther; Anderson, James A.; Dreisigacker, Susanne; Baenziger, Stephen; Carter, Arron; Korzun, Viktor; Morrell, Peter Laurent; Dubcovsky, Jorge; Morell, Matthew K.; Sorrells, Mark E.; Hayden, Matthew J.; Akhunov, Eduard

2013-01-01

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat. PMID:23630259

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

USDA-ARS?s Scientific Manuscript database

Background Several studies have examined the accuracy of genomic selection both within and across purebred beef or dairy populations. However, the accuracy of direct genomic breeding values (DGVs) has been less well studied in crossbred or admixed cattle populations. We used a population of 3,240 cr...

Selective recruitment of nuclear factors to productively replicating herpes simplex virus genomes.

PubMed

Dembowski, Jill A; DeLuca, Neal A

2015-05-01

Much of the HSV-1 life cycle is carried out in the cell nucleus, including the expression, replication, repair, and packaging of viral genomes. Viral proteins, as well as cellular factors, play essential roles in these processes. Isolation of proteins on nascent DNA (iPOND) was developed to label and purify cellular replication forks. We adapted aspects of this method to label viral genomes to both image, and purify replicating HSV-1 genomes for the identification of associated proteins. Many viral and cellular factors were enriched on viral genomes, including factors that mediate DNA replication, repair, chromatin remodeling, transcription, and RNA processing. As infection proceeded, packaging and structural components were enriched to a greater extent. Among the more abundant proteins that copurified with genomes were the viral transcription factor ICP4 and the replication protein ICP8. Furthermore, all seven viral replication proteins were enriched on viral genomes, along with cellular PCNA and topoisomerases, while other cellular replication proteins were not detected. The chromatin-remodeling complexes present on viral genomes included the INO80, SWI/SNF, NURD, and FACT complexes, which may prevent chromatinization of the genome. Consistent with this conclusion, histones were not readily recovered with purified viral genomes, and imaging studies revealed an underrepresentation of histones on viral genomes. RNA polymerase II, the mediator complex, TFIID, TFIIH, and several other transcriptional activators and repressors were also affinity purified with viral DNA. The presence of INO80, NURD, SWI/SNF, mediator, TFIID, and TFIIH components is consistent with previous studies in which these complexes copurified with ICP4. Therefore, ICP4 is likely involved in the recruitment of these key cellular chromatin remodeling and transcription factors to viral genomes. Taken together, iPOND is a valuable method for the study of viral genome dynamics during infection and

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

PubMed

He, Jun; Xu, Jiaqi; Wu, Xiao-Lin; Bauck, Stewart; Lee, Jungjae; Morota, Gota; Kachman, Stephen D; Spangler, Matthew L

2018-04-01

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations.

PubMed

Chimusa, Emile R; Meintjies, Ayton; Tchanga, Milaine; Mulder, Nicola; Seoighe, Cathal; Seioghe, Cathal; Soodyall, Himla; Ramesar, Rajkumar

2015-03-01

We report a study of genome-wide, dense SNP (∼ 900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.

A Genomic Portrait of Haplotype Diversity and Signatures of Selection in Indigenous Southern African Populations

PubMed Central

Chimusa, Emile R.; Meintjies, Ayton; Tchanga, Milaine; Mulder, Nicola; Seoighe, Cathal; Soodyall, Himla; Ramesar, Rajkumar

2015-01-01

We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region. PMID:25811879

Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations

DOE PAGES

Bendall, Matthew L.; Stevens, Sarah L.R.; Chan, Leong-Keat; ...

2016-01-08

Multiple models describe the formation and evolution of distinct microbial phylogenetic groups. These evolutionary models make different predictions regarding how adaptive alleles spread through populations and how genetic diversity is maintained. Processes predicted by competing evolutionary models, for example, genome-wide selective sweeps vs gene-specific sweeps, could be captured in natural populations using time-series metagenomics if the approach were applied over a sufficiently long time frame. Direct observations of either process would help resolve how distinct microbial groups evolve. Using a 9-year metagenomic study of a freshwater lake (2005–2013), we explore changes in single-nucleotide polymorphism (SNP) frequencies and patterns of genemore » gain and loss in 30 bacterial populations. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied by >1000-fold among populations. SNP allele frequencies also changed dramatically over time within some populations. Interestingly, nearly all SNP variants were slowly purged over several years from one population of green sulfur bacteria, while at the same time multiple genes either swept through or were lost from this population. Furthermore, these patterns were consistent with a genome-wide selective sweep in progress, a process predicted by the ‘ecotype model’ of speciation but not previously observed in nature. In contrast, other populations contained large, SNP-free genomic regions that appear to have swept independently through the populations prior to the study without purging diversity elsewhere in the genome. Finally, evidence for both genome-wide and gene-specific sweeps suggests that different models of bacterial speciation may apply to different populations coexisting in the same environment.« less

Genomic Selection in Commercial Perennial Crops: Applicability and Improvement in Oil Palm (Elaeis guineensis Jacq.).

PubMed

Kwong, Qi Bin; Ong, Ai Ling; Teh, Chee Keng; Chew, Fook Tim; Tammi, Martti; Mayes, Sean; Kulaveerasingam, Harikrishna; Yeoh, Suat Hui; Harikrishna, Jennifer Ann; Appleton, David Ross

2017-06-06

Genomic selection (GS) uses genome-wide markers to select individuals with the desired overall combination of breeding traits. A total of 1,218 individuals from a commercial population of Ulu Remis x AVROS (UR x AVROS) were genotyped using the OP200K array. The traits of interest included: shell-to-fruit ratio (S/F, %), mesocarp-to-fruit ratio (M/F, %), kernel-to-fruit ratio (K/F, %), fruit per bunch (F/B, %), oil per bunch (O/B, %) and oil per palm (O/P, kg/palm/year). Genomic heritabilities of these traits were estimated to be in the range of 0.40 to 0.80. GS methods assessed were RR-BLUP, Bayes A (BA), Cπ (BC), Lasso (BL) and Ridge Regression (BRR). All methods resulted in almost equal prediction accuracy. The accuracy achieved ranged from 0.40 to 0.70, correlating with the heritability of traits. By selecting the most important markers, RR-BLUP B has the potential to outperform other methods. The marker density for certain traits can be further reduced based on the linkage disequilibrium (LD). Together with in silico breeding, GS is now being used in oil palm breeding programs to hasten parental palm selection.

Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures

PubMed Central

Repar, Jelena; Warnecke, Tobias

2017-01-01

Abstract Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin–terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus–Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. PMID:28407093

A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds.

PubMed

Mokhber, Mahdi; Moradi-Shahrbabak, Mohammad; Sadeghi, Mostafa; Moradi-Shahrbabak, Hossein; Stella, Alessandra; Nicolzzi, Ezequiel; Rahmaninia, Javad; Williams, John L

2018-06-11

Identification of genomic regions that have been targets of selection may shed light on the genetic history of livestock populations and help to identify variation controlling commercially important phenotypes. The Azeri and Kuzestani buffalos are the most common indigenous Iranian breeds which have been subjected to divergent selection and are well adapted to completely different regions. Examining the genetic structure of these populations may identify genomic regions associated with adaptation to the different environments and production goals. A set of 385 water buffalo samples from Azeri (N = 262) and Khuzestani (N = 123) breeds were genotyped using the Axiom® Buffalo Genotyping 90 K Array. The unbiased fixation index method (F ST ) was used to detect signatures of selection. In total, 13 regions with outlier F ST values (0.1%) were identified. Annotation of these regions using the UMD3.1 Bos taurus Genome Assembly was performed to find putative candidate genes and QTLs within the selected regions. Putative candidate genes identified include FBXO9, NDFIP1, ACTR3, ARHGAP26, SERPINF2, BOLA-DRB3, BOLA-DQB, CLN8, and MYOM2. Candidate genes identified in regions potentially under selection were associated with physiological pathways including milk production, cytoskeleton organization, growth, metabolic function, apoptosis and domestication-related changes include immune and nervous system development. The QTL identified are involved in economically important traits in buffalo related to milk composition, udder structure, somatic cell count, meat quality, and carcass and body weight.

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

PubMed

Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

On causal roles and selected effects: our genome is mostly junk.

PubMed

Doolittle, W Ford; Brunet, Tyler D P

2017-12-05

The idea that much of our genome is irrelevant to fitness-is not the product of positive natural selection at the organismal level-remains viable. Claims to the contrary, and specifically that the notion of "junk DNA" should be abandoned, are based on conflating meanings of the word "function". Recent estimates suggest that perhaps 90% of our DNA, though biochemically active, does not contribute to fitness in any sequence-dependent way, and possibly in no way at all. Comparisons to vertebrates with much larger and smaller genomes (the lungfish and the pufferfish) strongly align with such a conclusion, as they have done for the last half-century.

Efficient Breeding by Genomic Mating.

PubMed

Akdemir, Deniz; Sánchez, Julio I

2016-01-01

Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection or genomic selection). All these methods are based on truncation selection, focusing on the best performance of parents before mating. In this article we proposed an approach to breeding, named genomic mating, which focuses on mating instead of truncation selection. Genomic mating uses information in a similar fashion to genomic selection but includes information on complementation of parents to be mated. Following the efficiency frontier surface, genomic mating uses concepts of estimated breeding values, risk (usefulness) and coefficient of ancestry to optimize mating between parents. We used a genetic algorithm to find solutions to this optimization problem and the results from our simulations comparing genomic selection, phenotypic selection and the mating approach indicate that current approach for breeding complex traits is more favorable than phenotypic and genomic selection. Genomic mating is similar to genomic selection in terms of estimating marker effects, but in genomic mating the genetic information and the estimated marker effects are used to decide which genotypes should be crossed to obtain the next breeding population.

A genomic scan for selection reveals candidates for genes involved in the evolution of cultivated sunflower (Helianthus annuus).

PubMed

Chapman, Mark A; Pashley, Catherine H; Wenzler, Jessica; Hvala, John; Tang, Shunxue; Knapp, Steven J; Burke, John M

2008-11-01

Genomic scans for selection are a useful tool for identifying genes underlying phenotypic transitions. In this article, we describe the results of a genome scan designed to identify candidates for genes targeted by selection during the evolution of cultivated sunflower. This work involved screening 492 loci derived from ESTs on a large panel of wild, primitive (i.e., landrace), and improved sunflower (Helianthus annuus) lines. This sampling strategy allowed us to identify candidates for selectively important genes and investigate the likely timing of selection. Thirty-six genes showed evidence of selection during either domestication or improvement based on multiple criteria, and a sequence-based test of selection on a subset of these loci confirmed this result. In view of what is known about the structure of linkage disequilibrium across the sunflower genome, these genes are themselves likely to have been targeted by selection, rather than being merely linked to the actual targets. While the selection candidates showed a broad range of putative functions, they were enriched for genes involved in amino acid synthesis and protein catabolism. Given that a similar pattern has been detected in maize (Zea mays), this finding suggests that selection on amino acid composition may be a general feature of the evolution of crop plants. In terms of genomic locations, the selection candidates were significantly clustered near quantitative trait loci (QTL) that contribute to phenotypic differences between wild and cultivated sunflower, and specific instances of QTL colocalization provide some clues as to the roles that these genes may have played during sunflower evolution.

Genome-wide detection of selection signatures in Chinese indigenous Laiwu pigs revealed candidate genes regulating fat deposition in muscle.

PubMed

Chen, Minhui; Wang, Jiying; Wang, Yanping; Wu, Ying; Fu, Jinluan; Liu, Jian-Feng

2018-05-18

Currently, genome-wide scans for positive selection signatures in commercial breed have been investigated. However, few studies have focused on selection footprints of indigenous breeds. Laiwu pig is an invaluable Chinese indigenous pig breed with extremely high proportion of intramuscular fat (IMF), and an excellent model to detect footprint as the result of natural and artificial selection for fat deposition in muscle. In this study, based on GeneSeek Genomic profiler Porcine HD data, three complementary methods, F ST , iHS (integrated haplotype homozygosity score) and CLR (composite likelihood ratio), were implemented to detect selection signatures in the whole genome of Laiwu pigs. Totally, 175 candidate selected regions were obtained by at least two of the three methods, which covered 43.75 Mb genomic regions and corresponded to 1.79% of the genome sequence. Gene annotation of the selected regions revealed a list of functionally important genes for feed intake and fat deposition, reproduction, and immune response. Especially, in accordance to the phenotypic features of Laiwu pigs, among the candidate genes, we identified several genes, NPY1R, NPY5R, PIK3R1 and JAKMIP1, involved in the actions of two sets of neurons, which are central regulators in maintaining the balance between food intake and energy expenditure. Our results identified a number of regions showing signatures of selection, as well as a list of functionally candidate genes with potential effect on phenotypic traits, especially fat deposition in muscle. Our findings provide insights into the mechanisms of artificial selection of fat deposition and further facilitate follow-up functional studies.

Prospects for Genomic Selection in Cassava Breeding.

PubMed

Wolfe, Marnin D; Del Carpio, Dunia Pino; Alabi, Olumide; Ezenwaka, Lydia C; Ikeogu, Ugochukwu N; Kayondo, Ismail S; Lozano, Roberto; Okeke, Uche G; Ozimati, Alfred A; Williams, Esuma; Egesi, Chiedozie; Kawuki, Robert S; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

2017-11-01

Cassava ( Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden. Copyright © 2017 Crop Science Society of America.

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.

Genome-wide analysis reveals signatures of selection for important traits in domestic sheep from different ecoregions.

PubMed

Liu, Zhaohua; Ji, Zhibin; Wang, Guizhi; Chao, Tianle; Hou, Lei; Wang, Jianmin

2016-11-03

Throughout a long period of adaptation and selection, sheep have thrived in a diverse range of ecological environments. Mongolian sheep is the common ancestor of the Chinese short fat-tailed sheep. Migration to different ecoregions leads to changes in selection pressures and results in microevolution. Mongolian sheep and its subspecies differ in a number of important traits, especially reproductive traits. Genome-wide intraspecific variation is required to dissect the genetic basis of these traits. This research resequenced 3 short fat-tailed sheep breeds with a 43.2-fold coverage of the sheep genome. We report more than 17 million single nucleotide polymorphisms and 2.9 million indels and identify 143 genomic regions with reduced pooled heterozygosity or increased genetic distance to each other breed that represent likely targets for selection during the migration. These regions harbor genes related to developmental processes, cellular processes, multicellular organismal processes, biological regulation, metabolic processes, reproduction, localization, growth and various components of the stress responses. Furthermore, we examined the haplotype diversity of 3 genomic regions involved in reproduction and found significant differences in TSHR and PRL gene regions among 8 sheep breeds. Our results provide useful genomic information for identifying genes or causal mutations associated with important economic traits in sheep and for understanding the genetic basis of adaptation to different ecological environments.

On the relative roles of background selection and genetic hitchhiking in shaping human cytomegalovirus genetic diversity.

PubMed

Renzette, Nicholas; Kowalik, Timothy F; Jensen, Jeffrey D

2016-01-01

A central focus of population genetics has been examining the contribution of selective and neutral processes in shaping patterns of intraspecies diversity. In terms of selection specifically, surveys of higher organisms have shown considerable variation in the relative contributions of background selection and genetic hitchhiking in shaping the distribution of polymorphisms, although these analyses have rarely been extended to bacteria and viruses. Here, we study the evolution of a ubiquitous, viral pathogen, human cytomegalovirus (HCMV), by analysing the relationship among intraspecies diversity, interspecies divergence and rates of recombination. We show that there is a strong correlation between diversity and divergence, consistent with expectations of neutral evolution. However, after correcting for divergence, there remains a significant correlation between intraspecies diversity and recombination rates, with additional analyses suggesting that this correlation is largely due to the effects of background selection. In addition, a small number of loci, centred on long noncoding RNAs, also show evidence of selective sweeps. These data suggest that HCMV evolution is dominated by neutral mechanisms as well as background selection, expanding our understanding of linked selection to a novel class of organisms. © 2015 John Wiley & Sons Ltd.

Multiplex Degenerate Primer Design for Targeted Whole Genome Amplification of Many Viral Genomes

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

Gardner, Shea N.; Jaing, Crystal J.; Elsheikh, Maher M.

Background . Targeted enrichment improves coverage of highly mutable viruses at low concentration in complex samples. Degenerate primers that anneal to conserved regions can facilitate amplification of divergent, low concentration variants, even when the strain present is unknown. Results . A tool for designing multiplex sets of degenerate sequencing primers to tile overlapping amplicons across multiple whole genomes is described. The new script, run_tiled_primers, is part of the PriMux software. Primers were designed for each segment of South American hemorrhagic fever viruses, tick-borne encephalitis, Henipaviruses, Arenaviruses, Filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, and Japanese encephalitis virus. Eachmore » group is highly diverse with as little as 5% genome consensus. Primer sets were computationally checked for nontarget cross reactions against the NCBI nucleotide sequence database. Primers for murine hepatitis virus were demonstrated in the lab to specifically amplify selected genes from a laboratory cultured strain that had undergone extensive passage in vitro and in vivo. Conclusions . This software should help researchers design multiplex sets of primers for targeted whole genome enrichment prior to sequencing to obtain better coverage of low titer, divergent viruses. Applications include viral discovery from a complex background and improved sensitivity and coverage of rapidly evolving strains or variants in a gene family.« less

Multiplex Degenerate Primer Design for Targeted Whole Genome Amplification of Many Viral Genomes

DOE PAGES

Gardner, Shea N.; Jaing, Crystal J.; Elsheikh, Maher M.; ...

2014-01-01

Background . Targeted enrichment improves coverage of highly mutable viruses at low concentration in complex samples. Degenerate primers that anneal to conserved regions can facilitate amplification of divergent, low concentration variants, even when the strain present is unknown. Results . A tool for designing multiplex sets of degenerate sequencing primers to tile overlapping amplicons across multiple whole genomes is described. The new script, run_tiled_primers, is part of the PriMux software. Primers were designed for each segment of South American hemorrhagic fever viruses, tick-borne encephalitis, Henipaviruses, Arenaviruses, Filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus, and Japanese encephalitis virus. Eachmore » group is highly diverse with as little as 5% genome consensus. Primer sets were computationally checked for nontarget cross reactions against the NCBI nucleotide sequence database. Primers for murine hepatitis virus were demonstrated in the lab to specifically amplify selected genes from a laboratory cultured strain that had undergone extensive passage in vitro and in vivo. Conclusions . This software should help researchers design multiplex sets of primers for targeted whole genome enrichment prior to sequencing to obtain better coverage of low titer, divergent viruses. Applications include viral discovery from a complex background and improved sensitivity and coverage of rapidly evolving strains or variants in a gene family.« less

Genome Patterns of Selection and Introgression of Haplotypes in Natural Populations of the House Mouse (Mus musculus)

PubMed Central

Staubach, Fabian; Lorenc, Anna; Messer, Philipp W.; Tang, Kun; Petrov, Dmitri A.; Tautz, Diethard

2012-01-01

General parameters of selection, such as the frequency and strength of positive selection in natural populations or the role of introgression, are still insufficiently understood. The house mouse (Mus musculus) is a particularly well-suited model system to approach such questions, since it has a defined history of splits into subspecies and populations and since extensive genome information is available. We have used high-density single-nucleotide polymorphism (SNP) typing arrays to assess genomic patterns of positive selection and introgression of alleles in two natural populations of each of the subspecies M. m. domesticus and M. m. musculus. Applying different statistical procedures, we find a large number of regions subject to apparent selective sweeps, indicating frequent positive selection on rare alleles or novel mutations. Genes in the regions include well-studied imprinted loci (e.g. Plagl1/Zac1), homologues of human genes involved in adaptations (e.g. alpha-amylase genes) or in genetic diseases (e.g. Huntingtin and Parkin). Haplotype matching between the two subspecies reveals a large number of haplotypes that show patterns of introgression from specific populations of the respective other subspecies, with at least 10% of the genome being affected by partial or full introgression. Using neutral simulations for comparison, we find that the size and the fraction of introgressed haplotypes are not compatible with a pure migration or incomplete lineage sorting model. Hence, it appears that introgressed haplotypes can rise in frequency due to positive selection and thus can contribute to the adaptive genomic landscape of natural populations. Our data support the notion that natural genomes are subject to complex adaptive processes, including the introgression of haplotypes from other differentiated populations or species at a larger scale than previously assumed for animals. This implies that some of the admixture found in inbred strains of mice may also have

A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

PubMed Central

Beissinger, Timothy M.; Hirsch, Candice N.; Vaillancourt, Brieanne; Deshpande, Shweta; Barry, Kerrie; Buell, C. Robin; Kaeppler, Shawn M.; Gianola, Daniel; de Leon, Natalia

2014-01-01

A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at >1.2 million single-nucleotide polymorphism loci were estimated from pooled whole-genome resequencing data, and FST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize. PMID:24381334

The population genomic signature of environmental selection in the widespread insect-pollinated tree species Frangula alnus at different geographical scales

PubMed Central

De Kort, H; Vandepitte, K; Mergeay, J; Mijnsbrugge, K V; Honnay, O

2015-01-01

The evaluation of the molecular signatures of selection in species lacking an available closely related reference genome remains challenging, yet it may provide valuable fundamental insights into the capacity of populations to respond to environmental cues. We screened 25 native populations of the tree species Frangula alnus subsp. alnus (Rhamnaceae), covering three different geographical scales, for 183 annotated single-nucleotide polymorphisms (SNPs). Standard population genomic outlier screens were combined with individual-based and multivariate landscape genomic approaches to examine the strength of selection relative to neutral processes in shaping genomic variation, and to identify the main environmental agents driving selection. Our results demonstrate a more distinct signature of selection with increasing geographical distance, as indicated by the proportion of SNPs (i) showing exceptional patterns of genetic diversity and differentiation (outliers) and (ii) associated with climate. Both temperature and precipitation have an important role as selective agents in shaping adaptive genomic differentiation in F. alnus subsp. alnus, although their relative importance differed among spatial scales. At the ‘intermediate' and ‘regional' scales, where limited genetic clustering and high population diversity were observed, some indications of natural selection may suggest a major role for gene flow in safeguarding adaptability. High genetic diversity at loci under selection in particular, indicated considerable adaptive potential, which may nevertheless be compromised by the combined effects of climate change and habitat fragmentation. PMID:25944466

Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing

PubMed Central

2013-01-01

Background Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed. Results A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified. Conclusions Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits. PMID:23984715

Genome-Wide Analyses Reveal Genes Subject to Positive Selection in Pasteurella multocida

PubMed Central

Cao, Peili; Guo, Dongchun; Liu, Jiasen; Jiang, Qian; Xu, Zhuofei; Qu, Liandong

2017-01-01

Pasteurella multocida, a Gram-negative opportunistic pathogen, has led to a broad range of diseases in mammals and birds, including fowl cholera in poultry, pneumonia and atrophic rhinitis in swine and rabbit, hemorrhagic septicemia in cattle, and bite infections in humans. In order to better interpret the genetic diversity and adaptation evolution of this pathogen, seven genomes of P. multocida strains isolated from fowls, rabbit and pigs were determined by using high-throughput sequencing approach. Together with publicly available P. multocida genomes, evolutionary features were systematically analyzed in this study. Clustering of 70,565 protein-coding genes showed that the pangenome of 33 P. multocida strains was composed of 1,602 core genes, 1,364 dispensable genes, and 1,070 strain-specific genes. Of these, we identified a full spectrum of genes related to virulence factors and revealed genetic diversity of these potential virulence markers across P. multocida strains, e.g., bcbAB, fcbC, lipA, bexDCA, ctrCD, lgtA, lgtC, lic2A involved in biogenesis of surface polysaccharides, hsf encoding autotransporter adhesin, and fhaB encoding filamentous haemagglutinin. Furthermore, based on genome-wide positive selection scanning, a total of 35 genes were subject to strong selection pressure. Extensive analyses of protein subcellular location indicated that membrane-associated genes were highly abundant among all positively selected genes. The detected amino acid sites undergoing adaptive selection were preferably located in extracellular space, perhaps associated with bacterial evasion of host immune responses. Our findings shed more light on conservation and distribution of virulence-associated genes across P. multocida strains. Meanwhile, this study provides a genetic context for future researches on the mechanism of adaptive evolution in P. multocida. PMID:28611758

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

PubMed Central

2012-01-01

Background Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. Results We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension – UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent

Genome-Wide Analysis Reveals Selection for Important Traits in Domestic Horse Breeds

PubMed Central

Petersen, Jessica L.; Mickelson, James R.; Rendahl, Aaron K.; Valberg, Stephanie J.; Andersson, Lisa S.; Axelsson, Jeanette; Bailey, Ernie; Bannasch, Danika; Binns, Matthew M.; Borges, Alexandre S.; Brama, Pieter; da Câmara Machado, Artur; Capomaccio, Stefano; Cappelli, Katia; Cothran, E. Gus; Distl, Ottmar; Fox-Clipsham, Laura; Graves, Kathryn T.; Guérin, Gérard; Haase, Bianca; Hasegawa, Telhisa; Hemmann, Karin; Hill, Emmeline W.; Leeb, Tosso; Lindgren, Gabriella; Lohi, Hannes; Lopes, Maria Susana; McGivney, Beatrice A.; Mikko, Sofia; Orr, Nicholas; Penedo, M. Cecilia T.; Piercy, Richard J.; Raekallio, Marja; Rieder, Stefan; Røed, Knut H.; Swinburne, June; Tozaki, Teruaki; Vaudin, Mark; Wade, Claire M.; McCue, Molly E.

2013-01-01

Intense selective pressures applied over short evolutionary time have resulted in homogeneity within, but substantial variation among, horse breeds. Utilizing this population structure, 744 individuals from 33 breeds, and a 54,000 SNP genotyping array, breed-specific targets of selection were identified using an FST-based statistic calculated in 500-kb windows across the genome. A 5.5-Mb region of ECA18, in which the myostatin (MSTN) gene was centered, contained the highest signature of selection in both the Paint and Quarter Horse. Gene sequencing and histological analysis of gluteal muscle biopsies showed a promoter variant and intronic SNP of MSTN were each significantly associated with higher Type 2B and lower Type 1 muscle fiber proportions in the Quarter Horse, demonstrating a functional consequence of selection at this locus. Signatures of selection on ECA23 in all gaited breeds in the sample led to the identification of a shared, 186-kb haplotype including two doublesex related mab transcription factor genes (DMRT2 and 3). The recent identification of a DMRT3 mutation within this haplotype, which appears necessary for the ability to perform alternative gaits, provides further evidence for selection at this locus. Finally, putative loci for the determination of size were identified in the draft breeds and the Miniature horse on ECA11, as well as when signatures of selection surrounding candidate genes at other loci were examined. This work provides further evidence of the importance of MSTN in racing breeds, provides strong evidence for selection upon gait and size, and illustrates the potential for population-based techniques to find genomic regions driving important phenotypes in the modern horse. PMID:23349635

All about the Human Genome Project (HGP)

MedlinePlus

... CSER), and Genome Sequencing Informatics Tools (GS-IT) Comparative Genomics Background information prepared for the media on ... other species to the human sequence. Background on Comparative Genomic Analysis New Process to Prioritize Animal Genomes ...

Evaluation of genome-enabled selection for bacterial cold water disease resistance using progeny performance data in Rainbow Trout: Insights on genotyping methods and genomic prediction models

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic br...

Optimization of multi-environment trials for genomic selection based on crop models.

PubMed

Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

2017-08-01

We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

PubMed

Lim, Dajeong; Strucken, Eva M; Choi, Bong Hwan; Chai, Han Ha; Cho, Yong Min; Jang, Gul Won; Kim, Tae-Hun; Gondro, Cedric; Lee, Seung Hwan

2016-01-01

Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle) and in China (Yanbian). These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN). We identified 37 significant SNPs (FDR corrected) in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes), reproduction including mammary gland development (3 genes), coat color (2 genes), and genes affecting behavioral traits in a broader sense (2 genes). We subsequently sequenced (Illumina HiSeq 2000 platform) 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val) and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

Whole-genome resequencing of honeybee drones to detect genomic selection in a population managed for royal jelly.

PubMed

Wragg, David; Marti-Marimon, Maria; Basso, Benjamin; Bidanel, Jean-Pierre; Labarthe, Emmanuelle; Bouchez, Olivier; Le Conte, Yves; Vignal, Alain

2016-06-03

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera, and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail.

Whole-genome resequencing of honeybee drones to detect genomic selection in a population managed for royal jelly

PubMed Central

Wragg, David; Marti-Marimon, Maria; Basso, Benjamin; Bidanel, Jean-Pierre; Labarthe, Emmanuelle; Bouchez, Olivier; Le Conte, Yves; Vignal, Alain

2016-01-01

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera, and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail. PMID:27255426

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

PubMed

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops

PubMed Central

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an “island model” inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of

Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures.

PubMed

Repar, Jelena; Warnecke, Tobias

2017-08-01

Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin-terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus-Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Somatic Mutation Patterns in Hemizygous Genomic Regions Unveil Purifying Selection during Tumor Evolution

PubMed Central

Basu, Swaraj; Larsson, Erik

2016-01-01

Identification of cancer driver genes using somatic mutation patterns indicative of positive selection has become a major goal in cancer genomics. However, cancer cells additionally depend on a large number of genes involved in basic cellular processes. While such genes should in theory be subject to strong purifying (negative) selection against damaging somatic mutations, these patterns have been elusive and purifying selection remains inadequately explored in cancer. Here, we hypothesized that purifying selection should be evident in hemizygous genomic regions, where damaging mutations cannot be compensated for by healthy alleles. Using a 7,781-sample pan-cancer dataset, we first confirmed this in POLR2A, an essential gene where hemizygous deletions are known to confer elevated sensitivity to pharmacological suppression. We next used this principle to identify several genes and pathways that show patterns indicative of purifying selection to avoid deleterious mutations. These include the POLR2A interacting protein INTS10 as well as genes involved in mRNA splicing, nonsense-mediated mRNA decay and other RNA processing pathways. Many of these genes belong to large protein complexes, and strong overlaps were observed with recent functional screens for gene essentiality in human cells. Our analysis supports that purifying selection acts to preserve the remaining function of many hemizygously deleted essential genes in tumors, indicating vulnerabilities that might be exploited by future therapeutic strategies. PMID:28027311

AnnotateGenomicRegions: a web application

PubMed Central

2014-01-01

Background Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Results Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. Conclusions The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://cru.genomics.iit.it/AnnotateGenomicRegions. PMID:24564446

Genomic selection accuracies within and between environments and small breeding groups in white spruce.

PubMed

Beaulieu, Jean; Doerksen, Trevor K; MacKay, John; Rainville, André; Bousquet, Jean

2014-12-02

Genomic selection (GS) may improve selection response over conventional pedigree-based selection if markers capture more detailed information than pedigrees in recently domesticated tree species and/or make it more cost effective. Genomic prediction accuracies using 1748 trees and 6932 SNPs representative of as many distinct gene loci were determined for growth and wood traits in white spruce, within and between environments and breeding groups (BG), each with an effective size of Ne ≈ 20. Marker subsets were also tested. Model fits and/or cross-validation (CV) prediction accuracies for ridge regression (RR) and the least absolute shrinkage and selection operator models approached those of pedigree-based models. With strong relatedness between CV sets, prediction accuracies for RR within environment and BG were high for wood (r = 0.71-0.79) and moderately high for growth (r = 0.52-0.69) traits, in line with trends in heritabilities. For both classes of traits, these accuracies achieved between 83% and 92% of those obtained with phenotypes and pedigree information. Prediction into untested environments remained moderately high for wood (r ≥ 0.61) but dropped significantly for growth (r ≥ 0.24) traits, emphasizing the need to phenotype in all test environments and model genotype-by-environment interactions for growth traits. Removing relatedness between CV sets sharply decreased prediction accuracies for all traits and subpopulations, falling near zero between BGs with no known shared ancestry. For marker subsets, similar patterns were observed but with lower prediction accuracies. Given the need for high relatedness between CV sets to obtain good prediction accuracies, we recommend to build GS models for prediction within the same breeding population only. Breeding groups could be merged to build genomic prediction models as long as the total effective population size does not exceed 50 individuals in order to obtain high prediction accuracy such as that

Thinking too positive? Revisiting current methods of population genetic selection inference.

PubMed

Bank, Claudia; Ewing, Gregory B; Ferrer-Admettla, Anna; Foll, Matthieu; Jensen, Jeffrey D

2014-12-01

In the age of next-generation sequencing, the availability of increasing amounts and improved quality of data at decreasing cost ought to allow for a better understanding of how natural selection is shaping the genome than ever before. However, alternative forces, such as demography and background selection (BGS), obscure the footprints of positive selection that we would like to identify. In this review, we illustrate recent developments in this area, and outline a roadmap for improved selection inference. We argue (i) that the development and obligatory use of advanced simulation tools is necessary for improved identification of selected loci, (ii) that genomic information from multiple time points will enhance the power of inference, and (iii) that results from experimental evolution should be utilized to better inform population genomic studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Whole-genome sequencing of two North American Drosophila melanogaster populations reveals genetic differentiation and positive selection.

PubMed

Campo, D; Lehmann, K; Fjeldsted, C; Souaiaia, T; Kao, J; Nuzhdin, S V

2013-10-01

The prevailing demographic model for Drosophila melanogaster suggests that the colonization of North America occurred very recently from a subset of European flies that rapidly expanded across the continent. This model implies a sudden population growth and range expansion consistent with very low or no population subdivision. As flies adapt to new environments, local adaptation events may be expected. To describe demographic and selective events during North American colonization, we have generated a data set of 35 individual whole-genome sequences from inbred lines of D. melanogaster from a west coast US population (Winters, California, USA) and compared them with a public genome data set from Raleigh (Raleigh, North Carolina, USA). We analysed nuclear and mitochondrial genomes and described levels of variation and divergence within and between these two North American D. melanogaster populations. Both populations exhibit negative values of Tajima's D across the genome, a common signature of demographic expansion. We also detected a low but significant level of genome-wide differentiation between the two populations, as well as multiple allele surfing events, which can be the result of gene drift in local subpopulations on the edge of an expansion wave. In contrast to this genome-wide pattern, we uncovered a 50-kilobase segment in chromosome arm 3L that showed all the hallmarks of a soft selective sweep in both populations. A comparison of allele frequencies within this divergent region among six populations from three continents allowed us to cluster these populations in two differentiated groups, providing evidence for the action of natural selection on a global scale. © 2013 John Wiley & Sons Ltd.

Parasitism drives host genome evolution: Insights from the Pasteuria ramosa-Daphnia magna system.

PubMed

Bourgeois, Yann; Roulin, Anne C; Müller, Kristina; Ebert, Dieter

2017-04-01

Because parasitism is thought to play a major role in shaping host genomes, it has been predicted that genomic regions associated with resistance to parasites should stand out in genome scans, revealing signals of selection above the genomic background. To test whether parasitism is indeed such a major factor in host evolution and to better understand host-parasite interaction at the molecular level, we studied genome-wide polymorphisms in 97 genotypes of the planktonic crustacean Daphnia magna originating from three localities across Europe. Daphnia magna is known to coevolve with the bacterial pathogen Pasteuria ramosa for which host genotypes (clonal lines) are either resistant or susceptible. Using association mapping, we identified two genomic regions involved in resistance to P. ramosa, one of which was already known from a previous QTL analysis. We then performed a naïve genome scan to test for signatures of positive selection and found that the two regions identified with the association mapping further stood out as outliers. Several other regions with evidence for selection were also found, but no link between these regions and phenotypic variation could be established. Our results are consistent with the hypothesis that parasitism is driving host genome evolution. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Genome comparison of two Magnaporthe oryzae field isolates reveals genome variations and potential virulence effectors

PubMed Central

2013-01-01

Background Rice blast caused by the fungus Magnaporthe oryzae is an important disease in virtually every rice growing region of the world, which leads to significant annual decreases of grain quality and yield. To prevent disease, resistance genes in rice have been cloned and introduced into susceptible cultivars. However, introduced resistance can often be broken within few years of release, often due to mutation of cognate avirulence genes in fungal field populations. Results To better understand the pattern of mutation of M. oryzae field isolates under natural selection forces, we used a next generation sequencing approach to analyze the genomes of two field isolates FJ81278 and HN19311, as well as the transcriptome of FJ81278. By comparing the de novo genome assemblies of the two isolates against the finished reference strain 70–15, we identified extensive polymorphisms including unique genes, SNPs (single nucleotide polymorphism) and indels, structural variations, copy number variations, and loci under strong positive selection. The 1.75 MB of isolate-specific genome content carrying 118 novel genes from FJ81278, and 0.83 MB from HN19311 were also identified. By analyzing secreted proteins carrying polymorphisms, in total 256 candidate virulence effectors were found and 6 were chosen for functional characterization. Conclusions We provide results from genome comparison analysis showing extensive genome variation, and generated a list of M. oryzae candidate virulence effectors for functional characterization. PMID:24341723

Exploitation of data from breeding programs supports rapid implementation of genomic selection for key agronomic traits in perennial ryegrass.

PubMed

Pembleton, Luke W; Inch, Courtney; Baillie, Rebecca C; Drayton, Michelle C; Thakur, Preeti; Ogaji, Yvonne O; Spangenberg, German C; Forster, John W; Daetwyler, Hans D; Cogan, Noel O I

2018-06-02

Exploitation of data from a ryegrass breeding program has enabled rapid development and implementation of genomic selection for sward-based biomass yield with a twofold-to-threefold increase in genetic gain. Genomic selection, which uses genome-wide sequence polymorphism data and quantitative genetics techniques to predict plant performance, has large potential for the improvement in pasture plants. Major factors influencing the accuracy of genomic selection include the size of reference populations, trait heritability values and the genetic diversity of breeding populations. Global diversity of the important forage species perennial ryegrass is high and so would require a large reference population in order to achieve moderate accuracies of genomic selection. However, diversity of germplasm within a breeding program is likely to be lower. In addition, de novo construction and characterisation of reference populations are a logistically complex process. Consequently, historical phenotypic records for seasonal biomass yield and heading date over a 18-year period within a commercial perennial ryegrass breeding program have been accessed, and target populations have been characterised with a high-density transcriptome-based genotyping-by-sequencing assay. Ability to predict observed phenotypic performance in each successive year was assessed by using all synthetic populations from previous years as a reference population. Moderate and high accuracies were achieved for the two traits, respectively, consistent with broad-sense heritability values. The present study represents the first demonstration and validation of genomic selection for seasonal biomass yield within a diverse commercial breeding program across multiple years. These results, supported by previous simulation studies, demonstrate the ability to predict sward-based phenotypic performance early in the process of individual plant selection, so shortening the breeding cycle, increasing the rate of genetic

Detecting the Population Structure and Scanning for Signatures of Selection in Horses (Equus caballus) From Whole-Genome Sequencing Data

PubMed Central

Zhang, Cheng; Ni, Pan; Ahmad, Hafiz Ishfaq; Gemingguli, M; Baizilaitibei, A; Gulibaheti, D; Fang, Yaping; Wang, Haiyang; Asif, Akhtar Rasool; Xiao, Changyi; Chen, Jianhai; Ma, Yunlong; Liu, Xiangdong; Du, Xiaoyong; Zhao, Shuhong

2018-01-01

Animal domestication gives rise to gradual changes at the genomic level through selection in populations. Selective sweeps have been traced in the genomes of many animal species, including humans, cattle, and dogs. However, little is known regarding positional candidate genes and genomic regions that exhibit signatures of selection in domestic horses. In addition, an understanding of the genetic processes underlying horse domestication, especially the origin of Chinese native populations, is still lacking. In our study, we generated whole genome sequences from 4 Chinese native horses and combined them with 48 publicly available full genome sequences, from which 15 341 213 high-quality unique single-nucleotide polymorphism variants were identified. Kazakh and Lichuan horses are 2 typical Asian native breeds that were formed in Kazakh or Northwest China and South China, respectively. We detected 1390 loss-of-function (LoF) variants in protein-coding genes, and gene ontology (GO) enrichment analysis revealed that some LoF-affected genes were overrepresented in GO terms related to the immune response. Bayesian clustering, distance analysis, and principal component analysis demonstrated that the population structure of these breeds largely reflected weak geographic patterns. Kazakh and Lichuan horses were assigned to the same lineage with other Asian native breeds, in agreement with previous studies on the genetic origin of Chinese domestic horses. We applied the composite likelihood ratio method to scan for genomic regions showing signals of recent selection in the horse genome. A total of 1052 genomic windows of 10 kB, corresponding to 933 distinct core regions, significantly exceeded neutral simulations. The GO enrichment analysis revealed that the genes under selective sweeps were overrepresented with GO terms, including “negative regulation of canonical Wnt signaling pathway,” “muscle contraction,” and “axon guidance.” Frequent exercise training

A Gene-Oriented Haplotype Comparison Reveals Recently Selected Genomic Regions in Temperate and Tropical Maize Germplasm

PubMed Central

Zhang, Jie; Li, Yongxiang; Zheng, Jun; Zhang, Hongwei; Yang, Xiaohong; Wang, Jianhua; Wang, Guoying

2017-01-01

The extensive genetic variation present in maize (Zea mays) germplasm makes it possible to detect signatures of positive artificial selection that occurred during temperate and tropical maize improvement. Here we report an analysis of 532,815 polymorphisms from a maize association panel consisting of 368 diverse temperate and tropical inbred lines. We developed a gene-oriented approach adapting exonic polymorphisms to identify recently selected alleles by comparing haplotypes across the maize genome. This analysis revealed evidence of selection for more than 1100 genomic regions during recent improvement, and included regulatory genes and key genes with visible mutant phenotypes. We find that selected candidate target genes in temperate maize are enriched in biosynthetic processes, and further examination of these candidates highlights two cases, sucrose flux and oil storage, in which multiple genes in a common pathway can be cooperatively selected. Finally, based on available parallel gene expression data, we hypothesize that some genes were selected for regulatory variations, resulting in altered gene expression. PMID:28099470

A crossbred reference population can improve the response to genomic selection for crossbred performance.

PubMed

Esfandyari, Hadi; Sørensen, Anders Christian; Bijma, Piter

2015-09-29

Breeding goals in a crossbreeding system should be defined at the commercial crossbred level. However, selection is often performed to improve purebred performance. A genomic selection (GS) model that includes dominance effects can be used to select purebreds for crossbred performance. Optimization of the GS model raises the question of whether marker effects should be estimated from data on the pure lines or crossbreds. Therefore, the first objective of this study was to compare response to selection of crossbreds by simulating a two-way crossbreeding program with either a purebred or a crossbred training population. We assumed a trait of interest that was controlled by loci with additive and dominance effects. Animals were selected on estimated breeding values for crossbred performance. There was no genotype by environment interaction. Linkage phase and strength of linkage disequilibrium between quantitative trait loci (QTL) and single nucleotide polymorphisms (SNPs) can differ between breeds, which causes apparent effects of SNPs to be line-dependent. Thus, our second objective was to compare response to GS based on crossbred phenotypes when the line origin of alleles was taken into account or not in the estimation of breeding values. Training on crossbred animals yielded a larger response to selection in crossbred offspring compared to training on both pure lines separately or on both pure lines combined into a single reference population. Response to selection in crossbreds was larger if both phenotypes and genotypes were collected on crossbreds than if phenotypes were only recorded on crossbreds and genotypes on their parents. If both parental lines were distantly related, tracing the line origin of alleles improved genomic prediction, whereas if both parental lines were closely related and the reference population was small, it was better to ignore the line origin of alleles. Response to selection in crossbreeding programs can be increased by training on

Hybridization Reveals the Evolving Genomic Architecture of Speciation

PubMed Central

Kronforst, Marcus R.; Hansen, Matthew E.B.; Crawford, Nicholas G.; Gallant, Jason R.; Zhang, Wei; Kulathinal, Rob J.; Kapan, Durrell D.; Mullen, Sean P.

2014-01-01

SUMMARY The rate at which genomes diverge during speciation is unknown, as are the physical dynamics of the process. Here, we compare full genome sequences of 32 butterflies, representing five species from a hybridizing Heliconius butterfly community, to examine genome-wide patterns of introgression and infer how divergence evolves during the speciation process. Our analyses reveal that initial divergence is restricted to a small fraction of the genome, largely clustered around known wing-patterning genes. Over time, divergence evolves rapidly, due primarily to the origin of new divergent regions. Furthermore, divergent genomic regions display signatures of both selection and adaptive introgression, demonstrating the link between microevolutionary processes acting within species and the origin of species across macroevolutionary timescales. Our results provide a uniquely comprehensive portrait of the evolving species boundary due to the role that hybridization plays in reducing the background accumulation of divergence at neutral sites. PMID:24183670

Evolutionary signals of selection on cognition from the great tit genome and methylome

PubMed Central

Laine, Veronika N.; Gossmann, Toni I.; Schachtschneider, Kyle M.; Garroway, Colin J.; Madsen, Ole; Verhoeven, Koen J. F.; de Jager, Victor; Megens, Hendrik-Jan; Warren, Wesley C.; Minx, Patrick; Crooijmans, Richard P. M. A.; Corcoran, Pádraic; Adriaensen, Frank; Belda, Eduardo; Bushuev, Andrey; Cichon, Mariusz; Charmantier, Anne; Dingemanse, Niels; Doligez, Blandine; Eeva, Tapio; Erikstad, Kjell Einar; Fedorov, Slava; Hau, Michaela; Hille, Sabine; Hinde, Camilla; Kempenaers, Bart; Kerimov, Anvar; Krist, Milos; Mand, Raivo; Matthysen, Erik; Nager, Reudi; Norte, Claudia; Orell, Markku; Richner, Heinz; Slagsvold, Tore; Tilgar, Vallo; Tinbergen, Joost; Torok, Janos; Tschirren, Barbara; Yuta, Tera; Sheldon, Ben C.; Slate, Jon; Zeng, Kai; van Oers, Kees; Visser, Marcel E.; Groenen, Martien A. M.

2016-01-01

For over 50 years, the great tit (Parus major) has been a model species for research in evolutionary, ecological and behavioural research; in particular, learning and cognition have been intensively studied. Here, to provide further insight into the molecular mechanisms behind these important traits, we de novo assemble a great tit reference genome and whole-genome re-sequence another 29 individuals from across Europe. We show an overrepresentation of genes related to neuronal functions, learning and cognition in regions under positive selection, as well as increased CpG methylation in these regions. In addition, great tit neuronal non-CpG methylation patterns are very similar to those observed in mammals, suggesting a universal role in neuronal epigenetic regulation which can affect learning-, memory- and experience-induced plasticity. The high-quality great tit genome assembly will play an instrumental role in furthering the integration of ecological, evolutionary, behavioural and genomic approaches in this model species. PMID:26805030

The impact of selection, gene flow and demographic history on heterogeneous genomic divergence: three-spine sticklebacks in divergent environments.

PubMed

Ferchaud, Anne-Laure; Hansen, Michael M

2016-01-01

Heterogeneous genomic divergence between populations may reflect selection, but should also be seen in conjunction with gene flow and drift, particularly population bottlenecks. Marine and freshwater three-spine stickleback (Gasterosteus aculeatus) populations often exhibit different lateral armour plate morphs. Moreover, strikingly parallel genomic footprints across different marine-freshwater population pairs are interpreted as parallel evolution and gene reuse. Nevertheless, in some geographic regions like the North Sea and Baltic Sea, different patterns are observed. Freshwater populations in coastal regions are often dominated by marine morphs, suggesting that gene flow overwhelms selection, and genomic parallelism may also be less pronounced. We used RAD sequencing for analysing 28 888 SNPs in two marine and seven freshwater populations in Denmark, Europe. Freshwater populations represented a variety of environments: river populations accessible to gene flow from marine sticklebacks and large and small isolated lakes with and without fish predators. Sticklebacks in an accessible river environment showed minimal morphological and genomewide divergence from marine populations, supporting the hypothesis of gene flow overriding selection. Allele frequency spectra suggested bottlenecks in all freshwater populations, and particularly two small lake populations. However, genomic footprints ascribed to selection could nevertheless be identified. No genomic regions were consistent freshwater-marine outliers, and parallelism was much lower than in other comparable studies. Two genomic regions previously described to be under divergent selection in freshwater and marine populations were outliers between different freshwater populations. We ascribe these patterns to stronger environmental heterogeneity among freshwater populations in our study as compared to most other studies, although the demographic history involving bottlenecks should also be considered in the

Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC.

PubMed

Kim, Eui-Soo; Sonstegard, Tad S; da Silva, Marcos V G B; Gasbarre, Louis C; Van Tassell, Curtis P

2015-01-01

Genetic markers associated with parasite indicator traits are ideal targets for study of marker assisted selection aimed at controlling infections that reduce herd use of anthelminthics. For this study, we collected gastrointestinal (GI) nematode fecal egg count (FEC) data from post-weaning animals of an Angus resource population challenged to a 26 week natural exposure on pasture. In all, data from 487 animals was collected over a 16 year period between 1992 and 2007, most of which were selected for a specific DRB1 allele to reduce the influence of potential allelic variant effects of the MHC locus. A genome-wide association study (GWAS) based on BovineSNP50 genotypes revealed six genomic regions located on bovine Chromosomes 3, 5, 8, 15 and 27; which were significantly associated (-log10 p=4.3) with Box-Cox transformed mean FEC (BC-MFEC). DAVID analysis of the genes within the significant genomic regions suggested a correlation between our results and annotation for genes involved in inflammatory response to infection. Furthermore, ROH and selection signature analyses provided strong evidence that the genomic regions associated BC-MFEC have not been affected by local autozygosity or recent experimental selection. These findings provide useful information for parasite resistance prediction for young grazing cattle and suggest new candidate gene targets for development of disease-modifying therapies or future studies of host response to GI parasite infection.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

PubMed

Resende, R T; Resende, M D V; Silva, F F; Azevedo, C F; Takahashi, E K; Silva-Junior, O B; Grattapaglia, D

2017-10-01

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F 2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

Rapid Cycling Genomic Selection in a Multiparental Tropical Maize Population

PubMed Central

Zhang, Xuecai; Pérez-Rodríguez, Paulino; Burgueño, Juan; Olsen, Michael; Buckler, Edward; Atlin, Gary; Prasanna, Boddupalli M.; Vargas, Mateo; San Vicente, Félix; Crossa, José

2017-01-01

Genomic selection (GS) increases genetic gain by reducing the length of the selection cycle, as has been exemplified in maize using rapid cycling recombination of biparental populations. However, no results of GS applied to maize multi-parental populations have been reported so far. This study is the first to show realized genetic gains of rapid cycling genomic selection (RCGS) for four recombination cycles in a multi-parental tropical maize population. Eighteen elite tropical maize lines were intercrossed twice, and self-pollinated once, to form the cycle 0 (C0) training population. A total of 1000 ear-to-row C0 families was genotyped with 955,690 genotyping-by-sequencing SNP markers; their testcrosses were phenotyped at four optimal locations in Mexico to form the training population. Individuals from families with the best plant types, maturity, and grain yield were selected and intermated to form RCGS cycle 1 (C1). Predictions of the genotyped individuals forming cycle C1 were made, and the best predicted grain yielders were selected as parents of C2; this was repeated for more cycles (C2, C3, and C4), thereby achieving two cycles per year. Multi-environment trials of individuals from populations C0, C1, C2, C3, and C4, together with four benchmark checks were evaluated at two locations in Mexico. Results indicated that realized grain yield from C1 to C4 reached 0.225 ton ha−1 per cycle, which is equivalent to 0.100 ton ha−1 yr−1 over a 4.5-yr breeding period from the initial cross to the last cycle. Compared with the original 18 parents used to form cycle 0 (C0), genetic diversity narrowed only slightly during the last GS cycles (C3 and C4). Results indicate that, in tropical maize multi-parental breeding populations, RCGS can be an effective breeding strategy for simultaneously conserving genetic diversity and achieving high genetic gains in a short period of time. PMID:28533335

Background Nutrients Affect the Biotransformation of Tetracycline by Stenotrophomonas maltophilia as Revealed by Genomics and Proteomics.

PubMed

Leng, Yifei; Bao, Jianguo; Song, Dandan; Li, Jing; Ye, Mao; Li, Xu

2017-09-19

Certain bacteria are resistant to antibiotics and can even transform antibiotics in the environment. It is unclear how the molecular mechanisms underlying the resistance and biotransformation processes vary under different environmental conditions. The objective of this study is to investigate the molecular mechanisms of tetracycline resistance and biotransformation by Stenotrophomonas maltophilia strain DT1 under various background nutrient conditions. Strain DT1 was exposed to tetracycline for 7 days with four background nutrient conditions: no background (NB), peptone (P), peptone plus citrate (PC), and peptone plus glucose (PG). The biotransformation rate follows the order of PC > P > PG > NB ≈ 0. Genomic analysis showed that strain DT1 contained tet(X1), a gene encoding an FAD-binding monooxygenase, and eight peroxidase genes that could be relevant to tetracycline biotransformation. Quantitative proteomic analyses revealed that nodulation protein transported tetracycline outside of cells; hypoxanthine-guanine phosphoribosyltransferase facilitated the activation of the ribosomal protection proteins to prevent the binding of tetracycline to the ribosome and superoxide dismutase and peroxiredoxin-modified tetracycline molecules. Comparing different nutrient conditions showed that the biotransformation rates of tetracycline were positively correlated with the expression levels of superoxide dismutase.

Role of genetic background in induced instability

NASA Technical Reports Server (NTRS)

Kadhim, Munira A.; Nelson, G. A. (Principal Investigator)

2003-01-01

Genomic instability is effectively induced by ionizing radiation. Recently, evidence has accumulated supporting a relationship between genetic background and the radiation-induced genomic instability phenotype. This is possibly due to alterations in proteins responsible for maintenance of genomic integrity or altered oxidative metabolism. Studies in human cell lines, human primary cells, and mouse models have been performed predominantly using high linear energy transfer (LET) radiation, or high doses of low LET radiation. The interplay between genetics, radiation response, and genomic instability has not been fully determined at low doses of low LET radiation. However, recent studies using low doses of low LET radiation suggest that the relationship between genetic background and radiation-induced genomic instability may be more complicated than these same relationships at high LET or high doses of low LET radiation. The complexity of this relationship at low doses of low LET radiation suggests that more of the population may be at risk than previously recognized and may have implications for radiation risk assessment.

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

PubMed

Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

PubMed

Ovenden, Ben; Milgate, Andrew; Wade, Len J; Rebetzke, Greg J; Holland, James B

2018-05-31

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection. Copyright © 2018 Ovenden et al.

Genetic association of marbling score with intragenic nucleotide variants at selection signals of the bovine genome.

PubMed

Ryu, J; Lee, C

2016-04-01

Selection signals of Korean cattle might be attributed largely to artificial selection for meat quality. Rapidly increased intragenic markers of newly annotated genes in the bovine genome would help overcome limited findings of genetic markers associated with meat quality at the selection signals in a previous study. The present study examined genetic associations of marbling score (MS) with intragenic nucleotide variants at selection signals of Korean cattle. A total of 39 092 nucleotide variants of 407 Korean cattle were utilized in the association analysis. A total of 129 variants were selected within newly annotated genes in the bovine genome. Their genetic associations were analyzed using the mixed model with random polygenic effects based on identical-by-state genetic relationships among animals in order to control for spurious associations produced by population structure. Genetic associations of MS were found (P<3.88×10-4) with six intragenic nucleotide variants on bovine autosomes 3 (cache domain containing 1, CACHD1), 5 (like-glycosyltransferase, LARGE), 16 (cell division cycle 42 binding protein kinase alpha, CDC42BPA) and 21 (snurportin 1, SNUPN; protein tyrosine phosphatase, non-receptor type 9, PTPN9; chondroitin sulfate proteoglycan 4, CSPG4). In particular, the genetic associations with CDC42BPA and LARGE were confirmed using an independent data set of Korean cattle. The results implied that allele frequencies of functional variants and their proximity variants have been augmented by directional selection for greater MS and remain selection signals in the bovine genome. Further studies of fine mapping would be useful to incorporate favorable alleles in marker-assisted selection for MS of Korean cattle.

BiFCROS: A Low-Background Fluorescence Repressor Operator System for Labeling of Genomic Loci.

PubMed

Milbredt, Sarah; Waldminghaus, Torsten

2017-06-07

Fluorescence-based methods are widely used to analyze elementary cell processes such as DNA replication or chromosomal folding and segregation. Labeling DNA with a fluorescent protein allows the visualization of its temporal and spatial organization. One popular approach is FROS (fluorescence repressor operator system). This method specifically labels DNA in vivo through binding of a fusion of a fluorescent protein and a repressor protein to an operator array, which contains numerous copies of the repressor binding site integrated into the genomic site of interest. Bound fluorescent proteins are then visible as foci in microscopic analyses and can be distinguished from the background fluorescence caused by unbound fusion proteins. Even though this method is widely used, no attempt has been made so far to decrease the background fluorescence to facilitate analysis of the actual signal of interest. Here, we present a new method that greatly reduces the background signal of FROS. BiFCROS (Bimolecular Fluorescence Complementation and Repressor Operator System) is based on fusions of repressor proteins to halves of a split fluorescent protein. Binding to a hybrid FROS array results in fluorescence signals due to bimolecular fluorescence complementation. Only proteins bound to the hybrid FROS array fluoresce, greatly improving the signal to noise ratio compared to conventional FROS. We present the development of BiFCROS and discuss its potential to be used as a fast and single-cell readout for copy numbers of genetic loci. Copyright © 2017 Milbredt and Waldminghaus.

BiFCROS: A Low-Background Fluorescence Repressor Operator System for Labeling of Genomic Loci

PubMed Central

Milbredt, Sarah; Waldminghaus, Torsten

2017-01-01

Fluorescence-based methods are widely used to analyze elementary cell processes such as DNA replication or chromosomal folding and segregation. Labeling DNA with a fluorescent protein allows the visualization of its temporal and spatial organization. One popular approach is FROS (fluorescence repressor operator system). This method specifically labels DNA in vivo through binding of a fusion of a fluorescent protein and a repressor protein to an operator array, which contains numerous copies of the repressor binding site integrated into the genomic site of interest. Bound fluorescent proteins are then visible as foci in microscopic analyses and can be distinguished from the background fluorescence caused by unbound fusion proteins. Even though this method is widely used, no attempt has been made so far to decrease the background fluorescence to facilitate analysis of the actual signal of interest. Here, we present a new method that greatly reduces the background signal of FROS. BiFCROS (Bimolecular Fluorescence Complementation and Repressor Operator System) is based on fusions of repressor proteins to halves of a split fluorescent protein. Binding to a hybrid FROS array results in fluorescence signals due to bimolecular fluorescence complementation. Only proteins bound to the hybrid FROS array fluoresce, greatly improving the signal to noise ratio compared to conventional FROS. We present the development of BiFCROS and discuss its potential to be used as a fast and single-cell readout for copy numbers of genetic loci. PMID:28450375

Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations

PubMed Central

2009-01-01

Background Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes. Results In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains. This mutation conferred an approximately 15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in an approximately 30% increase to growth rate when introduced to a background already harboring two adaptive mutations. Additionally, most endpoints had a mutation in a regulatory gene (crp or relA, for example) or the RNA polymerase. Conclusions The 82 base-pair deletion found in the rph-pyrE operon of many endpoints may function to relieve a pyrimidine biosynthesis defect present in MG1655. In contrast, a variety of regulators acquire mutations in the different endpoints, suggesting flexibility in overcoming regulatory challenges in the adaptation. PMID:19849850

Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection

USDA-ARS?s Scientific Manuscript database

Current advances in sequencing technologies and bioinformatics allow to determine a nearly complete genomic background of rice, a staple food for the poor people. Consequently, comprehensive databases of variation among thousands of varieties is currently being assembled and released. Proper analysi...

Genome-wide scans between two honeybee populations reveal putative signatures of human-mediated selection.

PubMed

Parejo, M; Wragg, D; Henriques, D; Vignal, A; Neuditschko, M

2017-12-01

Human-mediated selection has left signatures in the genomes of many domesticated animals, including the European dark honeybee, Apis mellifera mellifera, which has been selected by apiculturists for centuries. Using whole-genome sequence information, we investigated selection signatures in spatially separated honeybee subpopulations (Switzerland, n = 39 and France, n = 17). Three different test statistics were calculated in windows of 2 kb (fixation index, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio) and combined into a recently developed composite selection score. Applying a stringent false discovery rate of 0.01, we identified six significant selective sweeps distributed across five chromosomes covering eight genes. These genes are associated with multiple molecular and biological functions, including regulation of transcription, receptor binding and signal transduction. Of particular interest is a selection signature on chromosome 1, which corresponds to the WNT4 gene, the family of which is conserved across the animal kingdom with a variety of functions. In Drosophila melanogaster, WNT4 alleles have been associated with differential wing, cross vein and abdominal phenotypes. Defining phenotypic characteristics of different Apis mellifera ssp., which are typically used as selection criteria, include colour and wing venation pattern. This signal is therefore likely to be a good candidate for human mediated-selection arising from different applied breeding practices in the two managed populations. © 2017 The Authors. Animal Genetics published by John Wiley & Sons Ltd on behalf of Stichting International Foundation for Animal Genetics.

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat.

PubMed

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2018-01-01

To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat ( Fagopyrum esculentum Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598-50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

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

Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie

2014-06-18

Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealedmore » substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ‘ecotype model’ of diversification, but not previously observed in natural populations.« less

Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

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

Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie

2014-05-12

Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealedmore » substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ecotype model? of diversification, but not previously observed in natural populations.« less

Interpreting the genomic landscape of speciation: a road map for finding barriers to gene flow.

PubMed

Ravinet, M; Faria, R; Butlin, R K; Galindo, J; Bierne, N; Rafajlović, M; Noor, M A F; Mehlig, B; Westram, A M

2017-08-01

Speciation, the evolution of reproductive isolation among populations, is continuous, complex, and involves multiple, interacting barriers. Until it is complete, the effects of this process vary along the genome and can lead to a heterogeneous genomic landscape with peaks and troughs of differentiation and divergence. When gene flow occurs during speciation, barriers restricting gene flow locally in the genome lead to patterns of heterogeneity. However, genomic heterogeneity can also be produced or modified by variation in factors such as background selection and selective sweeps, recombination and mutation rate variation, and heterogeneous gene density. Extracting the effects of gene flow, divergent selection and reproductive isolation from such modifying factors presents a major challenge to speciation genomics. We argue one of the principal aims of the field is to identify the barrier loci involved in limiting gene flow. We first summarize the expected signatures of selection at barrier loci, at the genomic regions linked to them and across the entire genome. We then discuss the modifying factors that complicate the interpretation of the observed genomic landscape. Finally, we end with a road map for future speciation research: a proposal for how to account for these modifying factors and to progress towards understanding the nature of barrier loci. Despite the difficulties of interpreting empirical data, we argue that the availability of promising technical and analytical methods will shed further light on the important roles that gene flow and divergent selection have in shaping the genomic landscape of speciation. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

L2-Boosting algorithm applied to high-dimensional problems in genomic selection.

PubMed

González-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M

2010-06-01

The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive

Rhipicephalus microplus dataset of nonredundant raw sequence reads from 454 GS FLX sequencing of Cot-selected (Cot = 660) genomic DNA

USDA-ARS?s Scientific Manuscript database

A reassociation kinetics-based approach was used to reduce the complexity of genomic DNA from the Deutsch laboratory strain of the cattle tick, Rhipicephalus microplus, to facilitate genome sequencing. Selected genomic DNA (Cot value = 660) was sequenced using 454 GS FLX technology, resulting in 356...

Determining the Effect of Natural Selection on Linked Neutral Divergence across Species.

PubMed

Phung, Tanya N; Huber, Christian D; Lohmueller, Kirk E

2016-08-01

A major goal in evolutionary biology is to understand how natural selection has shaped patterns of genetic variation across genomes. Studies in a variety of species have shown that neutral genetic diversity (intra-species differences) has been reduced at sites linked to those under direct selection. However, the effect of linked selection on neutral sequence divergence (inter-species differences) remains ambiguous. While empirical studies have reported correlations between divergence and recombination, which is interpreted as evidence for natural selection reducing linked neutral divergence, theory argues otherwise, especially for species that have diverged long ago. Here we address these outstanding issues by examining whether natural selection can affect divergence between both closely and distantly related species. We show that neutral divergence between closely related species (e.g. human-primate) is negatively correlated with functional content and positively correlated with human recombination rate. We also find that neutral divergence between distantly related species (e.g. human-rodent) is negatively correlated with functional content and positively correlated with estimates of background selection from primates. These patterns persist after accounting for the confounding factors of hypermutable CpG sites, GC content, and biased gene conversion. Coalescent models indicate that even when the contribution of ancestral polymorphism to divergence is small, background selection in the ancestral population can still explain a large proportion of the variance in divergence across the genome, generating the observed correlations. Our findings reveal that, contrary to previous intuition, natural selection can indirectly affect linked neutral divergence between both closely and distantly related species. Though we cannot formally exclude the possibility that the direct effects of purifying selection drive some of these patterns, such a scenario would be possible only

Determining the Effect of Natural Selection on Linked Neutral Divergence across Species

PubMed Central

Phung, Tanya N.; Lohmueller, Kirk E.

2016-01-01

A major goal in evolutionary biology is to understand how natural selection has shaped patterns of genetic variation across genomes. Studies in a variety of species have shown that neutral genetic diversity (intra-species differences) has been reduced at sites linked to those under direct selection. However, the effect of linked selection on neutral sequence divergence (inter-species differences) remains ambiguous. While empirical studies have reported correlations between divergence and recombination, which is interpreted as evidence for natural selection reducing linked neutral divergence, theory argues otherwise, especially for species that have diverged long ago. Here we address these outstanding issues by examining whether natural selection can affect divergence between both closely and distantly related species. We show that neutral divergence between closely related species (e.g. human-primate) is negatively correlated with functional content and positively correlated with human recombination rate. We also find that neutral divergence between distantly related species (e.g. human-rodent) is negatively correlated with functional content and positively correlated with estimates of background selection from primates. These patterns persist after accounting for the confounding factors of hypermutable CpG sites, GC content, and biased gene conversion. Coalescent models indicate that even when the contribution of ancestral polymorphism to divergence is small, background selection in the ancestral population can still explain a large proportion of the variance in divergence across the genome, generating the observed correlations. Our findings reveal that, contrary to previous intuition, natural selection can indirectly affect linked neutral divergence between both closely and distantly related species. Though we cannot formally exclude the possibility that the direct effects of purifying selection drive some of these patterns, such a scenario would be possible only

Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

PubMed Central

Pardiñas, Antonio F.; Holmans, Peter; Pocklington, Andrew J.; Escott-Price, Valentina; Ripke, Stephan; Carrera, Noa; Legge, Sophie E.; Bishop, Sophie; Cameron, Darren; Hamshere, Marian L.; Han, Jun; Hubbard, Leon; Lynham, Amy; Mantripragada, Kiran; Rees, Elliott; MacCabe, James H.; McCarroll, Steven A.; Baune, Bernhard T.; Breen, Gerome; Byrne, Enda M.; Dannlowski, Udo; Eley, Thalia C.; Hayward, Caroline; Martin, Nicholas G.; McIntosh, Andrew M.; Plomin, Robert; Porteous, David J.; Wray, Naomi R.; Caballero, Armando; Geschwind, Daniel H.; Huckins, Laura M.; Ruderfer, Douglas M.; Santiago, Enrique; Sklar, Pamela; Stahl, Eli A.; Won, Hyejung; Agerbo, Esben; Als, Thomas D.; Andreassen, Ole A.; Bækvad-Hansen, Marie; Mortensen, Preben Bo; Pedersen, Carsten Bøcker; Børglum, Anders D.; Bybjerg-Grauholm, Jonas; Djurovic, Srdjan; Durmishi, Naser; Pedersen, Marianne Giørtz; Golimbet, Vera; Grove, Jakob; Hougaard, David M.; Mattheisen, Manuel; Molden, Espen; Mors, Ole; Nordentoft, Merete; Pejovic-Milovancevic, Milica; Sigurdsson, Engilbert; Silagadze, Teimuraz; Hansen, Christine Søholm; Stefansson, Kari; Stefansson, Hreinn; Steinberg, Stacy; Tosato, Sarah; Werge, Thomas; Collier, David A.; Rujescu, Dan; Kirov, George; Owen, Michael J.; O’Donovan, Michael C.; Walters, James T. R.

2018-01-01

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population. PMID:29483656

Genomic selection for slaughter age in pigs using the Cox frailty model.

PubMed

Santos, V S; Martins Filho, S; Resende, M D V; Azevedo, C F; Lopes, P S; Guimarães, S E F; Glória, L S; Silva, F F

2015-10-19

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

Whole-Genome Positive Selection and Habitat-Driven Evolution in a Shallow and a Deep-Sea Urchin

PubMed Central

Oliver, Thomas A.; Garfield, David A.; Manier, Mollie K.; Haygood, Ralph; Wray, Gregory A.; Palumbi, Stephen R.

2010-01-01

Comparisons of genomic sequence between divergent species can provide insight into the action of natural selection across many distinct classes of proteins. Here, we examine the extent of positive selection as a function of tissue-specific and stage-specific gene expression in two closely-related sea urchins, the shallow-water Strongylocentrotus purpuratus and the deep-sea Allocentrotus fragilis, which have diverged greatly in their adult but not larval habitats. Genes that are expressed specifically in adult somatic tissue have significantly higher dN/dS ratios than the genome-wide average, whereas those in larvae are indistinguishable from the genome-wide average. Testis-specific genes have the highest dN/dS values, whereas ovary-specific have the lowest. Branch-site models involving the outgroup S. franciscanus indicate greater selection (ωFG) along the A. fragilis branch than along the S. purpuratus branch. The A. fragilis branch also shows a higher proportion of genes under positive selection, including those involved in skeletal development, endocytosis, and sulfur metabolism. Both lineages are approximately equal in enrichment for positive selection of genes involved in immunity, development, and cell–cell communication. The branch-site models further suggest that adult-specific genes have experienced greater positive selection than those expressed in larvae and that ovary-specific genes are more conserved (i.e., experienced greater negative selection) than those expressed specifically in adult somatic tissues and testis. Our results chart the patterns of protein change that have occurred after habitat divergence in these two species and show that the developmental or functional context in which a gene acts can play an important role in how divergent species adapt to new environments. PMID:20935062

Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum.

PubMed

Oyebola, Kolapo M; Idowu, Emmanuel T; Olukosi, Yetunde A; Awolola, Taiwo S; Amambua-Ngwa, Alfred

2017-06-29

The burden of falciparum malaria is especially high in sub-Saharan Africa. Differences in pressure from host immunity and antimalarial drugs lead to adaptive changes responsible for high level of genetic variations within and between the parasite populations. Population-specific genetic studies to survey for genes under positive or balancing selection resulting from drug pressure or host immunity will allow for refinement of interventions. We performed a pooled sequencing (pool-seq) of the genomes of 100 Plasmodium falciparum isolates from Nigeria. We explored allele-frequency based neutrality test (Tajima's D) and integrated haplotype score (iHS) to identify genes under selection. Fourteen shared iHS regions that had at least 2 SNPs with a score > 2.5 were identified. These regions code for genes that were likely to have been under strong directional selection. Two of these genes were the chloroquine resistance transporter (CRT) on chromosome 7 and the multidrug resistance 1 (MDR1) on chromosome 5. There was a weak signature of selection in the dihydrofolate reductase (DHFR) gene on chromosome 4 and MDR5 genes on chromosome 13, with only 2 and 3 SNPs respectively identified within the iHS window. We observed strong selection pressure attributable to continued chloroquine and sulfadoxine-pyrimethamine use despite their official proscription for the treatment of uncomplicated malaria. There was also a major selective sweep on chromosome 6 which had 32 SNPs within the shared iHS region. Tajima's D of circumsporozoite protein (CSP), erythrocyte-binding antigen (EBA-175), merozoite surface proteins - MSP3 and MSP7, merozoite surface protein duffy binding-like (MSPDBL2) and serine repeat antigen (SERA-5) were 1.38, 1.29, 0.73, 0.84 and 0.21, respectively. We have demonstrated the use of pool-seq to understand genomic patterns of selection and variability in P. falciparum from Nigeria, which bears the highest burden of infections. This investigation identified known

Genomes as geography: using GIS technology to build interactive genome feature maps

PubMed Central

Dolan, Mary E; Holden, Constance C; Beard, M Kate; Bult, Carol J

2006-01-01

Background Many commonly used genome browsers display sequence annotations and related attributes as horizontal data tracks that can be toggled on and off according to user preferences. Most genome browsers use only simple keyword searches and limit the display of detailed annotations to one chromosomal region of the genome at a time. We have employed concepts, methodologies, and tools that were developed for the display of geographic data to develop a Genome Spatial Information System (GenoSIS) for displaying genomes spatially, and interacting with genome annotations and related attribute data. In contrast to the paradigm of horizontally stacked data tracks used by most genome browsers, GenoSIS uses the concept of registered spatial layers composed of spatial objects for integrated display of diverse data. In addition to basic keyword searches, GenoSIS supports complex queries, including spatial queries, and dynamically generates genome maps. Our adaptation of the geographic information system (GIS) model in a genome context supports spatial representation of genome features at multiple scales with a versatile and expressive query capability beyond that supported by existing genome browsers. Results We implemented an interactive genome sequence feature map for the mouse genome in GenoSIS, an application that uses ArcGIS, a commercially available GIS software system. The genome features and their attributes are represented as spatial objects and data layers that can be toggled on and off according to user preferences or displayed selectively in response to user queries. GenoSIS supports the generation of custom genome maps in response to complex queries about genome features based on both their attributes and locations. Our example application of GenoSIS to the mouse genome demonstrates the powerful visualization and query capability of mature GIS technology applied in a novel domain. Conclusion Mapping tools developed specifically for geographic data can be

Strong signatures of selection in the domestic pig genome.

PubMed

Rubin, Carl-Johan; Megens, Hendrik-Jan; Martinez Barrio, Alvaro; Maqbool, Khurram; Sayyab, Shumaila; Schwochow, Doreen; Wang, Chao; Carlborg, Örjan; Jern, Patric; Jørgensen, Claus B; Archibald, Alan L; Fredholm, Merete; Groenen, Martien A M; Andersson, Leif

2012-11-27

Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig--the elongation of the back and an increased number of vertebrae. The three loci were associated with the NR6A1, PLAG1, and LCORL genes. The latter two have repeatedly been associated with loci controlling stature in other domestic animals and in humans. Most European domestic pigs are homozygous for the same haplotype at these three loci. We found an excess of derived nonsynonymous substitutions in domestic pigs, most likely reflecting both positive selection and relaxed purifying selection after domestication. Our analysis of structural variation revealed four duplications at the KIT locus that were exclusively present in white or white-spotted pigs, carrying the Dominant white, Patch, or Belt alleles. This discovery illustrates how structural changes have contributed to rapid phenotypic evolution in domestic animals and how alleles in domestic animals may evolve by the accumulation of multiple causative mutations as a response to strong directional selection.

Strong signatures of selection in the domestic pig genome

PubMed Central

Rubin, Carl-Johan; Megens, Hendrik-Jan; Barrio, Alvaro Martinez; Maqbool, Khurram; Sayyab, Shumaila; Schwochow, Doreen; Wang, Chao; Carlborg, Örjan; Jern, Patric; Jørgensen, Claus B.; Archibald, Alan L.; Fredholm, Merete; Groenen, Martien A. M.; Andersson, Leif

2012-01-01

Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig—the elongation of the back and an increased number of vertebrae. The three loci were associated with the NR6A1, PLAG1, and LCORL genes. The latter two have repeatedly been associated with loci controlling stature in other domestic animals and in humans. Most European domestic pigs are homozygous for the same haplotype at these three loci. We found an excess of derived nonsynonymous substitutions in domestic pigs, most likely reflecting both positive selection and relaxed purifying selection after domestication. Our analysis of structural variation revealed four duplications at the KIT locus that were exclusively present in white or white-spotted pigs, carrying the Dominant white, Patch, or Belt alleles. This discovery illustrates how structural changes have contributed to rapid phenotypic evolution in domestic animals and how alleles in domestic animals may evolve by the accumulation of multiple causative mutations as a response to strong directional selection. PMID:23151514

Efficient use of historical data for genomic selection: a case study of rust resistance in wheat

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) is a new methodology that can improve wheat breeding efficiency. To implement GS, a training population (TP) with both phenotypic and genotypic data is required to train a statistical model used to predict genotyped selection candidates (SCs). Several factors impact prediction...

A Genome-Wide Scan of Selective Sweeps and Association Mapping of Fruit Traits Using Microsatellite Markers in Watermelon

PubMed Central

Reddy, Umesh K.; Abburi, Lavanya; Abburi, Venkata Lakshmi; Saminathan, Thangasamy; Cantrell, Robert; Vajja, Venkata Gopinath; Reddy, Rishi; Tomason, Yan R.; Levi, Amnon; Wehner, Todd C.; Nimmakayala, Padma

2015-01-01

Our genetic diversity study uses microsatellites of known map position to estimate genome level population structure and linkage disequilibrium, and to identify genomic regions that have undergone selection during watermelon domestication and improvement. Thirty regions that showed evidence of selective sweep were scanned for the presence of candidate genes using the watermelon genome browser (www.icugi.org). We localized selective sweeps in intergenic regions, close to the promoters, and within the exons and introns of various genes. This study provided an evidence of convergent evolution for the presence of diverse ecotypes with special reference to American and European ecotypes. Our search for location of linked markers in the whole-genome draft sequence revealed that BVWS00358, a GA repeat microsatellite, is the GAGA type transcription factor located in the 5′ untranslated regions of a structure and insertion element that expresses a Cys2His2 Zinc finger motif, with presumed biological processes related to chitin response and transcriptional regulation. In addition, BVWS01708, an ATT repeat microsatellite, located in the promoter of a DTW domain-containing protein (Cla002761); and 2 other simple sequence repeats that association mapping link to fruit length and rind thickness. PMID:25425675

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by

Cloud computing for comparative genomics

PubMed Central

2010-01-01

Background Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. Results We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. Conclusions The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems. PMID:20482786

Weakly Deleterious Mutations and Low Rates of Recombination Limit the Impact of Natural Selection on Bacterial Genomes

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

Price, Morgan N.; Arkin, Adam P.

Free-living bacteria are usually thought to have large effective population sizes, and so tiny selective differences can drive their evolution. However, because recombination is infrequent, “background selection” against slightly deleterious alleles should reduce the effective population size (N e) by orders of magnitude. For example, for a well-mixed population with 10 12 individuals and a typical level of homologous recombination (r/m= 3, i.e., nucleotide changes due to recombination [r] occur at 3 times the mutation rate [m]), we predict that N e is<10 7. An argument for high N e values for bacteria has been the high genetic diversity withinmore » many bacterial “species,” but this diversity may be due to population structure: diversity across subpopulations can be far higher than diversity within a subpopulation, which makes it difficult to estimate N e correctly. Given an estimate ofN e, standard population genetics models imply that selection should be sufficient to drive evolution if N e ×s is >1, where s is the selection coefficient. We found that this remains approximately correct if background selection is occurring or when population structure is present. Overall, we predict that even for free-living bacteria with enormous populations, natural selection is only a significant force ifs is above 10 -7 or so. Because bacteria form huge populations with trillions of individuals, the simplest theoretical prediction is that the better allele at a site would predominate even if its advantage was just 10 -9 per generation. In other words, virtually every nucleotide would be at the local optimum in most individuals. A more sophisticated theory considers that bacterial genomes have millions of sites each and selection events on these many sites could interfere with each other, so that only larger effects would be important. However, bacteria can exchange genetic material, and in principle, this exchange could eliminate the interference between the

Weakly Deleterious Mutations and Low Rates of Recombination Limit the Impact of Natural Selection on Bacterial Genomes

DOE PAGES

Price, Morgan N.; Arkin, Adam P.

2015-12-15

Free-living bacteria are usually thought to have large effective population sizes, and so tiny selective differences can drive their evolution. However, because recombination is infrequent, “background selection” against slightly deleterious alleles should reduce the effective population size (N e) by orders of magnitude. For example, for a well-mixed population with 10 12 individuals and a typical level of homologous recombination (r/m= 3, i.e., nucleotide changes due to recombination [r] occur at 3 times the mutation rate [m]), we predict that N e is<10 7. An argument for high N e values for bacteria has been the high genetic diversity withinmore » many bacterial “species,” but this diversity may be due to population structure: diversity across subpopulations can be far higher than diversity within a subpopulation, which makes it difficult to estimate N e correctly. Given an estimate ofN e, standard population genetics models imply that selection should be sufficient to drive evolution if N e ×s is >1, where s is the selection coefficient. We found that this remains approximately correct if background selection is occurring or when population structure is present. Overall, we predict that even for free-living bacteria with enormous populations, natural selection is only a significant force ifs is above 10 -7 or so. Because bacteria form huge populations with trillions of individuals, the simplest theoretical prediction is that the better allele at a site would predominate even if its advantage was just 10 -9 per generation. In other words, virtually every nucleotide would be at the local optimum in most individuals. A more sophisticated theory considers that bacterial genomes have millions of sites each and selection events on these many sites could interfere with each other, so that only larger effects would be important. However, bacteria can exchange genetic material, and in principle, this exchange could eliminate the interference between the

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat

PubMed Central

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2018-01-01

To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat (Fagopyrum esculentum Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598–50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding. PMID:29619035

Optimal selection of markers for validation or replication from genome-wide association studies.

PubMed

Greenwood, Celia M T; Rangrej, Jagadish; Sun, Lei

2007-07-01

With reductions in genotyping costs and the fast pace of improvements in genotyping technology, it is not uncommon for the individuals in a single study to undergo genotyping using several different platforms, where each platform may contain different numbers of markers selected via different criteria. For example, a set of cases and controls may be genotyped at markers in a small set of carefully selected candidate genes, and shortly thereafter, the same cases and controls may be used for a genome-wide single nucleotide polymorphism (SNP) association study. After such initial investigations, often, a subset of "interesting" markers is selected for validation or replication. Specifically, by validation, we refer to the investigation of associations between the selected subset of markers and the disease in independent data. However, it is not obvious how to choose the best set of markers for this validation. There may be a prior expectation that some sets of genotyping data are more likely to contain real associations. For example, it may be more likely for markers in plausible candidate genes to show disease associations than markers in a genome-wide scan. Hence, it would be desirable to select proportionally more markers from the candidate gene set. When a fixed number of markers are selected for validation, we propose an approach for identifying an optimal marker-selection configuration by basing the approach on minimizing the stratified false discovery rate. We illustrate this approach using a case-control study of colorectal cancer from Ontario, Canada, and we show that this approach leads to substantial reductions in the estimated false discovery rates in the Ontario dataset for the selected markers, as well as reductions in the expected false discovery rates for the proposed validation dataset. Copyright 2007 Wiley-Liss, Inc.

Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar).

PubMed

Bangera, Rama; Correa, Katharina; Lhorente, Jean P; Figueroa, René; Yáñez, José M

2017-01-31

Salmon Rickettsial Syndrome (SRS) caused by Piscirickettsia salmonis is a major disease affecting the Chilean salmon industry. Genomic selection (GS) is a method wherein genome-wide markers and phenotype information of full-sibs are used to predict genomic EBV (GEBV) of selection candidates and is expected to have increased accuracy and response to selection over traditional pedigree based Best Linear Unbiased Prediction (PBLUP). Widely used GS methods such as genomic BLUP (GBLUP), SNPBLUP, Bayes C and Bayesian Lasso may perform differently with respect to accuracy of GEBV prediction. Our aim was to compare the accuracy, in terms of reliability of genome-enabled prediction, from different GS methods with PBLUP for resistance to SRS in an Atlantic salmon breeding program. Number of days to death (DAYS), binary survival status (STATUS) phenotypes, and 50 K SNP array genotypes were obtained from 2601 smolts challenged with P. salmonis. The reliability of different GS methods at different SNP densities with and without pedigree were compared to PBLUP using a five-fold cross validation scheme. Heritability estimated from GS methods was significantly higher than PBLUP. Pearson's correlation between predicted GEBV from PBLUP and GS models ranged from 0.79 to 0.91 and 0.79-0.95 for DAYS and STATUS, respectively. The relative increase in reliability from different GS methods for DAYS and STATUS with 50 K SNP ranged from 8 to 25% and 27-30%, respectively. All GS methods outperformed PBLUP at all marker densities. DAYS and STATUS showed superior reliability over PBLUP even at the lowest marker density of 3 K and 500 SNP, respectively. 20 K SNP showed close to maximal reliability for both traits with little improvement using higher densities. These results indicate that genomic predictions can accelerate genetic progress for SRS resistance in Atlantic salmon and implementation of this approach will contribute to the control of SRS in Chile. We recommend GBLUP for routine

Reduced representation genome sequencing reveals patterns of genetic diversity and selection in apple.

PubMed

Ma, Baiquan; Liao, Liao; Peng, Qian; Fang, Ting; Zhou, Hui; Korban, Schuyler S; Han, Yuepeng

2017-03-01

Identifying DNA sequence variations is a fundamental step towards deciphering the genetic basis of traits of interest. Here, a total of 20 cultivated and 10 wild apples were genotyped using specific-locus amplified fragment sequencing, and 39,635 single nucleotide polymorphisms with no missing genotypes and evenly distributed along the genome were selected to investigate patterns of genome-wide genetic variations between cultivated and wild apples. Overall, wild apples displayed higher levels of genetic diversity than cultivated apples. Linkage disequilibrium (LD) decays were observed quite rapidly in cultivated and wild apples, with an r 2 -value below 0.2 at 440 and 280 bp, respectively. Moreover, bidirectional gene flow and different distribution patterns of LD blocks were detected between domesticated and wild apples. Most LD blocks unique to cultivated apples were located within QTL regions controlling fruit quality, thus suggesting that fruit quality had probably undergone selection during apple domestication. The genome of the earliest cultivated apple in China, Nai, was highly similar to that of Malus sieversii, and contained a small portion of genetic material from other wild apple species. This suggested that introgression could have been an important driving force during initial domestication of apple. These findings will facilitate future breeding and genetic dissection of complex traits in apple. © 2017 Institute of Botany, Chinese Academy of Sciences.

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

2012-01-01

Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897

Comparison of Marker-Based Genomic Estimated Breeding Values and Phenotypic Evaluation for Selection of Bacterial Spot Resistance in Tomato.

PubMed

Liabeuf, Debora; Sim, Sung-Chur; Francis, David M

2018-03-01

Bacterial spot affects tomato crops (Solanum lycopersicum) grown under humid conditions. Major genes and quantitative trait loci (QTL) for resistance have been described, and multiple loci from diverse sources need to be combined to improve disease control. We investigated genomic selection (GS) prediction models for resistance to Xanthomonas euvesicatoria and experimentally evaluated the accuracy of these models. The training population consisted of 109 families combining resistance from four sources and directionally selected from a population of 1,100 individuals. The families were evaluated on a plot basis in replicated inoculated trials and genotyped with single nucleotide polymorphisms (SNP). We compared the prediction ability of models developed with 14 to 387 SNP. Genomic estimated breeding values (GEBV) were derived using Bayesian least absolute shrinkage and selection operator regression (BL) and ridge regression (RR). Evaluations were based on leave-one-out cross validation and on empirical observations in replicated field trials using the next generation of inbred progeny and a hybrid population resulting from selections in the training population. Prediction ability was evaluated based on correlations between GEBV and phenotypes (r g ), percentage of coselection between genomic and phenotypic selection, and relative efficiency of selection (r g /r p ). Results were similar with BL and RR models. Models using only markers previously identified as significantly associated with resistance but weighted based on GEBV and mixed models with markers associated with resistance treated as fixed effects and markers distributed in the genome treated as random effects offered greater accuracy and a high percentage of coselection. The accuracy of these models to predict the performance of progeny and hybrids exceeded the accuracy of phenotypic selection.

Statistical Selection of Biological Models for Genome-Wide Association Analyses.

PubMed

Bi, Wenjian; Kang, Guolian; Pounds, Stanley B

2018-05-24

Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis of no association without indicating which biological model best explains the observed data. Correctly identifying a specific biological model may improve the scientific interpretation and can be used to more effectively select and design a follow-up validation study. Thus, statistical methodology to identify the correct biological model for a particular genotype-phenotype association can be very useful to investigators. Here, we propose a general statistical method to summarize how accurately each of five biological models (null, additive, dominant, recessive, co-dominant) represents the data observed for each variant in a GWAS study. We show that the new method stringently controls the false discovery rate and asymptotically selects the correct biological model. Simulations of two-stage discovery-validation studies show that the new method has these properties and that its validation power is similar to or exceeds that of simple methods that use the same statistical model for all SNPs. Example analyses of three data sets also highlight these advantages of the new method. An R package is freely available at www.stjuderesearch.org/site/depts/biostats/maew. Copyright © 2018. Published by Elsevier Inc.

Unraveling Selection in the Mitochondrial Genome of Drosophila

PubMed Central

Ballard, JWO.; Kreitman, M.

1994-01-01

We examine mitochondrial DNA variation at the cytochrome b locus within and between three species of Drosophila to determine whether patterns of variation conform to the predictions of neutral molecular evolution. The entire 1137-bp cytochrome b locus was sequenced in 16 lines of Drosophila melanogaster, 18 lines of Drosophila simulans and 13 lines of Drosophila yakuba. Patterns of variation depart from neutrality by several test criteria. Analysis of the evolutionary clock hypothesis shows unequal rates of change along D. simulans lineages. A comparison within and between species of the ratio of amino acid replacement change to synonymous change reveals a relative excess of amino acid replacement polymorphism compared to the neutral prediction, suggestive of slightly deleterious or diversifying selection. There is evidence for excess homozygosity in our world wide sample of D. melanogaster and D. simulans alleles, as well as a reduction in the number of segregating sites in D. simulans, indicative of selective sweeps. Furthermore, a test of neutrality for codon usage shows the direction of mutations at third positions differs among different topological regions of the gene tree. The analyses indicate that molecular variation and evolution of mtDNA are governed by many of the same selective forces that have been shown to govern nuclear genome evolution and suggest caution be taken in the use of mtDNA as a ``neutral'' molecular marker. PMID:7851772

Genome-wide detection of natural selection in African Americans pre- and post-admixture

PubMed Central

Jin, Wenfei; Xu, Shuhua; Wang, Haifeng; Yu, Yongguo; Shen, Yiping; Wu, Bailin; Jin, Li

2012-01-01

It is particularly meaningful to investigate natural selection in African Americans (AfA) due to the high mortality their African ancestry has experienced in history. In this study, we examined 491,526 autosomal single nucleotide polymorphisms (SNPs) genotyped in 5210 individuals and conducted a genome-wide search for selection signals in 1890 AfA. Several genomic regions showing an excess of African or European ancestry, which were considered the footprints of selection since population admixture, were detected based on a commonly used approach. However, we also developed a new strategy to detect natural selection both pre- and post-admixture by reconstructing an ancestral African population (AAF) from inferred African components of ancestry in AfA and comparing it with indigenous African populations (IAF). Interestingly, many selection-candidate genes identified by the new approach were associated with AfA-specific high-risk diseases such as prostate cancer and hypertension, suggesting an important role these disease-related genes might have played in adapting to a new environment. CD36 and HBB, whose mutations confer a degree of protection against malaria, were also located in the highly differentiated regions between AAF and IAF. Further analysis showed that the frequencies of alleles protecting against malaria in AAF were lower than those in IAF, which is consistent with the relaxed selection pressure of malaria in the New World. There is no overlap between the top candidate genes detected by the two approaches, indicating the different environmental pressures AfA experienced pre- and post-population admixture. We suggest that the new approach is reasonably powerful and can also be applied to other admixed populations such as Latinos and Uyghurs. PMID:22128132

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster

PubMed Central

Jha, Aashish R.; Miles, Cecelia M.; Lippert, Nodia R.; Brown, Christopher D.; White, Kevin P.; Kreitman, Martin

2015-01-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. PMID:26044351

PSAT: A web tool to compare genomic neighborhoods of multiple prokaryotic genomes

PubMed Central

Fong, Christine; Rohmer, Laurence; Radey, Matthew; Wasnick, Michael; Brittnacher, Mitchell J

2008-01-01

Background The conservation of gene order among prokaryotic genomes can provide valuable insight into gene function, protein interactions, or events by which genomes have evolved. Although some tools are available for visualizing and comparing the order of genes between genomes of study, few support an efficient and organized analysis between large numbers of genomes. The Prokaryotic Sequence homology Analysis Tool (PSAT) is a web tool for comparing gene neighborhoods among multiple prokaryotic genomes. Results PSAT utilizes a database that is preloaded with gene annotation, BLAST hit results, and gene-clustering scores designed to help identify regions of conserved gene order. Researchers use the PSAT web interface to find a gene of interest in a reference genome and efficiently retrieve the sequence homologs found in other bacterial genomes. The tool generates a graphic of the genomic neighborhood surrounding the selected gene and the corresponding regions for its homologs in each comparison genome. Homologs in each region are color coded to assist users with analyzing gene order among various genomes. In contrast to common comparative analysis methods that filter sequence homolog data based on alignment score cutoffs, PSAT leverages gene context information for homologs, including those with weak alignment scores, enabling a more sensitive analysis. Features for constraining or ordering results are designed to help researchers browse results from large numbers of comparison genomes in an organized manner. PSAT has been demonstrated to be useful for helping to identify gene orthologs and potential functional gene clusters, and detecting genome modifications that may result in loss of function. Conclusion PSAT allows researchers to investigate the order of genes within local genomic neighborhoods of multiple genomes. A PSAT web server for public use is available for performing analyses on a growing set of reference genomes through any web browser with no client

Rates and Genomic Consequences of Spontaneous Mutational Events in Drosophila melanogaster

PubMed Central

Schrider, Daniel R.; Houle, David; Lynch, Michael; Hahn, Matthew W.

2013-01-01

Because spontaneous mutation is the source of all genetic diversity, measuring mutation rates can reveal how natural selection drives patterns of variation within and between species. We sequenced eight genomes produced by a mutation-accumulation experiment in Drosophila melanogaster. Our analysis reveals that point mutation and small indel rates vary significantly between the two different genetic backgrounds examined. We also find evidence that ∼2% of mutational events affect multiple closely spaced nucleotides. Unlike previous similar experiments, we were able to estimate genome-wide rates of large deletions and tandem duplications. These results suggest that, at least in inbred lines like those examined here, mutational pressures may result in net growth rather than contraction of the Drosophila genome. By comparing our mutation rate estimates to polymorphism data, we are able to estimate the fraction of new mutations that are eliminated by purifying selection. These results suggest that ∼99% of duplications and deletions are deleterious—making them 10 times more likely to be removed by selection than nonsynonymous mutations. Our results illuminate not only the rates of new small- and large-scale mutations, but also the selective forces that they encounter once they arise. PMID:23733788

Genome-wide Scan of 29,141 African Americans Finds No Evidence of Directional Selection since Admixture

PubMed Central

Bhatia, Gaurav; Tandon, Arti; Patterson, Nick; Aldrich, Melinda C.; Ambrosone, Christine B.; Amos, Christopher; Bandera, Elisa V.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Bock, Cathryn H.; Caporaso, Neil; Casey, Graham; Deming, Sandra L.; Diver, W. Ryan; Gapstur, Susan M.; Gillanders, Elizabeth M.; Harris, Curtis C.; Henderson, Brian E.; Ingles, Sue A.; Isaacs, William; De Jager, Phillip L.; John, Esther M.; Kittles, Rick A.; Larkin, Emma; McNeill, Lorna H.; Millikan, Robert C.; Murphy, Adam; Neslund-Dudas, Christine; Nyante, Sarah; Press, Michael F.; Rodriguez-Gil, Jorge L.; Rybicki, Benjamin A.; Schwartz, Ann G.; Signorello, Lisa B.; Spitz, Margaret; Strom, Sara S.; Tucker, Margaret A.; Wiencke, John K.; Witte, John S.; Wu, Xifeng; Yamamura, Yuko; Zanetti, Krista A.; Zheng, Wei; Ziegler, Regina G.; Chanock, Stephen J.; Haiman, Christopher A.; Reich, David; Price, Alkes L.

2014-01-01

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study’s conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas. PMID:25242497

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

PubMed

Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

2016-03-01

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

Orchestrating the Selection and Packaging of Genomic RNA by Retroviruses: An Ensemble of Viral and Host Factors

PubMed Central

Kaddis Maldonado, Rebecca J.; Parent, Leslie J.

2016-01-01

Infectious retrovirus particles contain two copies of unspliced viral RNA that serve as the viral genome. Unspliced retroviral RNA is transcribed in the nucleus by the host RNA polymerase II and has three potential fates: (1) it can be spliced into subgenomic messenger RNAs (mRNAs) for the translation of viral proteins; or it can remain unspliced to serve as either (2) the mRNA for the translation of Gag and Gag–Pol; or (3) the genomic RNA (gRNA) that is packaged into virions. The Gag structural protein recognizes and binds the unspliced viral RNA to select it as a genome, which is selected in preference to spliced viral RNAs and cellular RNAs. In this review, we summarize the current state of understanding about how retroviral packaging is orchestrated within the cell and explore potential new mechanisms based on recent discoveries in the field. We discuss the cis-acting elements in the unspliced viral RNA and the properties of the Gag protein that are required for their interaction. In addition, we discuss the role of host factors in influencing the fate of the newly transcribed viral RNA, current models for how retroviruses distinguish unspliced viral mRNA from viral genomic RNA, and the possible subcellular sites of genomic RNA dimerization and selection by Gag. Although this review centers primarily on the wealth of data available for the alpharetrovirus Rous sarcoma virus, in which a discrete RNA packaging sequence has been identified, we have also summarized the cis- and trans-acting factors as well as the mechanisms governing gRNA packaging of other retroviruses for comparison. PMID:27657110

Eucalyptus applied genomics: from gene sequences to breeding tools.

PubMed

Grattapaglia, Dario; Kirst, Matias

2008-01-01

Eucalyptus is the most widely planted hardwood crop in the tropical and subtropical world because of its superior growth, broad adaptability and multipurpose wood properties. Plantation forestry of Eucalyptus supplies high-quality woody biomass for several industrial applications while reducing the pressure on tropical forests and associated biodiversity. This review links current eucalypt breeding practices with existing and emerging genomic tools. A brief discussion provides a background to modern eucalypt breeding together with some current applications of molecular markers in support of operational breeding. Quantitative trait locus (QTL) mapping and genetical genomics are reviewed and an in-depth perspective is provided on the power of association genetics to dissect quantitative variation in this highly diverse organism. Finally, some challenges and opportunities to integrate genomic information into directional selective breeding are discussed in light of the upcoming draft of the Eucalyptus grandis genome. Given the extraordinary genetic variation that exists in the genus Eucalyptus, the ingenuity of most breeders, and the powerful genomic tools that have become available, the prospects of applied genomics in Eucalyptus forest production are encouraging.

The effects of selection and genetic drift on the genomic distribution of sexually antagonistic alleles.

PubMed

Mullon, Charles; Pomiankowski, Andrew; Reuter, Max

2012-12-01

Sexual antagonism (SA) occurs when an allele that is beneficial to one sex, is detrimental to the other. This conflict can result in balancing, directional, or disruptive selection acting on SA alleles. A body of theory predicts the conditions under which sexually antagonistic mutants will invade and be maintained in stable polymorphism under balancing selection. There remains, however, considerable debate over the distribution of SA genetic variation across autosomes and sex chromosomes, with contradictory evidence coming from data and theory. In this article, we investigate how the interplay between selection and genetic drift will affect the genomic distribution of sexually antagonistic alleles. The effective population sizes can differ between the autosomes and the sex chromosomes due to a number of ecological factors and, consequently, the distribution of SA genetic variation in genomes. In general, we predict the interplay of SA selection and genetic drift should lead to the accumulation of SA alleles on the X in male heterogametic (XY) species and, on the autosomes in female heterogametic (ZW) species, especially when sexual competition is strong among males. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landrace and cultivars

USDA-ARS?s Scientific Manuscript database

Domesticated crops have experienced strong human-driven selection aimed at the development of improved varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated DNA m...

Genome-enabled selection doubles the accuracy of predicted breeding values for bacterial cold water disease resistance compared to traditional family-based selection in rainbow trout aquaculture

USDA-ARS?s Scientific Manuscript database

We have shown previously that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. Genomic selection (GS) is a new alternative enabling exploitation...

Role of genomics and transcriptomics in selection of reintroduction source populations.

PubMed

He, Xiaoping; Johansson, Mattias L; Heath, Daniel D

2016-10-01

The use and importance of reintroduction as a conservation tool to return a species to its historical range from which it has been extirpated will increase as climate change and human development accelerate habitat loss and population extinctions. Although the number of reintroduction attempts has increased rapidly over the past 2 decades, the success rate is generally low. As a result of population differences in fitness-related traits and divergent responses to environmental stresses, population performance upon reintroduction is highly variable, and it is generally agreed that selecting an appropriate source population is a critical component of a successful reintroduction. Conservation genomics is an emerging field that addresses long-standing challenges in conservation, and the potential for using novel molecular genetic approaches to inform and improve conservation efforts is high. Because the successful establishment and persistence of reintroduced populations is highly dependent on the functional genetic variation and environmental stress tolerance of the source population, we propose the application of conservation genomics and transcriptomics to guide reintroduction practices. Specifically, we propose using genome-wide functional loci to estimate genetic variation of source populations. This estimate can then be used to predict the potential for adaptation. We also propose using transcriptional profiling to measure the expression response of fitness-related genes to environmental stresses as a proxy for acclimation (tolerance) capacity. Appropriate application of conservation genomics and transcriptomics has the potential to dramatically enhance reintroduction success in a time of rapidly declining biodiversity and accelerating environmental change. © 2016 Society for Conservation Biology.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP

DETECTING SELECTION IN NATURAL POPULATIONS: MAKING SENSE OF GENOME SCANS AND TOWARDS ALTERNATIVE SOLUTIONS

PubMed Central

Haasl, Ryan J.; Payseur, Bret A.

2016-01-01

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example FST, cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach. PMID:26224644

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

The variable genomic architecture of isolation between hybridizing species of house mice.

PubMed

Teeter, Katherine C; Thibodeau, Lisa M; Gompert, Zachariah; Buerkle, C Alex; Nachman, Michael W; Tucker, Priscilla K

2010-02-01

Studies of the genetics of hybrid zones can provide insight into the genomic architecture of species boundaries. By examining patterns of introgression of multiple loci across a hybrid zone, it may be possible to identify regions of the genome that have experienced selection. Here, we present a comparison of introgression in two replicate transects through the house mouse hybrid zone through central Europe, using data from 41 single nucleotide markers. Using both genomic and geographic clines, we found many differences in patterns of introgression between the two transects, as well as some similarities. We found that many loci may have experienced the effects of selection at linked sites, including selection against hybrid genotypes, as well as positive selection in the form of genotypes introgressed into a foreign genetic background. We also found many positive associations of conspecific alleles among unlinked markers, which could be caused by epistatic interactions. Different patterns of introgression in the two transects highlight the challenge of using hybrid zones to identify genes underlying isolation and raise the possibility that the genetic basis of isolation between these species may be dependent on the local population genetic make-up or the local ecological setting.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Genome-wide scan of 29,141 African Americans finds no evidence of directional selection since admixture.

PubMed

Bhatia, Gaurav; Tandon, Arti; Patterson, Nick; Aldrich, Melinda C; Ambrosone, Christine B; Amos, Christopher; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Bock, Cathryn H; Caporaso, Neil; Casey, Graham; Deming, Sandra L; Diver, W Ryan; Gapstur, Susan M; Gillanders, Elizabeth M; Harris, Curtis C; Henderson, Brian E; Ingles, Sue A; Isaacs, William; De Jager, Phillip L; John, Esther M; Kittles, Rick A; Larkin, Emma; McNeill, Lorna H; Millikan, Robert C; Murphy, Adam; Neslund-Dudas, Christine; Nyante, Sarah; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Benjamin A; Schwartz, Ann G; Signorello, Lisa B; Spitz, Margaret; Strom, Sara S; Tucker, Margaret A; Wiencke, John K; Witte, John S; Wu, Xifeng; Yamamura, Yuko; Zanetti, Krista A; Zheng, Wei; Ziegler, Regina G; Chanock, Stephen J; Haiman, Christopher A; Reich, David; Price, Alkes L

2014-10-02

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study's conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Population genomics of the honey bee reveals strong signatures of positive selection on worker traits.

PubMed

Harpur, Brock A; Kent, Clement F; Molodtsova, Daria; Lebon, Jonathan M D; Alqarni, Abdulaziz S; Owayss, Ayman A; Zayed, Amro

2014-02-18

Most theories used to explain the evolution of eusociality rest upon two key assumptions: mutations affecting the phenotype of sterile workers evolve by positive selection if the resulting traits benefit fertile kin, and that worker traits provide the primary mechanism allowing social insects to adapt to their environment. Despite the common view that positive selection drives phenotypic evolution of workers, we know very little about the prevalence of positive selection acting on the genomes of eusocial insects. We mapped the footprints of positive selection in Apis mellifera through analysis of 40 individual genomes, allowing us to identify thousands of genes and regulatory sequences with signatures of adaptive evolution over multiple timescales. We found Apoidea- and Apis-specific genes to be enriched for signatures of positive selection, indicating that novel genes play a disproportionately large role in adaptive evolution of eusocial insects. Worker-biased proteins have higher signatures of adaptive evolution relative to queen-biased proteins, supporting the view that worker traits are key to adaptation. We also found genes regulating worker division of labor to be enriched for signs of positive selection. Finally, genes associated with worker behavior based on analysis of brain gene expression were highly enriched for adaptive protein and cis-regulatory evolution. Our study highlights the significant contribution of worker phenotypes to adaptive evolution in social insects, and provides a wealth of knowledge on the loci that influence fitness in honey bees.

Population genomics of the honey bee reveals strong signatures of positive selection on worker traits

PubMed Central

Harpur, Brock A.; Kent, Clement F.; Molodtsova, Daria; Lebon, Jonathan M. D.; Alqarni, Abdulaziz S.; Owayss, Ayman A.; Zayed, Amro

2014-01-01

Most theories used to explain the evolution of eusociality rest upon two key assumptions: mutations affecting the phenotype of sterile workers evolve by positive selection if the resulting traits benefit fertile kin, and that worker traits provide the primary mechanism allowing social insects to adapt to their environment. Despite the common view that positive selection drives phenotypic evolution of workers, we know very little about the prevalence of positive selection acting on the genomes of eusocial insects. We mapped the footprints of positive selection in Apis mellifera through analysis of 40 individual genomes, allowing us to identify thousands of genes and regulatory sequences with signatures of adaptive evolution over multiple timescales. We found Apoidea- and Apis-specific genes to be enriched for signatures of positive selection, indicating that novel genes play a disproportionately large role in adaptive evolution of eusocial insects. Worker-biased proteins have higher signatures of adaptive evolution relative to queen-biased proteins, supporting the view that worker traits are key to adaptation. We also found genes regulating worker division of labor to be enriched for signs of positive selection. Finally, genes associated with worker behavior based on analysis of brain gene expression were highly enriched for adaptive protein and cis-regulatory evolution. Our study highlights the significant contribution of worker phenotypes to adaptive evolution in social insects, and provides a wealth of knowledge on the loci that influence fitness in honey bees. PMID:24488971

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

PubMed

Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin

2015-01-01

Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed. We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study. Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Whole-Genome Resequencing of Experimental Populations Reveals Polygenic Basis of Egg-Size Variation in Drosophila melanogaster.

PubMed

Jha, Aashish R; Miles, Cecelia M; Lippert, Nodia R; Brown, Christopher D; White, Kevin P; Kreitman, Martin

2015-10-01

Complete genome resequencing of populations holds great promise in deconstructing complex polygenic traits to elucidate molecular and developmental mechanisms of adaptation. Egg size is a classic adaptive trait in insects, birds, and other taxa, but its highly polygenic architecture has prevented high-resolution genetic analysis. We used replicated experimental evolution in Drosophila melanogaster and whole-genome sequencing to identify consistent signatures of polygenic egg-size adaptation. A generalized linear-mixed model revealed reproducible allele frequency differences between replicated experimental populations selected for large and small egg volumes at approximately 4,000 single nucleotide polymorphisms (SNPs). Several hundred distinct genomic regions contain clusters of these SNPs and have lower heterozygosity than the genomic background, consistent with selection acting on polymorphisms in these regions. These SNPs are also enriched among genes expressed in Drosophila ovaries and many of these genes have well-defined functions in Drosophila oogenesis. Additional genes regulating egg development, growth, and cell size show evidence of directional selection as genes regulating these biological processes are enriched for highly differentiated SNPs. Genetic crosses performed with a subset of candidate genes demonstrated that these genes influence egg size, at least in the large genetic background. These findings confirm the highly polygenic architecture of this adaptive trait, and suggest the involvement of many novel candidate genes in regulating egg size. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Inter- and intra-specific pan-genomes of Borrelia burgdorferi sensu lato: genome stability and adaptive radiation

PubMed Central

2013-01-01

Background Lyme disease is caused by spirochete bacteria from the Borrelia burgdorferi sensu lato (B. burgdorferi s.l.) species complex. To reconstruct the evolution of B. burgdorferi s.l. and identify the genomic basis of its human virulence, we compared the genomes of 23 B. burgdorferi s.l. isolates from Europe and the United States, including B. burgdorferi sensu stricto (B. burgdorferi s.s., 14 isolates), B. afzelii (2), B. garinii (2), B. “bavariensis” (1), B. spielmanii (1), B. valaisiana (1), B. bissettii (1), and B. “finlandensis” (1). Results Robust B. burgdorferi s.s. and B. burgdorferi s.l. phylogenies were obtained using genome-wide single-nucleotide polymorphisms, despite recombination. Phylogeny-based pan-genome analysis showed that the rate of gene acquisition was higher between species than within species, suggesting adaptive speciation. Strong positive natural selection drives the sequence evolution of lipoproteins, including chromosomally-encoded genes 0102 and 0404, cp26-encoded ospC and b08, and lp54-encoded dbpA, a07, a22, a33, a53, a65. Computer simulations predicted rapid adaptive radiation of genomic groups as population size increases. Conclusions Intra- and inter-specific pan-genome sizes of B. burgdorferi s.l. expand linearly with phylogenetic diversity. Yet gene-acquisition rates in B. burgdorferi s.l. are among the lowest in bacterial pathogens, resulting in high genome stability and few lineage-specific genes. Genome adaptation of B. burgdorferi s.l. is driven predominantly by copy-number and sequence variations of lipoprotein genes. New genomic groups are likely to emerge if the current trend of B. burgdorferi s.l. population expansion continues. PMID:24112474

Genome-Wide Identification of Regulatory Sequences Undergoing Accelerated Evolution in the Human Genome

PubMed Central

Dong, Xinran; Wang, Xiao; Zhang, Feng; Tian, Weidong

2016-01-01

Accelerated evolution of regulatory sequence can alter the expression pattern of target genes, and cause phenotypic changes. In this study, we used DNase I hypersensitive sites (DHSs) to annotate putative regulatory sequences in the human genome, and conducted a genome-wide analysis of the effects of accelerated evolution on regulatory sequences. Working under the assumption that local ancient repeat elements of DHSs are under neutral evolution, we discovered that ∼0.44% of DHSs are under accelerated evolution (ace-DHSs). We found that ace-DHSs tend to be more active than background DHSs, and are strongly associated with epigenetic marks of active transcription. The target genes of ace-DHSs are significantly enriched in neuron-related functions, and their expression levels are positively selected in the human brain. Thus, these lines of evidences strongly suggest that accelerated evolution on regulatory sequences plays important role in the evolution of human-specific phenotypes. PMID:27401230

A genomic survey of the fish parasite Spironucleus salmonicida indicates genomic plasticity among diplomonads and significant lateral gene transfer in eukaryote genome evolution

PubMed Central

Andersson, Jan O; Sjögren, Åsa M; Horner, David S; Murphy, Colleen A; Dyal, Patricia L; Svärd, Staffan G; Logsdon, John M; Ragan, Mark A; Hirt, Robert P; Roger, Andrew J

2007-01-01

Background Comparative genomic studies of the mitochondrion-lacking protist group Diplomonadida (diplomonads) has been lacking, although Giardia lamblia has been intensively studied. We have performed a sequence survey project resulting in 2341 expressed sequence tags (EST) corresponding to 853 unique clones, 5275 genome survey sequences (GSS), and eleven finished contigs from the diplomonad fish parasite Spironucleus salmonicida (previously described as S. barkhanus). Results The analyses revealed a compact genome with few, if any, introns and very short 3' untranslated regions. Strikingly different patterns of codon usage were observed in genes corresponding to frequently sampled ESTs versus genes poorly sampled, indicating that translational selection is influencing the codon usage of highly expressed genes. Rigorous phylogenomic analyses identified 84 genes – mostly encoding metabolic proteins – that have been acquired by diplomonads or their relatively close ancestors via lateral gene transfer (LGT). Although most acquisitions were from prokaryotes, more than a dozen represent likely transfers of genes between eukaryotic lineages. Many genes that provide novel insights into the genetic basis of the biology and pathogenicity of this parasitic protist were identified including 149 that putatively encode variant-surface cysteine-rich proteins which are candidate virulence factors. A number of genomic properties that distinguish S. salmonicida from its human parasitic relative G. lamblia were identified such as nineteen putative lineage-specific gene acquisitions, distinct mutational biases and codon usage and distinct polyadenylation signals. Conclusion Our results highlight the power of comparative genomic studies to yield insights into the biology of parasitic protists and the evolution of their genomes, and suggest that genetic exchange between distantly-related protist lineages may be occurring at an appreciable rate in eukaryote genome evolution. PMID

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

PubMed

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

Genomic insights into natural selection in the common loon (Gavia immer): evidence for aquatic adaptation.

PubMed

Gayk, Zach G; Le Duc, Diana; Horn, Jeffrey; Lindsay, Alec R

2018-04-27

The common loon (Gavia immer) is one of five species that comprise the avian order Gaviiformes. Loons are specialized divers, reaching depths up to 60 m while staying submerged for intervals up to three minutes. In this study we used comparative genomics to investigate the genetic basis of the common loon adaptations to its ecological niche. We used Illumina short read DNA sequence data from a female bird to produce a draft assembly of the common loon (Gavia immer) genome. We identified 14,169 common loon genes, which based on well-resolved avian genomes, represent approximately 80.7% of common loon genes. Evolutionary analyses between common loon and Adelie penguin (Pygoscelis adeliae), red-throated loon (Gavia stellata), chicken (Gallus gallus), northern fulmar (Fulmarus glacialis), and rock pigeon (Columba livia) show 164 positively selected genes in common and red-throated loons. These genes were enriched for a number of protein classes, including those involved in muscle tissue development, immunoglobulin function, hemoglobin iron binding, G-protein coupled receptors, and ATP metabolism. Signatures of positive selection in these areas suggest the genus Gavia may have adapted for underwater diving by modulating their oxidative and metabolic pathways. While more research is required, these adaptations likely result in (1) compensations in oxygen respiration and energetic metabolism, (2) low-light visual acuity, and (3) elevated solute exchange. This work represents the first effort to understand the genomic adaptations of the common loon as well as other Gavia and may have implications for subsequent studies that target particular genes for loon population genetic, ecological or conservation studies.

Lignin-degrading Peroxidases from Genome of Selective Ligninolytic Fungus Ceriporiopsis subvermispora*

PubMed Central

Fernández-Fueyo, Elena; Ruiz-Dueñas, Francisco J.; Miki, Yuta; Martínez, María Jesús; Hammel, Kenneth E.; Martínez, Angel T.

2012-01-01

The white-rot fungus Ceriporiopsis subvermispora delignifies lignocellulose with high selectivity, but until now it has appeared to lack the specialized peroxidases, termed lignin peroxidases (LiPs) and versatile peroxidases (VPs), that are generally thought important for ligninolysis. We screened the recently sequenced C. subvermispora genome for genes that encode peroxidases with a potential ligninolytic role. A total of 26 peroxidase genes was apparent after a structural-functional classification based on homology modeling and a search for diagnostic catalytic amino acid residues. In addition to revealing the presence of nine heme-thiolate peroxidase superfamily members and the unexpected absence of the dye-decolorizing peroxidase superfamily, the search showed that the C. subvermispora genome encodes 16 class II enzymes in the plant-fungal-bacterial peroxidase superfamily, where LiPs and VPs are classified. The 16 encoded enzymes include 13 putative manganese peroxidases and one generic peroxidase but most notably two peroxidases containing the catalytic tryptophan characteristic of LiPs and VPs. We expressed these two enzymes in Escherichia coli and determined their substrate specificities on typical LiP/VP substrates, including nonphenolic lignin model monomers and dimers, as well as synthetic lignin. The results show that the two newly discovered C. subvermispora peroxidases are functionally competent LiPs and also suggest that they are phylogenetically and catalytically intermediate between classical LiPs and VPs. These results offer new insight into selective lignin degradation by C. subvermispora. PMID:22437835

Balancing selection maintains cryptic colour morphs.

PubMed

Wellenreuther, Maren

2017-11-01

Animals display incredibly diverse colour patterns, a testament to evolution's endless innovation in shaping life. In many species, the interplay between males and females in the pursuit of mates has driven the evolution of a myriad of colour forms, from the flashy peacock tail feathers to the tiniest colour markings in damselflies. In others, colour provides crypsis by allowing to blend into the background and to escape the eyes of predators. While the obvious benefits of this dazzling diversity for reproduction and survival seem straightforward, its maintenance is not. Theory predicts that genetic drift and various forms of selection reduce variation over time, making the persistence of colour variants over generations a puzzle. In this issue of Molecular Ecology, Lindtke et al. () study the cryptic colour morphs of Timema cristinae walking sticks to shed light on the genetic architecture and mechanisms that allow colour polymorphism maintenance over long timescales. By combining genome-wide data with phenotyping information from natural populations, they were able to map the green and melanistic colour to one genomic region with highly reduced effective recombination rate between two main chromosomal variants, consistent with an inversion polymorphism. These two main chromosomal variants showed geographically widespread heterozygote excess, and genomic signatures consistent with long-term balancing selection. A younger chromosomal variant was detected for the third morph, the green-striped colour morphs, in the same genomic regions as the melanistic and the green-unstriped morphs. Together, these results suggest that the genetic architecture of cryptic T. cristinae morphs is caused by nonrecombining genomic blocks that have been maintained over extended time periods by balancing selection making this study one of the few available empirical examples documenting that balancing selection of various forms may play an important role in maintaining adaptive genetic

Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions

USDA-ARS?s Scientific Manuscript database

Genome signatures of artificial selection in U.S. Jersey cattle were identified by examining changes in haplotype homozygosity for a resource population of animals born between 1962 and 2005. Genetic merit of this population changed dramatically during this period for a number of traits, especially ...

Exploring evidence of positive selection reveals genetic basis of meat quality traits in Berkshire pigs through whole genome sequencing.

PubMed

Jeong, Hyeonsoo; Song, Ki-Duk; Seo, Minseok; Caetano-Anollés, Kelsey; Kim, Jaemin; Kwak, Woori; Oh, Jae-Don; Kim, EuiSoo; Jeong, Dong Kee; Cho, Seoae; Kim, Heebal; Lee, Hak-Kyo

2015-08-20

Natural and artificial selection following domestication has led to the existence of more than a hundred pig breeds, as well as incredible variation in phenotypic traits. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Here we investigate the relationship between genomic composition and this phenotypic trait by scanning for signatures of positive selection in whole-genome sequencing data. We generated genomes of 10 Berkshire pigs at a total of 100.6 coverage depth, using the Illumina Hiseq2000 platform. Along with the genomes of 11 Landrace and 13 Yorkshire pigs, we identified genomic variants of 18.9 million SNVs and 3.4 million Indels in the mapped regions. We identified several associated genes related to lipid metabolism, intramuscular fatty acid deposition, and muscle fiber type which attribute to pork quality (TG, FABP1, AKIRIN2, GLP2R, TGFBR3, JPH3, ICAM2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR). A statistical enrichment test was also conducted to detect breed specific genetic variation. In addition, de novo short sequence read assembly strategy identified several candidate genes (SLC25A14, IGF1, PI4KA, CACNA1A) as also contributing to lipid metabolism. Results revealed several candidate genes involved in Berkshire meat quality; most of these genes are involved in lipid metabolism and intramuscular fat deposition. These results can provide a basis for future research on the genomic characteristics of Berkshire pigs.

Genetic diversity and genomic signatures of selection among cattle breeds from Siberia, eastern and northern Europe.

PubMed

Iso-Touru, T; Tapio, M; Vilkki, J; Kiseleva, T; Ammosov, I; Ivanova, Z; Popov, R; Ozerov, M; Kantanen, J

2016-12-01

Domestication in the near eastern region had a major impact on the gene pool of humpless taurine cattle (Bos taurus). As a result of subsequent natural and artificial selection, hundreds of different breeds have evolved, displaying a broad range of phenotypic traits. Here, 10 Eurasian B. taurus breeds from different biogeographic and production conditions, which exhibit different demographic histories and have been under artificial selection at various intensities, were investigated using the Illumina BovineSNP50 panel to understand their genetic diversity and population structure. In addition, we scanned genomes from eight breeds for signatures of diversifying selection. Our population structure analysis indicated six distinct breed groups, the most divergent being the Yakutian cattle from Siberia. Selection signals were shared (experimental P-value < 0.01) with more than four breeds on chromosomes 6, 7, 13, 16 and 22. The strongest selection signals in the Yakutian cattle were found on chromosomes 7 and 21, where a miRNA gene and genes related to immune system processes are respectively located. In general, genomic regions indicating selection overlapped with known QTL associated with milk production (e.g. on chromosome 19), reproduction (e.g. on chromosome 24) and meat quality (e.g. on chromosome 7). The selection map created in this study shows that native cattle breeds and their genetic resources represent unique material for future breeding. © 2016 Stichting International Foundation for Animal Genetics.

Genome-wide detection and characterization of positive selection in human populations.

PubMed

Sabeti, Pardis C; Varilly, Patrick; Fry, Ben; Lohmueller, Jason; Hostetter, Elizabeth; Cotsapas, Chris; Xie, Xiaohui; Byrne, Elizabeth H; McCarroll, Steven A; Gaudet, Rachelle; Schaffner, Stephen F; Lander, Eric S; Frazer, Kelly A; Ballinger, Dennis G; Cox, David R; Hinds, David A; Stuve, Laura L; Gibbs, Richard A; Belmont, John W; Boudreau, Andrew; Hardenbol, Paul; Leal, Suzanne M; Pasternak, Shiran; Wheeler, David A; Willis, Thomas D; Yu, Fuli; Yang, Huanming; Zeng, Changqing; Gao, Yang; Hu, Haoran; Hu, Weitao; Li, Chaohua; Lin, Wei; Liu, Siqi; Pan, Hao; Tang, Xiaoli; Wang, Jian; Wang, Wei; Yu, Jun; Zhang, Bo; Zhang, Qingrun; Zhao, Hongbin; Zhao, Hui; Zhou, Jun; Gabriel, Stacey B; Barry, Rachel; Blumenstiel, Brendan; Camargo, Amy; Defelice, Matthew; Faggart, Maura; Goyette, Mary; Gupta, Supriya; Moore, Jamie; Nguyen, Huy; Onofrio, Robert C; Parkin, Melissa; Roy, Jessica; Stahl, Erich; Winchester, Ellen; Ziaugra, Liuda; Altshuler, David; Shen, Yan; Yao, Zhijian; Huang, Wei; Chu, Xun; He, Yungang; Jin, Li; Liu, Yangfan; Shen, Yayun; Sun, Weiwei; Wang, Haifeng; Wang, Yi; Wang, Ying; Xiong, Xiaoyan; Xu, Liang; Waye, Mary M Y; Tsui, Stephen K W; Xue, Hong; Wong, J Tze-Fei; Galver, Luana M; Fan, Jian-Bing; Gunderson, Kevin; Murray, Sarah S; Oliphant, Arnold R; Chee, Mark S; Montpetit, Alexandre; Chagnon, Fanny; Ferretti, Vincent; Leboeuf, Martin; Olivier, Jean-François; Phillips, Michael S; Roumy, Stéphanie; Sallée, Clémentine; Verner, Andrei; Hudson, Thomas J; Kwok, Pui-Yan; Cai, Dongmei; Koboldt, Daniel C; Miller, Raymond D; Pawlikowska, Ludmila; Taillon-Miller, Patricia; Xiao, Ming; Tsui, Lap-Chee; Mak, William; Song, You Qiang; Tam, Paul K H; Nakamura, Yusuke; Kawaguchi, Takahisa; Kitamoto, Takuya; Morizono, Takashi; Nagashima, Atsushi; Ohnishi, Yozo; Sekine, Akihiro; Tanaka, Toshihiro; Tsunoda, Tatsuhiko; Deloukas, Panos; Bird, Christine P; Delgado, Marcos; Dermitzakis, Emmanouil T; Gwilliam, Rhian; Hunt, Sarah; Morrison, Jonathan; Powell, Don; Stranger, Barbara E; Whittaker, Pamela; Bentley, David R; Daly, Mark J; de Bakker, Paul I W; Barrett, Jeff; Chretien, Yves R; Maller, Julian; McCarroll, Steve; Patterson, Nick; Pe'er, Itsik; Price, Alkes; Purcell, Shaun; Richter, Daniel J; Sabeti, Pardis; Saxena, Richa; Schaffner, Stephen F; Sham, Pak C; Varilly, Patrick; Altshuler, David; Stein, Lincoln D; Krishnan, Lalitha; Smith, Albert Vernon; Tello-Ruiz, Marcela K; Thorisson, Gudmundur A; Chakravarti, Aravinda; Chen, Peter E; Cutler, David J; Kashuk, Carl S; Lin, Shin; Abecasis, Gonçalo R; Guan, Weihua; Li, Yun; Munro, Heather M; Qin, Zhaohui Steve; Thomas, Daryl J; McVean, Gilean; Auton, Adam; Bottolo, Leonardo; Cardin, Niall; Eyheramendy, Susana; Freeman, Colin; Marchini, Jonathan; Myers, Simon; Spencer, Chris; Stephens, Matthew; Donnelly, Peter; Cardon, Lon R; Clarke, Geraldine; Evans, David M; Morris, Andrew P; Weir, Bruce S; Tsunoda, Tatsuhiko; Johnson, Todd A; Mullikin, James C; Sherry, Stephen T; Feolo, Michael; Skol, Andrew; Zhang, Houcan; Zeng, Changqing; Zhao, Hui; Matsuda, Ichiro; Fukushima, Yoshimitsu; Macer, Darryl R; Suda, Eiko; Rotimi, Charles N; Adebamowo, Clement A; Ajayi, Ike; Aniagwu, Toyin; Marshall, Patricia A; Nkwodimmah, Chibuzor; Royal, Charmaine D M; Leppert, Mark F; Dixon, Missy; Peiffer, Andy; Qiu, Renzong; Kent, Alastair; Kato, Kazuto; Niikawa, Norio; Adewole, Isaac F; Knoppers, Bartha M; Foster, Morris W; Clayton, Ellen Wright; Watkin, Jessica; Gibbs, Richard A; Belmont, John W; Muzny, Donna; Nazareth, Lynne; Sodergren, Erica; Weinstock, George M; Wheeler, David A; Yakub, Imtaz; Gabriel, Stacey B; Onofrio, Robert C; Richter, Daniel J; Ziaugra, Liuda; Birren, Bruce W; Daly, Mark J; Altshuler, David; Wilson, Richard K; Fulton, Lucinda L; Rogers, Jane; Burton, John; Carter, Nigel P; Clee, Christopher M; Griffiths, Mark; Jones, Matthew C; McLay, Kirsten; Plumb, Robert W; Ross, Mark T; Sims, Sarah K; Willey, David L; Chen, Zhu; Han, Hua; Kang, Le; Godbout, Martin; Wallenburg, John C; L'Archevêque, Paul; Bellemare, Guy; Saeki, Koji; Wang, Hongguang; An, Daochang; Fu, Hongbo; Li, Qing; Wang, Zhen; Wang, Renwu; Holden, Arthur L; Brooks, Lisa D; McEwen, Jean E; Guyer, Mark S; Wang, Vivian Ota; Peterson, Jane L; Shi, Michael; Spiegel, Jack; Sung, Lawrence M; Zacharia, Lynn F; Collins, Francis S; Kennedy, Karen; Jamieson, Ruth; Stewart, John

2007-10-18

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.

A strongly selected mutation in the HIV-1 genome is independent of T cell responses and neutralizing antibodies

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

Liu, Donglai; Wang, Chu; Hora, Bhavna

Mutations rapidly accumulate in the HIV-1 genome after infection. Some of those mutations are selected by host immune responses and often cause viral fitness losses. This study is to investigate whether strongly selected mutations that are not associated with immune responses result in fitness losses. Strongly selected mutations were identified by analyzing 5'-half HIV-1 genome (gag/pol) sequences from longitudinal samples of subject CH0131. The K43R mutation in the gag gene was first detected at day 91 post screening and was fixed in the viral population at day 273 while the synonymous N323tc mutation was first detected at day 177 andmore » fixed at day 670. No conventional or cryptic T cell responses were detected against either mutation sites by ELISpot analysis. However, when fitness costs of both mutations were measured by introducing each mutation into their cognate transmitted/founder (T/F) viral genome, the K43R mutation caused a significant fitness loss while the N323tc mutation had little impact on viral fitness. In conclusion, the rapid fixation, the lack of detectable immune responses and the significant fitness cost of the K43R mutation suggests that it was strongly selected by host factors other than T cell responses and neutralizing antibodies.« less

A strongly selected mutation in the HIV-1 genome is independent of T cell responses and neutralizing antibodies

DOE PAGES

Liu, Donglai; Wang, Chu; Hora, Bhavna; ...

2017-10-10

Mutations rapidly accumulate in the HIV-1 genome after infection. Some of those mutations are selected by host immune responses and often cause viral fitness losses. This study is to investigate whether strongly selected mutations that are not associated with immune responses result in fitness losses. Strongly selected mutations were identified by analyzing 5'-half HIV-1 genome (gag/pol) sequences from longitudinal samples of subject CH0131. The K43R mutation in the gag gene was first detected at day 91 post screening and was fixed in the viral population at day 273 while the synonymous N323tc mutation was first detected at day 177 andmore » fixed at day 670. No conventional or cryptic T cell responses were detected against either mutation sites by ELISpot analysis. However, when fitness costs of both mutations were measured by introducing each mutation into their cognate transmitted/founder (T/F) viral genome, the K43R mutation caused a significant fitness loss while the N323tc mutation had little impact on viral fitness. In conclusion, the rapid fixation, the lack of detectable immune responses and the significant fitness cost of the K43R mutation suggests that it was strongly selected by host factors other than T cell responses and neutralizing antibodies.« less