DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

PubMed

Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

2013-07-01

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Maternal genetic effects on adaptive divergence between anadromous and resident brook charr during early life history.

PubMed

Perry, G M L; Audet, C; Bernatchez, L

2005-09-01

The importance of directional selection relative to neutral evolution may be determined by comparing quantitative genetic variation in phenotype (Q(ST)) to variation at neutral molecular markers (F(ST)). Quantitative divergence between salmonid life history types is often considerable, but ontogenetic changes in the significance of major sources of genetic variance during post-hatch development suggest that selective differentiation varies by developmental stage. In this study, we tested the hypothesis that maternal genetic differentiation between anadromous and resident brook charr (Salvelinus fontinalis Mitchill) populations for early quantitative traits (embryonic size/growth, survival, egg number and developmental time) would be greater than neutral genetic differentiation, but that the maternal genetic basis for differentiation would be higher for pre-resorption traits than post-resorption traits. Quantitative genetic divergence between anadromous (seawater migratory) and resident Laval River (Québec) brook charr based on maternal genetic variance was high (Q(ST) > 0.4) for embryonic length, yolk sac volume, embryonic growth rate and time to first response to feeding relative to neutral genetic differentiation [F(ST) = 0.153 (0.071-0.214)], with anadromous females having positive genetic coefficients for all of the above characters. However, Q(ST) was essentially zero for all traits post-resorption of the yolk sac. Our results indicate that the observed divergence between resident and anadromous brook charr has been driven by directional selection, and may therefore be adaptive. Moreover, they provide among the first evidence that the relative importance of selective differentiation may be highly context-specific, and varies by genetic contributions to phenotype by parental sex at specific points in offspring ontogeny. This in turn suggests that interpretations of Q(ST)-F(ST) comparisons may be improved by considering the structure of quantitative genetic architecture by age category and the sex of the parent used in estimation.

Study books on ADHD genetics: balanced or biased?

PubMed

Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-06-01

Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

Treesearch

Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

2005-01-01

Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

[The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

PubMed

Wang, Hai-yan

2015-08-01

The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

Modelling the co-evolution of indirect genetic effects and inherited variability.

PubMed

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of IGEs and variability, as the regression coefficient can respond to selection. Our simulations show that the model results in increased variability of body weight with increasing competition. When competition decreases, i.e., cooperation evolves, variability becomes significantly smaller. Hence, our model facilitates quantitative genetic studies on the relationship between IGEs and inherited variability. Moreover, our findings suggest that we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.

Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Learning abilities and disabilities: generalist genes in early adolescence.

PubMed

Davis, Oliver S P; Haworth, Claire M A; Plomin, Robert

2009-01-01

The new view of cognitive neuropsychology that considers not just case studies of rare severe disorders but also common disorders, as well as normal variation and quantitative traits, is more amenable to recent advances in molecular genetics, such as genome-wide association studies, and advances in quantitative genetics, such as multivariate genetic analysis. A surprising finding emerging from multivariate quantitative genetic studies across diverse learning abilities is that most genetic influences are shared: they are "generalist", rather than "specialist". We exploited widespread access to inexpensive and fast Internet connections in the United Kingdom to assess over 5000 pairs of 12-year-old twins from the Twins Early Development Study (TEDS) on four distinct batteries: reading, mathematics, general cognitive ability (g) and, for the first time, language. Genetic correlations remain high among all of the measured abilities, with language as highly correlated genetically with g as reading and mathematics. Despite developmental upheaval, generalist genes remain important into early adolescence, suggesting optimal strategies for molecular genetic studies seeking to identify the genes of small effect that influence learning abilities and disabilities.

Study books on ADHD genetics: balanced or biased?

PubMed Central

te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-01-01

ABSTRACT Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master’s programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics’ outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them. PMID:28532325

Rapid changes in genetic architecture of behavioural syndromes following colonization of a novel environment.

PubMed

Karlsson Green, K; Eroukhmanoff, F; Harris, S; Pettersson, L B; Svensson, E I

2016-01-01

Behavioural syndromes, that is correlated behaviours, may be a result from adaptive correlational selection, but in a new environmental setting, the trait correlation might act as an evolutionary constraint. However, knowledge about the quantitative genetic basis of behavioural syndromes, and the stability and evolvability of genetic correlations under different ecological conditions, is limited. We investigated the quantitative genetic basis of correlated behaviours in the freshwater isopod Asellus aquaticus. In some Swedish lakes, A. aquaticus has recently colonized a novel habitat and diverged into two ecotypes, presumably due to habitat-specific selection from predation. Using a common garden approach and animal model analyses, we estimated quantitative genetic parameters for behavioural traits and compared the genetic architecture between the ecotypes. We report that the genetic covariance structure of the behavioural traits has been altered in the novel ecotype, demonstrating divergence in behavioural correlations. Thus, our study confirms that genetic correlations behind behaviours can change rapidly in response to novel selective environments. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics

PubMed Central

Corwin, Jason A.; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J.

2016-01-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes. PMID:26866607

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

PubMed

Corwin, Jason A; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J

2016-02-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

[Study on once sampling quantitation based on information entropy of ISSR amplified bands of Houttuynia cordata].

PubMed

Wang, Haiqin; Liu, Wenlong; He, Fuyuan; Chen, Zuohong; Zhang, Xili; Xie, Xianggui; Zeng, Jiaoli; Duan, Xiaopeng

2012-02-01

To explore the once sampling quantitation of Houttuynia cordata through its DNA polymorphic bands that carried information entropy, from other form that the expression of traditional Chinese medicine polymorphism, genetic polymorphism, of traditional Chinese medicine. The technique of inter simple sequence repeat (ISSR) was applied to analyze genetic polymorphism of H. cordata samples from the same GAP producing area, the DNA genetic bands were transformed its into the information entropy, and the minimum once sampling quantitation with the mathematical mode was measured. One hundred and thirty-four DNA bands were obtained by using 9 screened ISSR primers to amplify from 46 strains DNA samples of H. cordata from the same GAP, the information entropy was H=0.365 6-0.978 6, and RSD was 14.75%. The once sampling quantitation was W=11.22 kg (863 strains). The "once minimum sampling quantitation" were calculated from the angle of the genetic polymorphism of H. cordata, and a great differences between this volume and the amount from the angle of fingerprint were found.

Quantitative genetic methods depending on the nature of the phenotypic trait.

PubMed

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

ERIC Educational Resources Information Center

Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

Universality and predictability in molecular quantitative genetics.

PubMed

Nourmohammad, Armita; Held, Torsten; Lässig, Michael

2013-12-01

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

Little effect of HSP90 inhibition on the quantitative wing traits variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2017-02-01

Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem.

PubMed

Xie, Weilong; Yu, Kangfu; Pauls, K Peter; Navabi, Alireza

2012-04-01

The effectiveness of image analysis (IA) compared with an ordinal visual scale, for quantitative measurement of disease severity, its application in quantitative genetic studies, and its effect on the estimates of genetic parameters were investigated. Studies were performed using eight backcross-derived families of common bean (Phaseolus vulgaris) (n = 172) segregating for the molecular marker SU91, known to be associated with a quantitative trait locus (QTL) for resistance to common bacterial blight (CBB), caused by Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans. Even though both IA and visual assessments were highly repeatable, IA was more sensitive in detecting quantitative differences between bean genotypes. The CBB phenotypic difference between the two SU91 genotypic groups was consistently more than fivefold for IA assessments but generally only two- to threefold for visual assessments. Results suggest that the visual assessment results in overestimation of the effect of QTL in genetic studies. This may have been caused by lack of additivity and uneven intervals of the visual scale. Although visual assessment of disease severity is a useful tool for general selection in breeding programs, assessments using IA may be more suitable for phenotypic evaluations in quantitative genetic studies involving CBB resistance as well as other foliar diseases.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Quantitative trait loci associated with anthracnose resistance in sorghum

USDA-ARS?s Scientific Manuscript database

With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

EPA Science Inventory

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

PubMed

Korolev, Kirill S; Xavier, João B; Nelson, David R; Foster, Kevin R

2011-10-01

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

Decay Of Bacterial Pathogens, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure-Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green...

Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

USDA-ARS?s Scientific Manuscript database

The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

Decay Of Bacterial Pathogen, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria, and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manre-amended agricultural soils. Known concentrations of transformed green fluore...

Comparison of genetic diversity and population structure of Pacific Coast whitebark pine across multiple markers

Treesearch

Andrew D. Bower; Bryce A. Richardson; Valerie Hipkins; Regina Rochefort; Carol Aubry

2011-01-01

Analysis of "neutral" molecular markers and "adaptive" quantitative traits are common methods of assessing genetic diversity and population structure. Molecular markers typically reflect the effects of demographic and stochastic processes but are generally assumed to not reflect natural selection. Conversely, quantitative (or "adaptive")...

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Real-time quantitative polymerase chain reaction methods for four genetically modified maize varieties and maize DNA content in food.

PubMed

Brodmann, Peter D; Ilg, Evelyn C; Berthoud, Hélène; Herrmann, Andre

2002-01-01

Quantitative detection methods are needed for enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients. This labeling threshold, which is set to 1% in the European Union and Switzerland, must be applied to all approved GMOs. Four different varieties of maize are approved in the European Union: the insect-resistant Bt176 maize (Maximizer), Btl 1 maize, Mon810 (YieldGard) maize, and the herbicide-tolerant T25 (Liberty Link) maize. Because the labeling must be considered individually for each ingredient, a quantitation system for the endogenous maize content is needed in addition to the GMO-specific detection systems. Quantitative real-time polymerase chain reaction detection methods were developed for the 4 approved genetically modified maize varieties and for an endogenous maize (invertase) gene system.

Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

PubMed

Santure, Anna W; Spencer, Hamish G

2006-08-01

The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

PubMed

Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

2014-06-01

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

On the reconciliation of missing heritability for genome-wide association studies

PubMed Central

Chen, Guo-Bo

2016-01-01

The definition of heritability has been unique and clear, but its estimation and estimates vary across studies. Linear mixed model (LMM) and Haseman–Elston (HE) regression analyses are commonly used for estimating heritability from genome-wide association data. This study provides an analytical resolution that can be used to reconcile the differences between LMM and HE in the estimation of heritability given the genetic architecture, which is responsible for these differences. The genetic architecture was classified into three forms via thought experiments: (i) coupling genetic architecture that the quantitative trait loci (QTLs) in the linkage disequilibrium (LD) had a positive covariance; (ii) repulsion genetic architecture that the QTLs in the LD had a negative covariance; (iii) and neutral genetic architecture that the QTLs in the LD had a covariance with a summation of zero. The neutral genetic architecture is so far most embraced, whereas the coupling and the repulsion genetic architecture have not been well investigated. For a quantitative trait under the coupling genetic architecture, HE overestimated the heritability and LMM underestimated the heritability; under the repulsion genetic architecture, HE underestimated but LMM overestimated the heritability for a quantitative trait. These two methods gave identical results under the neutral genetic architecture. A general analytical result for the statistic estimated under HE is given regardless of genetic architecture. In contrast, the performance of LMM remained elusive, such as further depended on the ratio between the sample size and the number of markers, but LMM converged to HE with increased sample size. PMID:27436266

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

PubMed Central

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L.; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-01-01

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. PMID:28325812

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

PubMed

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-05-05

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.

Multi-ethnic meta-analysis identifies RAI1 as a possible obstructive sleep apnea related quantitative trait locus in men

USDA-ARS?s Scientific Manuscript database

Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single et...

Quantitative genetics of disease traits.

PubMed

Wray, N R; Visscher, P M

2015-04-01

John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

Distribution of lod scores in oligogenic linkage analysis.

PubMed

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

Laboratory evolution of the migratory polymorphism in the sand cricket: combining physiology with quantitative genetics.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2007-01-01

Predicting evolutionary change is the central goal of evolutionary biology because it is the primary means by which we can test evolutionary hypotheses. In this article, we analyze the pattern of evolutionary change in a laboratory population of the wing-dimorphic sand cricket Gryllus firmus resulting from relaxation of selection favoring the migratory (long-winged) morph. Based on a well-characterized trade-off between fecundity and flight capability, we predict that evolution in the laboratory environment should result in a reduction in the proportion of long-winged morphs. We also predict increased fecundity and reduced functionality and weight of the major flight muscles in long-winged females but little change in short-winged (flightless) females. Based on quantitative genetic theory, we predict that the regression equation describing the trade-off between ovary weight and weight of the major flight muscles will show a change in its intercept but not in its slope. Comparisons across generations verify all of these predictions. Further, using values of genetic parameters estimated from previous studies, we show that a quantitative genetic simulation model can account for not only the qualitative changes but also the evolutionary trajectory. These results demonstrate the power of combining quantitative genetic and physiological approaches for understanding the evolution of complex traits.

Behavioral and molecular studies of quantitative differences in hygienic behavior in honeybees.

PubMed

Gempe, Tanja; Stach, Silke; Bienefeld, Kaspar; Otte, Marianne; Beye, Martin

2016-10-21

Hygienic behavior (HB) enables honeybees to tolerate parasites, including infection with the parasitic mite Varroa destructor, and it is a well-known example of a quantitative genetic trait. The understanding of the molecular processes underpinning the quantitative differences in this behavior remains limited. We performed gene expression studies in worker bees that displayed quantitative genetic differences in HB. We established a high and low genetic source of HB performance and studied the engagements into HB of single worker bees under the same environmental conditions. We found that the percentage of worker bees that engaged in a hygienic behavioral task tripled in the high versus low HB sources, thus suggesting that genetic differences may mediate differences in stimulated states to perform HB. We found 501 differently expressed genes (DEGs) in the brains of hygienic and non-hygienic performing workers in the high HB source bees, and 342 DEGs in the brains of hygienic performing worker bees, relative to the gene expression in non-hygienic worker bees from the low HB source group. "Cell surface receptor ligand signal transduction" in the high and "negative regulation of cell communication" in the low HB source were overrepresented molecular processes, suggesting that these molecular processes in the brain may play a role in the regulation of quantitative differences in HB. Moreover, only 21 HB-associated DEGs were common between the high and low HB sources. The better HB colony performance is primarily achieved by a high number of bees engaging in the hygienic tasks that associate with distinct molecular processes in the brain. We propose that different gene products and pathways may mediate the quantitative genetic differences of HB.

Multi-system Component Phenotypes of Bipolar Disorder for Genetic Investigations of Extended Pedigrees

PubMed Central

Fears, Scott C.; Service, Susan K.; Kremeyer, Barbara; Araya, Carmen; Araya, Xinia; Bejarano, Julio; Ramirez, Margarita; Castrillón, Gabriel; Gomez-Franco, Juliana; Lopez, Maria C.; Montoya, Gabriel; Montoya, Patricia; Aldana, Ileana; Teshiba, Terri M.; Abaryan, Zvart; Al-Sharif, Noor B.; Ericson, Marissa; Jalbrzikowski, Maria; Luykx, Jurjen J.; Navarro, Linda; Tishler, Todd A.; Altshuler, Lori; Bartzokis, George; Escobar, Javier; Glahn, David C.; Ospina-Duque, Jorge; Risch, Neil; Ruiz-Linares, Andrés; Thompson, Paul M.; Cantor, Rita M.; Lopez-Jaramillo, Carlos; Macaya, Gabriel; Molina, Julio; Reus, Victor I.; Sabatti, Chiara; Freimer, Nelson B.; Bearden, Carrie E.

2014-01-01

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), yet its pathogenesis remains poorly understood. A focus on measuring multi-system quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that impact on BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomic phenotypes that appear heritable and associated with severe bipolar disorder (BP-I), and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN Multi-generational pedigree study in two closely related, genetically isolated populations: the Central Valley of Costa Rica (CVCR) and Antioquia, Colombia (ANT). PARTICIPANTS 738 individuals, all from CVCR and ANT pedigrees, of whom 181 are affected with BP-I. MAIN OUTCOME MEASURE Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) phenotypes. RESULTS Seventy-five percent (126) of the phenotypes investigated were significantly heritable, and 31% (53) were associated with BP-I. About 1/4 of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions, and volume and microstructural integrity of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND RELEVANCE This is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I-association within families that is consistent with expectations from case-control studies. Together these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder. PMID:24522887

The IQ Quantitative Trait Loci Project: A Critique.

ERIC Educational Resources Information Center

King, David

1998-01-01

Describes the IQ Quantitative Trait Loci (QTL) project, an attempt to identify genes underlying IQ score variations using maps from the Human Genome Project. The essay argues against funding the IQ QTL project because it will end the debates about the genetic basis of intelligence and may lead directly to eugenic programs of genetic testing. (SLD)

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

PubMed

Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

2015-05-01

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Refining Intervention Targets in Family-Based Research: Lessons From Quantitative Behavioral Genetics

PubMed Central

Leve, Leslie D.; Harold, Gordon T.; Ge, Xiaojia; Neiderhiser, Jenae M.; Patterson, Gerald

2010-01-01

The results from a large body of family-based research studies indicate that modifying the environment (specifically dimensions of the social environment) through intervention is an effective mechanism for achieving positive outcomes. Parallel to this work is a growing body of evidence from genetically informed studies indicating that social environmental factors are central to enhancing or offsetting genetic influences. Increased precision in the understanding of the role of the social environment in offsetting genetic risk might provide new information about environmental mechanisms that could be applied to prevention science. However, at present, the multifaceted conceptualization of the environment in prevention science is mismatched with the more limited measurement of the environment in many genetically informed studies. A framework for translating quantitative behavioral genetic research to inform the development of preventive interventions is presented in this article. The measurement of environmental indices amenable to modification is discussed within the context of quantitative behavioral genetic studies. In particular, emphasis is placed on the necessary elements that lead to benefits in prevention science, specifically the development of evidence-based interventions. An example from an ongoing prospective adoption study is provided to illustrate the potential of this translational process to inform the selection of preventive intervention targets. PMID:21188273

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.

PubMed

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A; Maltecca, Christian; Mackay, Trudy F C

2015-05-06

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Current and future developments in patents for quantitative trait loci in dairy cattle.

PubMed

Weller, Joel I

2007-01-01

Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

PubMed

Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

2008-09-01

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

Hammerschmidt, K; Deines, P; Wilson, A J; Rolff, J

2012-05-01

Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects because of higher juvenile mortality, decreased adult survival or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here, we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (for example, a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for G × E interactions arising from the experimentally induced seasonality.

Entering the second century of maize quantitative genetics

USDA-ARS?s Scientific Manuscript database

Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

A Genome Wide Survey of SNP Variation Reveals the Genetic Structure of Sheep Breeds

USDA-ARS?s Scientific Manuscript database

The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identi...

SoyBase, The USDA-ARS Soybean Genetics and Genomics Database

USDA-ARS?s Scientific Manuscript database

SoyBase, the USDA-ARS soybean genetic database, is a comprehensive repository for professionally curated genetics, genomics and related data resources for soybean. SoyBase contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. The...

Effects of functionally asexual reproduction on quantitative genetic variation in the evening primroses (Oenothera, Onagraceae).

PubMed

Godfrey, Ryan M; Johnson, Marc T J

2014-11-01

It has long been predicted that a loss of sexual reproduction leads to decreased heritable variation within populations and increased differentiation between populations. Despite an abundance of theory, there are few empirical tests of how sex affects genetic variation in phenotypic traits, especially for plants. Here we test whether repeated losses of two critical components of sex (recombination and segregation) in the evening primroses (Oenothera L., Onagraceae) affect quantitative genetic variation within and between populations. We sampled multiple genetic families from 3-5 populations from each of eight Oenothera species, which represented four independent transitions between sexual reproduction and a functionally asexual genetic system called "permanent translocation heterozygosity." We used quantitative genetics methods to partition genetic variation within and between populations for eight plant traits related to growth, leaf physiology, flowering, and resistance to herbivores. Heritability was, on average, 74% higher in sexual Oenothera populations than in functionally asexual populations, with plant growth rate, specific leaf area, and the percentage of leaf water content showing the strongest differences. By contrast, genetic differentiation among populations was 2.8× higher in functionally asexual vs. sexual Oenothera species. This difference was particularly strong for specific leaf area. Sexual populations tended to exhibit higher genetic correlations among traits, but this difference was weakly supported. These results support the prediction that sexual reproduction maintains higher genetic variation within populations, which may facilitate adaptive evolution. We also found partial support for the prediction that a loss of sex leads to greater population differentiation, which may elevate speciation rates. © 2014 Botanical Society of America, Inc.

IWGT report on quantitative approaches to genotoxicity risk ...

EPA Pesticide Factsheets

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the need for quantitative dose–response analysis of genetic toxicology data, the existence and appropriate evaluation of threshold responses, and methods to analyze exposure-response relationships and derive points of departure (PoDs) from which acceptable exposure levels could be determined. This report summarizes the QWG discussions and recommendations regarding appropriate approaches to evaluate exposure-related risks of genotoxic damage, including extrapolation below identified PoDs and across test systems and species. Recommendations include the selection of appropriate genetic endpoints and target tissues, uncertainty factors and extrapolation methods to be considered, the importance and use of information on mode of action, toxicokinetics, metabolism, and exposure biomarkers when using quantitative exposure-response data to determine acceptable exposure levels in human populations or to assess the risk associated with known or anticipated exposures. The empirical relationship between genetic damage (mutation and chromosomal aberration) and cancer in animal models was also examined. It was concluded that there is a general correlation between cancer induction and mutagenic and/or clast

Is the child 'father of the man'? evaluating the stability of genetic influences across development.

PubMed

Ronald, Angelica

2011-11-01

This selective review considers findings in genetic research that have shed light on how genes operate across development. We will address the question of whether the child is 'father of the Man' from a genetic perspective. In other words, do the same genetic influences affect the same traits across development? Using a 'taster menu' approach and prioritizing newer findings on cognitive and behavioral traits, examples from the following genetic disciplines will be discussed: (a) developmental quantitative genetics (such as longitudinal twin studies), (b) neurodevelopmental genetic syndromes with known genetic causes (such as Williams syndrome), (c) developmental candidate gene studies (such as those that link infant and adult populations), (d) developmental genome-wide association studies (GWAS), and (e) DNA resequencing. Evidence presented here suggests that there is considerable genetic stability of cognitive and behavioral traits across development, but there is also evidence for genetic change. Quantitative genetic studies have a long history of assessing genetic continuity and change across development. It is now time for the newer, more technology-enabled fields such as GWAS and DNA resequencing also to take on board the dynamic nature of human behavior. 2011 Blackwell Publishing Ltd.

Genetic and Environmental Influences on Behavior: Capturing All the Interplay

ERIC Educational Resources Information Center

Johnson, Wendy

2007-01-01

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the…

Quantitative characterization of genetic parts and circuits for plant synthetic biology.

PubMed

Schaumberg, Katherine A; Antunes, Mauricio S; Kassaw, Tessema K; Xu, Wenlong; Zalewski, Christopher S; Medford, June I; Prasad, Ashok

2016-01-01

Plant synthetic biology promises immense technological benefits, including the potential development of a sustainable bio-based economy through the predictive design of synthetic gene circuits. Such circuits are built from quantitatively characterized genetic parts; however, this characterization is a significant obstacle in work with plants because of the time required for stable transformation. We describe a method for rapid quantitative characterization of genetic plant parts using transient expression in protoplasts and dual luciferase outputs. We observed experimental variability in transient-expression assays and developed a mathematical model to describe, as well as statistical normalization methods to account for, this variability, which allowed us to extract quantitative parameters. We characterized >120 synthetic parts in Arabidopsis and validated our method by comparing transient expression with expression in stably transformed plants. We also tested >100 synthetic parts in sorghum (Sorghum bicolor) protoplasts, and the results showed that our method works in diverse plant groups. Our approach enables the construction of tunable gene circuits in complex eukaryotic organisms.

Exploring the interaction among EPHX1, GSTP1, SERPINE2, and TGFB1 contributing to the quantitative traits of chronic obstructive pulmonary disease in Chinese Han population.

PubMed

An, Li; Lin, Yingxiang; Yang, Ting; Hua, Lin

2016-05-18

Currently, the majority of genetic association studies on chronic obstructive pulmonary disease (COPD) risk focused on identifying the individual effects of single nucleotide polymorphisms (SNPs) as well as their interaction effects on the disease. However, conventional genetic studies often use binary disease status as the primary phenotype, but for COPD, many quantitative traits have the potential correlation with the disease status and closely reflect pathological changes. Here, we genotyped 44 SNPs from four genes (EPHX1, GSTP1, SERPINE2, and TGFB1) in 310 patients and 203 controls which belonged to the Chinese Han population to test the two-way and three-way genetic interactions with COPD-related quantitative traits using recently developed generalized multifactor dimensionality reduction (GMDR) and quantitative multifactor dimensionality reduction (QMDR) algorithms. Based on the 310 patients and the whole samples of 513 subjects, the best gene-gene interactions models were detected for four lung-function-related quantitative traits. For the forced expiratory volume in 1 s (FEV1), the best interaction was seen from EPHX1, SERPINE2, and GSTP1. For FEV1%pre, the forced vital capacity (FVC), and FEV1/FVC, the best interactions were seen from SERPINE2 and TGFB1. The results of this study provide further evidence for the genotype combinations at risk of developing COPD in Chinese Han population and improve the understanding on the genetic etiology of COPD and COPD-related quantitative traits.

Population size is weakly related to quantitative genetic variation and trait differentiation in a stream fish.

PubMed

Wood, Jacquelyn L A; Tezel, Defne; Joyal, Destin; Fraser, Dylan J

2015-09-01

How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Making Quantitative Genetics Relevant: Effectiveness of a Laboratory Investigation that Links Scientific Research, Commercial Applications, and Legal Issues

ERIC Educational Resources Information Center

Rutledge, Michael L.; Mathis, Philip M.; Seipelt, Rebecca L.

2005-01-01

As students apply their knowledge of scientific concepts and of science as a method of inquiry, learning becomes relevant. This laboratory exercise is designed to foster students' understanding of the genetics of quantitative traits and of the nature of science as a method of inquiry by engaging them in a real-world business scenario. During the…

Genetic variation for agronomic and fiber quality traits in a population derived from high-quality cotton germplasm

USDA-ARS?s Scientific Manuscript database

Genetic improvement of fiber quality is necessary to meet the requirements of processors and users of cotton fiber. To foster genetic improvement of cotton fiber quality, adequate genetic variation for the quantitatively inherited physical properties of cotton is required. Additionally, knowledge of...

Capturing neutral and adaptive genetic diversity for conservation in a highly structured tree species.

PubMed

Rodríguez-Quilón, Isabel; Santos-Del-Blanco, Luis; Serra-Varela, María Jesús; Koskela, Jarkko; González-Martínez, Santiago C; Alía, Ricardo

2016-10-01

Preserving intraspecific genetic diversity is essential for long-term forest sustainability in a climate change scenario. Despite that, genetic information is largely neglected in conservation planning, and how conservation units should be defined is still heatedly debated. Here, we use maritime pine (Pinus pinaster Ait.), an outcrossing long-lived tree with a highly fragmented distribution in the Mediterranean biodiversity hotspot, to prove the importance of accounting for genetic variation, of both neutral molecular markers and quantitative traits, to define useful conservation units. Six gene pools associated to distinct evolutionary histories were identified within the species using 12 microsatellites and 266 single nucleotide polymorphisms (SNPs). In addition, height and survival standing variation, their genetic control, and plasticity were assessed in a multisite clonal common garden experiment (16 544 trees). We found high levels of quantitative genetic differentiation within previously defined neutral gene pools. Subsequent cluster analysis and post hoc trait distribution comparisons allowed us to define 10 genetically homogeneous population groups with high evolutionary potential. They constitute the minimum number of units to be represented in a maritime pine dynamic conservation program. Our results uphold that the identification of conservation units below the species level should account for key neutral and adaptive components of genetic diversity, especially in species with strong population structure and complex evolutionary histories. The environmental zonation approach currently used by the pan-European genetic conservation strategy for forest trees would be largely improved by gradually integrating molecular and quantitative trait information, as data become available. © 2016 by the Ecological Society of America.

Correlation of genetic risk and messenger RNA expression in a Th17/IL23 pathway analysis in inflammatory bowel disease.

PubMed

Fransen, Karin; van Sommeren, Suzanne; Westra, Harm-Jan; Veenstra, Monique; Lamberts, Letitia E; Modderman, Rutger; Dijkstra, Gerard; Fu, Jingyuan; Wijmenga, Cisca; Franke, Lude; Weersma, Rinse K; van Diemen, Cleo C

2014-05-01

The Th17/IL23 pathway has both genetically and biologically been implicated in the pathogenesis of the inflammatory bowel diseases (IBD), Crohn's disease, and ulcerative colitis. So far, it is unknown whether and how associated risk variants affect expression of the genes encoding for Th17/IL23 pathway proteins. Ten IBD-associated SNPs residing near Th17/IL23 genes were used to construct a genetic risk model in 753 Dutch IBD cases and 1045 controls. In an independent cohort of 40 Crohn's disease, 40 ulcerative colitis, and 40 controls, the genetic risk load and presence of IBD were correlated to quantitative PCR-generated messenger RNA (mRNA) expression of 9 representative Th17/IL23 genes in both unstimulated and PMA/CaLo stimulated peripheral blood mononuclear cells. In 1240 individuals with various immunological diseases with whole genome genotype and mRNA-expression data, we also assessed correlation between genetic risk load and differential mRNA expression and sought for SNPs affecting expression of all currently known Th17/IL23 pathway genes (cis-expression quantitative trait locus). The presence of IBD, but not the genetic risk load, was correlated to differential mRNA expression for IL6 in unstimulated peripheral blood mononuclear cells and to IL23A and RORC in response to stimulation. The cis-expression quantitative trait locus analysis showed little evidence for correlation between genetic risk load and mRNA expression of Th17/IL23 genes, because we identified for only 2 of 22 Th17/IL23 genes a cis-expression quantitative trait locus single nucleotide polymorphism that is also associated to IBD (STAT3 and CCR6). Our results suggest that only the presence of IBD and not the genetic risk load alters mRNA expression levels of IBD-associated Th17/IL23 genes.

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

PubMed Central

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A.; Maltecca, Christian; Mackay, Trudy F. C.

2015-01-01

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon. PMID:25943032

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

PubMed

Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability for ASD can accumulate in a given family in successive generations.

Genetic Architectures of Quantitative Variation in RNA Editing Pathways

PubMed Central

Gu, Tongjun; Gatti, Daniel M.; Srivastava, Anuj; Snyder, Elizabeth M.; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L.; Dotu, Ivan; Chuang, Jeffrey H.; Keller, Mark P.; Attie, Alan D.; Braun, Robert E.; Churchill, Gary A.

2016-01-01

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing. PMID:26614740

Development and application of SINE multilocus and quantitative genetic markers to study oilseed rape (Brassica napus L.) crops.

PubMed

Allnutt, T R; Roper, K; Henry, C

2008-01-23

A genetic marker system based on the S1 Short Interspersed Elements (SINEs) in the important commercial crop, oilseed rape ( Brassica napus L.) has been developed. SINEs provided a successful multilocus, dominant marker system that was capable of clearly delineating winter- and spring-type crop varieties. Sixteen of 20 varieties tested showed unique profiles from the 17 polymorphic SINE markers generated. The 3' or 5' flank region of nine SINE markers were cloned, and DNA was sequenced. In addition, one putative pre-transposition SINE allele was cloned and sequenced. Two SINE flanking sequences were used to design real-time PCR assays. These quantitative SINE assays were applied to study the genetic structure of eight fields of oilseed rape crops. Studied fields were more genetically diverse than expected for the chosen loci (mean H T = 0.23). The spatial distribution of SINE marker frequencies was highly structured in some fields, suggesting locations of volunteer impurities within the crop. In one case, the assay identified a mislabeling of the crop variety. SINE markers were a useful tool for crop genetics, phylogenetics, variety identification, and purity analysis. The use and further application of quantitative, real-time PCR markers are discussed.

Biology Undergraduates' Misconceptions about Genetic Drift

ERIC Educational Resources Information Center

Andrews, T. M.; Price, R. M.; Mead, L. S.; McElhinny, T. L.; Thanukos, A.; Perez, K. E.; Herreid, C. F.; Terry, D. R.; Lemons, P. P.

2012-01-01

This study explores biology undergraduates' misconceptions about genetic drift. We use qualitative and quantitative methods to describe students' definitions, identify common misconceptions, and examine differences before and after instruction on genetic drift. We identify and describe five overarching categories that include 16 distinct…

Generalist Genes: Genetic Links between Brain, Mind, and Education

ERIC Educational Resources Information Center

Plomin, Robert; Kovas, Yulia; Haworth, Claire M. A.

2007-01-01

Genetics contributes importantly to learning abilities and disabilities--not just to reading, the target of most genetic research, but also to mathematics and other academic areas as well. One of the most important recent findings from quantitative genetic research such as twin studies is that the same set of genes is largely responsible for…

Genetic and environmental factors affecting early rooting of six Populus genomic groups: implications for tree improvement

Treesearch

Ronald S., Jr. Zalesny

2006-01-01

Genetic and environmental factors affect the early rooting of Populus planted as unrooted hardwood cuttings. Populus genotypes of six genomic groups were tested in numerous studies for the quantitative genetics of rooting, along with effects of preplanting treatments and soil temperature. Genetics data (e.g. heritabilities,...

Genetic and Environmental Influences on Negative Life Events from Late Childhood to Adolescence

ERIC Educational Resources Information Center

Johnson, Daniel P.; Rhee, Soo Hyun; Whisman, Mark A.; Corley, Robin P.; Hewitt, John K.

2013-01-01

This multiwave longitudinal study tested two quantitative genetic developmental models to examine genetic and environmental influences on exposure to negative dependent and independent life events. Participants (N = 457 twin pairs) completed measures of life events annually from ages 9 to 16. The same genetic factors influenced exposure to…

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops.

PubMed

Qian, Lunwen; Hickey, Lee T; Stahl, Andreas; Werner, Christian R; Hayes, Ben; Snowdon, Rod J; Voss-Fels, Kai P

2017-01-01

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

USE OF GENOTOXIC ACTIVITY PROFILES IN ASSESSMENT OF CARCINOGENESIS AND TRANSMISSIBLE GENETIC EFFECTS

EPA Science Inventory

A methodology has been developed to display and evaluate multiple test quantitative information on genetic toxicants for purposes of assessing carcinogenesis and transmissible genetic effects. ose Information is collected from the open literature: either the lowest effective dose...

The efficiency of close inbreeding to reduce genetic adaptation to captivity

PubMed Central

Theodorou, K; Couvet, D

2015-01-01

Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs. PMID:25052417

The genetics of muscle atrophy and growth: the impact and implications of polymorphisms in animals and humans.

PubMed

Gordon, Erynn S; Gordish Dressman, Heather A; Hoffman, Eric P

2005-10-01

Much of the vast diversity we see in animals and people is governed by genetic loci that have quantitative effects of phenotype (quantitative trait loci; QTLs). Here we review the current knowledge of the genetics of atrophy and hypertrophy in both animal husbandry (meat quantity and quality), and humans (muscle size and performance). The selective breeding of animals for meat has apparently led to a few genetic loci with strong effects, with different loci in different animals. In humans, muscle quantitative trait loci (QTLs) appear to be more complex, with few "major" loci identified to date, although this is likely to change in the near future. We describe how the same phenotypic traits we see as positive, greater lean muscle mass in cattle or a better exercise results in humans, can also have negative "side effects" given specific environmental challenges. We also discuss the strength and limitations of single nucleotide polymorphisms (SNP) association studies; what the reader should look for and expect in a published study. Lastly we discuss the ethical and societal implications of this genetic information. As more and more research into the genetic loci that dictate phenotypic traits become available, the ethical implications of testing for these loci become increasingly important. As a society, most accept testing for genetic diseases or susceptibility, but do we as easily accept testing to determine one's athletic potential to be an Olympic endurance runner, or quarterback on the high school football team.

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.).

PubMed

Jiang, Congcong; Shi, Jiaqin; Li, Ruiyuan; Long, Yan; Wang, Hao; Li, Dianrong; Zhao, Jianyi; Meng, Jinling

2014-04-01

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations. Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F2 population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.

Adaptive potential of northernmost tree populations to climate change, with emphasis on Scots pine (Pinus sylvestris L.).

PubMed

Savolainen, Outi; Kujala, Sonja T; Sokol, Catherina; Pyhäjärvi, Tanja; Avia, Komlan; Knürr, Timo; Kärkkäinen, Katri; Hicks, Sheila

2011-01-01

The adaptive potential of the northernmost Pinus sylvestris L. (and other northern tree) populations is considered by examining first the current patterns of quantitative genetic adaptive traits, which show high population differentiation and clines. We then consider the postglacial history of the populations using both paleobiological and genetic data. The current patterns of diversity at nuclear genes suggest that the traces of admixture are mostly visible in mitochondrial DNA variation patterns. There is little evidence of increased diversity due to admixture between an eastern and western colonization lineage, but no signal of reduced diversity (due to sequential bottlenecks) either. Quantitative trait variation in the north is not associated with the colonizing lineages. The current clines arose rapidly and may be based on standing genetic variation. The initial phenotypic response of Scots pine in the north is predicted to be increased survival and growth. The genetic responses are examined based on quantitative genetic predictions of sustained selection response and compared with earlier simulation results that have aimed at more ecological realism. The phenotypic responses of increased growth and survival reduce the opportunity for selection and delay the evolutionary responses. The lengthening of the thermal growing period also causes selection on the critical photoperiod in the different populations. Future studies should aim at including multiple ecological and genetic factors in evaluating potential responses.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance. | Office of Cancer Genomics

Cancer.gov

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy.

A quantitative chemotherapy genetic interaction map reveals new factors associated with PARP inhibitor resistance | Office of Cancer Genomics

Cancer.gov

Nearly every cancer patient is treated with chemotherapy yet our understanding of factors that dictate response and resistance to such agents remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells that charts the impact of knockdown of 625 cancer and DNA repair related genes on sensitivity to 29 drugs, covering all classes of cancer chemotherapeutics.

Reply.

ERIC Educational Resources Information Center

Gottlieb, Gilbert

1995-01-01

Argues that a truly developmental behavior genetics will have to go beyond the traditional quantitative approach of population genetics in order to produce developmental explanatory content about differences and similarities in developmental outcomes. (MDM)

Attention Deficit Hyperactivity Disorder with Reading Disabilities: Preliminary Genetic Findings on the Involvement of the ADRA2A Gene

ERIC Educational Resources Information Center

Stevenson, J.; Langley, K.; Pay, H.; Payton, A.; Worthington, J.; Ollier, W.; Thapar, A.

2005-01-01

Background: Attention deficit/hyperactivity disorder (ADHD) and reading disability (RD) tend to co-occur and quantitative genetic studies have shown this to arise primarily through shared genetic influences. However, molecular genetic studies have shown different genes to be associated with each of these conditions. Neurobiological studies have…

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

PubMed

Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.

Dissecting genetic architecture of startle response in Drosophila melanogaster using multi-omics information.

PubMed

Xue, Angli; Wang, Hongcheng; Zhu, Jun

2017-09-28

Startle behavior is important for survival, and abnormal startle responses are related to several neurological diseases. Drosophila melanogaster provides a powerful system to investigate the genetic underpinnings of variation in startle behavior. Since mechanically induced, startle responses and environmental conditions can be readily quantified and precisely controlled. The 156 wild-derived fully sequenced lines of the Drosophila Genetic Reference Panel (DGRP) were used to identify SNPs and transcripts associated with variation in startle behavior. The results validated highly significant effects of 33 quantitative trait SNPs (QTSs) and 81 quantitative trait transcripts (QTTs) directly associated with phenotypic variation of startle response. We also detected QTT variation controlled by 20 QTSs (tQTSs) and 73 transcripts (tQTTs). Association mapping based on genomic and transcriptomic data enabled us to construct a complex genetic network that underlies variation in startle behavior. Based on principles of evolutionary conservation, human orthologous genes could be superimposed on this network. This study provided both genetic and biological insights into the variation of startle response behavior of Drosophila melanogaster, and highlighted the importance of genetic network to understand the genetic architecture of complex traits.

Bridging the Gap between Genomics and Education

ERIC Educational Resources Information Center

Petrill, Stephen A.; Justice, Laura M.

2007-01-01

Despite several decades of research suggesting the importance of both genetic and environmental factors, these findings are not well integrated into the larger educational literature. Following a discussion of quantitative and molecular genetic methods, this article reviews behavioral genetic findings related to cognitive and academic skills. This…

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

Systematic profiling of Caenorhabditis elegans locomotive behaviors reveals additional components in G-protein Gαq signaling.

PubMed

Yu, Hui; Aleman-Meza, Boanerges; Gharib, Shahla; Labocha, Marta K; Cronin, Christopher J; Sternberg, Paul W; Zhong, Weiwei

2013-07-16

Genetic screens have been widely applied to uncover genetic mechanisms of movement disorders. However, most screens rely on human observations of qualitative differences. Here we demonstrate the application of an automatic imaging system to conduct a quantitative screen for genes regulating the locomotive behavior in Caenorhabditis elegans. Two hundred twenty-seven neuronal signaling genes with viable homozygous mutants were selected for this study. We tracked and recorded each animal for 4 min and analyzed over 4,400 animals of 239 genotypes to obtain a quantitative, 10-parameter behavioral profile for each genotype. We discovered 87 genes whose inactivation causes movement defects, including 50 genes that had never been associated with locomotive defects. Computational analysis of the high-content behavioral profiles predicted 370 genetic interactions among these genes. Network partition revealed several functional modules regulating locomotive behaviors, including sensory genes that detect environmental conditions, genes that function in multiple types of excitable cells, and genes in the signaling pathway of the G protein Gαq, a protein that is essential for animal life and behavior. We developed quantitative epistasis analysis methods to analyze the locomotive profiles and validated the prediction of the γ isoform of phospholipase C as a component in the Gαq pathway. These results provided a system-level understanding of how neuronal signaling genes coordinate locomotive behaviors. This study also demonstrated the power of quantitative approaches in genetic studies.

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

PubMed

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

2017-01-01

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

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in Brassica rapa Fast Plants

PubMed Central

Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225

Compatibility of breeding for increased wood production and longterm sustainability: the genetic variation of seed orchard seed and associated risks.

Treesearch

R Johnson; S. Lipow

2002-01-01

Because breeding imposes strong artificial selection for a narrow suite of economically important traits, genetic variation is reduced in seedlings derived from operational seed orchards. Both quantitative genetics theory and studies of allozyme variation show that seed orchards contain most of the genetic diversity found in natural populations, although low-frequency...

Congruent climate-related genecological responses from molecular markers and quantitative traits for western white pine (Pinus monticola)

Treesearch

Bryce A. Richardson; Gerald E. Rehfeldt; Mee-Sook Kim

2009-01-01

Analyses of molecular and quantitative genetic data demonstrate the existence of congruent climate-related patterns in western white pine (Pinus monticola). Two independent studies allowed comparisons of amplified fragment length polymorphism (AFLP) markers with quantitative variation in adaptive traits. Principal component analyses...

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings.

PubMed

Sariaslan, A; Larsson, H; Fazel, S

2016-09-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8-10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h(2)=53-71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30-0.33) than bipolar disorder (r=0.23; 0.21-0.25), and large proportions (51-67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21%; 20-22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait networks if the edges can be anchored to genetic marker data. R software tutorials, data, and supplementary material can be downloaded from: http://www.genetics.ucla.edu/labs/horvath/aten/NEO.

Environmental Influences on Reading-Related Outcomes: An Adoption Study

ERIC Educational Resources Information Center

Petrill, Stephen A.; Deater-Deckard, Kirby; Schatschneider, Christopher; Davis, Chayna

2007-01-01

Evidence from intervention studies, quantitative genetic and molecular genetic studies suggests that genetic, and to a lesser extent, shared environmental influences are important to the development of reading and related cognitive skills. The Northeast-Northwest Collaborative Adoption Projects (N2CAP) is a sample of 241 adoptive families,…

Evaluation of breeding strategies for polledness in dairy cattle using a newly developed simulation framework for quantitative and Mendelian traits.

PubMed

Scheper, Carsten; Wensch-Dorendorf, Monika; Yin, Tong; Dressel, Holger; Swalve, Herrmann; König, Sven

2016-06-29

Intensified selection of polled individuals has recently gained importance in predominantly horned dairy cattle breeds as an alternative to routine dehorning. The status quo of the current polled breeding pool of genetically-closely related artificial insemination sires with lower breeding values for performance traits raises questions regarding the effects of intensified selection based on this founder pool. We developed a stochastic simulation framework that combines the stochastic simulation software QMSim and a self-designed R program named QUALsim that acts as an external extension. Two traits were simulated in a dairy cattle population for 25 generations: one quantitative (QMSim) and one qualitative trait with Mendelian inheritance (i.e. polledness, QUALsim). The assignment scheme for qualitative trait genotypes initiated realistic initial breeding situations regarding allele frequencies, true breeding values for the quantitative trait and genetic relatedness. Intensified selection for polled cattle was achieved using an approach that weights estimated breeding values in the animal best linear unbiased prediction model for the quantitative trait depending on genotypes or phenotypes for the polled trait with a user-defined weighting factor. Selection response for the polled trait was highest in the selection scheme based on genotypes. Selection based on phenotypes led to significantly lower allele frequencies for polled. The male selection path played a significantly greater role for a fast dissemination of polled alleles compared to female selection strategies. Fixation of the polled allele implies selection based on polled genotypes among males. In comparison to a base breeding scenario that does not take polledness into account, intensive selection for polled substantially reduced genetic gain for this quantitative trait after 25 generations. Reducing selection intensity for polled males while maintaining strong selection intensity among females, simultaneously decreased losses in genetic gain and achieved a final allele frequency of 0.93 for polled. A fast transition to a completely polled population through intensified selection for polled was in contradiction to the preservation of high genetic gain for the quantitative trait. Selection on male polled genotypes with moderate weighting, and selection on female polled phenotypes with high weighting, could be a suitable compromise regarding all important breeding aspects.

Genetic approaches in comparative and evolutionary physiology

PubMed Central

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

2015-01-01

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

Genetic approaches in comparative and evolutionary physiology.

PubMed

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

2015-08-01

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

A unifying theory for genetic epidemiological analysis of binary disease data

PubMed Central

2014-01-01

Background Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Results Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. Conclusions We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness. PMID:24552188

A unifying theory for genetic epidemiological analysis of binary disease data.

PubMed

Lipschutz-Powell, Debby; Woolliams, John A; Doeschl-Wilson, Andrea B

2014-02-19

Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness.

Terminology, concepts, and models in genetic epidemiology.

PubMed

Teare, M Dawn; Koref, Mauro F Santibàñez

2011-01-01

Genetic epidemiology brings together approaches and techniques developed in mathematical genetics and statistics, medical genetics, quantitative genetics, and epidemiology. In the 1980s, the focus was on the mapping and identification of genes where defects had large effects at the individual level. More recently, statistical and experimental advances have made possible to identify and characterise genes associated with small effects at the individual level. In this chapter, we provide a brief outline of the models, concepts, and terminology used in genetic epidemiology.

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that the continuous variation in anthocyanin content in grape was explained mainly by a single gene cluster of three VvMybA genes. The use of natural diversity helped to reduce one QTL to a set of five quantitative trait nucleotides and gave a clear picture of how isogenes combined their effects to shape grape color. Such analysis also illustrates how isogenes combine their effect to shape a complex quantitative trait and enables the definition of markers directly targeted for upcoming breeding programs.

Sibling recurrence and the genetic epidemiology of autism

PubMed Central

Constantino, John N.; Zhang, Yi; Frazier, Thomas; Abbacchi, Anna M.; Law, Paul

2010-01-01

Objective Although the symptoms of autism exhibit quantitative distributions in nature, estimates of recurrence risk in families have never previously considered or incorporated quantitative characterization of the autistic phenotype among siblings. Method We report the results of quantitative characterization of 2,920 children from 1,235 families participating in a national volunteer register who met the criteria of having at least one child clinically-affected by an autism spectrum disorder (ASD) and at least one full biological sibling. Results The occurrence of a traditionally-defined ASD in an additional child occurred in 10.9% of the families. An additional 20% of non-ASD-affected siblings had a history of language delay, half of whom had exhibited autistic qualities of speech. Quantitative characterization using the Social Responsiveness Scale (SRS) supported previously-reported aggregation of a wide range of subclinical (quantitative) autistic traits among otherwise unaffected children in multiple-incidence families, and a relative absence of quantitative autistic traits among siblings in single-incidence autism families. Girls whose standardized severity ratings fell above a first percentile severity threshold (relative to the general population distribution) were significantly less likely to have elicited community diagnoses than their male counterparts. Conclusions These data suggest that, depending on how it is defined, sibling recurrence in ASD may exceed previously-published estimates, and varies as a function of family type. The results support differences in mechanisms of genetic transmission between simplex and multiplex autism, and advance current understanding of the genetic epidemiology of autism. PMID:20889652

Antagonistic versus non-antagonistic models of balancing selection: Characterizing the relative timescales and hitchhiking effects of partial selective sweeps

PubMed Central

Connallon, Tim; Clark, Andrew G.

2012-01-01

Antagonistically selected alleles -- those with opposing fitness effects between sexes, environments, or fitness components -- represent an important component of additive genetic variance in fitness-related traits, with stably balanced polymorphisms often hypothesized to contribute to observed quantitative genetic variation. Balancing selection hypotheses imply that intermediate-frequency alleles disproportionately contribute to genetic variance of life history traits and fitness. Such alleles may also associate with population genetic footprints of recent selection, including reduced genetic diversity and inflated linkage disequilibrium at linked, neutral sites. Here, we compare the evolutionary dynamics of different balancing selection models, and characterize the evolutionary timescale and hitchhiking effects of partial selective sweeps generated under antagonistic versus non-antagonistic (e.g., overdominant and frequency-dependent selection) processes. We show that that the evolutionary timescales of partial sweeps tend to be much longer, and hitchhiking effects are drastically weaker, under scenarios of antagonistic selection. These results predict an interesting mismatch between molecular population genetic and quantitative genetic patterns of variation. Balanced, antagonistically selected alleles are expected to contribute more to additive genetic variance for fitness than alleles maintained by classic, non-antagonistic mechanisms. Nevertheless, classical mechanisms of balancing selection are much more likely to generate strong population genetic signatures of recent balancing selection. PMID:23461340

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

NASA Astrophysics Data System (ADS)

Aurah, Catherine Muhonja

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the outcomes and the processes of students' genetics problem-solving ability. Focus group interviews substantiated and supported findings from the quantitative instruments. The study was conducted in 17 high schools in Western Province, Kenya. A total of 2,138 high school students were purposively sampled. A sub-sample of 48 students participated in focus group interviews to understand their perspectives and experiences during the study so as to corroborate the quantitative data. Quantitative data were analyzed through descriptive statistics, zero-order correlations, 2 x 2 factorial ANOVA,, and sequential hierarchical multiple regressions. Qualitative data were transcribed, coded, and reported thematically. Results revealed metacognitive prompts had significant positive effects on student problem-solving ability independent of gender. Self-efficacy and metacognitive prompting significantly predicted genetics problem-solving ability. Gender differences were revealed, with girls outperforming boys on the genetics problem-solving test. Furthermore, self-efficacy moderated the relationship between metacognitive prompting and genetics problem-solving ability. This study established a foundation for instructional methods for biology teachers and recommendations are made for implementing metacognitive prompting in a problem-based learning environment in high schools and science teacher education programs in Kenya.

Quantitative genetics of circulating Hyaluronic Acid (HA) and its correlation with hand osteoarthritis and obesity-related phenotypes in a community-based sample.

PubMed

Prakash, Jai; Gabdulina, Gulzhan; Trofimov, Svetlana; Livshits, Gregory

2017-09-01

One of the potential molecular biomarkers of osteoarthritis (OA) is hyaluronic acid (HA). HA levels may be related to the severity and progression of OA. However, little is known about the contribution of major risk factors for osteoarthritis, e.g. obesity-related phenotypes and genetics to HA variation. To clarify the quantitative effect of these factors on HA. An ethnically homogeneous sample of 911 apparently healthy European-derived individuals, assessed for radiographic hand osteoarthritis (RHOA), HA, leptin, adiponectin, and several anthropometrical measures of obesity-related phenotypes was studied. Model-based quantitative genetic analysis was used to reveal genetic and shared environmental factors affecting the variation of the study's phenotypes. The HA levels significantly correlated with the age, RHOA, adiponectin, obesity-related phenotypes, and the waist-to-hip ratio. The putative genetic effects contributed significantly to the variation of HA (66.2 ± 9.3%) and they were also significant factors in the variations of all the other studied phenotypes, with the heritability estimate ranging between 0.122 ± 4.4% (WHR) and 45.7 ± 2.2% (joint space narrowing). This is the first study to report heritability estimates of HA variation and its correlation with obesity-related phenotypes, ADP and RHOA. However, the nature of genetic effects on HA and its correlation with other study phenotypes require further clarification.

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic variation and gene expression across multiple tissues and developmental stages in a nonhuman primate.

PubMed

Jasinska, Anna J; Zelaya, Ivette; Service, Susan K; Peterson, Christine B; Cantor, Rita M; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A; Fears, Scott; Furterer, Allison E; Huang, Yu S; Ramensky, Vasily; Schmitt, Christopher A; Svardal, Hannes; Jorgensen, Matthew J; Kaplan, Jay R; Villar, Diego; Aken, Bronwen L; Flicek, Paul; Nag, Rishi; Wong, Emily S; Blangero, John; Dyer, Thomas D; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K; Jentsch, J David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P; Freimer, Nelson B

2017-12-01

By analyzing multitissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalog of expression quantitative trait loci (eQTLs) in a nonhuman primate model. This catalog contains more genome-wide significant eQTLs per sample than comparable human resources and identifies sex- and age-related expression patterns. Findings include a master regulatory locus that likely has a role in immune function and a locus regulating hippocampal long noncoding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

PubMed

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

Genetic and phenotypic correlations of quantitative traits in two long-term randomly mated soybean populations

USDA-ARS?s Scientific Manuscript database

The genetic effects of long term random mating and natural selection aided by genetic male sterility (gms) were evaluated in two soybean [Glycine max (L.) Merr.] populations designated: RSII and RSIII. These populations were evaluated in the field at three locations each with two replications. Genot...

Understanding Genetic and Environmental Influences on the Development of Reading: Reaching for Higher Fruit

ERIC Educational Resources Information Center

Wagner, Richard K.

2005-01-01

The transition from first-generation to second-generation studies of genetic and environmental influences on the development of reading is underway. The first generation of quantitative genetic studies yielded an extraordinary conclusion: Fifty percent or more of the variance in most constructs, including reading, is attributable to genetic…

Creativity and the Genome: The State of Affairs

ERIC Educational Resources Information Center

Grigorenko, Elena L.

2017-01-01

This essay is focused on the research into the genetic etiology of creativity and related processes. In an attempt to identify the most salient points of this research, the article provides a brief overview of quantitative-genetic (family and twin) and molecular-genetic (candidate-gene and whole-genome) studies of creativity. To conclude, the…

Novel Applications of Multi-task Learning and Multiple Output Regression to Multiple Genetic Trait Prediction

USDA-ARS?s Scientific Manuscript database

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...

Estimation of genetic parameters and their sampling variances of quantitative traits in the type 2 modified augmented design

USDA-ARS?s Scientific Manuscript database

We proposed a method to estimate the error variance among non-replicated genotypes, thus to estimate the genetic parameters by using replicated controls. We derived formulas to estimate sampling variances of the genetic parameters. Computer simulation indicated that the proposed methods of estimatin...

Communicating the role of genetics in management

Treesearch

Mary F. Mahalovich

1997-01-01

Three current issues serve as examples to convey the role of genetics in management. (1) Consequences of silvicultural systems on the genetic resource of tree species are limited to one generation of study and isozyme (qualitative) data. Results of simulated data for diameter (quantitative data) over several generations, illustrate the pitfalls of working towards...

Development of an innovative immunoassay for CP4EPSPS and Cry1AB genetically modified protein detection and quantification.

PubMed

Ermolli, M; Prospero, A; Balla, B; Querci, M; Mazzeo, A; Van Den Eede, G

2006-09-01

An innovative immunoassay, called enzyme-linked immunoabsorbant assay (ELISA) Reverse, based on a new conformation of the solid phase, was developed. The solid support was expressly designed to be immersed directly in liquid samples to detect the presence of protein targets. Its application is proposed in those cases where a large number of samples have to be screened simultaneously or when the simultaneous detection of different proteins is required. As a first application, a quantitative immunoassay for Cry1AB protein in genetically modified maize was optimized. The method was tested using genetically modified organism concentrations from 0.1 to 2.0%. The limit of detection and limit of quantitation of the method were determined as 0.0056 and 0.0168 (expressed as the percentage of genetically modified organisms content), respectively. A qualitative multiplex assay to assess the presence of two genetically modified proteins simultaneously was also established for the case of the Cry1AB and the CP4EPSPS (5-enolpyruvylshikimate-3-phosphate synthase) present in genetically modified maize and soy, respectively.

Experimental evidence for the evolution of indirect genetic effects: changes in the interaction effect coefficient, psi (Psi), due to sexual selection.

PubMed

Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W

2010-06-01

Indirect genetics effects (IGEs)--when the genotype of one individual affects the phenotypic expression of a trait in another--may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Psi). The extent to which Psi exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories--the evolution of interaction effects themselves.

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

PubMed

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

2015-04-01

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

PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

PubMed Central

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

2018-01-01

Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

PubMed

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

2008-05-15

A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

Genomic atlas of the human plasma proteome.

PubMed

Sun, Benjamin B; Maranville, Joseph C; Peters, James E; Stacey, David; Staley, James R; Blackshaw, James; Burgess, Stephen; Jiang, Tao; Paige, Ellie; Surendran, Praveen; Oliver-Williams, Clare; Kamat, Mihir A; Prins, Bram P; Wilcox, Sheri K; Zimmerman, Erik S; Chi, An; Bansal, Narinder; Spain, Sarah L; Wood, Angela M; Morrell, Nicholas W; Bradley, John R; Janjic, Nebojsa; Roberts, David J; Ouwehand, Willem H; Todd, John A; Soranzo, Nicole; Suhre, Karsten; Paul, Dirk S; Fox, Caroline S; Plenge, Robert M; Danesh, John; Runz, Heiko; Butterworth, Adam S

2018-06-01

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

Quantitative genetic analysis of injury liability in infants and toddlers

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

Phillips, K.; Matheny, A.P. Jr.

1995-02-27

A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries.more » Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.« less

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

PubMed

Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Mathematical Ability of 10-Year-Old Boys and Girls: Genetic and Environmental Etiology of Typical and Low Performance

PubMed Central

Kovas, Yulia; Haworth, Claire M. A.; Petrill, Stephen A.; Plomin, Robert

2009-01-01

The genetic and environmental etiologies of 3 aspects of low mathematical performance (math disability) and the full range of variability (math ability) were compared for boys and girls in a sample of 5,348 children age 10 years (members of 2,674 pairs of same-sex and opposite-sex twins) from the United Kingdom (UK). The measures, which we developed for Web-based testing, included problems from 3 domains of mathematics taught as part of the UK National Curriculum. Using quantitative genetic model-fitting analyses, similar results were found for math disabilities and abilities for all 3 measures: Moderate genetic influence and environmental influence were mainly due to nonshared environmental factors that were unique to the individual, with little influence from shared environment. No sex differences were found in the etiologies of math abilities and disabilities. We conclude that low mathematical performance is the quantitative extreme of the same genetic and environmental factors responsible for variation throughout the distribution. PMID:18064980

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

PubMed

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

Quantitative measures of healthy aging and biological age

PubMed Central

Kim, Sangkyu; Jazwinski, S. Michal

2015-01-01

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including ‘successful aging’ and ‘frailty’, have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the ‘frailty index’, which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity. PMID:26005669

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

PubMed Central

Lin, J. Z.; Ritland, K.

1997-01-01

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

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

PubMed Central

Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

2012-01-01

Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

Toxic hydrogen sulfide and dark caves: phenotypic and genetic divergence across two abiotic environmental gradients in Poecilia mexicana.

PubMed

Tobler, Michael; Dewitt, Thomas J; Schlupp, Ingo; García de León, Francisco J; Herrmann, Roger; Feulner, Philine G D; Tiedemann, Ralph; Plath, Martin

2008-10-01

Divergent natural selection drives evolutionary diversification. It creates phenotypic diversity by favoring developmental plasticity within populations or genetic differentiation and local adaptation among populations. We investigated phenotypic and genetic divergence in the livebearing fish Poecilia mexicana along two abiotic environmental gradients. These fish typically inhabit nonsulfidic surface rivers, but also colonized sulfidic and cave habitats. We assessed phenotypic variation among a factorial combination of habitat types using geometric and traditional morphometrics, and genetic divergence using quantitative and molecular genetic analyses. Fish in caves (sulfidic or not) exhibited reduced eyes and slender bodies. Fish from sulfidic habitats (surface or cave) exhibited larger heads and longer gill filaments. Common-garden rearing suggested that these morphological differences are partly heritable. Population genetic analyses using microsatellites as well as cytochrome b gene sequences indicate high population differentiation over small spatial scale and very low rates of gene flow, especially among different habitat types. This suggests that divergent environmental conditions constitute barriers to gene flow. Strong molecular divergence over short distances as well as phenotypic and quantitative genetic divergence across habitats in directions classic to fish ecomorphology suggest that divergent selection is structuring phenotypic variation in this system.

Genome-Wide Association Studies of Quantitatively Measured Skin, Hair, and Eye Pigmentation in Four European Populations

PubMed Central

Candille, Sophie I.; Absher, Devin M.; Beleza, Sandra; Bauchet, Marc; McEvoy, Brian; Garrison, Nanibaa’ A.; Li, Jun Z.; Myers, Richard M.; Barsh, Gregory S.; Tang, Hua; Shriver, Mark D.

2012-01-01

Pigmentation of the skin, hair, and eyes varies both within and between human populations. Identifying the genes and alleles underlying this variation has been the goal of many candidate gene and several genome-wide association studies (GWAS). Most GWAS for pigmentary traits to date have been based on subjective phenotypes using categorical scales. But skin, hair, and eye pigmentation vary continuously. Here, we seek to characterize quantitative variation in these traits objectively and accurately and to determine their genetic basis. Objective and quantitative measures of skin, hair, and eye color were made using reflectance or digital spectroscopy in Europeans from Ireland, Poland, Italy, and Portugal. A GWAS was conducted for the three quantitative pigmentation phenotypes in 176 women across 313,763 SNP loci, and replication of the most significant associations was attempted in a sample of 294 European men and women from the same countries. We find that the pigmentation phenotypes are highly stratified along axes of European genetic differentiation. The country of sampling explains approximately 35% of the variation in skin pigmentation, 31% of the variation in hair pigmentation, and 40% of the variation in eye pigmentation. All three quantitative phenotypes are correlated with each other. In our two-stage association study, we reproduce the association of rs1667394 at the OCA2/HERC2 locus with eye color but we do not identify new genetic determinants of skin and hair pigmentation supporting the lack of major genes affecting skin and hair color variation within Europe and suggesting that not only careful phenotyping but also larger cohorts are required to understand the genetic architecture of these complex quantitative traits. Interestingly, we also see that in each of these four populations, men are more lightly pigmented in the unexposed skin of the inner arm than women, a fact that is underappreciated and may vary across the world. PMID:23118974

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population.

PubMed

Bonnet, Timothée; Wandeler, Peter; Camenisch, Glauco; Postma, Erik

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called "stasis paradox" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is superior to purely phenotypic estimates of selection and evolutionary change.

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population

PubMed Central

Wandeler, Peter; Camenisch, Glauco

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called “stasis paradox” highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is superior to purely phenotypic estimates of selection and evolutionary change. PMID:28125583

Kernel-based whole-genome prediction of complex traits: a review.

PubMed

Morota, Gota; Gianola, Daniel

2014-01-01

Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

Local selection modifies phenotypic divergence among Rana temporaria populations in the presence of gene flow.

PubMed

Richter-Boix, Alex; Teplitsky, Céline; Rogell, Björn; Laurila, Anssi

2010-02-01

In ectotherms, variation in life history traits among populations is common and suggests local adaptation. However, geographic variation itself is not a proof for local adaptation, as genetic drift and gene flow may also shape patterns of quantitative variation. We studied local and regional variation in means and phenotypic plasticity of larval life history traits in the common frog Rana temporaria using six populations from central Sweden, breeding in either open-canopy or partially closed-canopy ponds. To separate local adaptation from genetic drift, we compared differentiation in quantitative genetic traits (Q(ST)) obtained from a common garden experiment with differentiation in presumably neutral microsatellite markers (F(ST)). We found that R. temporaria populations differ in means and plasticities of life history traits in different temperatures at local, and in F(ST) at regional scale. Comparisons of differentiation in quantitative traits and in molecular markers suggested that natural selection was responsible for the divergence in growth and development rates as well as in temperature-induced plasticity, indicating local adaptation. However, at low temperature, the role of genetic drift could not be separated from selection. Phenotypes were correlated with forest canopy closure, but not with geographical or genetic distance. These results indicate that local adaptation can evolve in the presence of ongoing gene flow among the populations, and that natural selection is strong in this system.

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

PubMed

Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

2016-09-10

Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source code, along with the manual and the example files can be downloaded at http://lissp.irb.hr/software/magellan-1-0/ and https://github.com/sristov/magellan .

Investigating Factors that Generate and Maintain Variation in Migratory Orientation: A Primer for Recent and Future Work.

PubMed

Delmore, Kira E; Liedvogel, Miriam

2016-01-01

The amazing accuracy of migratory orientation performance across the animal kingdom is facilitated by the use of magnetic and celestial compass systems that provide individuals with both directional and positional information. Quantitative genetics analyses in several animal systems suggests that migratory orientation has a strong genetic component. Nevertheless, the exact identity of genes controlling orientation remains largely unknown, making it difficult to obtain an accurate understanding of this fascinating behavior on the molecular level. Here, we provide an overview of molecular genetic techniques employed thus far, highlight the pros and cons of various approaches, generalize results from species-specific studies whenever possible, and evaluate how far the field has come since early quantitative genetics studies. We emphasize the importance of examining different levels of molecular control, and outline how future studies can take advantage of high-resolution tracking and sequencing techniques to characterize the genomic architecture of migratory orientation.

The correlation between relatives on the supposition of genomic imprinting.

PubMed Central

Spencer, Hamish G

2002-01-01

Standard genetic analyses assume that reciprocal heterozygotes are, on average, phenotypically identical. If a locus is subject to genomic imprinting, however, this assumption does not hold. We incorporate imprinting into the standard quantitative-genetic model for two alleles at a single locus, deriving expressions for the additive and dominance components of genetic variance, as well as measures of resemblance among relatives. We show that, in contrast to the case with Mendelian expression, the additive and dominance deviations are correlated. In principle, this correlation allows imprinting to be detected solely on the basis of different measures of familial resemblances, but in practice, the standard error of the estimate is likely to be too large for a test to have much statistical power. The effects of genomic imprinting will need to be incorporated into quantitative-genetic models of many traits, for example, those concerned with mammalian birthweight. PMID:12019254

The correlation between relatives on the supposition of genomic imprinting.

PubMed

Spencer, Hamish G

2002-05-01

Standard genetic analyses assume that reciprocal heterozygotes are, on average, phenotypically identical. If a locus is subject to genomic imprinting, however, this assumption does not hold. We incorporate imprinting into the standard quantitative-genetic model for two alleles at a single locus, deriving expressions for the additive and dominance components of genetic variance, as well as measures of resemblance among relatives. We show that, in contrast to the case with Mendelian expression, the additive and dominance deviations are correlated. In principle, this correlation allows imprinting to be detected solely on the basis of different measures of familial resemblances, but in practice, the standard error of the estimate is likely to be too large for a test to have much statistical power. The effects of genomic imprinting will need to be incorporated into quantitative-genetic models of many traits, for example, those concerned with mammalian birthweight.

An introduction to genetic quality in the context of sexual selection.

PubMed

Pitcher, Trevor E; Mays, Herman L

2008-09-01

This special issue of Genetica brings together empirical researchers and theoreticians to present the latest on the evolutionary ecology of genetic quality in the context of sexual selection. The work comes from different fields of study including behavioral ecology, quantitative genetics and molecular genetics on a diversity of organisms using different approaches from comparative studies, mathematical modeling, field studies and laboratory experiments. The papers presented in this special issue primarily focus on genetic quality in relation to (1) sources of genetic variation, (2) polyandry, (3) new theoretical developments and (4) comprehensive reviews.

Genetical Genomics Identifies the Genetic Architecture for Growth and Weevil Resistance in Spruce

PubMed Central

Porth, Ilga; White, Richard; Jaquish, Barry; Alfaro, René; Ritland, Carol; Ritland, Kermit

2012-01-01

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce. PMID:22973444

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

2016-12-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

Yadav, Anupama; Dhole, Kaustubh

2016-01-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

2011-08-01

In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

Ultraviolet light induction of diphtheria toxin-resistant mutations in normal and DNA repair-deficient human and Chinese hamster fibroblasts

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

Trosko, J.E.; Schultz, R.S.; Chang, C.C.

1980-01-01

The role on unrepaired DNA lesions in the production of mutations is suspected of contributing to the initiation phase of carcinogenesis. Since the molecular basis of mutagenesis is not understood in eukaryotic cells, development of new genetic markers for quantitative in vitro measurement of mutations for mammalian cells is needed. Furthermore, mammalian cells, genetically deficient for various DNA repair enzymes, will be needed to study the role of unrepaired DNA lesions in mutagenesis. The results in this report relate to preliminary attempts to characterize the diphtheria toxin resistance marker as a useful quantitative genetic marker in human cells and tomore » isolate and characterize various DNA repair-deficient Chinese hamster cells.« less

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate

PubMed Central

Jasinska, Anna J.; Zelaya, Ivette; Service, Susan K.; Peterson, Christine B.; Cantor, Rita M.; Choi, Oi-Wa; DeYoung, Joseph; Eskin, Eleazar; Fairbanks, Lynn A.; Fears, Scott; Furterer, Allison E.; Huang, Yu S.; Ramensky, Vasily; Schmitt, Christopher A.; Svardal, Hannes; Jorgensen, Matthew J.; Kaplan, Jay R.; Villar, Diego; Aken, Bronwen L.; Flicek, Paul; Nag, Rishi; Wong, Emily S.; Blangero, John; Dyer, Thomas D.; Bogomolov, Marina; Benjamini, Yoav; Weinstock, George M.; Dewar, Ken; Sabatti, Chiara; Wilson, Richard K.; Jentsch, J. David; Warren, Wesley; Coppola, Giovanni; Woods, Roger P.; Freimer, Nelson B.

2017-01-01

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders. PMID:29083405

A 100-year review: Methods and impact of genetic selection in dairy cattle—From daughter–dam comparisons to deep learning algorithms

USDA-ARS?s Scientific Manuscript database

In the early 1900s, breed society herdbooks had been established, and milk recording programs were in their infancy. Farmers were interested in improving the productivity of dairy cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not yet been laid. Li...

Comparative genetic analysis of lint yield and fiber quality among single, three-way, and double crosses in upland cotton

USDA-ARS?s Scientific Manuscript database

Decisions on the appropriate crossing systems to employ for genetic improvement of quantitative traits are critical in cotton breeding. Determination of genetic variance for lint yield and fiber quality in three different crossing schemes, i.e., single cross (SC), three-way cross (TWC), and double ...

Identification of Novel Associations of Candidate Genes with Resistance to Late Blight in Solanum tuberosum Group Phureja

PubMed Central

Álvarez, María F.; Angarita, Myrian; Delgado, María C.; García, Celsa; Jiménez-Gomez, José; Gebhardt, Christiane; Mosquera, Teresa

2017-01-01

The genetic basis of quantitative disease resistance has been studied in crops for several decades as an alternative to R gene mediated resistance. The most important disease in the potato crop is late blight, caused by the oomycete Phytophthora infestans. Quantitative disease resistance (QDR), as any other quantitative trait in plants, can be genetically mapped to understand the genetic architecture. Association mapping using DNA-based markers has been implemented in many crops to dissect quantitative traits. We used an association mapping approach with candidate genes to identify the first genes associated with quantitative resistance to late blight in Solanum tuberosum Group Phureja. Twenty-nine candidate genes were selected from a set of genes that were differentially expressed during the resistance response to late blight in tetraploid European potato cultivars. The 29 genes were amplified and sequenced in 104 accessions of S. tuberosum Group Phureja from Latin America. We identified 238 SNPs in the selected genes and tested them for association with resistance to late blight. The phenotypic data were obtained under field conditions by determining the area under disease progress curve (AUDPC) in two seasons and in two locations. Two genes were associated with QDR to late blight, a potato homolog of thylakoid lumen 15 kDa protein (StTL15A) and a stem 28 kDa glycoprotein (StGP28). Key message: A first association mapping experiment was conducted in Solanum tuberosum Group Phureja germplasm, which identified among 29 candidates two genes associated with quantitative resistance to late blight. PMID:28674545

Identification of Novel Associations of Candidate Genes with Resistance to Late Blight in Solanum tuberosum Group Phureja.

PubMed

Álvarez, María F; Angarita, Myrian; Delgado, María C; García, Celsa; Jiménez-Gomez, José; Gebhardt, Christiane; Mosquera, Teresa

2017-01-01

The genetic basis of quantitative disease resistance has been studied in crops for several decades as an alternative to R gene mediated resistance. The most important disease in the potato crop is late blight, caused by the oomycete Phytophthora infestans. Quantitative disease resistance (QDR), as any other quantitative trait in plants, can be genetically mapped to understand the genetic architecture. Association mapping using DNA-based markers has been implemented in many crops to dissect quantitative traits. We used an association mapping approach with candidate genes to identify the first genes associated with quantitative resistance to late blight in Solanum tuberosum Group Phureja. Twenty-nine candidate genes were selected from a set of genes that were differentially expressed during the resistance response to late blight in tetraploid European potato cultivars. The 29 genes were amplified and sequenced in 104 accessions of S. tuberosum Group Phureja from Latin America. We identified 238 SNPs in the selected genes and tested them for association with resistance to late blight. The phenotypic data were obtained under field conditions by determining the area under disease progress curve (AUDPC) in two seasons and in two locations. Two genes were associated with QDR to late blight, a potato homolog of thylakoid lumen 15 kDa protein ( StTL15A ) and a stem 28 kDa glycoprotein ( StGP28 ). Key message : A first association mapping experiment was conducted in Solanum tuberosum Group Phureja germplasm, which identified among 29 candidates two genes associated with quantitative resistance to late blight.

Identifying Genotype-by-Environment Interactions in the Metabolism of Germinating Arabidopsis Seeds Using Generalized Genetical Genomics 1[C][W][OA

PubMed Central

Joosen, Ronny Viktor Louis; Arends, Danny; Li, Yang; Willems, Leo A.J.; Keurentjes, Joost J.B.; Ligterink, Wilco; Jansen, Ritsert C.; Hilhorst, Henk W.M.

2013-01-01

A complex phenotype such as seed germination is the result of several genetic and environmental cues and requires the concerted action of many genes. The use of well-structured recombinant inbred lines in combination with “omics” analysis can help to disentangle the genetic basis of such quantitative traits. This so-called genetical genomics approach can effectively capture both genetic and epistatic interactions. However, to understand how the environment interacts with genomic-encoded information, a better understanding of the perception and processing of environmental signals is needed. In a classical genetical genomics setup, this requires replication of the whole experiment in different environmental conditions. A novel generalized setup overcomes this limitation and includes environmental perturbation within a single experimental design. We developed a dedicated quantitative trait loci mapping procedure to implement this approach and used existing phenotypical data to demonstrate its power. In addition, we studied the genetic regulation of primary metabolism in dry and imbibed Arabidopsis (Arabidopsis thaliana) seeds. In the metabolome, many changes were observed that were under both environmental and genetic controls and their interaction. This concept offers unique reduction of experimental load with minimal compromise of statistical power and is of great potential in the field of systems genetics, which requires a broad understanding of both plasticity and dynamic regulation. PMID:23606598

Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

PubMed

Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

2016-05-01

Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

Quantitative PCR for Genetic Markers of Human Fecal Pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantificationapproach. We report the development of quantitative PCR assays for quantification of two recently described human-...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

Coconut, date and oil palm genomics

USDA-ARS?s Scientific Manuscript database

A review of genomics research is presented for the three most economically important palm crops, coconut (Cocos nucifera), date palm (Phoenix dactylifera) and oil palm (Elaeis guineensis), encompassing molecular markers studies of genetic diversity, genetic mapping, quantitative trait loci discovery...

GENETIC ACTIVITY PROFILES AND HAZARD ASSESSMENT

EPA Science Inventory

A methodology has been developed to display and evaluate multiple test quantitative information on genetic toxicants for purposes of hazard/risk assessment. ose information is collected from the open literature: either the lowest effective dose (LED) or the highest ineffective do...

A CAL-Based Undergraduate Genetics Course.

ERIC Educational Resources Information Center

Garbutt, K.; And Others

1979-01-01

Describes a second-year undergraduate practical course in quantitative genetics and biometrics, based upon computer-assisted learning (CAL); and discusses the educational benefits of the course, some problems encountered, and some implications of the extensive use of CAL. (Author/CMV)

Quantitative Genetic Interactions Reveal Layers of Biological Modularity

PubMed Central

Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

2010-01-01

In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings

PubMed Central

Sariaslan, A; Larsson, H; Fazel, S

2016-01-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8–10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h2=53–71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30–0.33) than bipolar disorder (r=0.23; 0.21–0.25), and large proportions (51–67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21% 20–22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence. PMID:26666206

Development of an event-specific hydrolysis probe quantitative real-time polymerase chain reaction assay for Embrapa 5.1 genetically modified common bean (Phaseolus vulgaris).

PubMed

Treml, Diana; Venturelli, Gustavo L; Brod, Fábio C A; Faria, Josias C; Arisi, Ana C M

2014-12-10

A genetically modified (GM) common bean event, namely Embrapa 5.1, resistant to the bean golden mosaic virus (BGMV), was approved for commercialization in Brazil. Brazilian regulation for genetically modified organism (GMO) labeling requires that any food containing more than 1% GMO be labeled. The event-specific polymerase chain reaction (PCR) method has been the primary trend for GMO identification and quantitation because of its high specificity based on the flanking sequence. This work reports the development of an event-specific assay, named FGM, for Embrapa 5.1 detection and quantitation by use of SYBR Green or hydrolysis probe. The FGM assay specificity was tested for Embrapa 2.3 event (a noncommercial GM common bean also resistant to BGMV), 46 non-GM common bean varieties, and other crop species including maize, GM maize, soybean, and GM soybean. The FGM assay showed high specificity to detect the Embrapa 5.1 event. Standard curves for the FGM assay presented a mean efficiency of 95% and a limit of detection (LOD) of 100 genome copies in the presence of background DNA. The primers and probe developed are suitable for the detection and quantitation of Embrapa 5.1.

Quantitative PCR for genetic markers of human fecal pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantification approach. We report the development of quantitative PCR assays for enumeration of two recently described hum...

The Future of Genetics in Psychology and Psychiatry: Microarrays, Genome-Wide Association, and Non-Coding RNA

ERIC Educational Resources Information Center

Plomin, Robert; Davis, Oliver S. P.

2009-01-01

Background: Much of what we thought we knew about genetics needs to be modified in light of recent discoveries. What are the implications of these advances for identifying genes responsible for the high heritability of many behavioural disorders and dimensions in childhood? Methods: Although quantitative genetics such as twin studies will continue…

Long-Range Regulatory Polymorphisms Affecting a GABA Receptor Constitute a Quantitative Trait Locus (QTL) for Social Behavior in Caenorhabditis elegans

PubMed Central

Bendesky, Andres; Pitts, Jason; Rockman, Matthew V.; Chen, William C.; Tan, Man-Wah; Kruglyak, Leonid; Bargmann, Cornelia I.

2012-01-01

Aggregation is a social behavior that varies between and within species, providing a model to study the genetic basis of behavioral diversity. In the nematode Caenorhabditis elegans, aggregation is regulated by environmental context and by two neuromodulatory pathways, one dependent on the neuropeptide receptor NPR-1 and one dependent on the TGF-β family protein DAF-7. To gain further insight into the genetic regulation of aggregation, we characterize natural variation underlying behavioral differences between two wild-type C. elegans strains, N2 and CB4856. Using quantitative genetic techniques, including a survey of chromosome substitution strains and QTL analysis of recombinant inbred lines, we identify three new QTLs affecting aggregation in addition to the two known N2 mutations in npr-1 and glb-5. Fine-mapping with near-isogenic lines localized one QTL, accounting for 5%–8% of the behavioral variance between N2 and CB4856, 3′ to the transcript of the GABA neurotransmitter receptor gene exp-1. Quantitative complementation tests demonstrated that this QTL affects exp-1, identifying exp-1 and GABA signaling as new regulators of aggregation. exp-1 interacts genetically with the daf-7 TGF-β pathway, which integrates food availability and population density, and exp-1 mutations affect the level of daf-7 expression. Our results add to growing evidence that genetic variation affecting neurotransmitter receptor genes is a source of natural behavioral variation. PMID:23284308

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

PubMed

Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

2015-10-01

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

PubMed Central

Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

2010-01-01

The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses

PubMed Central

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-01-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population. PMID:28722705

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses.

PubMed

Zhang, S; Meng, L; Wang, J; Zhang, L

2017-10-01

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population.

Quantitative genetic correlation between trait and preference supports a sexually selected sperm process

PubMed Central

Simmons, Leigh W.; Kotiaho, Janne S.

2007-01-01

Sperm show patterns of rapid and divergent evolution that are characteristic of sexual selection. Sperm competition has been proposed as an important selective agent in the evolution of sperm morphology. However, several comparative analyses have revealed evolutionary associations between sperm length and female reproductive tract morphology that suggest patterns of male–female coevolution. In the dung beetle Onthophagus taurus, males with short sperm have a fertilization advantage that depends on the size of the female's sperm storage organ, the spermatheca; large spermathecae select for short sperm. Sperm length is heritable and is genetically correlated with male condition. Here we report significant additive genetic variation and heritability for spermatheca size and genetic covariance between spermatheca size and sperm length predicted by both the “good-sperm” and “sexy-sperm” models of postcopulatory female preference. Our data thus provide quantitative genetic support for the role of a sexually selected sperm process in the evolutionary divergence of sperm morphology, in much the same manner as precopulatory female preferences drive the evolutionary divergence of male secondary sexual traits. PMID:17921254

Path analysis of the genetic integration of traits in the sand cricket: a novel use of BLUPs.

PubMed

Roff, D A; Fairbairn, D J

2011-09-01

This study combines path analysis with quantitative genetics to analyse a key life history trade-off in the cricket, Gryllus firmus. We develop a path model connecting five traits associated with the trade-off between flight capability and reproduction and test this model using phenotypic data and estimates of breeding values (best linear unbiased predictors) from a half-sibling experiment. Strong support by both types of data validates our causal model and indicates concordance between the phenotypic and genetic expression of the trade-off. Comparisons of the trade-off between sexes and wing morphs reveal that these discrete phenotypes are not genetically independent and that the evolutionary trajectories of the two wing morphs are more tightly constrained to covary than those of the two sexes. Our results illustrate the benefits of combining a quantitative genetic analysis, which examines statistical correlations between traits, with a path model that focuses upon the causal components of variation. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction

PubMed Central

Hill, William G.

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives’ performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher’s infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with “genomic selection” is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas. PMID:24395822

Assessment of a Competency-Based Undergraduate Course on Genetic and Genomics.

PubMed

Kronk, Rebecca; Colbert, Alison; Lengetti, Evelyn

2017-08-24

In response to new demands in the nursing profession, an innovative undergraduate genetics course was designed based on the Essential Nursing Competencies and Curricula Guidelines for Genetics and Genomics. Reflective journaling and storytelling were used as major pedagogies, alongside more traditional approaches. Thematic content analysis of student reflections revealed transformational learning as the major theme emerging from genomic and genetic knowledge acquisition. Quantitative analyses of precourse/postcourse student self-assessments of competencies revealed significant findings.

Genetic and Environmental Influences on Smoking Behavior across Adolescence and Young Adulthood in the Virginia Twin Study of Adolescent Behavioral Development and the Transitions to Substance Abuse Follow-Up

PubMed Central

Do, Elizabeth K.; Prom-Wormley, Elizabeth C.; Eaves, Lindon J.; Silberg, Judy L.; Miles, Donna R.; Maes, Hermine H.

2016-01-01

Little is known regarding the underlying relationship between smoking initiation and current quantity smoked during adolescence into young adulthood. It is possible that the influences of genetic and environmental factors on this relationship vary across sex and age. To investigate this further, the current study applied a common causal contingency model to data from a Virginia-based twin study to determine: (1) if the same genetic and environmental factors are contributing to smoking initiation and current quantity smoked; (2) whether the magnitude of genetic and environmental factor contributions are the same across adolescence and young adulthood; and (3) if qualitative and quantitative differences in the sources of variance between males and females exist. Study results found no qualitative or quantitative sex differences in the relationship between smoking initiation and current quantity smoked, though relative contributions of genetic and environmental factors changed across adolescence and young adulthood. More specifically, smoking initiation and current quantity smoked remain separate constructs until young adulthood, when liabilities are correlated. Smoking initiation is explained by genetic, shared, and unique environmental factors in early adolescence and by genetic and unique environmental factors in young adulthood; while current quantity smoked is explained by shared environmental and unique environmental factors until young adulthood, when genetic and unique environmental factors play a larger role. PMID:25662421

Genetic and Environmental Influences on Smoking Behavior across Adolescence and Young Adulthood in the Virginia Twin Study of Adolescent Behavioral Development and the Transitions to Substance Abuse Follow-Up.

PubMed

Do, Elizabeth K; Prom-Wormley, Elizabeth C; Eaves, Lindon J; Silberg, Judy L; Miles, Donna R; Maes, Hermine H

2015-02-01

Little is known regarding the underlying relationship between smoking initiation and current quantity smoked during adolescence into young adulthood. It is possible that the influences of genetic and environmental factors on this relationship vary across sex and age. To investigate this further, the current study applied a common causal contingency model to data from a Virginia-based twin study to determine: (1) if the same genetic and environmental factors are contributing to smoking initiation and current quantity smoked; (2) whether the magnitude of genetic and environmental factor contributions are the same across adolescence and young adulthood; and (3) if qualitative and quantitative differences in the sources of variance between males and females exist. Study results found no qualitative or quantitative sex differences in the relationship between smoking initiation and current quantity smoked, though relative contributions of genetic and environmental factors changed across adolescence and young adulthood. More specifically, smoking initiation and current quantity smoked remain separate constructs until young adulthood, when liabilities are correlated. Smoking initiation is explained by genetic, shared, and unique environmental factors in early adolescence and by genetic and unique environmental factors in young adulthood; while current quantity smoked is explained by shared environmental and unique environmental factors until young adulthood, when genetic and unique environmental factors play a larger role.

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.

Human fecal source identification with real-time quantitative PCR

EPA Science Inventory

Waterborne diseases represent a significant public health risk worldwide, and can originate from contact with water contaminated with human fecal material. We describe a real-time quantitative PCR (qPCR) method that targets a Bacteroides dori human-associated genetic marker for...

Ensemble learning of QTL models improves prediction of complex traits

USDA-ARS?s Scientific Manuscript database

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability, but are less useful for genetic prediction due to difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage ...

Quality of Life and Psychological State in Chinese Breast Cancer Patients Who Received BRCA1/2 Genetic Testing

PubMed Central

Qiu, Jiajia; Guan, Jiaqin; Yang, Xiaochen; Wu, Jiong; Liu, Guangyu; Di, Genhong; Chen, Canming; Hou, Yifeng; Han, Qixia; Shen, Zhenzhou; Shao, Zhimin; Hu, Zhen

2016-01-01

Background This study aims to understand the quality of life (QOL) and psychological state (PS) of Chinese breast cancer patients who received BRCA1/2 genetic testing; to examine the psychological changes between BRCA1/2 mutation carriers and non-carriers; and to further explore the psychological experience of BRCA1/2 mutation carriers. Methods This study was combined with quantitative and qualitative designs. First, we performed a quantitative investigation using FACT-B (Chinese version) and Irritability, Depression and Anxiety scale (IDA) to assess the QOL and PS in breast cancer patients who received BRCA1/2 genetic testing. Then semi-structured in-depth qualitative interviews among 13 mutation carriers were conducted in hospital. Results Results from the quantitative study showed QOL scores were relatively high and the IDA scores were relatively low among the patients, and there was no significant difference in the QOL or IDA scores between non-carriers and carriers. Based on the qualitative analysis, four main themes emerged: (1) Finding the reason for having breast cancer; (2) Negative emotions; (3) Behavioral changes; (4) Lack of information. Conclusions The present study showed that QOL and PS are good among the breast cancer patients who received genetic testing. Genetic testing itself does not cause long psychosocial effects. BRCA1/2 mutation carriers may have certain negative emotions at the first stage they knew the testing results and may initiate behavioral and lifestyle changes. The patients with a BRCA1/2 mutation desire knowledge with regard to genetic aspects in mainland China. Professional information and advice can be provided to relieve the patients’ negative emotions when they were informed of gene defect. PMID:27428375

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

A hot topic: the genetics of adaptation to geothermal vents in Mimulus guttatus.

PubMed

Ferris, Kathleen G

2016-11-01

Identifying the individual loci and mutations that underlie adaptation to extreme environments has long been a goal of evolutionary biology. However, finding the genes that underlie adaptive traits is difficult for several reasons. First, because many traits and genes evolve simultaneously as populations diverge, it is difficult to disentangle adaptation from neutral demographic processes. Second, finding the individual loci involved in any trait is challenging given the respective limitations of quantitative and population genetic methods. In this issue of Molecular Ecology, Hendrick et al. (2016) overcome these difficulties and determine the genetic basis of microgeographic adaptation between geothermal vent and nonthermal populations of Mimulus guttatus in Yellowstone National Park. The authors accomplish this by combining population and quantitative genetic techniques, a powerful, but labour-intensive, strategy for identifying individual causative adaptive loci that few studies have used (Stinchcombe & Hoekstra ). In a previous common garden experiment (Lekberg et al. 2012), thermal M. guttatus populations were found to differ from their closely related nonthermal neighbours in various adaptive phenotypes including trichome density. Hendrick et al. (2016) combine quantitative trait loci (QTL) mapping, population genomic scans for selection and admixture mapping to identify a single genetic locus underlying differences in trichome density between thermal and nonthermal M. guttatus. The candidate gene, R2R3 MYB, is homologous to genes involved in trichome development across flowering plants. The major trichome QTL, Tr14, is also involved in trichome density differences in an independent M. guttatus population comparison (Holeski et al. 2010) making this an example of parallel genetic evolution. © 2016 John Wiley & Sons Ltd.

A quantitative genetic analysis of hibernation emergence date in a wild population of Columbian ground squirrels.

PubMed

Lane, J E; Kruuk, L E B; Charmantier, A; Murie, J O; Coltman, D W; Buoro, M; Raveh, S; Dobson, F S

2011-09-01

The life history schedules of wild organisms have long attracted scientific interest, and, in light of ongoing climate change, an understanding of their genetic and environmental underpinnings is increasingly becoming of applied concern. We used a multi-generation pedigree and detailed phenotypic records, spanning 18 years, to estimate the quantitative genetic influences on the timing of hibernation emergence in a wild population of Columbian ground squirrels (Urocitellus columbianus). Emergence date was significantly heritable [h(2) = 0.22 ± 0.05 (in females) and 0.34 ± 0.14 (in males)], and there was a positive genetic correlation (r(G) = 0.76 ± 0.22) between male and female emergence dates. In adult females, the heritabilities of body mass at emergence and oestrous date were h(2) = 0.23 ± 0.09 and h(2) = 0.18 ± 0.12, respectively. The date of hibernation emergence has been hypothesized to have evolved so as to synchronize subsequent reproduction with upcoming peaks in vegetation abundance. In support of this hypothesis, although levels of phenotypic variance in emergence date were higher than oestrous date, there was a highly significant genetic correlation between the two (r(G) = 0.98 ± 0.01). Hibernation is a prominent feature in the annual cycle of many small mammals, but our understanding of its influences lags behind that for phenological traits in many other taxa. Our results provide the first insight into its quantitative genetic influences and thus help contribute to a more general understanding of its evolutionary significance. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

PubMed Central

Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A.

2016-01-01

The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647

Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait

PubMed Central

Hernández-Serrano, Ana; Verdú, Miguel; Santos-del-Blanco, Luís; Climent, José; González-Martínez, Santiago C.; Pausas, Juli G.

2014-01-01

Background and Aims Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST–FST comparison). Methods A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h2) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an ‘animal model’ fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. Key Results Serotiny showed a significant narrow-sense heritability (h2) of 0·20 (credible interval 0·09–0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. Conclusions Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels among populations depending on the fire regime, and supporting the role of fire in generating genetic divergence for adaptive traits. PMID:25008363

QUANTITATIVE CANCER RISK ASSESSMENT METHODOLOGY USING SHORT-TERM GENETIC BIOASSAYS: THE COMPARATIVE POTENCY METHOD

EPA Science Inventory

Quantitative risk assessment is fraught with many uncertainties. The validity of the assumptions underlying the methods employed are often difficult to test or validate. Cancer risk assessment has generally employed either human epidemiological data from relatively high occupatio...

A quantitative framework for the forward design of synthetic miRNA circuits.

PubMed

Bloom, Ryan J; Winkler, Sally M; Smolke, Christina D

2014-11-01

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast

PubMed Central

Jeffares, Daniel C.; Jolly, Clemency; Hoti, Mimoza; Speed, Doug; Shaw, Liam; Rallis, Charalampos; Balloux, Francois; Dessimoz, Christophe; Bähler, Jürg; Sedlazeck, Fritz J.

2017-01-01

Large structural variations (SVs) within genomes are more challenging to identify than smaller genetic variants but may substantially contribute to phenotypic diversity and evolution. We analyse the effects of SVs on gene expression, quantitative traits and intrinsic reproductive isolation in the yeast Schizosaccharomyces pombe. We establish a high-quality curated catalogue of SVs in the genomes of a worldwide library of S. pombe strains, including duplications, deletions, inversions and translocations. We show that copy number variants (CNVs) show a variety of genetic signals consistent with rapid turnover. These transient CNVs produce stoichiometric effects on gene expression both within and outside the duplicated regions. CNVs make substantial contributions to quantitative traits, most notably intracellular amino acid concentrations, growth under stress and sugar utilization in winemaking, whereas rearrangements are strongly associated with reproductive isolation. Collectively, these findings have broad implications for evolution and for our understanding of quantitative traits including complex human diseases. PMID:28117401

Quantitative genetics and utilization of mutants

USDA-ARS?s Scientific Manuscript database

The relatively low level of genetic variability currently available in cotton makes mutagenesis attractive to overcome this problem. Mutations can occur either spontaneously or be induced. The majority of the genes we use today are spontaneous mutants that developed over a long period of time. Induc...

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

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

PubMed Central

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

2015-01-01

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

Coalescent patterns for chromosomal inversions in divergent populations

PubMed Central

Guerrero, Rafael F.; Rousset, François; Kirkpatrick, Mark

2012-01-01

Chromosomal inversions allow genetic divergence of locally adapted populations by reducing recombination between chromosomes with different arrangements. Divergence between populations (or hybridization between species) is expected to leave signatures in the neutral genetic diversity of the inverted region. Quantitative expectations for these patterns, however, have not been obtained. Here, we develop coalescent models of neutral sites linked to an inversion polymorphism in two locally adapted populations. We consider two scenarios of local adaptation: selection on the inversion breakpoints and selection on alleles inside the inversion. We find that ancient inversion polymorphisms cause genetic diversity to depart dramatically from neutral expectations. Other situations, however, lead to patterns that may be difficult to detect; important determinants are the age of the inversion and the rate of gene flux between arrangements. We also study inversions under genetic drift, finding that they produce patterns similar to locally adapted inversions of intermediate age. Our results are consistent with empirical observations, and provide the foundation for quantitative analyses of the roles that inversions have played in speciation. PMID:22201172

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

PubMed

Zhang, Xuehai; Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Xiong, Lizhong; Yang, Wanneng; Yan, Jianbing

2017-03-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize ( Zea mays ) recombinant inbred line population ( n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. © 2017 American Society of Plant Biologists. All Rights Reserved.

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth1[OPEN

PubMed Central

Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Yang, Wanneng

2017-01-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923

Prospects and challenges of quantitative phase imaging in tumor cell biology

NASA Astrophysics Data System (ADS)

Kemper, Björn; Götte, Martin; Greve, Burkhard; Ketelhut, Steffi

2016-03-01

Quantitative phase imaging (QPI) techniques provide high resolution label-free quantitative live cell imaging. Here, prospects and challenges of QPI in tumor cell biology are presented, using the example of digital holographic microscopy (DHM). It is shown that the evaluation of quantitative DHM phase images allows the retrieval of different parameter sets for quantification of cellular motion changes in migration and motility assays that are caused by genetic modifications. Furthermore, we demonstrate simultaneously label-free imaging of cell growth and morphology properties.

Integrated electrochemical microsystems for genetic detection of pathogens at the point of care.

PubMed

Hsieh, Kuangwen; Ferguson, B Scott; Eisenstein, Michael; Plaxco, Kevin W; Soh, H Tom

2015-04-21

The capacity to achieve rapid, sensitive, specific, quantitative, and multiplexed genetic detection of pathogens via a robust, portable, point-of-care platform could transform many diagnostic applications. And while contemporary technologies have yet to effectively achieve this goal, the advent of microfluidics provides a potentially viable approach to this end by enabling the integration of sophisticated multistep biochemical assays (e.g., sample preparation, genetic amplification, and quantitative detection) in a monolithic, portable device from relatively small biological samples. Integrated electrochemical sensors offer a particularly promising solution to genetic detection because they do not require optical instrumentation and are readily compatible with both integrated circuit and microfluidic technologies. Nevertheless, the development of generalizable microfluidic electrochemical platforms that integrate sample preparation and amplification as well as quantitative and multiplexed detection remains a challenging and unsolved technical problem. Recognizing this unmet need, we have developed a series of microfluidic electrochemical DNA sensors that have progressively evolved to encompass each of these critical functionalities. For DNA detection, our platforms employ label-free, single-step, and sequence-specific electrochemical DNA (E-DNA) sensors, in which an electrode-bound, redox-reporter-modified DNA "probe" generates a current change after undergoing a hybridization-induced conformational change. After successfully integrating E-DNA sensors into a microfluidic chip format, we subsequently incorporated on-chip genetic amplification techniques including polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP) to enable genetic detection at clinically relevant target concentrations. To maximize the potential point-of-care utility of our platforms, we have further integrated sample preparation via immunomagnetic separation, which allowed the detection of influenza virus directly from throat swabs and developed strategies for the multiplexed detection of related bacterial strains from the blood of septic mice. Finally, we developed an alternative electrochemical detection platform based on real-time LAMP, which not is only capable of detecting across a broad dynamic range of target concentrations, but also greatly simplifies quantitative measurement of nucleic acids. These efforts represent considerable progress toward the development of a true sample-in-answer-out platform for genetic detection of pathogens at the point of care. Given the many advantages of these systems, and the growing interest and innovative contributions from researchers in this field, we are optimistic that iterations of these systems will arrive in clinical settings in the foreseeable future.

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

PubMed Central

Sim, Sheina B.; Geib, Scott M.

2017-01-01

Genetic sexing strains (GSS) used in sterile insect technique (SIT) programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp), also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera. PMID:28450369

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

PubMed

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Genetic data analysis for plant and animal breeding

USDA-ARS?s Scientific Manuscript database

This book is an advanced textbook covering the application of quantitative genetics theory to analysis of actual data (both trait and DNA marker information) for breeding populations of crops, trees, and animals. Chapter 1 is an introduction to basic software used for trait data analysis. Chapter 2 ...

Quantifying and predicting Drosophila larvae crawling phenotypes

NASA Astrophysics Data System (ADS)

Günther, Maximilian N.; Nettesheim, Guilherme; Shubeita, George T.

2016-06-01

The fruit fly Drosophila melanogaster is a widely used model for cell biology, development, disease, and neuroscience. The fly’s power as a genetic model for disease and neuroscience can be augmented by a quantitative description of its behavior. Here we show that we can accurately account for the complex and unique crawling patterns exhibited by individual Drosophila larvae using a small set of four parameters obtained from the trajectories of a few crawling larvae. The values of these parameters change for larvae from different genetic mutants, as we demonstrate for fly models of Alzheimer’s disease and the Fragile X syndrome, allowing applications such as genetic or drug screens. Using the quantitative model of larval crawling developed here we use the mutant-specific parameters to robustly simulate larval crawling, which allows estimating the feasibility of laborious experimental assays and aids in their design.

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations

PubMed Central

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A.

2012-01-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure. PMID:22927824

Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure.

PubMed

Iancu, Ovidiu D; Darakjian, Priscila; Kawane, Sunita; Bottomly, Daniel; Hitzemann, Robert; McWeeney, Shannon

2012-01-01

Complex Mus musculus crosses, e.g., heterogeneous stock (HS), provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, HS populations have complex genetic architectures not fully captured by the whole genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F(2) intercross, a HS formed by crossing four inbred strains (HS4), and a HS (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome specific relatedness can result in improved eQTL detection.

Construction of a high-density linkage map and mapping quantitative trait loci for somatic embryogenesis using leaf petioles as explants in upland cotton (Gossypium hirsutum L.).

PubMed

Xu, Zhenzhen; Zhang, Chaojun; Ge, Xiaoyang; Wang, Ni; Zhou, Kehai; Yang, Xiaojie; Wu, Zhixia; Zhang, Xueyan; Liu, Chuanliang; Yang, Zuoren; Li, Changfeng; Liu, Kun; Yang, Zhaoen; Qian, Yuyuan; Li, Fuguang

2015-07-01

The first high-density linkage map was constructed to identify quantitative trait loci (QTLs) for somatic embryogenesis (SE) in cotton ( Gossypium hirsutum L.) using leaf petioles as explants. Cotton transformation is highly limited by only a few regenerable genotypes and the lack of understanding of the genetic and molecular basis of somatic embryogenesis (SE) in cotton (Gossypium hirsutum L.). To construct a more saturated linkage map and further identify quantitative trait loci (QTLs) for SE using leaf petioles as explants, a high embryogenesis frequency line (W10) from the commercial Chinese cotton cultivar CRI24 was crossed with TM-1, a genetic standard upland cotton with no embryogenesis frequency. The genetic map spanned 2300.41 cM in genetic distance and contained 411 polymorphic simple sequence repeat (SSR) loci. Of the 411 mapped loci, 25 were developed from unigenes identified for SE in our previous study. Six QTLs for SE were detected by composite interval mapping method, each explaining 6.88-37.07% of the phenotypic variance. Single marker analysis was also performed to verify the reliability of QTLs detection, and the SSR markers NAU3325 and DPL0209 were detected by the two methods. Further studies on the relatively stable and anchoring QTLs/markers for SE in an advanced population of W10 × TM-1 and other cross combinations with different SE abilities may shed light on the genetic and molecular mechanism of SE in cotton.

A quantitative comparison of the similarity between genes and geography in worldwide human populations.

PubMed

Wang, Chaolong; Zöllner, Sebastian; Rosenberg, Noah A

2012-08-01

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

Beyond Punnett squares: Student word association and explanations of phenotypic variation through an integrative quantitative genetics unit investigating anthocyanin inheritance and expression in Brassica rapa Fast plants.

PubMed

Batzli, Janet M; Smith, Amber R; Williams, Paul H; McGee, Seth A; Dósa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students' cognitive structures before and after the unit and explanations in students' final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on "variation" as a proposed threshold concept and primary goal for students' explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from "plug and play," this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. © 2014 J. M. Batzli et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Genetics of Genome-Wide Recombination Rate Evolution in Mice from an Isolated Island.

PubMed

Wang, Richard J; Payseur, Bret A

2017-08-01

Recombination rate is a heritable quantitative trait that evolves despite the fundamentally conserved role that recombination plays in meiosis. Differences in recombination rate can alter the landscape of the genome and the genetic diversity of populations. Yet our understanding of the genetic basis of recombination rate evolution in nature remains limited. We used wild house mice ( Mus musculus domesticus ) from Gough Island (GI), which diverged recently from their mainland counterparts, to characterize the genetics of recombination rate evolution. We quantified genome-wide autosomal recombination rates by immunofluorescence cytology in spermatocytes from 240 F 2 males generated from intercrosses between GI-derived mice and the wild-derived inbred strain WSB/EiJ. We identified four quantitative trait loci (QTL) responsible for inter-F 2 variation in this trait, the strongest of which had effects that opposed the direction of the parental trait differences. Candidate genes and mutations for these QTL were identified by overlapping the detected intervals with whole-genome sequencing data and publicly available transcriptomic profiles from spermatocytes. Combined with existing studies, our findings suggest that genome-wide recombination rate divergence is not directional and its evolution within and between subspecies proceeds from distinct genetic loci. Copyright © 2017 by the Genetics Society of America.

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

PubMed

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Advances in Genetical Genomics of Plants

PubMed Central

Joosen, R.V.L.; Ligterink, W.; Hilhorst, H.W.M.; Keurentjes, J.J.B.

2009-01-01

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research. PMID:20514216

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Interdependence of PRECIS Role Operators: A Quantitative Analysis of Their Associations.

ERIC Educational Resources Information Center

Mahapatra, Manoranjan; Biswas, Subal Chandra

1986-01-01

Analyzes associations among different role operators quantitatively by taking input strings from 200 abstracts, each related to subject fields of taxation, genetic psychology, and Shakespearean drama, and subjecting them to the Chi-square test. Significant associations by other differencing operators and connectives are discussed. A schema of role…

Detection of QTL for forage yield, lodging resistance and spring vigor traits in alfalfa (Medicago sativa L.)

USDA-ARS?s Scientific Manuscript database

Alfalfa (Medicago sativa L.) is an internationally significant forage crop. Forage yield, lodging resistance and spring vigor are important agronomic traits conditioned by quantitative genetic and environmental effects. The objective of this study was to identify quantitative trait loci (QTL) and mo...

Genes, Environment, and Race: Quantitative Genetic Approaches

ERIC Educational Resources Information Center

Whitfield, Keith E.; McClearn, Gerald

2005-01-01

Understanding the origins of racial health disparities is currently a central focus of health-oriented funding agencies and the health policy community. In particular, the role of genetics in the origin of racial health disparities is receiving growing attention and has been susceptible to considerable misinterpretation. In this article, the…

Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

USDA-ARS?s Scientific Manuscript database

The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

Predictive Heterosis in Multibreed Evaluations Using Quantitative and Molecular Approaches

USDA-ARS?s Scientific Manuscript database

Heterosis is the extra genetic boost in performance obtained by crossing two cattle breeds. It is an important tool for increasing the efficiency of beef production. It is also important to adjust data used to calculate genetic evaluations for differences in heterosis. Good estimates of heterosis...

Physical Aggression and Expressive Vocabulary in 19-Month-Old Twins.

ERIC Educational Resources Information Center

Dionne, Ginette; Tremblay, Richard; Boivin, Michel; Laplante, David; Perusse, Daniel

2003-01-01

Used a genetic design to investigate association between physical aggression and language development in 19-month-old twins. Found a modest but significant correlation between aggression and expressive vocabulary. Substantial heritability was found for physical aggression. Quantitative genetic modeling suggested that the correlation could not be…

The Consortium on the Genetics of Schizophrenia: Neurocognitive Endophenotypes

PubMed Central

Gur, Raquel E.; Calkins, Monica E.; Gur, Ruben C.; Horan, William P.; Nuechterlein, Keith H.; Seidman, Larry J.; Stone, William S.

2007-01-01

The Consortium on the Genetics of Schizophrenia (COGS) is a 7-site collaboration that examines the genetic architecture of quantitative endophenotypes in families with schizophrenia. Here we review the background and rationale for selecting neurocognitive tasks as endophenotypic measures in genetic studies. Criteria are outlined for the potential of measures as endophenotypic vulnerability markers. These include association with illness, state independence (ie, adequate test-retest stability, adequate between-site reliability, impairments in patients not due to medications, impairments observed regardless of illness state), heritability, findings of higher rates in relatives of probands than in the general population, and cosegregation within families. The COGS required that, in addition, the measures be “neurocognitive” and thus linked to neurobiology and that they be feasible in multisite studies. The COGS neurocognitive assessment includes measures of attention, verbal memory, working memory, and a computerized neurocognitive battery that also includes facial processing tasks. Here we describe data demonstrating that these neurobehavioral measures meet criteria for endophenotypic candidacy. We conclude that quantitative neurocognitive endophenotypes need further evidence for efficacy in identifying genetic effects but have the potential of providing unprecedented insight into gene-environment interaction related to dimensions of brain and behavior in health and disease. PMID:17101692

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

PubMed Central

Charmantier, Anne; Perrins, Christopher; McCleery, Robin H.; Sheldon, Ben C.

2006-01-01

Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs. PMID:16618935

Development of a colloidal gold immunochromatographic strip assay for simple and fast detection of human α-lactalbumin in genetically modified cow milk.

PubMed

Tao, Chenyu; Zhang, Qingde; Feng, Na; Shi, Deshi; Liu, Bang

2016-03-01

The qualitative and quantitative declaration of food ingredients is important to consumers, especially for genetically modified food as it experiences a rapid increase in sales. In this study, we designed an accurate and rapid detection system using colloidal gold immunochromatographic strip assay (GICA) methods to detect genetically modified cow milk. First, we prepared 2 monoclonal antibodies for human α-lactalbumin (α-LA) and measured their antibody titers; the one with the higher titer was used for further experiments. Then, we found the optimal pH value and protein amount of GICA for detection of pure milk samples. The developed strips successfully detected genetically modified cow milk and non-modified cow milk. To determine the sensitivity of GICA, a quantitative ELISA system was used to determine the exact amount of α-LA, and then genetically modified milk was diluted at different rates to test the sensitivity of GICA; the sensitivity was 10 μg/mL. Our results demonstrated that the applied method was effective to detect human α-LA in cow milk. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis

PubMed Central

Routaboul, Jean-Marc; Dubos, Christian; Beck, Gilles; Marquis, Catherine; Bidzinski, Przemyslaw; Loudet, Olivier; Lepiniec, Loïc

2012-01-01

Little is known about the range and the genetic bases of naturally occurring variation for flavonoids. Using Arabidopsis thaliana seed as a model, the flavonoid content of 41 accessions and two recombinant inbred line (RIL) sets derived from divergent accessions (Cvi-0×Col-0 and Bay-0×Shahdara) were analysed. These accessions and RILs showed mainly quantitative rather than qualitative changes. To dissect the genetic architecture underlying these differences, a quantitative trait locus (QTL) analysis was performed on the two segregating populations. Twenty-two flavonoid QTLs were detected that accounted for 11–64% of the observed trait variations, only one QTL being common to both RIL sets. Sixteen of these QTLs were confirmed and coarsely mapped using heterogeneous inbred families (HIFs). Three genes, namely TRANSPARENT TESTA (TT)7, TT15, and MYB12, were proposed to underlie their variations since the corresponding mutants and QTLs displayed similar specific flavonoid changes. Interestingly, most loci did not co-localize with any gene known to be involved in flavonoid metabolism. This latter result shows that novel functions have yet to be characterized and paves the way for their isolation. PMID:22442426

Quantifying cryptic Symbiodinium diversity within Orbicella faveolata and Orbicella franksi at the Flower Garden Banks, Gulf of Mexico

PubMed Central

Green, Elizabeth A.; Davies, Sarah W.; Matz, Mikhail V.

2014-01-01

The genetic composition of the resident Symbiodinium endosymbionts can strongly modulate the physiological performance of reef-building corals. Here, we used quantitative metabarcoding to investigate Symbiodinium genetic diversity in two species of mountainous star corals, Orbicella franksi and Orbicella faveolata, from two reefs separated by 19 km of deep water. We aimed to determine if the frequency of different symbiont genotypes varied with respect to coral host species or geographic location. Our results demonstrate that across the two reefs both coral species contained seven haplotypes of Symbiodinium, all identifiable as clade B and most closely related to type B1. Five of these haplotypes have not been previously described and may be endemic to the Flower Garden Banks. No significant differences in symbiont composition were detected between the two coral species. However, significant quantitative differences were detected between the east and west banks for three background haplotypes comprising 0.1%–10% of the total. The quantitative metabarcoding approach described here can help to sensitively characterize cryptic genetic diversity of Symbiodinium and potentially contribute to the understanding of physiological variations among coral populations. PMID:24883247

Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1.

PubMed

Kronholm, Ilkka; Picó, F Xavier; Alonso-Blanco, Carlos; Goudet, Jérôme; de Meaux, Juliette

2012-07-01

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation. © 2012 The Author(s).

Quantifying cryptic Symbiodinium diversity within Orbicella faveolata and Orbicella franksi at the Flower Garden Banks, Gulf of Mexico.

PubMed

Green, Elizabeth A; Davies, Sarah W; Matz, Mikhail V; Medina, Mónica

2014-01-01

The genetic composition of the resident Symbiodinium endosymbionts can strongly modulate the physiological performance of reef-building corals. Here, we used quantitative metabarcoding to investigate Symbiodinium genetic diversity in two species of mountainous star corals, Orbicella franksi and Orbicella faveolata, from two reefs separated by 19 km of deep water. We aimed to determine if the frequency of different symbiont genotypes varied with respect to coral host species or geographic location. Our results demonstrate that across the two reefs both coral species contained seven haplotypes of Symbiodinium, all identifiable as clade B and most closely related to type B1. Five of these haplotypes have not been previously described and may be endemic to the Flower Garden Banks. No significant differences in symbiont composition were detected between the two coral species. However, significant quantitative differences were detected between the east and west banks for three background haplotypes comprising 0.1%-10% of the total. The quantitative metabarcoding approach described here can help to sensitively characterize cryptic genetic diversity of Symbiodinium and potentially contribute to the understanding of physiological variations among coral populations.

Dual gene activation and knockout screen reveals directional dependencies in genetic networks. | Office of Cancer Genomics

Cancer.gov

Understanding the direction of information flow is essential for characterizing how genetic networks affect phenotypes. However, methods to find genetic interactions largely fail to reveal directional dependencies. We combine two orthogonal Cas9 proteins from Streptococcus pyogenes and Staphylococcus aureus to carry out a dual screen in which one gene is activated while a second gene is deleted in the same cell. We analyze the quantitative effects of activation and knockout to calculate genetic interaction and directionality scores for each gene pair.

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

PubMed

Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

2016-01-01

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

PubMed

Wu, Wensheng; Zhang, Canyang; Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.

Quantitative Structure-Property Relationship (QSPR) Modeling of Drug-Loaded Polymeric Micelles via Genetic Function Approximation

PubMed Central

Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments. PMID:25780923

Development and Evaluation of Event-Specific Quantitative PCR Method for Genetically Modified Soybean MON87701.

PubMed

Tsukahara, Keita; Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Nishimaki-Mogami, Tomoko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event, MON87701. First, a standard plasmid for MON87701 quantification was constructed. The conversion factor (C f ) required to calculate the amount of genetically modified organism (GMO) was experimentally determined for a real-time PCR instrument. The determined C f for the real-time PCR instrument was 1.24. For the evaluation of the developed method, a blind test was carried out in an inter-laboratory trial. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr), respectively. The determined biases and the RSDr values were less than 30 and 13%, respectively, at all evaluated concentrations. The limit of quantitation of the method was 0.5%, and the developed method would thus be applicable for practical analyses for the detection and quantification of MON87701.

Development and interlaboratory validation of quantitative polymerase chain reaction method for screening analysis of genetically modified soybeans.

PubMed

Takabatake, Reona; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2013-01-01

A novel real-time polymerase chain reaction (PCR)-based quantitative screening method was developed for three genetically modified soybeans: RRS, A2704-12, and MON89788. The 35S promoter (P35S) of cauliflower mosaic virus is introduced into RRS and A2704-12 but not MON89788. We then designed a screening method comprised of the combination of the quantification of P35S and the event-specific quantification of MON89788. The conversion factor (Cf) required to convert the amount of a genetically modified organism (GMO) from a copy number ratio to a weight ratio was determined experimentally. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDR), respectively. The determined RSDR values for the method were less than 25% for both targets. We consider that the developed method would be suitable for the simple detection and approximate quantification of GMO.

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

PubMed

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

PubMed

Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

2017-07-01

One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events. Copyright © 2017 Elsevier Ltd. All rights reserved.

In-Silico Genomic Approaches To Understanding Lactation, Mammary Development, And Breast Cancer

USDA-ARS?s Scientific Manuscript database

Lactation-related traits are influenced by genetics. From a quantitative standpoint, these traits have been well studied in dairy species, but there has also been work on the genetics of lactation in humans and mice. In addition, there is evidence to support the notion that other mammary gland trait...

Comparative Effectiveness of Context-Based and Traditional Approaches in Teaching Genetics: Student Views and Achievement

ERIC Educational Resources Information Center

Kazeni, Monde; Onwu, Gilbert

2013-01-01

The study aimed to determine the comparative effectiveness of context-based and traditional teaching approaches in enhancing student achievement in genetics, problem-solving, science inquiry and decision-making skills, and attitude towards the study of life sciences. A mixed method but essentially quantitative research approach involving a…

Charles W. Stuber: Maize geneticist and pioneer of marker-assisted selection

USDA-ARS?s Scientific Manuscript database

Charles W. Stuber is considered a pioneer of quantitative genetic mapping and marker-assisted selection in maize. The achievements of his four decade career in research include the development of genetic marker systems used in maize and adapted in many other crops, the first methods and studies to i...

Twin Studies and Their Implications for Molecular Genetic Studies: Endophenotypes Integrate Quantitative and Molecular Genetics in ADHD Research

ERIC Educational Resources Information Center

Wood, Alexis C.; Neale, Michael C.

2010-01-01

Objective: To describe the utility of twin studies for attention-deficit/hyperactivity disorder (ADHD) research and demonstrate their potential for the identification of alternative phenotypes suitable for genomewide association, developmental risk assessment, treatment response, and intervention targets. Method: Brief descriptions of the classic…

Genetics, Environment, and Behavior: Implications for Educational Policy.

ERIC Educational Resources Information Center

Ehrman, Lee, Ed.; And Others

The contents of this book, which presents the fruits of one of a series of conferences organized by the National Research Council Committee on Basic Research in Education, includes 12 papers, with discussion and comments: "Introductory Remarks," Ernst W. Caspari; "Quantitative Aspects of Genetics and Environment in the Determination of Behavior,"…

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

USDA-ARS?s Scientific Manuscript database

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

The accuracies of DNA-based estimates of genetic merit derived from Angus or multibreed beef cattle training populations

USDA-ARS?s Scientific Manuscript database

Several organizations have developed prediction models for molecular breeding values (MBV) for quantitative growth and carcass traits in beef cattle using BovineSNP50 genotypes and phenotypic or EBV data. MBV for Angus cattle have been developed by IGENITY, Pfizer Animal Genetics, and a collaboratio...

Allele Mining in Barley Genetic Resources Reveals Genes of Race-Non-Specific Powdery Mildew Resistance

PubMed Central

Spies, Annika; Korzun, Viktor; Bayles, Rosemary; Rajaraman, Jeyaraman; Himmelbach, Axel; Hedley, Pete E.; Schweizer, Patrick

2012-01-01

Race-non-specific, or quantitative, pathogen resistance is of high importance to plant breeders due to its expected durability. However, it is usually controlled by multiple quantitative trait loci (QTL) and therefore difficult to handle in practice. Knowing the genes that underlie race-non-specific resistance (NR) would allow its exploitation in a more targeted manner. Here, we performed an association-genetic study in a customized worldwide collection of spring barley accessions for candidate genes of race-NR to the powdery mildew fungus Blumeria graminis f. sp. hordei (Bgh) and combined data with results from QTL mapping as well as functional-genomics approaches. This led to the identification of 11 associated genes with converging evidence for an important role in race-NR in the presence of the Mlo gene for basal susceptibility. Outstanding in this respect was the gene encoding the transcription factor WRKY2. The results suggest that unlocking plant genetic resources and integrating functional-genomic with genetic approaches can accelerate the discovery of genes underlying race-NR in barley and other crop plants. PMID:22629270

Heritabilities of Directional Asymmetry in the Fore- and Hindlimbs of Rabbit Fetuses

PubMed Central

Breno, Matteo; Bots, Jessica; Van Dongen, Stefan

2013-01-01

Directional asymmetry (DA), where at the population level symmetry differs from zero, has been reported in a wide range of traits and taxa, even for traits in which symmetry is expected to be the target of selection such as limbs or wings. In invertebrates, DA has been suggested to be non-adaptive. In vertebrates, there has been a wealth of research linking morphological asymmetry to behavioural lateralisation. On the other hand, the prenatal expression of DA and evidences for quantitative genetic variation for asymmetry may suggest it is not solely induced by differences in mechanic loading between sides. We estimate quantitative genetic variation of fetal limb asymmetry in a large dataset of rabbits. Our results showed a low but highly significant level of DA that is partially under genetic control for all traits, with forelimbs displaying higher levels of asymmetry. Genetic correlations were positive within limbs, but negative across bones of fore and hind limbs. Environmental correlations were positive for all, but smaller across fore and hind limbs. We discuss our results in light of the existence and maintenance of DA in locomotory traits. PMID:24130770

KRN4 Controls Quantitative Variation in Maize Kernel Row Number

PubMed Central

Liu, Lei; Du, Yanfang; Shen, Xiaomeng; Li, Manfei; Sun, Wei; Huang, Juan; Liu, Zhijie; Tao, Yongsheng; Zheng, Yonglian; Yan, Jianbing; Zhang, Zuxin

2015-01-01

Kernel row number (KRN) is an important component of yield during the domestication and improvement of maize and controlled by quantitative trait loci (QTL). Here, we fine-mapped a major KRN QTL, KRN4, which can enhance grain productivity by increasing KRN per ear. We found that a ~3-Kb intergenic region about 60 Kb downstream from the SBP-box gene Unbranched3 (UB3) was responsible for quantitative variation in KRN by regulating the level of UB3 expression. Within the 3-Kb region, the 1.2-Kb Presence-Absence variant was found to be strongly associated with quantitative variation in KRN in diverse maize inbred lines, and our results suggest that this 1.2-Kb transposon-containing insertion is likely responsible for increased KRN. A previously identified A/G SNP (S35, also known as Ser220Asn) in UB3 was also found to be significantly associated with KRN in our association-mapping panel. Although no visible genetic effect of S35 alone could be detected in our linkage mapping population, it was found to genetically interact with the 1.2-Kb PAV to modulate KRN. The KRN4 was under strong selection during maize domestication and the favorable allele for the 1.2-Kb PAV and S35 has been significantly enriched in modern maize improvement process. The favorable haplotype (Hap1) of 1.2-Kb-PAV-S35 was selected during temperate maize improvement, but is still rare in tropical and subtropical maize germplasm. The dissection of the KRN4 locus improves our understanding of the genetic basis of quantitative variation in complex traits in maize. PMID:26575831

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

The SCHEIE Visual Field Grading System

PubMed Central

Sankar, Prithvi S.; O’Keefe, Laura; Choi, Daniel; Salowe, Rebecca; Miller-Ellis, Eydie; Lehman, Amanda; Addis, Victoria; Ramakrishnan, Meera; Natesh, Vikas; Whitehead, Gideon; Khachatryan, Naira; O’Brien, Joan

2017-01-01

Objective No method of grading visual field (VF) defects has been widely accepted throughout the glaucoma community. The SCHEIE (Systematic Classification of Humphrey visual fields-Easy Interpretation and Evaluation) grading system for glaucomatous visual fields was created to convey qualitative and quantitative information regarding visual field defects in an objective, reproducible, and easily applicable manner for research purposes. Methods The SCHEIE grading system is composed of a qualitative and quantitative score. The qualitative score consists of designation in one or more of the following categories: normal, central scotoma, paracentral scotoma, paracentral crescent, temporal quadrant, nasal quadrant, peripheral arcuate defect, expansive arcuate, or altitudinal defect. The quantitative component incorporates the Humphrey visual field index (VFI), location of visual defects for superior and inferior hemifields, and blind spot involvement. Accuracy and speed at grading using the qualitative and quantitative components was calculated for non-physician graders. Results Graders had a median accuracy of 96.67% for their qualitative scores and a median accuracy of 98.75% for their quantitative scores. Graders took a mean of 56 seconds per visual field to assign a qualitative score and 20 seconds per visual field to assign a quantitative score. Conclusion The SCHEIE grading system is a reproducible tool that combines qualitative and quantitative measurements to grade glaucomatous visual field defects. The system aims to standardize clinical staging and to make specific visual field defects more easily identifiable. Specific patterns of visual field loss may also be associated with genetic variants in future genetic analysis. PMID:28932621

Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

PubMed Central

Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

2011-01-01

The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

Genetic dissection of the maize (Zea mays L.) MAMP response.

PubMed

Zhang, Xinye; Valdés-López, Oswaldo; Arellano, Consuelo; Stacey, Gary; Balint-Kurti, Peter

2017-06-01

Loci associated with variation in maize responses to two microbe-associated molecular patterns (MAMPs) were identified. MAMP responses were correlated. No relationship between MAMP responses and quantitative disease resistance was identified. Microbe-associated molecular patterns (MAMPs) are highly conserved molecules commonly found in microbes which can be recognized by plant pattern recognition receptors. Recognition triggers a suite of responses including production of reactive oxygen species (ROS) and nitric oxide (NO) and expression changes of defense-related genes. In this study, we used two well-studied MAMPs (flg22 and chitooctaose) to challenge different maize lines to determine whether there was variation in the level of responses to these MAMPs, to dissect the genetic basis underlying that variation and to understand the relationship between MAMP response and quantitative disease resistance (QDR). Naturally occurring quantitative variation in ROS, NO production, and defense genes expression levels triggered by MAMPs was observed. A major quantitative traits locus (QTL) associated with variation in the ROS production response to both flg22 and chitooctaose was identified on chromosome 2 in a recombinant inbred line (RIL) population derived from the maize inbred lines B73 and CML228. Minor QTL associated with variation in the flg22 ROS response was identified on chromosomes 1 and 4. Comparison of these results with data previously obtained for variation in QDR and the defense response in the same RIL population did not provide any evidence for a common genetic basis controlling variation in these traits.

Quantitative mutant analysis of viral quasispecies by chip-based matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry

PubMed Central

Amexis, Georgios; Oeth, Paul; Abel, Kenneth; Ivshina, Anna; Pelloquin, Francois; Cantor, Charles R.; Braun, Andreas; Chumakov, Konstantin

2001-01-01

RNA viruses exist as quasispecies, heterogeneous and dynamic mixtures of mutants having one or more consensus sequences. An adequate description of the genomic structure of such viral populations must include the consensus sequence(s) plus a quantitative assessment of sequence heterogeneities. For example, in quality control of live attenuated viral vaccines, the presence of even small quantities of mutants or revertants may indicate incomplete or unstable attenuation that may influence vaccine safety. Previously, we demonstrated the monitoring of oral poliovirus vaccine with the use of mutant analysis by PCR and restriction enzyme cleavage (MAPREC). In this report, we investigate genetic variation in live attenuated mumps virus vaccine by using both MAPREC and a platform (DNA MassArray) based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Mumps vaccines prepared from the Jeryl Lynn strain typically contain at least two distinct viral substrains, JL1 and JL2, which have been characterized by full length sequencing. We report the development of assays for characterizing sequence variants in these substrains and demonstrate their use in quantitative analysis of substrains and sequence variations in mixed virus cultures and mumps vaccines. The results obtained from both the MAPREC and MALDI-TOF methods showed excellent correlation. This suggests the potential utility of MALDI-TOF for routine quality control of live viral vaccines and for assessment of genetic stability and quantitative monitoring of genetic changes in other RNA viruses of clinical interest. PMID:11593021

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

Heritabilities of somatotype components in a population from rural Mozambique.

PubMed

Saranga, Sílvio Pedro José; Prista, António; Nhantumbo, Leonardo; Beunen, Gaston; Rocha, Jorge; Williams-Blangero, Sarah; Maia, José A

2008-01-01

There have been few genetic studies of normal variation in body size and composition conducted in Africa. In particular, the genetic determinants of somatotype remain to be established for an African population. (1) To estimate the heritabilities of aspects of somatotype and (2) to compare the quantitative genetic effects in an African population to those that have been assessed in European and American populations. The sample composed of 329 subjects (173 males and 156 females) aged 7-17 years, belonging to 132 families. The sibships in the sample ranged in size from two to seven individuals. All sampled individuals were residents of the Calanga region, an area located to the north of Maputo in Mozambique. Somatotype was assessed using the Heath-Carter technique. Herit abilities were estimated using SAGE software. Moderate heritabilities were determined for each trait. Between 30 and 40% of the variation in each somatotype measure was attributable to genetic factors. The heritability of ectomorphy was 31%. Mesomorphy was similarly moderately heritable, with approximately 30% of the variationattributable to genetic factors. The heritability of endomorph was higher in the Calanga population (h(2) = 0.40). Quantitative genetic analyses of somatotype variation among siblings indicate that genetic factors significantly influence endomorphy, mesomorhpy, and ectomorphy. However, environmental factors also have significant effects on the variation in physique present in the population of Calanga. Lack of proper nutrition, housing, medical assistance, and primary health care, together with very demanding and sex-specific daily chores may contribute to the environmental effects on these traits.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Unraveling additive from nonadditive effects using genomic relationship matrices.

PubMed

Muñoz, Patricio R; Resende, Marcio F R; Gezan, Salvador A; Resende, Marcos Deon Vilela; de Los Campos, Gustavo; Kirst, Matias; Huber, Dudley; Peter, Gary F

2014-12-01

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies. Copyright © 2014 by the Genetics Society of America.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

PubMed Central

Serin, Elise A. R.; Snoek, L. B.; Nijveen, Harm; Willems, Leo A. J.; Jiménez-Gómez, Jose M.; Hilhorst, Henk W. M.; Ligterink, Wilco

2017-01-01

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches. PMID:29259624

Quantitative Genetic Modeling of the Parental Care Hypothesis for the Evolution of Endothermy

PubMed Central

Bacigalupe, Leonardo D.; Moore, Allen J.; Nespolo, Roberto F.; Rezende, Enrico L.; Bozinovic, Francisco

2017-01-01

There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood. PMID:29311952

Additive genetic variation in the craniofacial skeleton of baboons (genus Papio) and its relationship to body and cranial size.

PubMed

Joganic, Jessica L; Willmore, Katherine E; Richtsmeier, Joan T; Weiss, Kenneth M; Mahaney, Michael C; Rogers, Jeffrey; Cheverud, James M

2018-02-01

Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (V P ) and additive genetic (V A ) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution? We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone. Covariates account for 1.2-91% of craniofacial V P . EID V A decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males. Because a relatively large proportion of EID V A is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual V P patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes. © 2017 Wiley Periodicals, Inc.

The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

PubMed

Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

2014-01-01

Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

PubMed Central

Poissant, J; Davis, C S; Malenfant, R M; Hogg, J T; Coltman, D W

2012-01-01

Dissecting the genetic architecture of fitness-related traits in wild populations is key to understanding evolution and the mechanisms maintaining adaptive genetic variation. We took advantage of a recently developed genetic linkage map and phenotypic information from wild pedigreed individuals from Ram Mountain, Alberta, Canada, to study the genetic architecture of ecologically important traits (horn volume, length, base circumference and body mass) in bighorn sheep. In addition to estimating sex-specific and cross-sex quantitative genetic parameters, we tested for the presence of quantitative trait loci (QTLs), colocalization of QTLs between bighorn sheep and domestic sheep, and sex × QTL interactions. All traits showed significant additive genetic variance and genetic correlations tended to be positive. Linkage analysis based on 241 microsatellite loci typed in 310 pedigreed animals resulted in no significant and five suggestive QTLs (four for horn dimension on chromosomes 1, 18 and 23, and one for body mass on chromosome 26) using genome-wide significance thresholds (Logarithm of odds (LOD) >3.31 and >1.88, respectively). We also confirmed the presence of a horn dimension QTL in bighorn sheep at the only position known to contain a similar QTL in domestic sheep (on chromosome 10 near the horns locus; nominal P<0.01) and highlighted a number of regions potentially containing weight-related QTLs in both species. As expected for sexually dimorphic traits involved in male–male combat, loci with sex-specific effects were detected. This study lays the foundation for future work on adaptive genetic variation and the evolutionary dynamics of sexually dimorphic traits in bighorn sheep. PMID:21847139

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

PubMed Central

Chen, Xinwei; Hackett, Christine A.; Niks, Rients E.; Hedley, Peter E.; Booth, Clare; Druka, Arnis; Marcel, Thierry C.; Vels, Anton; Bayer, Micha; Milne, Iain; Morris, Jenny; Ramsay, Luke; Marshall, David; Cardle, Linda; Waugh, Robbie

2010-01-01

Background Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes. Methodology/Principal Findings We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis. Conclusions/Significance The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this population. PMID:20066049

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Mapping Adipose and Muscle Tissue Expression Quantitative Trait Loci in African Americans to Identify Genes for Type 2 Diabetes and Obesity

PubMed Central

Sajuthi, Satria P.; Sharma, Neeraj K.; Chou, Jeff W.; Palmer, Nicholette D.; McWilliams, David R.; Beal, John; Comeau, Mary E.; Ma, Lijun; Calles-Escandon, Jorge; Demons, Jamehl; Rogers, Samantha; Cherry, Kristina; Menon, Lata; Kouba, Ethel; Davis, Donna; Burris, Marcie; Byerly, Sara J.; Ng, Maggie C.Y.; Maruthur, Nisa M.; Patel, Sanjay R.; Bielak, Lawrence F.; Lange, Leslie; Guo, Xiuqing; Sale, Michèle M.; Chan, Kei Hang; Monda, Keri L.; Chen, Gary K.; Taylor, Kira; Palmer, Cameron; Edwards, Todd L; North, Kari E.; Haiman, Christopher A.; Bowden, Donald W.; Freedman, Barry I.; Langefeld, Carl D.; Das, Swapan K.

2016-01-01

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes. PMID:27193597

The chicken genome: some good news and some bad news.

PubMed

Dodgson, J B

2007-07-01

The sequencing of the chicken genome has generated a wealth of good news for poultry science. It allows the chicken to be a major player in 21st century biology by providing an entrée into an arsenal of new technologies that can be used to explore virtually any chicken phenotype of interest. The initial technological onslaught has been described in this symposium. The wealth of data available now or soon to be available cannot be explained by simplistic models and will force us to treat the inherent complexity of the chicken in ways that are more realistic but at the same time more difficult to comprehend. Initial single nucleotide polymorphism analyses suggest that broilers retain a remarkable amount of the genetic diversity of predomesticated Jungle Fowl, whereas commercial layer genomes display less diversity and broader linkage disequilibrium. Thus, intensive commercial selection has not fixed a genome rich in wide selective sweeps, at least within the broiler population. Rather, a complex assortment of combinations of ancient allelic diversity survives. Low levels of linkage disequilibrium will make association analysis in broilers more difficult. The wider disequilibrium observed in layers should facilitate the mapping of quantitative trait loci, and at the same time make it more difficult to identify the causative nucleotide change(s). In addition, many quantitative traits may be specific to the genetic background in which they arose and not readily transferable to, or detectable in, other line backgrounds. Despite the obstacles it presents, the genetic complexity of the chicken may also be viewed as good news because it insures that long-term genetic progress will continue via breeding using quantitative genetics, and it surely will keep poultry scientists busy for decades to come. It is now time to move from an emphasis on obtaining "THE" chicken genome sequence to obtaining multiple sequences, especially of foundation stocks, and a broader understanding of the full genetic and phenotypic diversity of the domesticated chicken.

Functional linear models for association analysis of quantitative traits.

PubMed

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.

The genetics of shovel shape in maxillary central incisors in man.

PubMed

Blanco, R; Chakraborty, R

1976-03-01

From dental casts of 94 parent-offspring and 127 full-sib pairs, sampled from two Chilean populations, shovelling indices are computed to measure the degree of shovelling of maxillary central incisors quantitatively. Genetic correlations are computed to determine the role of genetic factors in explaining the variation in this trait. Assuming only hereditary factors to be responsible for the transmission of shovel shape, 68% of total variability is ascribed to the additive effect of genes.

Single-Cell Quantitative PCR: Advances and Potential in Cancer Diagnostics.

PubMed

Ok, Chi Young; Singh, Rajesh R; Salim, Alaa A

2016-01-01

Tissues are heterogeneous in their components. If cells of interest are a minor population of collected tissue, it would be difficult to obtain genetic or genomic information of the interested cell population with conventional genomic DNA extraction from the collected tissue. Single-cell DNA analysis is important in the analysis of genetics of cell clonality, genetic anticipation, and single-cell DNA polymorphisms. Single-cell PCR using Single Cell Ampligrid/GeXP platform is described in this chapter.

The long-term evolution of multilocus traits under frequency-dependent disruptive selection.

PubMed

van Doorn, G Sander; Dieckmann, Ulf

2006-11-01

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

PubMed Central

Orr, H A

1998-01-01

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

Development and in-house validation of the event-specific qualitative and quantitative PCR detection methods for genetically modified cotton MON15985.

PubMed

Jiang, Lingxi; Yang, Litao; Rao, Jun; Guo, Jinchao; Wang, Shu; Liu, Jia; Lee, Seonghun; Zhang, Dabing

2010-02-01

To implement genetically modified organism (GMO) labeling regulations, an event-specific analysis method based on the junction sequence between exogenous integration and host genomic DNA has become the preferential approach for GMO identification and quantification. In this study, specific primers and TaqMan probes based on the revealed 5'-end junction sequence of GM cotton MON15985 were designed, and qualitative and quantitative polymerase chain reaction (PCR) assays were established employing the designed primers and probes. In the qualitative PCR assay, the limit of detection (LOD) was 0.5 g kg(-1) in 100 ng total cotton genomic DNA, corresponding to about 17 copies of haploid cotton genomic DNA, and the LOD and limit of quantification (LOQ) for quantitative PCR assay were 10 and 17 copies of haploid cotton genomic DNA, respectively. Furthermore, the developed quantitative PCR assays were validated in-house by five different researchers. Also, five practical samples with known GM contents were quantified using the developed PCR assay in in-house validation, and the bias between the true and quantification values ranged from 2.06% to 12.59%. This study shows that the developed qualitative and quantitative PCR methods are applicable for the identification and quantification of GM cotton MON15985 and its derivates.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

PubMed Central

2012-01-01

Background Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different genetic architectures for grape PA composition between berry skin and seeds. This work also uncovers novel genomic regions for further investigation in order to increase our knowledge of the genetic basis of PA composition. PMID:22369244

Testing for a genetic response to sexual selection in a wild Drosophila population.

PubMed

Gosden, T P; Thomson, J R; Blows, M W; Schaul, A; Chenoweth, S F

2016-06-01

In accordance with the consensus that sexual selection is responsible for the rapid evolution of display traits on macroevolutionary scales, microevolutionary studies suggest sexual selection is a widespread and often strong form of directional selection in nature. However, empirical evidence for the contemporary evolution of sexually selected traits via sexual rather than natural selection remains weak. In this study, we used a novel application of quantitative genetic breeding designs to test for a genetic response to sexual selection on eight chemical display traits from a field population of the fly, Drosophila serrata. Using our quantitative genetic approach, we were able to detect a genetically based difference in means between groups of males descended from fathers who had either successfully sired offspring or were randomly collected from the same wild population for one of these display traits, the diene (Z,Z)-5,9-C27 : 2 . Our experimental results, in combination with previous laboratory studies on this system, suggest that both natural and sexual selection may be influencing the evolutionary trajectories of these traits in nature, limiting the capacity for a contemporary evolutionary response. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain

PubMed Central

Quinkert, Amy Wells; Vimal, Vivek; Weil, Zachary M.; Reeke, George N.; Schiff, Nicholas D.; Banavar, Jayanth R.; Pfaff, Donald W.

2011-01-01

We review a concept of the most primitive, fundamental function of the vertebrate CNS, generalized arousal (GA). Three independent lines of evidence indicate the existence of GA: statistical, genetic, and mechanistic. Here we ask, is this concept amenable to quantitative analysis? Answering in the affirmative, four quantitative approaches have proven useful: (i) factor analysis, (ii) information theory, (iii) deterministic chaos, and (iv) application of a Gaussian equation. It strikes us that, to date, not just one but at least four different quantitative approaches seem necessary for describing different aspects of scientific work on GA. PMID:21555568

Validation and Estimation of Additive Genetic Variation Associated with DNA Tests for Quantitative Beef Cattle Traits

USDA-ARS?s Scientific Manuscript database

The U.S. National Beef Cattle Evaluation Consortium (NBCEC) has been involved in the validation of commercial DNA tests for quantitative beef quality traits since their first appearance on the U.S. market in the early 2000s. The NBCEC Advisory Council initially requested that the NBCEC set up a syst...

Identification of genotyping-by-sequencing sequence tags associated with milling performance and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat quality is defined by culinary end-uses and processing characteristics. Wheat breeders are interested to identify quantitative trait loci for grain, milling, and end-use quality traits because it is imperative to understand the genetic complexity underlying quantitatively inherited traits to ...

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci

USDA-ARS?s Scientific Manuscript database

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structura...

MONITORING MYCOTOXIN PRODUCTION AT THE GENETIC LEVEL ON VARIOUS GROWTH SUBSTRATES USING QUANTITATIVE REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION?EXPERIMENT DESIGN

EPA Science Inventory

The paper describes a method of analyzing the production of mycotoxins at the genetic level by monitoring the intracellular levels of messenger RNA (mRNA). Initial work will focus on threshing out the mycotoxin gene clusters in Stachybotrys chartarum followed by analysis of toxin...

Early rooting of dormant hardwood cuttings of Populus: analysis of quantitative genetics and genotype x environment interactions

Treesearch

Ronald S., Jr. Zalesny; Don E. Riemenschneider; Richard B. Hall

2005-01-01

Rooting of hardwood cuttings is under strong genetic control, although genotype x environment interactions affect selection of promising genotypes. Our objectives were (1) to assess the variation in rooting ability among 21 Populus clones and (2) to examine genotype x environment interactions to refine clonal recommendations. The clones belonged to...

Genetic analysis of grain attributes, milling performance, and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class and culinary end-uses. Of interest to wheat breeders is to identify quantitative trait loci (QTL) for wheat kernel texture, milling performance, or end-use quality because it is imperative for wheat breeders to ascertain the genetic architecture ...

Construction of a Genetic Linkage Map and Identification of QTLs for Resistance to TSWV in Cultivated Peanut (Arachis hypagea L.)

USDA-ARS?s Scientific Manuscript database

A genetic linkage map is critical for identifying the QTL (quantitative trait loci) underling targeted traits. Over the last few years, progress has been made in marker development from multiple sources enabling the expansion of quality resources needed for genotyping applications in cultivated x cu...

Applications of the 1000 Genomes Project resources

PubMed Central

Zheng-Bradley, Xiangqun

2017-01-01

Abstract The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. PMID:27436001

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

PubMed

Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

2015-10-01

Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

PubMed

Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

2017-04-01

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Integrating Genomic Analysis with the Genetic Basis of Gene Expression: Preliminary Evidence of the Identification of Causal Genes for Cardiovascular and Metabolic Traits Related to Nutrition in Mexicans123

PubMed Central

Bastarrachea, Raúl A.; Gallegos-Cabriales, Esther C.; Nava-González, Edna J.; Haack, Karin; Voruganti, V. Saroja; Charlesworth, Jac; Laviada-Molina, Hugo A.; Veloz-Garza, Rosa A.; Cardenas-Villarreal, Velia Margarita; Valdovinos-Chavez, Salvador B.; Gomez-Aguilar, Patricia; Meléndez, Guillermo; López-Alvarenga, Juan Carlos; Göring, Harald H. H.; Cole, Shelley A.; Blangero, John; Comuzzie, Anthony G.; Kent, Jack W.

2012-01-01

Whole-transcriptome expression profiling provides novel phenotypes for analysis of complex traits. Gene expression measurements reflect quantitative variation in transcript-specific messenger RNA levels and represent phenotypes lying close to the action of genes. Understanding the genetic basis of gene expression will provide insight into the processes that connect genotype to clinically significant traits representing a central tenet of system biology. Synchronous in vivo expression profiles of lymphocytes, muscle, and subcutaneous fat were obtained from healthy Mexican men. Most genes were expressed at detectable levels in multiple tissues, and RNA levels were correlated between tissue types. A subset of transcripts with high reliability of expression across tissues (estimated by intraclass correlation coefficients) was enriched for cis-regulated genes, suggesting that proximal sequence variants may influence expression similarly in different cellular environments. This integrative global gene expression profiling approach is proving extremely useful for identifying genes and pathways that contribute to complex clinical traits. Clearly, the coincidence of clinical trait quantitative trait loci and expression quantitative trait loci can help in the prioritization of positional candidate genes. Such data will be crucial for the formal integration of positional and transcriptomic information characterized as genetical genomics. PMID:22797999

A Unified Framework Integrating Parent-of-Origin Effects for Association Study

PubMed Central

Xiao, Feifei; Ma, Jianzhong; Amos, Christopher I.

2013-01-01

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including the POEs. We conducted simulation studies for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits. PMID:23991061

[Study on tests of genetics experiments in universities].

PubMed

Jie, He; Hao, Zhang; Lili, Zhang

2015-03-01

Based on the present situation and the development of experiment tests in universities, we introduced a reform in tests of genetics experiments. According to the teaching goals and course contents of genetics experiment, the tests of genetics experiments contain four aspects on the performance of students: the adherence to the experimental procedures, the depth of participation in experiment, the quality of experiment report, and the mastery of experiment principles and skills, which account for 10 %, 20 %, 40 % and 30 % in the total scores, respectively. All four aspects were graded quantitatively. This evaluation system has been tested in our experiment teaching. The results suggest that it has an effect on the promotion of teaching in genetics experiments.

The genetic basis of female multiple mating in a polyandrous livebearing fish

PubMed Central

Evans, Jonathan P; Gasparini, Clelia

2013-01-01

The widespread occurrence of female multiple mating (FMM) demands evolutionary explanation, particularly in the light of the costs of mating. One explanation encapsulated by “good sperm” and “sexy-sperm” (GS-SS) theoretical models is that FMM facilitates sperm competition, thus ensuring paternity by males that pass on genes for elevated sperm competitiveness to their male offspring. While support for this component of GS-SS theory is accumulating, a second but poorly tested assumption of these models is that there should be corresponding heritable genetic variation in FMM – the proposed mechanism of postcopulatory preferences underlying GS-SS models. Here, we conduct quantitative genetic analyses on paternal half-siblings to test this component of GS-SS theory in the guppy (Poecilia reticulata), a freshwater fish with some of the highest known rates of FMM in vertebrates. As with most previous quantitative genetic analyses of FMM in other species, our results reveal high levels of phenotypic variation in this trait and a correspondingly low narrow-sense heritability (h2 = 0.11). Furthermore, although our analysis of additive genetic variance in FMM was not statistically significant (probably owing to limited statistical power), the ensuing estimate of mean-standardized additive genetic variance (IA = 0.7) was nevertheless relatively low compared with estimates published for life-history traits across a broad range of taxa. Our results therefore add to a growing body of evidence that FMM is characterized by relatively low additive genetic variation, thus apparently contradicting GS-SS theory. However, we qualify this conclusion by drawing attention to potential deficiencies in most designs (including ours) that have tested for genetic variation in FMM, particularly those that fail to account for intersexual interactions that underlie FMM in many systems. PMID:23403856

Heritability of seed weight in Maritime pine, a relevant trait in the transmission of environmental maternal effects

PubMed Central

Zas, R; Sampedro, L

2015-01-01

Quantitative seed provisioning is an important life-history trait with strong effects on offspring phenotype and fitness. As for any other trait, heritability estimates are vital for understanding its evolutionary dynamics. However, being a trait in between two generations, estimating additive genetic variation of seed provisioning requires complex quantitative genetic approaches for distinguishing between true genetic and environmental maternal effects. Here, using Maritime pine as a long-lived plant model, we quantified additive genetic variation of cone and seed weight (SW) mean and SW within-individual variation. We used a powerful approach combining both half-sib analysis and parent–offspring regression using several common garden tests established in contrasting environments to separate G, E and G × E effects. Both cone weight and SW mean showed significant genetic variation but were also influenced by the maternal environment. Most of the large variation in SW mean was attributable to additive genetic effects (h2=0.55–0.74). SW showed no apparent G × E interaction, particularly when accounting for cone weight covariation, suggesting that the maternal genotypes actively control the SW mean irrespective of the amount of resources allocated to cones. Within-individual variation in SW was low (12%) relative to between-individual variation (88%), and showed no genetic variation but was largely affected by the maternal environment, with greater variation in the less favourable sites for pine growth. In summary, results were very consistent between the parental and the offspring common garden tests, and clearly indicated heritable genetic variation for SW mean but not for within-individual variation in SW. PMID:25160045

Sex differences in genetic and environmental influences on educational attainment and income.

PubMed

Orstavik, Ragnhild E; Czajkowski, Nikolai; Røysamb, Espen; Knudsen, Gun Peggy; Tambs, Kristian; Reichborn-Kjennerud, Ted

2014-12-01

In many Western countries, women now reach educational levels comparable to men, although their income remains considerably lower. For the past decades, it has become increasingly clear that these measures of socio-economic status are influenced by genetic as well as environmental factors. Less is known about the relationship between education and income, and sex differences. The aim of this study was to explore genetic and environmental factors influencing education and income in a large cohort of young Norwegian twins, with special emphasis on gender differences. National register data on educational level and income were obtained for 7,710 twins (aged 29-41 years). Bivariate Cholesky models were applied to estimate qualitative and quantitative gender differences in genetic and environmental influences, the relative contribution of genetic and environmental factors to the correlation between education and income, and genetic correlations within and between sexes and phenotypes. The phenotypic correlation between educational level and income was 0.34 (0.32-0.39) for men and 0.45 (0.43-0.48) for women. An ACE model with both qualitative and quantitative sex differences fitted the data best. The genetic correlation between men and women (rg) was 0.66 (0.22-1.00) for educational attainment and 0.38 (0.01-0.75) for income, and between the two phenotypes 0.31 (0.08-0.52) for men and 0.72 (0.64-0.85) for women. Our results imply that, in relatively egalitarian societies with state-supported access to higher education and political awareness of gender equality, genetic factors may play an important role in explaining sex differences in the relationship between education and income.

Overlapping Genetic and Child-Specific Nonshared Environmental Influences on Listening Comprehension, Reading Motivation, and Reading Comprehension

PubMed Central

Schenker, Victoria J.; Petrill, Stephen A.

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. PMID:26321677

Overlapping genetic and child-specific nonshared environmental influences on listening comprehension, reading motivation, and reading comprehension.

PubMed

Schenker, Victoria J; Petrill, Stephen A

2015-01-01

This study investigated the genetic and environmental influences on observed associations between listening comprehension, reading motivation, and reading comprehension. Univariate and multivariate quantitative genetic models were conducted in a sample of 284 pairs of twins at a mean age of 9.81 years. Genetic and nonshared environmental factors accounted for statistically significant variance in listening and reading comprehension, and nonshared environmental factors accounted for variance in reading motivation. Furthermore, listening comprehension demonstrated unique genetic and nonshared environmental influences but also had overlapping genetic influences with reading comprehension. Reading motivation and reading comprehension each had unique and overlapping nonshared environmental contributions. Therefore, listening comprehension appears to be related to reading primarily due to genetic factors whereas motivation appears to affect reading via child-specific, nonshared environmental effects. Copyright © 2015 Elsevier Inc. All rights reserved.

Development and evaluation of event-specific quantitative PCR method for genetically modified soybean A2704-12.

PubMed

Takabatake, Reona; Akiyama, Hiroshi; Sakata, Kozue; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Teshima, Reiko; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event; A2704-12. During the plant transformation, DNA fragments derived from pUC19 plasmid were integrated in A2704-12, and the region was found to be A2704-12 specific. The pUC19-derived DNA sequences were used as primers for the specific detection of A2704-12. We first tried to construct a standard plasmid for A2704-12 quantification using pUC19. However, non-specific signals appeared with both qualitative and quantitative PCR analyses using the specific primers with pUC19 as a template, and we then constructed a plasmid using pBR322. The conversion factor (C(f)), which is required to calculate the amount of the genetically modified organism (GMO), was experimentally determined with two real-time PCR instruments, the Applied Biosystems 7900HT and the Applied Biosystems 7500. The determined C(f) values were both 0.98. The quantitative method was evaluated by means of blind tests in multi-laboratory trials using the two real-time PCR instruments. The limit of quantitation for the method was estimated to be 0.1%. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSD(R)), and the determined bias and RSD(R) values for the method were each less than 20%. These results suggest that the developed method would be suitable for practical analyses for the detection and quantification of A2704-12.

Genome-wide Linkage Analysis for Identifying Quantitative Trait Loci Involved in the Regulation of Lipoprotein a (Lpa) Levels

PubMed Central

López, Sonia; Buil, Alfonso; Ordoñez, Jordi; Souto, Juan Carlos; Almasy, Laura; Lathrop, Mark; Blangero, John; Blanco-Vaca, Francisco; Fontcuberta, Jordi; Soria, José Manuel

2009-01-01

Lipoprotein Lp(a) levels are highly heritable and are associated with cardiovascular risk. We performed a genome-wide linkage analysis to delineate the genomic regions that influence the concentration of Lp(a) in families from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. Lp(a) levels were measured in 387 individuals belonging to 21 extended Spanish families. A total of 485 DNA microsatellite markers were genotyped to provide a 7.1 cM genetic map. A variance component linkage method was used to evaluate linkage and to detect quantitative trait loci (QTLs). The main QTL that showed strong evidence of linkage with Lp(a) levels was located at the structural gene for apo(a) on Chromosome 6 (LOD score=13.8). Interestingly, another QTL influencing Lp(a) concentration was located on Chromosome 2 with a LOD score of 2.01. This region contains several candidate genes. One of them is the tissue factor pathway inhibitor (TFPI), which has antithrombotic action and also has the ability to bind lipoproteins. However, quantitative trait association analyses performed with 12 SNPs in TFPI gene revealed no association with Lp(a) levels. Our study confirms previous results on the genetic basis of Lp(a) levels. In addition, we report a new QTL on Chromosome 2 involved in the quantitative variation of Lp(a). These data should serve as the basis for further detection of candidate genes and to elucidate the relationship between the concentration of Lp(a) and cardiovascular risk. PMID:18560444

Hybrid wheat: quantitative genetic parameters and consequences for the design of breeding programs.

PubMed

Longin, Carl Friedrich Horst; Gowda, Manje; Mühleisen, Jonathan; Ebmeyer, Erhard; Kazman, Ebrahim; Schachschneider, Ralf; Schacht, Johannes; Kirchhoff, Martin; Zhao, Yusheng; Reif, Jochen Christoph

2013-11-01

Commercial heterosis for grain yield is present in hybrid wheat but long-term competiveness of hybrid versus line breeding depends on the development of heterotic groups to improve hybrid prediction. Detailed knowledge of the amount of heterosis and quantitative genetic parameters are of paramount importance to assess the potential of hybrid breeding. Our objectives were to (1) examine the extent of midparent, better-parent and commercial heterosis in a vast population of 1,604 wheat (Triticum aestivum L.) hybrids and their parental elite inbred lines and (2) discuss the consequences of relevant quantitative parameters for the design of hybrid wheat breeding programs. Fifteen male lines were crossed in a factorial mating design with 120 female lines, resulting in 1,604 of the 1,800 potential single-cross hybrid combinations. The hybrids, their parents, and ten commercial wheat varieties were evaluated in multi-location field experiments for grain yield, plant height, heading time and susceptibility to frost, lodging, septoria tritici blotch, yellow rust, leaf rust, and powdery mildew at up to five locations. We observed that hybrids were superior to the mean of their parents for grain yield (10.7 %) and susceptibility to frost (-7.2 %), leaf rust (-8.4 %) and septoria tritici blotch (-9.3 %). Moreover, 69 hybrids significantly (P < 0.05) outyielded the best commercial inbred line variety underlining the potential of hybrid wheat breeding. The estimated quantitative genetic parameters suggest that the establishment of reciprocal recurrent selection programs is pivotal for a successful long-term hybrid wheat breeding.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.

PubMed

Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal; Lu, Xiaodong; Mani, D R

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Jaffe, Jacob D.; Feeney, Caitlin M.; Patel, Jinal; Lu, Xiaodong; Mani, D. R.

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques.

A mixed model for the relationship between climate and human cranial form.

PubMed

Katz, David C; Grote, Mark N; Weaver, Timothy D

2016-08-01

We expand upon a multivariate mixed model from quantitative genetics in order to estimate the magnitude of climate effects in a global sample of recent human crania. In humans, genetic distances are correlated with distances based on cranial form, suggesting that population structure influences both genetic and quantitative trait variation. Studies controlling for this structure have demonstrated significant underlying associations of cranial distances with ecological distances derived from climate variables. However, to assess the biological importance of an ecological predictor, estimates of effect size and uncertainty in the original units of measurement are clearly preferable to significance claims based on units of distance. Unfortunately, the magnitudes of ecological effects are difficult to obtain with distance-based methods, while models that produce estimates of effect size generally do not scale to high-dimensional data like cranial shape and form. Using recent innovations that extend quantitative genetics mixed models to highly multivariate observations, we estimate morphological effects associated with a climate predictor for a subset of the Howells craniometric dataset. Several measurements, particularly those associated with cranial vault breadth, show a substantial linear association with climate, and the multivariate model incorporating a climate predictor is preferred in model comparison. Previous studies demonstrated the existence of a relationship between climate and cranial form. The mixed model quantifies this relationship concretely. Evolutionary questions that require population structure and phylogeny to be disentangled from potential drivers of selection may be particularly well addressed by mixed models. Am J Phys Anthropol 160:593-603, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Genomic Rearrangements in Arabidopsis Considered as Quantitative Traits.

PubMed

Imprialou, Martha; Kahles, André; Steffen, Joshua G; Osborne, Edward J; Gan, Xiangchao; Lempe, Janne; Bhomra, Amarjit; Belfield, Eric; Visscher, Anne; Greenhalgh, Robert; Harberd, Nicholas P; Goram, Richard; Hein, Jotun; Robert-Seilaniantz, Alexandre; Jones, Jonathan; Stegle, Oliver; Kover, Paula; Tsiantis, Miltos; Nordborg, Magnus; Rätsch, Gunnar; Clark, Richard M; Mott, Richard

2017-04-01

To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred Arabidopsis thaliana genomes, we identified 6502 segregating structural variants. Remarkably, 25% of these were transpositions. While many structural variants cannot be delineated precisely, we validated 83% of 44 predicted transposition breakpoints by polymerase chain reaction. We show that specific structural variants may be causative for quantitative trait loci for germination and resistance to infection by the fungus Albugo laibachii , isolate Nc14. Further we show that the phenotypic heritability attributable to read-mapping anomalies differs from, and, in the case of time to germination and bolting, exceeds that due to standard genetic variation. Genes within structural variants are also more likely to be silenced or dysregulated. This approach complements the prevalent strategy of structural variant discovery in fewer individuals sequenced at high coverage. It is generally applicable to large populations sequenced at low-coverage, and is particularly suited to mapping transpositions. Copyright © 2017 by the Genetics Society of America.

Statistics for Learning Genetics

NASA Astrophysics Data System (ADS)

Charles, Abigail Sheena

This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless, although the necessity for infusing these quantitative subjects with genetics and, overall, the biological sciences is growing (topics including synthetic biology, molecular systems biology and phylogenetics) there remains little time in the semester to be dedicated to the consolidation of learning and understanding.

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

PubMed

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

IWGT report on quantitative approaches to genotoxicity risk assessment II. Use of point-of-departure (PoD) metrics in defining acceptable exposure limits and assessing human risk

EPA Science Inventory

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the ne...

IWGT report on quantitative approaches to genotoxicity risk assessment I. Methods and metrics for defining exposure-response relationships and points of departure (PoDs)

EPA Science Inventory

This report summarizes the discussion, conclusions, and points of consensus of the IWGT Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (QWG) based on a meeting in Foz do Iguaçu, Brazil October 31–November 2, 2013. Topics addressed incl...

The Quantitative Nature of Autistic Social Impairment

PubMed Central

Constantino, John N.

2011-01-01

Autism, like intellectual disability, represents the severe end of a continuous distribution of developmental impairments that occur in nature, that are highly inherited, and that are orthogonally related to other parameters of development. A paradigm shift in understanding the core social abnormality of autism as a quantitative trait rather than as a categorically-defined condition has key implications for diagnostic classification, the measurement of change over time, the search for underlying genetic and neurobiologic mechanisms, and public health efforts to identify and support affected children. Here a recent body of research in genetics and epidemiology is presented to examine a dimensional reconceptualization of autistic social impairment—as manifested in clinical autistic syndromes, the broader autism phenotype, and normal variation in the general population. It illustrates how traditional categorical approaches to diagnosis may lead to misclassification of subjects (especially girls and mildly affected boys in multiple-incidence autism families), which can be particularly damaging to biological studies, and proposes continued efforts to derive a standardized quantitative system by which to characterize this family of conditions. PMID:21289537

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

PubMed

Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati; Robillard, Lilliane; Barthelet, Antoine; Lin, Kevin K; Shah, Khyati N; Simmons, Andy D; Raponi, Mitch; Harding, Thomas C; Bandyopadhyay, Sourav

2018-04-17

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Variation in seed dormancy quantitative trait loci in Arabidopsis thaliana originating from one site.

PubMed

Silady, Rebecca A; Effgen, Sigi; Koornneef, Maarten; Reymond, Matthieu

2011-01-01

A Quantitative Trait Locus (QTL) analysis was performed using two novel Recombinant Inbred Line (RIL) populations, derived from the progeny between two Arabidopsis thaliana genotypes collected at the same site in Kyoto (Japan) crossed with the reference laboratory strain Landsberg erecta (Ler). We used these two RIL populations to determine the genetic basis of seed dormancy and flowering time, which are assumed to be the main traits controlling life history variation in Arabidopsis. The analysis revealed quantitative variation for seed dormancy that is associated with allelic variation at the seed dormancy QTL DOG1 (for Delay Of Germination 1) in one population and at DOG6 in both. These DOG QTL have been previously identified using mapping populations derived from accessions collected at different sites around the world. Genetic variation within a population may enhance its ability to respond accurately to variation within and between seasons. In contrast, variation for flowering time, which also segregated within each mapping population, is mainly governed by the same QTL.

Reverse transcription-polymerase chain reaction molecular testing of cytology specimens: Pre-analytic and analytic factors.

PubMed

Bridge, Julia A

2017-01-01

The introduction of molecular testing into cytopathology laboratory practice has expanded the types of samples considered feasible for identifying genetic alterations that play an essential role in cancer diagnosis and treatment. Reverse transcription-polymerase chain reaction (RT-PCR), a sensitive and specific technical approach for amplifying a defined segment of RNA after it has been reverse-transcribed into its DNA complement, is commonly used in clinical practice for the identification of recurrent or tumor-specific fusion gene events. Real-time RT-PCR (quantitative RT-PCR), a technical variation, also permits the quantitation of products generated during each cycle of the polymerase chain reaction process. This review addresses qualitative and quantitative pre-analytic and analytic considerations of RT-PCR as they relate to various cytologic specimens. An understanding of these aspects of genetic testing is central to attaining optimal results in the face of the challenges that cytology specimens may present. Cancer Cytopathol 2017;125:11-19. © 2016 American Cancer Society. © 2016 American Cancer Society.

Quantitative trait loci and metabolic pathways

PubMed Central

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR.

PubMed

Kodama, Takashi; Kurosawa, Yasunori; Kitta, Kazumi; Naito, Shigehiro

2010-01-01

The Horwitz curve estimates interlaboratory precision as a function only of concentration, and is frequently used as a method performance criterion in food analysis with chemical methods. The quantitative biochemical methods based on real-time PCR require an analogous criterion to progressively promote method validation. We analyzed the tendency of precision using a simplex real-time PCR technique in 53 collaborative studies of seven genetically modified (GM) crops. Reproducibility standard deviation (SR) and repeatability standard deviation (Sr) of the genetically modified organism (GMO) amount (%) was more or less independent of GM crops (i.e., maize, soybean, cotton, oilseed rape, potato, sugar beet, and rice) and evaluation procedure steps. Some studies evaluated whole steps consisting of DNA extraction and PCR quantitation, whereas others focused only on the PCR quantitation step by using DNA extraction solutions. Therefore, SR and Sr for GMO amount (%) are functions only of concentration similar to the Horwitz curve. We proposed S(R) = 0.1971C 0.8685 and S(r) = 0.1478C 0.8424, where C is the GMO amount (%). We also proposed a method performance index in GMO quantitative methods that is analogous to the Horwitz Ratio.

Development and validation of an event-specific quantitative PCR method for genetically modified maize MIR162.

PubMed

Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2014-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize event, MIR162. We first prepared a standard plasmid for MIR162 quantification. The conversion factor (Cf) required to calculate the genetically modified organism (GMO) amount was empirically determined for two real-time PCR instruments, the Applied Biosystems 7900HT (ABI7900) and the Applied Biosystems 7500 (ABI7500) for which the determined Cf values were 0.697 and 0.635, respectively. To validate the developed method, a blind test was carried out in an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr). The determined biases were less than 25% and the RSDr values were less than 20% at all evaluated concentrations. These results suggested that the limit of quantitation of the method was 0.5%, and that the developed method would thus be suitable for practical analyses for the detection and quantification of MIR162.

Development of a screening method for genetically modified soybean by plasmid-based quantitative competitive polymerase chain reaction.

PubMed

Shimizu, Eri; Kato, Hisashi; Nakagawa, Yuki; Kodama, Takashi; Futo, Satoshi; Minegishi, Yasutaka; Watanabe, Takahiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

2008-07-23

A novel type of quantitative competitive polymerase chain reaction (QC-PCR) system for the detection and quantification of the Roundup Ready soybean (RRS) was developed. This system was designed based on the advantage of a fully validated real-time PCR method used for the quantification of RRS in Japan. A plasmid was constructed as a competitor plasmid for the detection and quantification of genetically modified soy, RRS. The plasmid contained the construct-specific sequence of RRS and the taxon-specific sequence of lectin1 (Le1), and both had 21 bp oligonucleotide insertion in the sequences. The plasmid DNA was used as a reference molecule instead of ground seeds, which enabled us to precisely and stably adjust the copy number of targets. The present study demonstrated that the novel plasmid-based QC-PCR method could be a simple and feasible alternative to the real-time PCR method used for the quantification of genetically modified organism contents.

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

PubMed Central

Li, Zhijian; Vizeacoumar, Franco J; Bahr, Sondra; Li, Jingjing; Warringer, Jonas; Vizeacoumar, Frederick S; Min, Renqiang; VanderSluis, Benjamin; Bellay, Jeremy; DeVit, Michael; Fleming, James A; Stephens, Andrew; Haase, Julian; Lin, Zhen-Yuan; Baryshnikova, Anastasia; Lu, Hong; Yan, Zhun; Jin, Ke; Barker, Sarah; Datti, Alessandro; Giaever, Guri; Nislow, Corey; Bulawa, Chris; Myers, Chad L; Costanzo, Michael; Gingras, Anne-Claude; Zhang, Zhaolei; Blomberg, Anders; Bloom, Kerry; Andrews, Brenda; Boone, Charles

2012-01-01

Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes. PMID:21441928

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Sex Differences in Magical Ideation: A Community-Based Twin Study

PubMed Central

Karcher, Nicole R.; Slutske, Wendy S.; Kerns, John G.; Piasecki, Thomas M.; Martin, Nicholas G.

2014-01-01

Two questions regarding sex differences in magical ideation were investigated in this study: (1) whether there are mean level sex differences on the Magical Ideation Scale (MIS), and (2) whether there are quantitative and/or qualitative sex differences in the genetic contributions to variation on this scale. These questions were evaluated using data obtained from a large community sample of adult Australian twins (N=4,355) that included opposite-sex pairs. Participants completed a modified 15-item version of the MIS within a larger assessment battery. Women reported both higher means and variability on the MIS than men; this was also observed within families (in opposite-sex twin pairs). Biometric modeling indicated that the proportion of variation in MIS scores due to genetic influences (indicating quantitative sex differences) and the specific latent genetic contributions to this variation (indicating qualitative sex differences) were the same in men and women. These findings clarify the nature of sex differences in magical ideation and point to avenues for future research. PMID:24364500

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology.

PubMed

Wang, Baojun; Kitney, Richard I; Joly, Nicolas; Buck, Martin

2011-10-18

Modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AND gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae. The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ(54)-dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AND integration behaviour. The AND gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a NOT gate module to produce a combinatorial NAND gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts. © 2011 Macmillan Publishers Limited. All rights reserved.

In Search of Genes Associated with Risk for Psychopathic Tendencies in Children: A Two-Stage Genome-Wide Association Study of Pooled DNA

ERIC Educational Resources Information Center

Viding, Essi; Hanscombe, Ken B.; Curtis, Charles J. C.; Davis, Oliver S. P.; Meaburn, Emma L.; Plomin, Robert

2010-01-01

Background: Quantitative genetic data from our group indicates that antisocial behaviour (AB) is strongly heritable when coupled with psychopathic, callous-unemotional (CU) personality traits. We have also demonstrated that the genetic influences for AB and CU overlap considerably. We conducted a genome-wide association scan that capitalises on…

Age-Related Shifts in the Density and Distribution of Genetic Marker Water Quality Indicators in Cow and Calf Feces (Journal)

EPA Science Inventory

Calves (≤ 226 kg body mass) make up about 16% of the current bovine population in the United States and can excrete high levels of human pathogens. We describe the density and distribution of genetic markers from 11 PCR- and real-time quantitative PCR-based assays including CF...

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

Single Cell Transfection through Precise Microinjection with Quantitatively Controlled Injection Volumes

NASA Astrophysics Data System (ADS)

Chow, Yu Ting; Chen, Shuxun; Wang, Ran; Liu, Chichi; Kong, Chi-Wing; Li, Ronald A.; Cheng, Shuk Han; Sun, Dong

2016-04-01

Cell transfection is a technique wherein foreign genetic molecules are delivered into cells. To elucidate distinct responses during cell genetic modification, methods to achieve transfection at the single-cell level are of great value. Herein, we developed an automated micropipette-based quantitative microinjection technology that can deliver precise amounts of materials into cells. The developed microinjection system achieved precise single-cell microinjection by pre-patterning cells in an array and controlling the amount of substance delivered based on injection pressure and time. The precision of the proposed injection technique was examined by comparing the fluorescence intensities of fluorescent dye droplets with a standard concentration and water droplets with a known injection amount of the dye in oil. Injection of synthetic modified mRNA (modRNA) encoding green fluorescence proteins or a cocktail of plasmids encoding green and red fluorescence proteins into human foreskin fibroblast cells demonstrated that the resulting green fluorescence intensity or green/red fluorescence intensity ratio were well correlated with the amount of genetic material injected into the cells. Single-cell transfection via the developed microinjection technique will be of particular use in cases where cell transfection is challenging and genetically modified of selected cells are desired.

Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits.

PubMed

Adriaens, M E; Bezzina, C R

2018-06-22

Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.

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

PubMed Central

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

2011-01-01

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

Preserving genes, species, or ecosystems? Healing the fractured foundations of conservation policy.

PubMed

Bowen, B W

1999-12-01

The scientific foundations of conservation policy are the subject of a recent tripolar debate, with systematists arguing for the primacy of phylogenetic rankings, ecologists arguing for protection at the level of populations or ecosystems, and evolutionary biologists urging more attention for the factors that enhance adaptation and biodiversity. In the field of conservation genetics, this controversy is manifested in the diverse viewpoints of molecular systematists, population biologists, and evolutionary (and quantitative) geneticists. A resolution of these viewpoints is proposed here, based on the premise that preserving particular objects (genes, species, or ecosystems) is not the ultimate goal of conservation. In order to be successful, conservation efforts must preserve the processes of life. This task requires the identification and protection of diverse branches in the tree of life (phylogenetics), the maintenance of life-support systems for organisms (ecology), and the continued adaptation of organisms to changing environments (evolution). None of these objectives alone is sufficient to preserve the threads of life across time. Under this temporal perspective, molecular genetic technologies have applications in all three conservation agendas; DNA sequence comparisons serve the phylogenetic goals, population genetic markers serve the ecological goals, quantitative genetics and genome explorations serve the evolutionary goals.

An example of demographic anthropology, the study of matrimonial exchanges--endogamy, choice of spouse and preferential marriage.

PubMed

Cazes, Marie-Hélène

2006-09-01

The development of demographic studies in anthropology is directly linked to the success of population genetics. The anthropodemographic or anthropogenetic approach is thus underpinned by questions of genetics. While demographers focus on population dynamics and renewal in quantitative terms, population geneticists refer not to individuals but to the sets of genes carried by individuals in a population. Their aim is to detect the factors and processes which influence the genetic evolution of a group, i.e. which modify gene frequencies from one generation to the next. Among them are the factors which affect modes of reproduction. To illustrate the association of these three approaches, i.e. demographic, anthropological and genetic, I use here the example of matrimonial exchanges--which lie at the heart of the population renewal process--among the Dogon of Boni, a Malian ethnic group living in the southern Sahel. We can see how successive analyses--starting with endogamy at macroscopic level and moving down to the individual with choice of spouse and preferential marriage-- combining both quantitative and qualitative approaches, can be used to obtain a detailed description of matrimonial exchanges which shed light upon and complement the three different viewpoints.

Single Cell Transfection through Precise Microinjection with Quantitatively Controlled Injection Volumes.

PubMed

Chow, Yu Ting; Chen, Shuxun; Wang, Ran; Liu, Chichi; Kong, Chi-Wing; Li, Ronald A; Cheng, Shuk Han; Sun, Dong

2016-04-12

Cell transfection is a technique wherein foreign genetic molecules are delivered into cells. To elucidate distinct responses during cell genetic modification, methods to achieve transfection at the single-cell level are of great value. Herein, we developed an automated micropipette-based quantitative microinjection technology that can deliver precise amounts of materials into cells. The developed microinjection system achieved precise single-cell microinjection by pre-patterning cells in an array and controlling the amount of substance delivered based on injection pressure and time. The precision of the proposed injection technique was examined by comparing the fluorescence intensities of fluorescent dye droplets with a standard concentration and water droplets with a known injection amount of the dye in oil. Injection of synthetic modified mRNA (modRNA) encoding green fluorescence proteins or a cocktail of plasmids encoding green and red fluorescence proteins into human foreskin fibroblast cells demonstrated that the resulting green fluorescence intensity or green/red fluorescence intensity ratio were well correlated with the amount of genetic material injected into the cells. Single-cell transfection via the developed microinjection technique will be of particular use in cases where cell transfection is challenging and genetically modified of selected cells are desired.

DENSITY-DEPENDENT SELECTION ON CONTINUOUS CHARACTERS: A QUANTITATIVE GENETIC MODEL.

PubMed

Tanaka, Yoshinari

1996-10-01

A quantitative genetic model of density-dependent selection is presented and analysed with parameter values obtained from laboratory selection experiments conducted by Mueller and his coworkers. The ecological concept of r- and K-selection is formulated in terms of selection gradients on underlying phenotypic characters that influence the density-dependent measure of fitness. Hence the selection gradients on traits are decomposed into two components, one that changes in the direction to increase r, and one that changes in the direction to increase K. The relative importance of the two components is determined by temporal fluctuations in population density. The evolutionary rate of r and K (per-generation changes in r and K due to the genetic responses of the underlying traits) is also formulated. Numerical simulation has shown that with moderate genetic variances of the underlying characters, r and K can evolve rapidly and the evolutionary rate is influenced by synergistic interaction between characters that contribute to r and K. But strong r-selection can occur only with severe and continuous disturbances of populations so that the population density is kept low enough to prevent K-selection. © 1996 The Society for the Study of Evolution.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Genetic constraints predict evolutionary divergence in Dalechampia blossoms.

PubMed

Bolstad, Geir H; Hansen, Thomas F; Pélabon, Christophe; Falahati-Anbaran, Mohsen; Pérez-Barrales, Rocío; Armbruster, W Scott

2014-08-19

If genetic constraints are important, then rates and direction of evolution should be related to trait evolvability. Here we use recently developed measures of evolvability to test the genetic constraint hypothesis with quantitative genetic data on floral morphology from the Neotropical vine Dalechampia scandens (Euphorbiaceae). These measures were compared against rates of evolution and patterns of divergence among 24 populations in two species in the D. scandens species complex. We found clear evidence for genetic constraints, particularly among traits that were tightly phenotypically integrated. This relationship between evolvability and evolutionary divergence is puzzling, because the estimated evolvabilities seem too large to constitute real constraints. We suggest that this paradox can be explained by a combination of weak stabilizing selection around moving adaptive optima and small realized evolvabilities relative to the observed additive genetic variance.

Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

PubMed Central

Kappen, Claudia

2016-01-01

The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342

Longevity and aging. Mechanisms and perspectives.

PubMed

Labat-Robert, J; Robert, L

2015-12-01

Longevity can mostly be determined with relative accuracy from birth and death registers when available. Aging is a multifactorial process, much more difficult to quantitate. Every measurable physiological function declines with specific speeds over a wide range. The mechanisms involved are also different, genetic factors are of importance for longevity determinations. The best-known genes involved are the Sirtuins, active at the genetic and epigenetic level. Aging is multifactorial, not "coded" in the genome. There are, however, a number of well-studied physical and biological parameters involved in aging, which can be determined and quantitated. We shall try to identify parameters affecting longevity as well as aging and suggest some reasonable predictions for the future. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Effect of genetic algorithm as a variable selection method on different chemometric models applied for the analysis of binary mixture of amoxicillin and flucloxacillin: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2016-03-01

Different chemometric models were applied for the quantitative analysis of amoxicillin (AMX), and flucloxacillin (FLX) in their binary mixtures, namely, partial least squares (PLS), spectral residual augmented classical least squares (SRACLS), concentration residual augmented classical least squares (CRACLS) and artificial neural networks (ANNs). All methods were applied with and without variable selection procedure (genetic algorithm GA). The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample via handling the UV spectral data. Robust and simpler models were obtained by applying GA. The proposed methods were found to be rapid, simple and required no preliminary separation steps.

Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism.

PubMed

Guo, Longhua; Qiu, Bin; Chi, Yuwu; Chen, Guonan

2008-09-01

In this paper, an ultrasensitive CE-CL detection system coupled with a novel double-on-column coaxial flow detection interface was developed for the detection of PCR products. A reliable procedure based on this system had been demonstrated for qualitative and quantitative analysis of genetically modified organism-the detection of Roundup Ready Soy (RRS) samples was presented as an example. The promoter, terminator, function and two reference genes of RRS were amplified with multiplex PCR simultaneously. After that, the multiplex PCR products were labeled with acridinium ester at the 5'-terminal through an amino modification and then analyzed by the proposed CE-CL system. Reproducibility of analysis times and peak heights for the CE-CL analysis were determined to be better than 0.91 and 3.07% (RSD, n=15), respectively, for three consecutive days. It was shown that this method could accurately and qualitatively detect RRS standards and the simulative samples. The evaluation in terms of quantitative analysis of RRS provided by this new method was confirmed by comparing our assay results with those of the standard real-time quantitative PCR (RT-QPCR) using SYBR Green I dyes. The results showed a good coherence between the two methods. This approach demonstrated the possibility for accurate qualitative and quantitative detection of GM plants in a single run.

Genomic Characterization of the Evolutionary Potential of the Sea Urchin Strongylocentrotus droebachiensis Facing Ocean Acidification

PubMed Central

Dorey, Narimane; Garfield, David A.; Stumpp, Meike; Dupont, Sam; Wray, Gregory A.

2016-01-01

Abstract Ocean acidification (OA) is increasing due to anthropogenic CO2 emissions and poses a threat to marine species and communities worldwide. To better project the effects of acidification on organisms’ health and persistence, an understanding is needed of the 1) mechanisms underlying developmental and physiological tolerance and 2) potential populations have for rapid evolutionary adaptation. This is especially challenging in nonmodel species where targeted assays of metabolism and stress physiology may not be available or economical for large-scale assessments of genetic constraints. We used mRNA sequencing and a quantitative genetics breeding design to study mechanisms underlying genetic variability and tolerance to decreased seawater pH (-0.4 pH units) in larvae of the sea urchin Strongylocentrotus droebachiensis. We used a gene ontology-based approach to integrate expression profiles into indirect measures of cellular and biochemical traits underlying variation in larval performance (i.e., growth rates). Molecular responses to OA were complex, involving changes to several functions such as growth rates, cell division, metabolism, and immune activities. Surprisingly, the magnitude of pH effects on molecular traits tended to be small relative to variation attributable to segregating functional genetic variation in this species. We discuss how the application of transcriptomics and quantitative genetics approaches across diverse species can enrich our understanding of the biological impacts of climate change. PMID:28082601

A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait

PubMed Central

Geroldinger, Ludwig; Bürger, Reinhard

2014-01-01

The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated. PMID:24726489

A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait.

PubMed

Geroldinger, Ludwig; Bürger, Reinhard

2014-06-01

The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

PubMed

Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

2017-07-14

Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

Genetic analysis of PAX3 for diagnosis of Waardenburg syndrome type I.

PubMed

Matsunaga, Tatsuo; Mutai, Hideki; Namba, Kazunori; Morita, Noriko; Masuda, Sawako

2013-04-01

PAX3 genetic analysis increased the diagnostic accuracy for Waardenburg syndrome type I (WS1). Analysis of the three-dimensional (3D) structure of PAX3 helped verify the pathogenicity of a missense mutation, and multiple ligation-dependent probe amplification (MLPA) analysis of PAX3 increased the sensitivity of genetic diagnosis in patients with WS1. Clinical diagnosis of WS1 is often difficult in individual patients with isolated, mild, or non-specific symptoms. The objective of the present study was to facilitate the accurate diagnosis of WS1 through genetic analysis of PAX3 and to expand the spectrum of known PAX3 mutations. In two Japanese families with WS1, we conducted a clinical evaluation of symptoms and genetic analysis, which involved direct sequencing, MLPA analysis, quantitative PCR of PAX3, and analysis of the predicted 3D structure of PAX3. The normal-hearing control group comprised 92 subjects who had normal hearing according to pure tone audiometry. In one family, direct sequencing of PAX3 identified a heterozygous mutation, p.I59F. Analysis of PAX3 3D structures indicated that this mutation distorted the DNA-binding site of PAX3. In the other family, MLPA analysis and subsequent quantitative PCR detected a large, heterozygous deletion spanning 1759-2554 kb that eliminated 12-18 genes including a whole PAX3 gene.

A formulation of the foundations of genetics and evolution.

PubMed

Bahr, Brian Edward

2016-05-01

This paper proposes a formulation of theories of the foundations of genetics and evolution that can be used to mathematically simulate phenotype expression, reproduction, mutation, and natural selection. It will be shown that Mendelian inheritance can be mathematically simulated with expressions involving matrices and that these expressions can also simulate phenomena that are modifications to Mendel's basic principles, like alleles that give rise to quantitative effects and traits that are the expression of multiple alleles and/or multiple genetic loci. Copyright © 2016 Elsevier Inc. All rights reserved.

Applications of the 1000 Genomes Project resources.

PubMed

Zheng-Bradley, Xiangqun; Flicek, Paul

2017-05-01

The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. © The Author 2016. Published by Oxford University Press.

Recent genetic discoveries in osteoporosis, sarcopenia and obesity.

PubMed

Urano, Tomohiko; Inoue, Satoshi

2015-01-01

Osteoporosis is a skeletal disorder characterized by low bone mineral density (BMD) and an increased susceptibility to fractures. Evidence from genetic studies indicates that BMD, a complex quantitative trait with a normal distribution, is genetically controlled. Genome-wide association studies (GWAS) as well as studies using candidate gene approaches have identified single-nucleotide polymorphisms (SNPs) that are associated with BMD, osteoporosis and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding WNT/β-catenin signaling proteins. Understanding the genetics of osteoporosis will help to identify novel candidates for diagnostic and therapeutic targets. Genetic factors are also important for the development of sarcopenia, which is characterized by a loss of lean body mass, and obesity, which is characterized by high fat mass. Hence, in this review, we discuss the genetic factors, identified by genetic studies, which regulate the body components related to osteoporosis, sarcopenia, and obesity.

Molecular biology of Homo sapiens: Abstracts of papers presented at the 51st Cold Spring Harbor symposium on quantitative biology

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

Watson, J.D.; Siniscalco, M.

This volume contains abstracts of papers presented at the 51st Cold Springs Harbor Symposium on Quantitative Biology. The topic for this meeting was the ''Molecular Biology of Homo sapiens.'' Sessions were entitled Human Gene Map, Human Cancer Genes, Genetic Diagnosis, Human Evolution, Drugs Made Off Human Genes, Receptors, and Gene Therapy. (DT)

EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits.

PubMed

Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen

2018-01-25

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

An ultra-high-density map as a community resource for discerning the genetic basis of quantitative traits in maize

USDA-ARS?s Scientific Manuscript database

In this study, we generated a linkage map containing 1,151,856 high quality SNPs between Mo17 and B73, which were verified in the maize intermated B73'×'Mo17 (IBM) Syn10 population. This resource is an excellent complement to existing maize genetic maps available in an online database (iPlant, http:...

A SNP genetic linkage map based on the ‘Hamilton’ by ‘Spencer’ recombinant inbred line (RIL) population identified QTL for seed Isoflavone contents in soybean

USDA-ARS?s Scientific Manuscript database

Soybean is one of the most important crops worldwide for its protein, oil as well as the health beneficial phytoestrogens or isoflavone. This study reports a relatively dense SNP-Based genetic map based on ‘Hamilton’ by ‘Spencer’ recombinant inbred line (RIL) population and quantitative t...

Quantitative genetics in natural populations: Means of monitoring natural biological processes

Treesearch

Brook G. Milligan

2001-01-01

One of the goals of conservation biology is to maintain the integrity of natural processes in populations of rare plants. In the short term one of the main concerns is often whether the mating system of rare plants is disrupted, for example, by fragmentation. In the long term one of the main concerns is often whether small isolated populations maintain enough genetic...

Investigating genetic loci that encode plant-derived paleoclimate proxies

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Consistent etiology of severe, frequent psychotic experiences and milder, less frequent manifestations: A twin study of specific psychotic experiences in adolescence

PubMed Central

Zavos, Helena M.S.; Freeman, Daniel; Haworth, Claire M. A.; McGuire, Philip; Plomin, Robert; Cardno, Alastair G.; Ronald, Angelica

2014-01-01

Context The onset of psychosis is usually preceded by psychotic experiences, but little is known about their causes. The present study investigated the degree of genetic and environmental influences on specific psychotic experiences, assessed dimensionally, in adolescence in the community and in individuals with many, frequent experiences (defined using quantitative cut-offs). The degree of overlap in etiological influences between specific psychotic experiences was also investigated Objective Investigate degree of genetic and environmental influences on specific psychotic experiences, assessed dimensionally, in adolescence in the community and in individuals having many, frequent experiences (defined using quantitative cut-offs). Test degree of overlap in etiological influences between specific psychotic experiences. Design Classic twin design. Structural equation model-fitting. Univariate and bivariate twin models, liability threshold models, DeFries-Fulker extremes analysis and the Cherny Method. Setting Representative community sample of twins from England and Wales. Participants 5059 adolescent twin pairs (Mean age: 16.31 yrs, SD: 0.68 yrs). Main outcome measure Psychotic experiences assessed as quantitative traits (self-rated paranoia, hallucinations, cognitive disorganization, grandiosity, anhedonia; parent-rated negative symptoms). Results Genetic influences were apparent for all psychotic experiences (15-59%) with modest shared environment for hallucinations and negative symptoms (17-24%) and significant nonshared environment (49-64% for the self-rated scales, 17% for Parent-rated Negative Symptoms). Three different empirical approaches converged to suggest that the etiology in extreme groups (most extreme-scoring 5%, 10% and 15%) did not differ significantly from that of the whole distribution. There was no linear change in the heritability across the distribution of psychotic experiences, with the exception of a modest increase in heritability for increasing severity of parent-rated negative symptoms. Of the psychotic experiences that showed covariation, this appeared to be due to shared genetic influences (bivariate heritabilities = .54-.71). Conclusions and Relevance These findings are consistent with the concept of a psychosis continuum, suggesting that the same genetic and environmental factors influence both extreme, frequent psychotic experiences and milder, less frequent manifestations in adolescents. Individual psychotic experiences in adolescence, assessed quantitatively, have lower heritability estimates and higher estimates of nonshared environment than those for the liability to schizophrenia. Heritability varies by type of psychotic experience, being highest for paranoia and parent-rated negative symptoms, and lowest for hallucinations. PMID:25075799

International collaborative study of the endogenous reference gene, sucrose phosphate synthase (SPS), used for qualitative and quantitative analysis of genetically modified rice.

PubMed

Jiang, Lingxi; Yang, Litao; Zhang, Haibo; Guo, Jinchao; Mazzara, Marco; Van den Eede, Guy; Zhang, Dabing

2009-05-13

One rice ( Oryza sativa ) gene, sucrose phosphate synthase (SPS), has been proven to be a suitable endogenous reference gene for genetically modified (GM) rice detection in a previous study. Herein are the reported results of an international collaborative ring trial for validation of the SPS gene as an endogenous reference gene and its optimized qualitative and quantitative polymerase chain reaction (PCR) systems. A total of 12 genetically modified organism (GMO) detection laboratories from seven countries participated in the ring trial and returned their results. The validated results confirmed the species specificity of the method through testing 10 plant genomic DNAs, low heterogeneity, and a stable single-copy number of the rice SPS gene among 7 indica varieties and 5 japonica varieties. The SPS qualitative PCR assay was validated with a limit of detection (LOD) of 0.1%, which corresponded to about 230 copies of haploid rice genomic DNA, while the limit of quantification (LOQ) for the quantitative PCR system was about 23 copies of haploid rice genomic DNA, with acceptable PCR efficiency and linearity. Furthermore, the bias between the test and true values of eight blind samples ranged from 5.22 to 26.53%. Thus, we believe that the SPS gene is suitable for use as an endogenous reference gene for the identification and quantification of GM rice and its derivates.

Determination of Mycotoxin Production of Fusarium Species in Genetically Modified Maize Varieties by Quantitative Flow Immunocytometry.

PubMed

Bánáti, Hajnalka; Darvas, Béla; Fehér-Tóth, Szilvia; Czéh, Árpád; Székács, András

2017-02-22

Levels of mycotoxins produced by Fusarium species in genetically modified (GM) and near-isogenic maize, were determined using multi-analyte, microbead-based flow immunocytometry with fluorescence detection, for the parallel quantitative determination of fumonisin B1, deoxynivalenol, zearalenone, T-2, ochratoxin A, and aflatoxin B1. Maize varieties included the genetic events MON 810 and DAS-59122-7 , and their isogenic counterparts. Cobs were artificially infested by F. verticillioides and F. proliferatum conidia, and contained F. graminearum and F. sporotrichoides natural infestation. The production of fumonisin B1 and deoxynivalenol was substantially affected in GM maize lines: F. verticillioides , with the addition of F. graminearum and F. sporotrichoides , produced significantly lower levels of fumonisin B1 (~300 mg·kg -1 ) in DAS-59122-7 than in its isogenic line (~580 mg·kg -1 ), while F. proliferatum , in addition to F. graminearum and F. sporotrichoides , produced significantly higher levels of deoxynivalenol (~18 mg·kg -1 ) in MON 810 than in its isogenic line (~5 mg·kg -1 ). Fusarium verticillioides , with F. graminearum and F. sporotrichoides , produced lower amounts of deoxynivalenol and zearalenone than F. proliferatum , with F. graminearum and F. sporotrichoides . T-2 toxin production remained unchanged when considering the maize variety. The results demonstrate the utility of the Fungi-Plex™ quantitative flow immunocytometry method, applied for the high throughput parallel determination of the target mycotoxins.

Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations

PubMed Central

Evans, Kathryn S.; Zhao, Yuehui; Brady, Shannon C.; Long, Lijiang; McGrath, Patrick T.; Andersen, Erik C.

2016-01-01

Species inhabit a variety of environmental niches, and the adaptation to a particular niche is often controlled by genetic factors, including gene-by-environment interactions. The genes that vary in order to regulate the ability to colonize a niche are often difficult to identify, especially in the context of complex ecological systems and in experimentally uncontrolled natural environments. Quantitative genetic approaches provide an opportunity to investigate correlations between genetic factors and environmental parameters that might define a niche. Previously, we have shown how a collection of 208 whole-genome sequenced wild Caenorhabditis elegans can facilitate association mapping approaches. To correlate climate parameters with the variation found in this collection of wild strains, we used geographic data to exhaustively curate daily weather measurements in short-term (3 month), middle-term (one year), and long-term (three year) durations surrounding the date of strain isolation. These climate parameters were used as quantitative traits in association mapping approaches, where we identified 11 quantitative trait loci (QTL) for three climatic variables: elevation, relative humidity, and average temperature. We then narrowed the genomic interval of interest to identify gene candidates with variants potentially underlying phenotypic differences. Additionally, we performed two-strain competition assays at high and low temperatures to validate a QTL that could underlie adaptation to temperature and found suggestive evidence supporting that hypothesis. PMID:27866149

An event-specific method for the detection and quantification of ML01, a genetically modified Saccharomyces cerevisiae wine strain, using quantitative PCR.

PubMed

Vaudano, Enrico; Costantini, Antonella; Garcia-Moruno, Emilia

2016-10-03

The availability of genetically modified (GM) yeasts for winemaking and, in particular, transgenic strains based on the integration of genetic constructs deriving from other organisms into the genome of Saccharomyces cerevisiae, has been a reality for several years. Despite this, their use is only authorized in a few countries and limited to two strains: ML01, able to convert malic acid into lactic acid during alcoholic fermentation, and ECMo01 suitable for reducing the risk of carbamate production. In this work we propose a quali-quantitative culture-independent method for the detection of GM yeast ML01 in commercial preparations of ADY (Active Dry Yeast) consisting of efficient extraction of DNA and qPCR (quantitative PCR) analysis based on event-specific assay targeting MLC (malolactic cassette), and a taxon-specific S. cerevisiae assay detecting the MRP2 gene. The ADY DNA extraction methodology has been shown to provide good purity DNA suitable for subsequent qPCR. The MLC and MRP2 qPCR assay showed characteristics of specificity, dynamic range, limit of quantification (LOQ) limit of detection (LOD), precision and trueness, which were fully compliant with international reference guidelines. The method has been shown to reliably detect 0.005% (mass/mass) of GM ML01 S. cerevisiae in commercial preparations of ADY. Copyright © 2016 Elsevier B.V. All rights reserved.

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID:29547617

Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT).

PubMed

Tsairidou, Smaragda; Brotherstone, Susan; Coffey, Mike; Bishop, Stephen C; Woolliams, John A

2016-11-24

Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control. The aim of this study was to conduct a quantitative genetic analysis of SICCT measurements collected during bTB herd testing. Genetic selection for bTB resistance will be partially informed by SICCT-based diagnosis; therefore it is important to know whether, in addition to increasing bTB resistance, this might also alter genetically the epidemiological characteristics of SICCT. Our main findings are that: (1) the SICCT test is robust at the genetic level, since its hierarchy and comparative nature provide substantial protection against random genetic changes that arise from genetic drift and from correlated responses among its components due to either natural or artificial selection; (2) the comparative nature of SICCT provides effective control for initial skin thickness and age-dependent differences; and (3) continuous variation in SICCT is only lowly heritable and has a weak correlation with SICCT positivity among healthy animals which was not significantly different from zero (P > 0.05). These emerging results demonstrate that genetic selection for bTB resistance is unlikely to change the probability of correctly identifying non-infected animals, i.e. the test's specificity, while reducing the overall number of cases. This study cannot exclude all theoretical risks from selection on resistance to bTB infection but the role of SICCT in disease control is unlikely to be rapidly undermined, with any adverse correlated responses expected to be weak and slow, which allow them to be monitored and managed.

Genetic constraints predict evolutionary divergence in Dalechampia blossoms

PubMed Central

Bolstad, Geir H.; Hansen, Thomas F.; Pélabon, Christophe; Falahati-Anbaran, Mohsen; Pérez-Barrales, Rocío; Armbruster, W. Scott

2014-01-01

If genetic constraints are important, then rates and direction of evolution should be related to trait evolvability. Here we use recently developed measures of evolvability to test the genetic constraint hypothesis with quantitative genetic data on floral morphology from the Neotropical vine Dalechampia scandens (Euphorbiaceae). These measures were compared against rates of evolution and patterns of divergence among 24 populations in two species in the D. scandens species complex. We found clear evidence for genetic constraints, particularly among traits that were tightly phenotypically integrated. This relationship between evolvability and evolutionary divergence is puzzling, because the estimated evolvabilities seem too large to constitute real constraints. We suggest that this paradox can be explained by a combination of weak stabilizing selection around moving adaptive optima and small realized evolvabilities relative to the observed additive genetic variance. PMID:25002700

Short Communication: Genetic linkage map of Cucurbita maxima with molecular and morphological markers.

PubMed

Ge, Y; Li, X; Yang, X X; Cui, C S; Qu, S P

2015-05-22

Cucurbita maxima is one of the most widely cultivated vegetables in China and exhibits distinct morphological characteristics. In this study, genetic linkage analysis with 57 simple-sequence repeats, 21 amplified fragment length polymorphisms, 3 random-amplified polymorphic DNA, and one morphological marker revealed 20 genetic linkage groups of C. maxima covering a genetic distance of 991.5 cM with an average of 12.1 cM between adjacent markers. Genetic linkage analysis identified the simple-sequence repeat marker 'PU078072' 5.9 cM away from the locus 'Rc', which controls rind color. The genetic map in the present study will be useful for better mapping, tagging, and cloning of quantitative trait loci/gene(s) affecting economically important traits and for breeding new varieties of C. maxima through marker-assisted selection.

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

Waters, M.D.; Stack, H.F.; Garrett, N.E.

A graphic approach, terms a Genetic Activity Profile (GAP), was developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose or highest ineffective dose is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for producing and evaluating genetic activity profilemore » was developed in collaboration with the International Agency for Research on Cancer (IARC). Data on individual chemicals were compiles by IARC and by the US Environmental Protection Agency (EPA). Data are available on 343 compounds selected from volumes 1-53 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar profiles of genetic activity. Through examination of the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluation of chemical analogs. GAPs provided useful data for development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from an assessment of the genetic activity profiles of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines. 36 refs., 2 figs.« less

Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

PubMed Central

Watson, Nathaniel F.; Harden, Kathryn Paige; Buchwald, Dedra; Vitiello, Michael V.; Pack, Allan I.; Strachan, Eric; Goldberg, Jack

2014-01-01

Objective: We used quantitative genetic models to assess whether sleep duration modifies genetic and environmental influences on depressive symptoms. Method: Participants were 1,788 adult twins from 894 same-sex twin pairs (192 male and 412 female monozygotic [MZ] pairs, and 81 male and 209 female dizygotic [DZ] pairs] from the University of Washington Twin Registry. Participants self-reported habitual sleep duration and depressive symptoms. Data were analyzed using quantitative genetic interaction models, which allowed the magnitude of additive genetic, shared environmental, and non-shared environmental influences on depressive symptoms to vary with sleep duration. Results: Within MZ twin pairs, the twin who reported longer sleep duration reported fewer depressive symptoms (ec = -0.17, SE = 0.06, P < 0.05). There was a significant gene × sleep duration interaction effect on depressive symptoms (a'c = 0.23, SE = 0.08, P < 0.05), with the interaction occurring on genetic influences that are common to both sleep duration and depressive symptoms. Among individuals with sleep duration within the normal range (7-8.9 h/night), the total heritability (h2) of depressive symptoms was approximately 27%. However, among individuals with sleep duration within the low (< 7 h/night) or high (≥ 9 h/night) range, increased genetic influence on depressive symptoms was observed, particularly at sleep duration extremes (5 h/night: h2 = 53%; 10 h/night: h2 = 49%). Conclusion: Genetic contributions to depressive symptoms increase at both short and long sleep durations. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Stachan E; Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. SLEEP 2014;37(2):351-358. PMID:24497663

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

PubMed

Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2016-06-01

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

Targeted and Untargeted Approaches Unravel Novel Candidate Genes and Diagnostic SNPs for Quantitative Resistance of the Potato (Solanum tuberosum L.) to Phytophthora infestans Causing the Late Blight Disease.

PubMed

Mosquera, Teresa; Alvarez, Maria Fernanda; Jiménez-Gómez, José M; Muktar, Meki Shehabu; Paulo, Maria João; Steinemann, Sebastian; Li, Jinquan; Draffehn, Astrid; Hofmann, Andrea; Lübeck, Jens; Strahwald, Josef; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Walkemeier, Birgit; Gebhardt, Christiane

2016-01-01

The oomycete Phytophthora infestans causes late blight of potato, which can completely destroy the crop. Therefore, for the past 160 years, late blight has been the most important potato disease worldwide. The identification of cultivars with high and durable field resistance to P. infestans is an objective of most potato breeding programs. This type of resistance is polygenic and therefore quantitative. Its evaluation requires multi-year and location trials. Furthermore, quantitative resistance to late blight correlates with late plant maturity, a negative agricultural trait. Knowledge of the molecular genetic basis of quantitative resistance to late blight not compromised by late maturity is very limited. It is however essential for developing diagnostic DNA markers that facilitate the efficient combination of superior resistance alleles in improved cultivars. We used association genetics in a population of 184 tetraploid potato cultivars in order to identify single nucleotide polymorphisms (SNPs) that are associated with maturity corrected resistance (MCR) to late blight. The population was genotyped for almost 9000 SNPs from three different sources. The first source was candidate genes specifically selected for their function in the jasmonate pathway. The second source was novel candidate genes selected based on comparative transcript profiling (RNA-Seq) of groups of genotypes with contrasting levels of quantitative resistance to P. infestans. The third source was the first generation 8.3k SolCAP SNP genotyping array available in potato for genome wide association studies (GWAS). Twenty seven SNPs from all three sources showed robust association with MCR. Some of those were located in genes that are strong candidates for directly controlling quantitative resistance, based on functional annotation. Most important were: a lipoxygenase (jasmonate pathway), a 3-hydroxy-3-methylglutaryl coenzyme A reductase (mevalonate pathway), a P450 protein (terpene biosynthesis), a transcription factor and a homolog of a major gene for resistance to P. infestans from the wild potato species Solanum venturii. The candidate gene approach and GWAS complemented each other as they identified different genes. The results of this study provide new insight in the molecular genetic basis of quantitative resistance in potato and a toolbox of diagnostic SNP markers for breeding applications.

Targeted and Untargeted Approaches Unravel Novel Candidate Genes and Diagnostic SNPs for Quantitative Resistance of the Potato (Solanum tuberosum L.) to Phytophthora infestans Causing the Late Blight Disease

PubMed Central

Jiménez-Gómez, José M.; Muktar, Meki Shehabu; Paulo, Maria João; Steinemann, Sebastian; Li, Jinquan; Draffehn, Astrid; Hofmann, Andrea; Lübeck, Jens; Strahwald, Josef; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Walkemeier, Birgit; Gebhardt, Christiane

2016-01-01

The oomycete Phytophthora infestans causes late blight of potato, which can completely destroy the crop. Therefore, for the past 160 years, late blight has been the most important potato disease worldwide. The identification of cultivars with high and durable field resistance to P. infestans is an objective of most potato breeding programs. This type of resistance is polygenic and therefore quantitative. Its evaluation requires multi-year and location trials. Furthermore, quantitative resistance to late blight correlates with late plant maturity, a negative agricultural trait. Knowledge of the molecular genetic basis of quantitative resistance to late blight not compromised by late maturity is very limited. It is however essential for developing diagnostic DNA markers that facilitate the efficient combination of superior resistance alleles in improved cultivars. We used association genetics in a population of 184 tetraploid potato cultivars in order to identify single nucleotide polymorphisms (SNPs) that are associated with maturity corrected resistance (MCR) to late blight. The population was genotyped for almost 9000 SNPs from three different sources. The first source was candidate genes specifically selected for their function in the jasmonate pathway. The second source was novel candidate genes selected based on comparative transcript profiling (RNA-Seq) of groups of genotypes with contrasting levels of quantitative resistance to P. infestans. The third source was the first generation 8.3k SolCAP SNP genotyping array available in potato for genome wide association studies (GWAS). Twenty seven SNPs from all three sources showed robust association with MCR. Some of those were located in genes that are strong candidates for directly controlling quantitative resistance, based on functional annotation. Most important were: a lipoxygenase (jasmonate pathway), a 3-hydroxy-3-methylglutaryl coenzyme A reductase (mevalonate pathway), a P450 protein (terpene biosynthesis), a transcription factor and a homolog of a major gene for resistance to P. infestans from the wild potato species Solanum venturii. The candidate gene approach and GWAS complemented each other as they identified different genes. The results of this study provide new insight in the molecular genetic basis of quantitative resistance in potato and a toolbox of diagnostic SNP markers for breeding applications. PMID:27281327

mGluR7 genetics and alcohol: intersection yields clues for addiction.

PubMed

Gyetvai, Beatrix; Simonyi, Agnes; Oros, Melinda; Saito, Mariko; Smiley, John; Vadász, Csaba

2011-06-01

Development of addiction to alcohol or other substances can be attributed in part to exposure-dependent modifications at synaptic efficacy leading to an organism which functions at an altered homeostatic setpoint. Genetic factors may also influence setpoints and the stability of the homeostatic system of an organism. Quantitative genetic analysis of voluntary alcohol drinking, and mapping of the involved genes in the quasi-congenic Recombinant QTL Introgression strain system, identified Eac2 as a Quantitative Trait Locus (QTL) on mouse chromosome 6 which explained 18% of the variance with an effect size of 2.09 g/kg/day alcohol consumption, and Grm7 as a quantitative trait gene underlying Eac2 [Vadasz et al. in Neurochem Res 32:1099-1112, 100, Genomics 90:690-702, 102]. In earlier studies, the product of Grm7 mGluR7, a G protein-coupled receptor, has been implicated in stress systems [Mitsukawa et al. in Proc Natl Acad Sci USA 102:18712-18717, 63], anxiety-like behaviors [Cryan et al. in Eur J Neurosci 17:2409-2417, 14], memory [Holscher et al. in Learn Mem 12:450-455, 26], and psychiatric disorders (e.g., [Mick et al. in Am J Med Genet B Neuropsychiatr Genet 147B:1412-1418, 61; Ohtsuki et al. in Schizophr Res 101:9-16, 72; Pergadia et al. in Paper presented at the 38th Annual Meeting of the Behavior Genetics Association, Louisville, Kentucky, USA, 76]. Here, in experiments with mice, we show that (1) Grm7 knockout mice express increased alcohol consumption, (2) sub-congenic, and congenic mice carrying a Grm7 variant characterized by higher Grm7 mRNA drink less alcohol, and show a tendency for higher circadian dark phase motor activity in a wheel running paradigm, respectively, and (3) there are significant genetic differences in Grm7 mRNA abundance in the mouse brain between congenic and background mice identifying brain areas whose function is implicated in addiction related processes. We hypothesize that metabotropic glutamate receptors may function as regulators of homeostasis, and Grm7 (mGluR7) is involved in multiple processes (including stress, circadian activity, reward control, memory, etc.) which interact with substance use and the development of addiction. In conclusion, we suggest that mGluR7 is a significant new therapeutic target in addiction and related neurobehavioral disorders.

Genetic linkage map construction and QTL mapping of salt tolerance traits in Zoysiagrass (Zoysia japonica).

PubMed

Guo, Hailin; Ding, Wanwen; Chen, Jingbo; Chen, Xuan; Zheng, Yiqi; Wang, Zhiyong; Liu, Jianxiu

2014-01-01

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F1 population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.

Genetics of Variation in Serum Uric Acid and Cardiovascular Risk Factors in Mexican Americans

PubMed Central

Voruganti, V. Saroja; Nath, Subrata D.; Cole, Shelley A.; Thameem, Farook; Jowett, Jeremy B.; Bauer, Richard; MacCluer, Jean W.; Blangero, John; Comuzzie, Anthony G.; Abboud, Hanna E.; Arar, Nedal H.

2009-01-01

Background: Elevated serum uric acid is associated with several cardiovascular disease (CVD) risk factors such as hypertension, inflammation, endothelial dysfunction, insulin resistance, dyslipidemia, and obesity. However, the role of uric acid as an independent risk factor for CVD is not yet clear. Objective: The aim of the study was to localize quantitative trait loci regulating variation in serum uric acid and also establish the relationship between serum uric acid and other CVD risk factors in Mexican Americans (n = 848; men = 310, women = 538) participating in the San Antonio Family Heart Study. Methods: Quantitative genetic analysis was conducted using variance components decomposition method, implemented in the software program SOLAR. Results: Mean ± sd of serum uric acid was 5.35 ± 1.38 mg/dl. Univariate genetic analysis showed serum uric acid and other CVD risk markers to be significantly heritable (P < 0.005). Bivariate analysis showed significant correlation of serum uric acid with body mass index, waist circumference, waist/hip ratio, total body fat, plasma insulin, serum triglycerides, high-density lipoprotein cholesterol, C-reactive protein, and granulocyte macrophage-colony stimulating factor (P < 0.05). A genome-wide scan for detecting quantitative trait loci regulating serum uric acid variation showed a significant logarithm of odds (LOD) score of 4.72 (empirical LOD score = 4.62; P < 0.00001) on chromosome 3p26. One LOD support interval contains 25 genes, of which an interesting candidate gene is chemokine receptor 2. Summary: There is a significant genetic component in the variation in serum uric acid and evidence of pleiotropy between serum uric acid and other cardiovascular risk factors. PMID:19001525

Variation in life-history traits and their plasticities to elevational transplantation among seed families suggests potential for adaptative evolution of 15 tropical plant species to climate change.

PubMed

Ensslin, Andreas; Fischer, Markus

2015-08-01

• Because not all plant species will be able to move in response to global warming, adaptive evolution matters largely for plant persistence. As prerequisites for adaptive evolution, genetic variation in and selection on phenotypic traits are needed, but these aspects have not been studied in tropical species. We studied how plants respond to transplantation to different elevations on Mt. Kilimanjaro, Tanzania, and whether there is quantitative genetic (among-seed family) variation in and selection on life-history traits and their phenotypic plasticity to the different environments.• We reciprocally transplanted seed families of 15 common tropical, herbaceous species of the montane and savanna vegetation zone at Mt. Kilimanjaro to a watered experimental garden in the montane (1450 m) and in the savanna (880 m) zone at the mountain's slope and measured performance, reproductive, and phenological traits.• Plants generally performed worse in the savanna garden, indicating that the savanna climate was more stressful and thus that plants may suffer from future climate warming. We found significant quantitative genetic variation in all measured performance and reproductive traits in both gardens and for several measures of phenotypic plasticity in response to elevational transplantation. Moreover, we found positive selection on traits at low and intermediate trait values levelling to neutral or negative selection at high values.• We conclude that common plants at Mt. Kilimanjaro express quantitative genetic variation in fitness-relevant traits and in their plasticities, suggesting potential to adapt evolutionarily to future climate warming and increased temperature variability. © 2015 Botanical Society of America, Inc.

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

PubMed

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

2018-06-01

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

Event specific qualitative and quantitative polymerase chain reaction detection of genetically modified MON863 maize based on the 5'-transgene integration sequence.

PubMed

Yang, Litao; Xu, Songci; Pan, Aihu; Yin, Changsong; Zhang, Kewei; Wang, Zhenying; Zhou, Zhigang; Zhang, Dabing

2005-11-30

Because of the genetically modified organisms (GMOs) labeling policies issued in many countries and areas, polymerase chain reaction (PCR) methods were developed for the execution of GMO labeling policies, such as screening, gene specific, construct specific, and event specific PCR detection methods, which have become a mainstay of GMOs detection. The event specific PCR detection method is the primary trend in GMOs detection because of its high specificity based on the flanking sequence of the exogenous integrant. This genetically modified maize, MON863, contains a Cry3Bb1 coding sequence that produces a protein with enhanced insecticidal activity against the coleopteran pest, corn rootworm. In this study, the 5'-integration junction sequence between the host plant DNA and the integrated gene construct of the genetically modified maize MON863 was revealed by means of thermal asymmetric interlaced-PCR, and the specific PCR primers and TaqMan probe were designed based upon the revealed 5'-integration junction sequence; the conventional qualitative PCR and quantitative TaqMan real-time PCR detection methods employing these primers and probes were successfully developed. In conventional qualitative PCR assay, the limit of detection (LOD) was 0.1% for MON863 in 100 ng of maize genomic DNA for one reaction. In the quantitative TaqMan real-time PCR assay, the LOD and the limit of quantification were eight and 80 haploid genome copies, respectively. In addition, three mixed maize samples with known MON863 contents were detected using the established real-time PCR systems, and the ideal results indicated that the established event specific real-time PCR detection systems were reliable, sensitive, and accurate.

Quantitative genetic models of sexual selection by male choice.

PubMed

Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

Genetic Changes Accompanying the Domestication of Pisum sativum: Is there a Common Genetic Basis to the ‘Domestication Syndrome’ for Legumes?

PubMed Central

Weeden, Norman F.

2007-01-01

Background and Aims The changes that occur during the domestication of crops such as maize and common bean appear to be controlled by relatively few genes. This study investigates the genetic basis of domestication in pea (Pisum sativum) and compares the genes involved with those determined to be important in common bean domestication. Methods Quantitative trait loci and classical genetic analysis are used to investigate and identify the genes modified at three stages of the domestication process. Five recombinant inbred populations involving crosses between different lines representing different stages are examined. Key Results A minimum of 15 known genes, in addition to a relatively few major quantitative trait loci, are identified as being critical to the domestication process. These genes control traits such as pod dehiscence, seed dormancy, seed size and other seed quality characters, stem height, root mass, and harvest index. Several of the genes have pleiotropic effects that in species possessing a more rudimentary genetic characterization might have been interpreted as clusters of genes. Very little evidence for gene clustering was found in pea. When compared with common bean, pea has used a different set of genes to produce the same or similar phenotypic changes. Conclusions Similar to results for common bean, relatively few genes appear to have been modified during the domestication of pea. However, the genes involved are different, and there does not appear to be a common genetic basis to ‘domestication syndrome’ in the Fabaceae. PMID:17660515

The influence of mutation, recombination, population history, and selection on patterns of genetic diversity in Neisseria meningitidis.

PubMed

Jolley, K A; Wilson, D J; Kriz, P; McVean, G; Maiden, M C J

2005-03-01

Patterns of genetic diversity within populations of human pathogens, shaped by the ecology of host-microbe interactions, contain important information about the epidemiological history of infectious disease. Exploiting this information, however, requires a systematic approach that distinguishes the genetic signal generated by epidemiological processes from the effects of other forces, such as recombination, mutation, and population history. Here, a variety of quantitative techniques were employed to investigate multilocus sequence information from isolate collections of Neisseria meningitidis, a major cause of meningitis and septicemia world wide. This allowed quantitative evaluation of alternative explanations for the observed population structure. A coalescent-based approach was employed to estimate the rate of mutation, the rate of recombination, and the size distribution of recombination fragments from samples from disease-associated and carried meningococci obtained in the Czech Republic in 1993 and a global collection of disease-associated isolates collected globally from 1937 to 1996. The parameter estimates were used to reject a model in which genetic structure arose by chance in small populations, and analysis of molecular variation showed that geographically restricted gene flow was unlikely to be the cause of the genetic structure. The genetic differentiation between disease and carriage isolate collections indicated that, whereas certain genotypes were overrepresented among the disease-isolate collections (the "hyperinvasive" lineages), disease-associated and carried meningococci exhibited remarkably little differentiation at the level of individual nucleotide polymorphisms. In combination, these results indicated the repeated action of natural selection on meningococcal populations, possibly arising from the coevolutionary dynamic of host-pathogen interactions.

Morphoagronomic characterization and genetic diversity of a common bean RIL mapping population derived from the cross Rudá x AND 277.

PubMed

Silva, L C; Batista, R O; Anjos, R S R; Souza, M H; Carneiro, P C S; Souza, T L P O; Barros, E G; Carneiro, J E S

2016-07-29

Recombinant inbred lines (RILs) are a valuable resource for building genetic linkage maps. The presence of genetic variability in the RILs is essential for detecting associations between molecular markers and loci controlling agronomic traits of interest. The main goal of this study was to quantify the genetic diversity of a common bean RIL population derived from a cross between Rudá (Mesoamerican gene pool) and AND 277 (Andean gene pool). This population was developed by the single seed descent method from 500 F2 plants until the F10 generation. Seven quantitative traits were evaluated in the field in 393 RILs, the parental lines, and five control cultivars. The plants were grown using a randomized block design with additional controls and three replicates. Significant differences were observed among the RILs for all evaluated traits (P < 0.01). A comparison of the RILs and parental lines showed significant differences (P < 0.01) for the number of days to flowering (DFL) and to harvest (DH), productivity (PROD) and mass of 100 beans (M100); however, there were no significant differences for plant architecture, degree of seed flatness, or seed shape. These results indicate the occurrence of additive x additive epistatic interactions for DFL, DH, PROD, and M100. The 393 RILs were shown to fall into 10 clusters using Tocher's method. This RIL population clearly contained genetic variability for the evaluated traits, and this variability will be crucial for future studies involving genetic mapping and quantitative trait locus identification and analysis.

The genetic architecture of susceptibility to parasites.

PubMed

Wilfert, Lena; Schmid-Hempel, Paul

2008-06-30

The antagonistic co-evolution of hosts and their parasites is considered to be a potential driving force in maintaining host genetic variation including sexual reproduction and recombination. The examination of this hypothesis calls for information about the genetic basis of host-parasite interactions - such as how many genes are involved, how big an effect these genes have and whether there is epistasis between loci. We here examine the genetic architecture of quantitative resistance in animal and plant hosts by concatenating published studies that have identified quantitative trait loci (QTL) for host resistance in animals and plants. Collectively, these studies show that host resistance is affected by few loci. We particularly show that additional epistatic interactions, especially between loci on different chromosomes, explain a majority of the effects. Furthermore, we find that when experiments are repeated using different host or parasite genotypes under otherwise identical conditions, the underlying genetic architecture of host resistance can vary dramatically - that is, involves different QTLs and epistatic interactions. QTLs and epistatic loci vary much less when host and parasite types remain the same but experiments are repeated in different environments. This pattern of variability of the genetic architecture is predicted by strong interactions between genotypes and corroborates the prevalence of varying host-parasite combinations over varying environmental conditions. Moreover, epistasis is a major determinant of phenotypic variance for host resistance. Because epistasis seems to occur predominantly between, rather than within, chromosomes, segregation and chromosome number rather than recombination via cross-over should be the major elements affecting adaptive change in host resistance.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Genetical genomics of Populus leaf shape variation

DOE PAGES

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

2015-06-30

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

Convergence between biological, behavioural and genetic determinants of obesity.

PubMed

Ghosh, Sujoy; Bouchard, Claude

2017-12-01

Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.

Genetics of the Framingham Heart Study Population

PubMed Central

Govindaraju, Diddahally R.; Cupples, L. Adrienne; Kannel, William B.; O’Donnell, Christopher J.; Atwood, Larry D.; D’Agostino, Ralph B.; Fox, Caroline S.; Larson, Marty; Levy, Daniel; Morabito, Joanne; Vasan, Ramachandran S.; Splansky, Greta Lee; Wolf, Philip A.; Benjamin, Emelia J.

2010-01-01

This article provides an introduction to the Framingham Heart Study (FHS) and the genetic research related to cardiovascular diseases conducted in this unique population1. It briefly describes the origins of the study, the risk factors that contribute to heart disease and the approaches taken to discover the genetic basis of some of these risk factors. The genetic architecture of several biological risk factors has been explained using family studies, segregation analysis, heritability, phenotypic and genetic correlations. Many quantitative trait loci underlying cardiovascular diseases have been discovered using different molecular markers. Additionally, results from genome-wide association studies using 100,000 markers, and the prospects of using 550,000 markers for association studies are presented. Finally, the use of this unique sample in genotype and environment interaction is described. PMID:19010253

COMPARISON OF GENETIC METHODS TO OPTICAL METHODS IN THE IDENTIFICATION AND ASSESSMENT OF MOLD IN THE BUILT ENVIRONMENT -- COMPARISON OF TAQMAN AND MICROSCOPIC ANALYSIS OF CLADOSPORIUM SPORES RETRIEVED FROM ZEFON AIR-O-CELL TRACES

EPA Science Inventory

Recent advances in the sequencing of relevant water intrusion fungi by the EPA, combined with the development of probes and primers have allowed for the unequivocal quantitative and qualitative identification of fungi in selected matrices.

In this pilot study, quantitative...

Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

PubMed

Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

2011-01-01

Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

Power Analysis of Artificial Selection Experiments Using Efficient Whole Genome Simulation of Quantitative Traits

PubMed Central

Kessner, Darren; Novembre, John

2015-01-01

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates. PMID:25672748

Evidences of local adaptation in quantitative traits in Prosopis alba (Leguminosae).

PubMed

Bessega, C; Pometti, C; Ewens, M; Saidman, B O; Vilardi, J C

2015-02-01

Signals of selection on quantitative traits can be detected by the comparison between the genetic differentiation of molecular (neutral) markers and quantitative traits, by multivariate extensions of the same model and by the observation of the additive covariance among relatives. We studied, by three different tests, signals of occurrence of selection in Prosopis alba populations over 15 quantitative traits: three economically important life history traits: height, basal diameter and biomass, 11 leaf morphology traits that may be related with heat-tolerance and physiological responses and spine length that is very important from silvicultural purposes. We analyzed 172 G1-generation trees growing in a common garden belonging to 32 open pollinated families from eight sampling sites in Argentina. The multivariate phenotypes differ significantly among origins, and the highest differentiation corresponded to foliar traits. Molecular genetic markers (SSR) exhibited significant differentiation and allowed us to provide convincing evidence that natural selection is responsible for the patterns of morphological differentiation. The heterogeneous selection over phenotypic traits observed suggested different optima in each population and has important implications for gene resource management. The results suggest that the adaptive significance of traits should be considered together with population provenance in breeding program as a crucial point prior to any selecting program, especially in Prosopis where the first steps are under development.

Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii

Treesearch

Chak Han Im; Young-Hoon Park; Kenneth E. Hammel; Bokyung Park; Soon Wook Kwon; Hojin Ryu; Jae-San Ryu

2016-01-01

Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type...

Protein conformation by EPR spectroscopy using gadolinium tags clicked to genetically encoded p-azido-L-phenylalanine.

PubMed

Abdelkader, E H; Feintuch, A; Yao, X; Adams, L A; Aurelio, L; Graham, B; Goldfarb, D; Otting, G

2015-11-14

Quantitative cysteine-independent ligation of a Gd(3+) tag to genetically encoded p-azido-L-phenylalanine via Cu(I)-catalyzed click chemistry is shown to deliver an exceptionally powerful tool for Gd(3+)-Gd(3+) distance measurements by double electron-electron resonance (DEER) experiments, as the position of the Gd(3+) ion relative to the protein can be predicted with high accuracy.

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

PubMed

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic polymorphisms and their association with brain and behavioural measures in heterogeneous stock mice

PubMed Central

Janecka, Magdalena; Marzi, Sarah J.; Parsons, Michael J.; Liu, Lin; Paya-Cano, Jose L.; Smith, Rebecca G.; Fernandes, Cathy; Schalkwyk, Leonard C.

2017-01-01

Although the search for quantitative trait loci for behaviour remains a considerable challenge, the complicated genetic architecture of quantitative traits is beginning to be understood. The current project utilised heterogeneous stock (HS) male mice (n = 580) to investigate the genetic basis for brain weights, activity, anxiety and cognitive phenotypes. We identified 126 single nucleotide polymorphisms (SNPs) in genes involved in regulation of neurotransmitter systems, nerve growth/death and gene expression, and subsequently investigated their associations with changes in behaviour and/or brain weights in our sample. We found significant associations between four SNP-phenotype pairs, after controlling for multiple testing. Specificity protein 2 (Sp2, rs3708840), tryptophan hydroxylase 1 (Tph1, rs262731280) and serotonin receptor 3A (Htr3a, rs50670893) were associated with activity/anxiety behaviours, and microtubule-associated protein 2 (Map2, rs13475902) was associated with cognitive performance. All these genes except for Tph1 were expressed in the brain above the array median, and remained significantly associated with relevant behaviours after controlling for the family structure. Additionally, we found evidence for a correlation between Htr3a expression and activity. We discuss our findings in the light of the advantages and limitations of currently available mouse genetic tools, suggesting further directions for association studies in rodents. PMID:28145470

The genetic architecture of reproductive isolation in Louisiana irises: pollination syndromes and pollinator preferences.

PubMed

Martin, Noland H; Sapir, Yuval; Arnold, Michael L

2008-04-01

In animal-pollinated plants, pollinator preferences for divergent floral forms can lead to partial reproductive isolation. We describe regions of plant genomes that affect pollinator preferences for two species of Louisiana Irises, Iris brevicaulis and Iris fulva, and their artificial hybrids. Iris brevicaulis and I. fulva possess bee and bird-pollination syndromes, respectively. Hummingbirds preferred I. fulva and under-visited both I. brevicaulis and backcrosses toward this species. Lepidopterans preferred I. fulva and backcrosses toward I. fulva, but also under-visited I. brevicaulis and I. brevicaulis backcrosses. Bumblebees preferred I. brevicaulis and F1 hybrids and rarely visited I. fulva. Although all three pollen vectors preferred one or the other species, these preferences did not prevent visitation to other hybrid/parental classes. Quantitative trait locus (QTL) mapping, in reciprocal BC1 mapping populations, defined the genetic architecture of loci that affected pollinator behavior. We detected six and nine QTLs that affected pollinator visitation rates in the BCIb and BCIf mapping populations, respectively, with as many as three QTLs detected for each trait. Overall, this study reflects the possible role of quantitative genetic factors in determining (1) reproductive isolation, (2) the pattern of pollinator-mediated genetic exchange, and thus (3) hybrid zone evolution.

Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

PubMed Central

Grattapaglia, D.; Bertolucci, FLG.; Penchel, R.; Sederoff, R. R.

1996-01-01

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding. PMID:8913761

Mapping Quantitative Field Resistance Against Apple Scab in a 'Fiesta' x 'Discovery' Progeny.

PubMed

Liebhard, R; Koller, B; Patocchi, A; Kellerhals, M; Pfammatter, W; Jermini, M; Gessler, C

2003-04-01

ABSTRACT Breeding of resistant apple cultivars (Malus x domestica) as a disease management strategy relies on the knowledge and understanding of the underlying genetics. The availability of molecular markers and genetic linkage maps enables the detection and the analysis of major resistance genes as well as of quantitative trait loci (QTL) contributing to the resistance of a genotype. Such a genetic linkage map was constructed, based on a segregating population of the cross between apple cvs. Fiesta (syn. Red Pippin) and Discovery. The progeny was observed for 3 years at three different sites in Switzerland and field resistance against apple scab (Venturia inaequalis) was assessed. Only a weak correlation was detected between leaf scab and fruit scab. A QTL analysis was performed, based on the genetic linkage map consisting of 804 molecular markers and covering all 17 chromosomes of apple. With the maximum likelihood-based interval mapping method, eight genomic regions were identified, six conferring resistance against leaf scab and two conferring fruit scab resistance. Although cv. Discovery showed a much stronger resistance against scab in the field, most QTL identified were attributed to the more susceptible parent 'Fiesta'. This indicated a high degree of homozygosity at the scab resistance loci in 'Discovery', preventing their detection in the progeny due to the lack of segregation.

Qualitative and Quantitative Pedigree Analysis: Graph Theory, Computer Software, and Case Studies.

ERIC Educational Resources Information Center

Jungck, John R.; Soderberg, Patti

1995-01-01

Presents a series of elementary mathematical tools for re-representing pedigrees, pedigree generators, pedigree-driven database management systems, and case studies for exploring genetic relationships. (MKR)

Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

PubMed

Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid.

PubMed

Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Park, Sunghoon; Shin, Min-Ki; Moon, Gui Im; Hong, Jin-Hwan; Kim, Hae-Yeong

2015-06-01

With the increasing number of genetically modified (GM) events, unauthorized GMO releases into the food market have increased dramatically, and many countries have developed detection tools for them. This study described the qualitative and quantitative detection methods of unauthorized the GM wheat MON71800 with a reference plasmid (pGEM-M71800). The wheat acetyl-CoA carboxylase (acc) gene was used as the endogenous gene. The plasmid pGEM-M71800, which contains both the acc gene and the event-specific target MON71800, was constructed as a positive control for the qualitative and quantitative analyses. The limit of detection in the qualitative PCR assay was approximately 10 copies. In the quantitative PCR assay, the standard deviation and relative standard deviation repeatability values ranged from 0.06 to 0.25 and from 0.23% to 1.12%, respectively. This study supplies a powerful and very simple but accurate detection strategy for unauthorized GM wheat MON71800 that utilizes a single calibrator plasmid. Copyright © 2014 Elsevier Ltd. All rights reserved.

Simulation of the M13 life cycle I: Assembly of a genetically-structured deterministic chemical kinetic simulation.

PubMed

Smeal, Steven W; Schmitt, Margaret A; Pereira, Ronnie Rodrigues; Prasad, Ashok; Fisk, John D

2017-01-01

To expand the quantitative, systems level understanding and foster the expansion of the biotechnological applications of the filamentous bacteriophage M13, we have unified the accumulated quantitative information on M13 biology into a genetically-structured, experimentally-based computational simulation of the entire phage life cycle. The deterministic chemical kinetic simulation explicitly includes the molecular details of DNA replication, mRNA transcription, protein translation and particle assembly, as well as the competing protein-protein and protein-nucleic acid interactions that control the timing and extent of phage production. The simulation reproduces the holistic behavior of M13, closely matching experimentally reported values of the intracellular levels of phage species and the timing of events in the M13 life cycle. The computational model provides a quantitative description of phage biology, highlights gaps in the present understanding of M13, and offers a framework for exploring alternative mechanisms of regulation in the context of the complete M13 life cycle. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI.

PubMed

Adler, Sophie; Lorio, Sara; Jacques, Thomas S; Benova, Barbora; Gunny, Roxana; Cross, J Helen; Baldeweg, Torsten; Carmichael, David W

2017-01-01

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual.

Collaborative ring trial of the papaya endogenous reference gene and its polymerase chain reaction assays for genetically modified organism analysis.

PubMed

Wei, Jiaojun; Li, Feiwu; Guo, Jinchao; Li, Xiang; Xu, Junfeng; Wu, Gang; Zhang, Dabing; Yang, Litao

2013-11-27

The papaya (Carica papaya L.) Chymopapain (CHY) gene has been reported as a suitable endogenous reference gene for genetically modified (GM) papaya detection in previous studies. Herein, we further validated the use of the CHY gene and its qualitative and quantitative polymerase chain reaction (PCR) assays through an interlaboratory collaborative ring trial. A total of 12 laboratories working on detection of genetically modified organisms participated in the ring trial and returned test results. Statistical analysis of the returned results confirmed the species specificity, low heterogeneity, and single-copy number of the CHY gene among different papaya varieties. The limit of detection of the CHY qualitative PCR assay was 0.1%, while the limit of quantification of the quantitative PCR assay was ∼25 copies of haploid papaya genome with acceptable PCR efficiency and linearity. The differences between the tested and true values of papaya content in 10 blind samples ranged from 0.84 to 6.58%. These results indicated that the CHY gene was suitable as an endogenous reference gene for the identification and quantification of GM papaya.

A linkage and family-based association analysis of a potential neurocognitive endophenotype of bipolar disorder.

PubMed

Savitz, Jonathan; van der Merwe, Lize; Solms, Mark; Ramesar, Rajkumar

2007-01-01

The identification of the genetic variants underpinning bipolar disorder (BPD) has been impeded by a complex pattern of inheritance characterized by genetic and phenotypic heterogeneity, genetic epistasis, and gene-environment interactions. In this paper two strategies were used to ameliorate these confounding factors. A unique South African sample including 190 individuals of the relatively, reproductively isolated Afrikaner population was assessed with a battery of neuropsychological tests in an attempt to identify a BPD-associated quantitative trait or endophenotype. BPD individuals performed significantly worse than their unaffected relatives on visual and verbal memory tasks, a finding congruent with the literature. Afocused linkage and family-based association study was carried out using this memory-related endophenotype. In the largest 77-strong Afrikaner pedigree significant evidence for linkage was detected on chromosome 22q11, a region previously implicated in BPD. The quantitative transmission disequilibrium tests-based association analysis suggested that functional variants of the DRD4 and MAO-A genes modulate memory-related cognition. We speculate that polymorphisms at these loci may predispose to a subtype of BPD characterized by memory-related deficits.

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.

Quantitative genome re-sequencing defines multiple mutations conferring chloroquine resistance in rodent malaria

PubMed Central

2012-01-01

Background Drug resistance in the malaria parasite Plasmodium falciparum severely compromises the treatment and control of malaria. A knowledge of the critical mutations conferring resistance to particular drugs is important in understanding modes of drug action and mechanisms of resistances. They are required to design better therapies and limit drug resistance. A mutation in the gene (pfcrt) encoding a membrane transporter has been identified as a principal determinant of chloroquine resistance in P. falciparum, but we lack a full account of higher level chloroquine resistance. Furthermore, the determinants of resistance in the other major human malaria parasite, P. vivax, are not known. To address these questions, we investigated the genetic basis of chloroquine resistance in an isogenic lineage of rodent malaria parasite P. chabaudi in which high level resistance to chloroquine has been progressively selected under laboratory conditions. Results Loci containing the critical genes were mapped by Linkage Group Selection, using a genetic cross between the high-level chloroquine-resistant mutant and a genetically distinct sensitive strain. A novel high-resolution quantitative whole-genome re-sequencing approach was used to reveal three regions of selection on chr11, chr03 and chr02 that appear progressively at increasing drug doses on three chromosomes. Whole-genome sequencing of the chloroquine-resistant parent identified just four point mutations in different genes on these chromosomes. Three mutations are located at the foci of the selection valleys and are therefore predicted to confer different levels of chloroquine resistance. The critical mutation conferring the first level of chloroquine resistance is found in aat1, a putative aminoacid transporter. Conclusions Quantitative trait loci conferring selectable phenotypes, such as drug resistance, can be mapped directly using progressive genome-wide linkage group selection. Quantitative genome-wide short-read genome resequencing can be used to reveal these signatures of drug selection at high resolution. The identities of three genes (and mutations within them) conferring different levels of chloroquine resistance generate insights regarding the genetic architecture and mechanisms of resistance to chloroquine and other drugs. Importantly, their orthologues may now be evaluated for critical or accessory roles in chloroquine resistance in human malarias P. vivax and P. falciparum. PMID:22435897

Humanity in a Dish: Population Genetics with iPSCs.

PubMed

Warren, Curtis R; Cowan, Chad A

2018-01-01

Induced pluripotent stem cells (iPSCs) are powerful tools for investigating the relationship between genotype and phenotype. Recent publications have described iPSC cohort studies of common genetic variants and their effects on gene expression and cellular phenotypes. These in vitro quantitative trait locus (QTL) studies are the first experiments in a new paradigm with great potential: iPSC-based functional population genetic studies. iPSC collections from large cohorts are currently under development to facilitate the next wave of these studies, which have the potential to discover the effects of common genetic variants on cellular phenotypes and to uncover the molecular basis of common genetic diseases. Here, we describe the recent advances in this developing field, and provide a road map for future in vitro functional population genetic studies and trial-in-a-dish experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.

The genetic landscape of a physical interaction

PubMed Central

Diss, Guillaume

2018-01-01

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions. PMID:29638215

Genomic Characterization of the Evolutionary Potential of the Sea Urchin Strongylocentrotus droebachiensis Facing Ocean Acidification.

PubMed

Runcie, Daniel E; Dorey, Narimane; Garfield, David A; Stumpp, Meike; Dupont, Sam; Wray, Gregory A

2016-12-01

Ocean acidification (OA) is increasing due to anthropogenic CO2 emissions and poses a threat to marine species and communities worldwide. To better project the effects of acidification on organisms' health and persistence, an understanding is needed of the 1) mechanisms underlying developmental and physiological tolerance and 2) potential populations have for rapid evolutionary adaptation. This is especially challenging in nonmodel species where targeted assays of metabolism and stress physiology may not be available or economical for large-scale assessments of genetic constraints. We used mRNA sequencing and a quantitative genetics breeding design to study mechanisms underlying genetic variability and tolerance to decreased seawater pH (-0.4 pH units) in larvae of the sea urchin Strongylocentrotus droebachiensis. We used a gene ontology-based approach to integrate expression profiles into indirect measures of cellular and biochemical traits underlying variation in larval performance (i.e., growth rates). Molecular responses to OA were complex, involving changes to several functions such as growth rates, cell division, metabolism, and immune activities. Surprisingly, the magnitude of pH effects on molecular traits tended to be small relative to variation attributable to segregating functional genetic variation in this species. We discuss how the application of transcriptomics and quantitative genetics approaches across diverse species can enrich our understanding of the biological impacts of climate change. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

PubMed

Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-02-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

PubMed Central

Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-01-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites.

PubMed

Routtu, J; Ebert, D

2015-02-01

Understanding the genetic architecture of host resistance is key for understanding the evolution of host-parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host-parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host-parasite systems. Only the Pasteuria-Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium-Daphnia system remains unclear.

Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites

PubMed Central

Routtu, J; Ebert, D

2015-01-01

Understanding the genetic architecture of host resistance is key for understanding the evolution of host–parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host–parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host–parasite systems. Only the Pasteuria–Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium–Daphnia system remains unclear. PMID:25335558

Genome-wide analysis of ivermectin response by Onchocerca volvulus reveals that genetic drift and soft selective sweeps contribute to loss of drug sensitivity

PubMed Central

Nana-Djeunga, Hugues C.; Kengne-Ouafo, Jonas A.; Pion, Sébastien D. S.; Bopda, Jean; Kamgno, Joseph; Wanji, Samuel; Che, Hua; Kuesel, Annette C.; Walker, Martin; Basáñez, Maria-Gloria; Boakye, Daniel A.; Osei-Atweneboana, Mike Y.; Boussinesq, Michel; Prichard, Roger K.; Grant, Warwick N.

2017-01-01

Background Treatment of onchocerciasis using mass ivermectin administration has reduced morbidity and transmission throughout Africa and Central/South America. Mass drug administration is likely to exert selection pressure on parasites, and phenotypic and genetic changes in several Onchocerca volvulus populations from Cameroon and Ghana—exposed to more than a decade of regular ivermectin treatment—have raised concern that sub-optimal responses to ivermectin's anti-fecundity effect are becoming more frequent and may spread. Methodology/Principal findings Pooled next generation sequencing (Pool-seq) was used to characterise genetic diversity within and between 108 adult female worms differing in ivermectin treatment history and response. Genome-wide analyses revealed genetic variation that significantly differentiated good responder (GR) and sub-optimal responder (SOR) parasites. These variants were not randomly distributed but clustered in ~31 quantitative trait loci (QTLs), with little overlap in putative QTL position and gene content between the two countries. Published candidate ivermectin SOR genes were largely absent in these regions; QTLs differentiating GR and SOR worms were enriched for genes in molecular pathways associated with neurotransmission, development, and stress responses. Finally, single worm genotyping demonstrated that geographic isolation and genetic change over time (in the presence of drug exposure) had a significantly greater role in shaping genetic diversity than the evolution of SOR. Conclusions/Significance This study is one of the first genome-wide association analyses in a parasitic nematode, and provides insight into the genomics of ivermectin response and population structure of O. volvulus. We argue that ivermectin response is a polygenically-determined quantitative trait (QT) whereby identical or related molecular pathways but not necessarily individual genes are likely to determine the extent of ivermectin response in different parasite populations. Furthermore, we propose that genetic drift rather than genetic selection of SOR is the underlying driver of population differentiation, which has significant implications for the emergence and potential spread of SOR within and between these parasite populations. PMID:28746337

Developmental changes in genetic and environmental influences on rule-breaking and aggression: age and pubertal development.

PubMed

Harden, K Paige; Patterson, Megan W; Briley, Daniel A; Engelhardt, Laura E; Kretsch, Natalie; Mann, Frank D; Tackett, Jennifer L; Tucker-Drob, Elliot M

2015-12-01

Antisocial behavior (ASB) can be meaningfully divided into nonaggressive rule-breaking versus aggressive dimensions, which differ in developmental course and etiology. Previous research has found that genetic influences on rule-breaking, but not aggression, increase from late childhood to mid-adolescence. This study tested the extent to which the developmental increase in genetic influence on rule-breaking was associated with pubertal development compared to chronological age. Child and adolescent twins (n = 1,031), ranging in age from 8 to 20 years (M age = 13.5 years), were recruited from public schools as part of the Texas Twin Project. Participants reported on their pubertal development using the Pubertal Development Scale and on their involvement in ASB on items from the Child Behavior Checklist. Measurement invariance of ASB subtypes across age groups (≤12 years vs. >12 years old) was tested using confirmatory factor analyses. Quantitative genetic modeling was used to test whether the genetic and environmental influences on aggression and rule-breaking were moderated by age, pubertal status, or both. Quantitative genetic modeling indicated that genetic influences specific to rule-breaking increased as a function of pubertal development controlling for age (a gene × puberty interaction), but did not vary as a function of age controlling for pubertal status. There were no developmental differences in the genetic etiology of aggression. Family-level environmental influences common to aggression and rule-breaking decreased with age, further contributing to the differentiation between these subtypes of ASB from childhood to adolescence. Future research should discriminate between alternative possible mechanisms underlying gene × puberty interactions on rule-breaking forms of antisocial behavior, including possible effects of pubertal hormones on gene expression. © 2015 Association for Child and Adolescent Mental Health.

Association between dietary fat intake and insulin resistance in Chinese child twins.

PubMed

Huang, Tao; Beaty, Terri; Li, Ji; Liu, Huijuan; Zhao, Wei; Wang, Youfa

2017-01-01

Dietary fat intake is correlated with increased insulin resistance (IR). However, it is unknown whether gene-diet interaction modulates the association. This study estimated heritability of IR measures and the related genetic correlations with fat intake, and tested whether dietary fat intake modifies the genetic influence on type 2 diabetes (T2D)-related traits in Chinese child twins. We included 622 twins aged 7-15 years (n 311 pairs, 162 monozygotic (MZ), 149 dizygotic (DZ)) from south-eastern China. Dietary factors were measured using FFQ. Structural equation models were fit using Mx statistical package. The intra-class correlation coefficients for all traits related to T2D were higher for MZ twins than for DZ twins. Dietary fat and fasting serum insulin (additive genetic correlation (r A) 0·20; 95 % CI 0·08, 0·43), glucose (r A 0·12; 95 % CI 0·01, 0·40), homoeostasis model of assessment-insulin resistance (Homa-IR) (r A 0·22; 95 % CI 0·10, 0·50) and the quantitative insulin sensitivity check index (Quicki) (r A -0·22; 95 % CI -0·40, 0·04) showed strong genetic correlations. Heritabilities of dietary fat intake, fasting glucose and insulin were estimated to be 52, 70 and 70 %, respectively. More than 70 % of the phenotypic correlations between dietary fat and insulin, glucose, Homa-IR and the Quicki index appeared to be mediated by shared genetic influence. Dietary fat significantly modified additive genetic effects on these quantitative traits associated with T2D. Analysis of Chinese twins yielded high estimates of heritability of dietary fat intake and IR. Genetic factors appear to contribute to a high proportion of the variance for both insulin sensitivity and IR. Dietary fat intake modifies the genetic influence on blood levels of insulin and glucose, Homa-IR and the Quicki index.

APOE Genotyping, Cardiovascular Disease

MedlinePlus

... Time and International Normalized Ratio (PT/INR) PSEN1 Quantitative Immunoglobulins Red Blood Cell (RBC) Antibody Identification Red ... tests are most often done as part of research protocols to help understand the role of genetic ...

Good genes, genetic compatibility and the evolution of polyandry: use of the diallel cross to address competing hypotheses.

PubMed

Ivy, T M

2007-03-01

Genetic benefits can enhance the fitness of polyandrous females through the high intrinsic genetic quality of females' mates or through the interaction between female and male genes. I used a full diallel cross, a quantitative genetics design that involves all possible crosses among a set of genetically homogeneous lines, to determine the mechanism through which polyandrous female decorated crickets (Gryllodes sigillatus) obtain genetic benefits. I measured several traits related to fitness and partitioned the phenotypic variance into components representing the contribution of additive genetic variance ('good genes'), nonadditive genetic variance (genetic compatibility), as well as maternal and paternal effects. The results reveal a significant variance attributable to both nonadditive and additive sources in the measured traits, and their influence depended on which trait was considered. The lack of congruence in sources of phenotypic variance among these fitness-related traits suggests that the evolution and maintenance of polyandry are unlikely to have resulted from one selective influence, but rather are the result of the collective effects of a number of factors.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

PubMed

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

[Induced autotetraploid grape mutants].

PubMed

Kuliev, V M

2011-01-01

The methods of experimental mitotic and meiotic polyploidy in grapes are represented in the article. Results of cytological, histo-anatomical, biomorphological researches of induced autotetraploids are shown. Genetic characteristics, parameters of generative organs, quantitative and structural genome changes were studied. Comparative quantitative changes in the content of chloroplast and mitochondrion DNAs and RNAs in diploids and autotetraploids were defined. Also are shown. The biology-economic evaluation of autotetraploids on comparison with the initial grape variety is represented.

Where Lab Tests Are Performed

MedlinePlus

... Time and International Normalized Ratio (PT/INR) PSEN1 Quantitative Immunoglobulins Red Blood Cell (RBC) Antibody Identification Red ... Accessed June 2011. Genetics and Public Policy Center. Survey of Direct-to-Consumer Testing Statutes and Regulations. ...

Mimicry on the QT(L): genetics of speciation in Mimulus.

PubMed

Bleiweiss, R

2001-08-01

Ecological studies suggest that hummingbird-pollinated plants in North America mimic each other to increase visitation by birds. Published quantitative trait locus (QTL) data for two Mimulus species indicate that floral traits associated with hummingbird versus bee pollination results from a few loci with major effects on morphology, as predicted by classical models for the evolution of mimicry. Thus, the architecture of genetic divergence associated with speciation may depend on the ecological context.

Real-Time PCR-Based Quantitation Method for the Genetically Modified Soybean Line GTS 40-3-2.

PubMed

Kitta, Kazumi; Takabatake, Reona; Mano, Junichi

2016-01-01

This chapter describes a real-time PCR-based method for quantitation of the relative amount of genetically modified (GM) soybean line GTS 40-3-2 [Roundup Ready(®) soybean (RRS)] contained in a batch. The method targets a taxon-specific soybean gene (lectin gene, Le1) and the specific DNA construct junction region between the Petunia hybrida chloroplast transit peptide sequence and the Agrobacterium 5-enolpyruvylshikimate-3-phosphate synthase gene (epsps) sequence present in GTS 40-3-2. The method employs plasmid pMulSL2 as a reference material in order to quantify the relative amount of GTS 40-3-2 in soybean samples using a conversion factor (Cf) equal to the ratio of the RRS-specific DNA to the taxon-specific DNA in representative genuine GTS 40-3-2 seeds.

Validation and application of quantitative PCR assays using host-specific Bacteroidales genetic markers for swine fecal pollution tracking.

PubMed

Fan, Lihua; Shuai, Jiangbing; Zeng, Ruoxue; Mo, Hongfei; Wang, Suhua; Zhang, Xiaofeng; He, Yongqiang

2017-12-01

Genome fragment enrichment (GFE) method was applied to identify host-specific bacterial genetic markers that differ among different fecal metagenomes. To enrich for swine-specific DNA fragments, swine fecal DNA composite (n = 34) was challenged against a DNA composite consisting of cow, human, goat, sheep, chicken, duck and goose fecal DNA extracts (n = 83). Bioinformatic analyses of 384 non-redundant swine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode metabolism-associated, cellular processes and information storage and processing. After challenged against fecal DNA extracted from different animal sources, four sequences from the clone libraries targeting two Bacteroidales- (genes 1-38 and 3-53), a Clostridia- (gene 2-109) as well as a Bacilli-like sequence (gene 2-95), respectively, showed high specificity to swine feces based on PCR analysis. Host-specificity and host-sensitivity analysis confirmed that oligonucleotide primers and probes capable of annealing to select Bacteroidales-like sequences (1-38 and 3-53) exhibited high specificity (>90%) in quantitative PCR assays with 71 fecal DNAs from non-target animal sources. The two assays also demonstrated broad distributions of corresponding genetic markers (>94% positive) among 72 swine feces. After evaluation with environmental water samples from different areas, swine-targeted assays based on two Bacteroidales-like GFE sequences appear to be suitable quantitative tracing tools for swine fecal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Publication Trends Over 55 Years of Behavioral Genetic Research.

PubMed

Ayorech, Ziada; Selzam, Saskia; Smith-Woolley, Emily; Knopik, Valerie S; Neiderhiser, Jenae M; DeFries, John C; Plomin, Robert

2016-09-01

We document the growth in published papers on behavioral genetics for 5-year intervals from 1960 through 2014. We used 1861 papers published in Behavior Genetics to train our search strategy which, when applied to Ovid PsychINFO, selected more than 45,000 publications. Five trends stand out: (1) the number of behavioral genetic publications has grown enormously; nearly 20,000 papers were published in 2010-2014. (2) The number of human quantitative genetic (QG) publications (e.g., twin and adoption studies) has steadily increased with more than 3000 papers published in 2010-2014. (3) The number of human molecular genetic (MG) publications increased substantially from about 2000 in 2000-2004 to 5000 in 2005-2009 to 9000 in 2010-2014. (4) Nonhuman publications yielded similar trends. (5) Although there has been exponential growth in MG publications, both human and nonhuman QG publications continue to grow. A searchable resource of this corpus of behavioral genetic papers is freely available online at http://www.teds.ac.uk/public_datasets.html and will be updated annually.

Genetic background effects in quantitative genetics: gene-by-system interactions.

PubMed

Sardi, Maria; Gasch, Audrey P

2018-04-11

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

[The genetic control of mouse coat color and its applications in genetics teaching].

PubMed

Xing, Wanjin; Morigen, Morigen

2014-10-01

Mice are the most commonly used mammalian model. The coat colors of mice are typical Mendelian traits, which have various colors such as white, black, yellow and agouti. The inheritance of mouse coat color is usually stated as an example only in teaching the knowledge of recessive lethal alleles. After searched the related literatures and summarized the molecular mechanisms of mouse coat color inheritance, we further expanded the application of this example into the introduction of the basic concepts of alleles and Mendelian laws, demonstration of the gene structure and function, regulation of gene expression, gene interaction, epigenetic modification, quantitative genetics, as well as evolutionary genetics. By running this example through the whole genetics-teaching lectures, we help the student to form a systemic and developmental view of genetic analysis. At the same time, this teaching approach not only highlights the advancement and integrity of genetics, but also results in a good teaching effect on inspiring the students' interest and attracting students' attention.

Real-time quantitative PCR detection of genetically modified Maximizer maize and Roundup Ready soybean in some representative foods.

PubMed

Vaïtilingom, M; Pijnenburg, H; Gendre, F; Brignon, P

1999-12-01

A fast and quantitative method was developed to detect transgenic "Maximizer" maize "event 176" (Novartis) and "Roundup Ready" soybean (Monsanto) in food by real-time quantitative PCR. The use of the ABI Prism 7700 sequence detection system allowed the determination of the amplified product accumulation through a fluorogenic probe (TaqMan). Fluorescent dyes were chosen in such a way as to coamplify total and transgenic DNA in the same tube. Using real-time quantitative PCR, 2 pg of transgenic or total DNA per gram of starting sample was detected in 3 h after DNA extraction and the relative amounts of "Maximizer" maize and "Roundup Ready" soybean in some representative food products were quantified.

The molecular genetics of von Willebrand disease.

PubMed

Berber, Ergül

2012-12-01

Quantitative and/or qualitative deficiency of von Willebrand factor (vWF) is associated with the most common inherited bleeding disease von Willebrand disease (vWD). vWD is a complex disease with clinical and genetic heterogeneity. Incomplete penetrance and variable expression due to genetic and environmental factors contribute to its complexity. vWD also has a complex molecular pathogenesis. Some vWF gene mutations are associated with the affected vWF biosynthesis and multimerization, whereas others are associated with increased clearance and functional impairment. Moreover, in addition to a particular mutation, type O blood may result in the more severe phenotype. The present review aimed to provide a summary of the current literature on the molecular genetics of vWD. None declared.

Quantitative assessment of skin, hair, and iris variation in a diverse sample of individuals and associated genetic variation.

PubMed

Norton, Heather L; Edwards, Melissa; Krithika, S; Johnson, Monique; Werren, Elizabeth A; Parra, Esteban J

2016-08-01

The main goals of this study are to 1) quantitatively measure skin, hair, and iris pigmentation in a diverse sample of individuals, 2) describe variation within and between these samples, and 3) demonstrate how quantitative measures can facilitate genotype-phenotype association tests. We quantitatively characterize skin, hair, and iris pigmentation using the Melanin (M) Index (skin) and CIELab values (hair) in 1,450 individuals who self-identify as African American, East Asian, European, Hispanic, or South Asian. We also quantify iris pigmentation in a subset of these individuals using CIELab values from high-resolution iris photographs. We compare mean skin M index and hair and iris CIELab values among populations using ANOVA and MANOVA respectively and test for genotype-phenotype associations in the European sample. All five populations are significantly different for skin (P <2 × 10(-16) ) and hair color (P <2 × 10(-16) ). Our quantitative analysis of iris and hair pigmentation reinforces the continuous, rather than discrete, nature of these traits. We confirm the association of three loci (rs16891982, rs12203592, and rs12913832) with skin pigmentation and four loci (rs12913832, rs12203592, rs12896399, and rs16891982) with hair pigmentation. Interestingly, the derived rs12203592 T allele located within the IRF4 gene is associated with lighter skin but darker hair color. The quantitative methods used here provide a fine-scale assessment of pigmentation phenotype and facilitate genotype-phenotype associations, even with relatively small sample sizes. This represents an important expansion of current investigations into pigmentation phenotype and associated genetic variation by including non-European and admixed populations. Am J Phys Anthropol 160:570-581, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Rapid genotyping by low-coverage resequencing to construct genetic linkage maps of fungi: a case study in Lentinula edodes

PubMed Central

2013-01-01

Background Genetic linkage maps are important tools in breeding programmes and quantitative trait analyses. Traditional molecular markers used for genotyping are limited in throughput and efficiency. The advent of next-generation sequencing technologies has facilitated progeny genotyping and genetic linkage map construction in the major grains. However, the applicability of the approach remains untested in the fungal system. Findings Shiitake mushroom, Lentinula edodes, is a basidiomycetous fungus that represents one of the most popular cultivated edible mushrooms. Here, we developed a rapid genotyping method based on low-coverage (~0.5 to 1.5-fold) whole-genome resequencing. We used the approach to genotype 20 single-spore isolates derived from L. edodes strain L54 and constructed the first high-density sequence-based genetic linkage map of L. edodes. The accuracy of the proposed genotyping method was verified experimentally with results from mating compatibility tests and PCR-single-strand conformation polymorphism on a few known genes. The linkage map spanned a total genetic distance of 637.1 cM and contained 13 linkage groups. Two hundred sequence-based markers were placed on the map, with an average marker spacing of 3.4 cM. The accuracy of the map was confirmed by comparing with previous maps the locations of known genes such as matA and matB. Conclusions We used the shiitake mushroom as an example to provide a proof-of-principle that low-coverage resequencing could allow rapid genotyping of basidiospore-derived progenies, which could in turn facilitate the construction of high-density genetic linkage maps of basidiomycetous fungi for quantitative trait analyses and improvement of genome assembly. PMID:23915543

Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

PubMed

Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

2018-05-15

A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

Natural Genetic Variation and Candidate Genes for Morphological Traits in Drosophila melanogaster

PubMed Central

Carreira, Valeria Paula; Mensch, Julián; Hasson, Esteban; Fanara, Juan José

2016-01-01

Body size is a complex character associated to several fitness related traits that vary within and between species as a consequence of environmental and genetic factors. Latitudinal and altitudinal clines for different morphological traits have been described in several species of Drosophila and previous work identified genomic regions associated with such variation in D. melanogaster. However, the genetic factors that orchestrate morphological variation have been barely studied. Here, our main objective was to investigate genetic variation for different morphological traits associated to the second chromosome in natural populations of D. melanogaster along latitudinal and altitudinal gradients in Argentina. Our results revealed weak clinal signals and a strong population effect on morphological variation. Moreover, most pairwise comparisons between populations were significant. Our study also showed important within-population genetic variation, which must be associated to the second chromosome, as the lines are otherwise genetically identical. Next, we examined the contribution of different candidate genes to natural variation for these traits. We performed quantitative complementation tests using a battery of lines bearing mutated alleles at candidate genes located in the second chromosome and six second chromosome substitution lines derived from natural populations which exhibited divergent phenotypes. Results of complementation tests revealed that natural variation at all candidate genes studied, invected, Fasciclin 3, toucan, Reticulon-like1, jing and CG14478, affects the studied characters, suggesting that they are Quantitative Trait Genes for morphological traits. Finally, the phenotypic patterns observed suggest that different alleles of each gene might contribute to natural variation for morphological traits. However, non-additive effects cannot be ruled out, as wild-derived strains differ at myriads of second chromosome loci that may interact epistatically with mutant alleles. PMID:27459710

Evolutionary speed of species invasions.

PubMed

García-Ramos, Gisela; Rodríguez, Diego

2002-04-01

Successful invasion may depend of the capacity of a species to adjust genetically to a spatially varying environment. This research modeled a species invasion by examining the interaction between a quantitative genetic trait and population density. It assumed: (I) a quantitative genetic trait describes the adaptation of an individual to its local ecological conditions; (2) populations far from the local optimum grow more slowly than those near the optimum; and (3) the evolution of a trait depends on local population density, because differences in local population densities cause asymmetrical gene flow. This genetics-density interaction determined the propagation speed of populations. Numerical simulations showed that populations spread by advancing as two synchronic traveling waves, one for population density and one for trait adaptation. The form of the density wave was a step front that advances homogenizing populations at their carrying capacity; the adaptation wave was a curve with finite slope that homogenizes populations at full adaptation. The largest speed of population expansion, for a dimensionless analysis, corresponded to an almost homogeneous spatial environment when this model approached an ecological description such as the Fisher-Skellam's model. A large genetic response also favored faster speeds. Evolutionary speeds, in a natural scale, showed a wide range of rates that were also slower compared to models that only consider demographics. This evolutionary speed increased with high heritability, strong stabilizing selection, and high intrinsic growth rate. It decreased for steeper environmental gradients. Also indicated was an optimal dispersal rate over which evolutionary speed declined. This is expected because dispersal moves individuals further, but homogenizes populations genetically, making them maladapted. The evolutionary speed was compared to observed data. Furthermore, a moderate increase in the speed of expansion was predicted for ecological changes related to global warming.

Simplification of genotyping techniques of the ABO blood type experiment and exploration of population genetics.

PubMed

Hu, Jian; Zhou, Yi-ren; Ding, Jia-lin; Wang, Zhi-yuan; Liu, Ling; Wang, Ye-kai; Lou, Hui-ling; Qiao, Shou-yi; Wu, Yan-hua

2017-05-20

The ABO blood type is one of the most common and widely used genetic traits in humans. Three glycosyltransferase-encoding gene alleles, I A , I B and i, produce three red blood cell surface antigens, by which the ABO blood type is classified. By using the ABO blood type experiment as an ideal case for genetics teaching, we can easily introduce to the students several genetic concepts, including multiple alleles, gene interaction, single nucleotide polymorphism (SNP) and gene evolution. Herein we have innovated and integrated our ABO blood type genetics experiments. First, in the section of Molecular Genetics, a new method of ABO blood genotyping was established: specific primers based on SNP sites were designed to distinguish three alleles through quantitative real-time PCR. Next, the experimental teaching method of Gene Evolution was innovated in the Population Genetics section: a gene-evolution software was developed to simulate the evolutionary tendency of the ABO genotype encoding alleles under diverse conditions. Our reform aims to extend the contents of genetics experiments, to provide additional teaching approaches, and to improve the learning efficiency of our students eventually.

Association Mapping of the High-Grade Myopia MYP3 Locus Reveals Novel Candidates UHRF1BP1L, PTPRR, and PPFIA2

PubMed Central

Hawthorne, Felicia; Feng, Sheng; Metlapally, Ravikanth; Li, Yi-Ju; Tran-Viet, Khanh-Nhat; Guggenheim, Jeremy A.; Malecaze, Francois; Calvas, Patrick; Rosenberg, Thomas; Mackey, David A.; Venturini, Cristina; Hysi, Pirro G.; Hammond, Christopher J.; Young, Terri L.

2013-01-01

Purpose. Myopia, or nearsightedness, is a common ocular genetic disease for which over 20 candidate genomic loci have been identified. The high-grade myopia locus, MYP3, has been reported on chromosome 12q21–23 by four independent linkage studies. Methods. We performed a genetic association study of the MYP3 locus in a family-based high-grade myopia cohort (n = 82) by genotyping 768 single-nucleotide polymorphisms (SNPs) within the linkage region. Qualitative testing for high-grade myopia (sphere ≤ −5 D affected, > −0.5 D unaffected) and quantitative testing on the average dioptric sphere were performed. Results. Several genetic markers were nominally significantly associated with high-grade myopia in qualitative testing, including rs3803036, a missense mutation in PTPRR (P = 9.1 × 10−4) and rs4764971, an intronic SNP in UHRF1BP1L (P = 6.1 × 10−4). Quantitative testing determined statistically significant SNPs rs4764971, also found by qualitative testing (P = 3.1 × 10−6); rs7134216, in the 3′ untranslated region (UTR) of DEPDC4 (P = 5.4 × 10−7); and rs17306116, an intronic SNP within PPFIA2 (P < 9 × 10−4). Independently conducted whole genome expression array analyses identified protein tyrosine phosphatase genes PTPRR and PPFIA2, which are in the same gene family, as differentially expressed in normal rapidly growing fetal relative to normal adult ocular tissue (confirmed by RT-qPCR). Conclusions. In an independent high-grade myopia cohort, an intronic SNP in UHRF1BP1L, rs4764971, was validated for quantitative association, and SNPs within PTPRR (quantitative) and PPFIA2 (qualitative and quantitative) approached significance. Three genes identified by our association study and supported by ocular expression and/or replication, UHRF1BP1L, PTPRR, and PPFIA2, are novel candidates for myopic development within the MYP3 locus that should be further studied. PMID:23422819

Applications and limitations of radiomics

NASA Astrophysics Data System (ADS)

Yip, Stephen S. F.; Aerts, Hugo J. W. L.

2016-07-01

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized medicine. In this technical review, we describe applications and challenges of the radiomic field. We will review radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.

A test for selection employing quantitative trait locus and mutation accumulation data.

PubMed

Rice, Daniel P; Townsend, Jeffrey P

2012-04-01

Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

On normality, ethnicity, and missing values in quantitative trait locus mapping

PubMed Central

Labbe, Aurélie; Wormald, Hanna

2005-01-01

Background This paper deals with the detection of significant linkage for quantitative traits using a variance components approach. Microsatellite markers were obtained for the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism data. Ethnic heterogeneity, highly skewed quantitative measures, and a high rate of missing values are all present in this dataset and well known to impact upon linkage analysis. This makes it a good candidate for investigation. Results As expected, we observed a number of changes in LOD scores, especially for chromosomes 1, 7, and 18, along with the three factors studied. A dramatic example of such changes can be found in chromosome 7. Highly significant linkage to one of the quantitative traits became insignificant when a proper normalizing transformation of the trait was used and when analysis was carried out on an ethnically homogeneous subset of the original pedigrees. Conclusion In agreement with existing literature, transforming a trait to ensure normality using a Box-Cox transformation is highly recommended in order to avoid false-positive linkages. Furthermore, pedigrees should be sorted by ethnic groups and analyses should be carried out separately. Finally, one should be aware that the inclusion of covariates with a high rate of missing values reduces considerably the number of subjects included in the model. In such a case, the loss in power may be large. Imputation methods are then recommended. PMID:16451664

Single molecule quantitation and sequencing of rare translocations using microfluidic nested digital PCR.

PubMed

Shuga, Joe; Zeng, Yong; Novak, Richard; Lan, Qing; Tang, Xiaojiang; Rothman, Nathaniel; Vermeulen, Roel; Li, Laiyu; Hubbard, Alan; Zhang, Luoping; Mathies, Richard A; Smith, Martyn T

2013-09-01

Cancers are heterogeneous and genetically unstable. New methods are needed that provide the sensitivity and specificity to query single cells at the genetic loci that drive cancer progression, thereby enabling researchers to study the progression of individual tumors. Here, we report the development and application of a bead-based hemi-nested microfluidic droplet digital PCR (dPCR) technology to achieve 'quantitative' measurement and single-molecule sequencing of somatically acquired carcinogenic translocations at extremely low levels (<10(-6)) in healthy subjects. We use this technique in our healthy study population to determine the overall concentration of the t(14;18) translocation, which is strongly associated with follicular lymphoma. The nested dPCR approach improves the detection limit to 1×10(-7) or lower while maintaining the analysis efficiency and specificity. Further, the bead-based dPCR enabled us to isolate and quantify the relative amounts of the various clonal forms of t(14;18) translocation in these subjects, and the single-molecule sensitivity and resolution of dPCR led to the discovery of new clonal forms of t(14;18) that were otherwise masked by the conventional quantitative PCR measurements. In this manner, we created a quantitative map for this carcinogenic mutation in this healthy population and identified the positions on chromosomes 14 and 18 where the vast majority of these t(14;18) events occur.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

PubMed

Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun

2017-01-01

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Four Linked Genes Participate in Controlling Sporulation Efficiency in Budding Yeast

PubMed Central

Ben-Ari, Giora; Zenvirth, Drora; Sherman, Amir; David, Lior; Klutstein, Michael; Lavi, Uri; Hillel, Jossi; Simchen, Giora

2006-01-01

Quantitative traits are conditioned by several genetic determinants. Since such genes influence many important complex traits in various organisms, the identification of quantitative trait loci (QTLs) is of major interest, but still encounters serious difficulties. We detected four linked genes within one QTL, which participate in controlling sporulation efficiency in Saccharomyces cerevisiae. Following the identification of single nucleotide polymorphisms by comparing the sequences of 145 genes between the parental strains SK1 and S288c, we analyzed the segregating progeny of the cross between them. Through reciprocal hemizygosity analysis, four genes, RAS2, PMS1, SWS2, and FKH2, located in a region of 60 kilobases on Chromosome 14, were found to be associated with sporulation efficiency. Three of the four “high” sporulation alleles are derived from the “low” sporulating strain. Two of these sporulation-related genes were verified through allele replacements. For RAS2, the causative variation was suggested to be a single nucleotide difference in the upstream region of the gene. This quantitative trait nucleotide accounts for sporulation variability among a set of ten closely related winery yeast strains. Our results provide a detailed view of genetic complexity in one “QTL region” that controls a quantitative trait and reports a single nucleotide polymorphism-trait association in wild strains. Moreover, these findings have implications on QTL identification in higher eukaryotes. PMID:17112318

Quantitative trait locus analysis of heterosis for plant height and ear height in an elite maize hybrid zhengdan 958 by design III.

PubMed

Li, Hongjian; Yang, Qingsong; Fan, Nannan; Zhang, Ming; Zhai, Huijie; Ni, Zhongfu; Zhang, Yirong

2017-04-17

Plant height (PH) and ear height (EH) are two important agronomic traits in maize selection breeding. F 1 hybrid exhibit significant heterosis for PH and EH as compared to their parental inbred lines. To understand the genetic basis of heterosis controlling PH and EH, we conducted quantitative trait locus (QTL) analysis using a recombinant inbreed line (RIL) based design III population derived from the elite maize hybrid Zhengdan 958 in five environments. A total of 14 environmentally stable QTLs were identified, and the number of QTLs for Z 1 and Z 2 populations was six and eight, respectively. Notably, all the eight environmentally stable QTLs for Z 2 were characterized by overdominance effect (OD), suggesting that overdominant QTLs were the most important contributors to heterosis for PH and EH. Furthermore, 14 environmentally stable QTLs were anchored on six genomic regions, among which four are trait-specific QTLs, suggesting that the genetic basis for PH and EH is partially different. Additionally, qPH.A-1.3, modifying about 10 centimeters of PH, was further validated in backcross populations. The genetic basis for PH and EH is partially different, and overdominant QTLs are important factors for heterosis of PH and EH. A major QTL qPH.A-1.3 may be a desired target for genetic improvement of maize plant height.

Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

PubMed

Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

2010-04-01

Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

PubMed

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Biological and molecular characterization of silkworm strains from the Brazilian germplasm bank of Bombyx mori.

PubMed

Pereira, N C; Munhoz, R E F; Bignotto, T S; Bespalhuk, R; Garay, L B; Saez, C R N; Fassina, V A; Nembri, A; Fernandez, M A

2013-06-28

Brazil has only one public genetic pool of Bombyx mori strains, which was established in 2005 at Universidade Estadual de Maringá, Maringá, Paraná State. This genetic bank has been maintained, and the strains have been characterized using genetic and morphological tools. The quantitative and qualitative traits, directly or indirectly related to productivity, were evaluated in 14 silkworm strains. In addition to biological and productivity analyses, DNA markers related to susceptibility to the B. mori nucleopolyhedrovirus (BmNPV) were analyzed. BmNPV is a major cause of production loss and is a serious problem for Paraná sericulture. The silkworm strains from diverse geographic origins were found to have different characteristics, including body weight, larval stage duration, cocoon weight, and other biological traits. In terms of productivity, the raw silk percentages were almost uniform, with an overall average of 16.28%. Overall, the Chinese strain C37 gave the best performance in many of the quantitative traits, and it surpassed the other strains in productivity traits. Therefore, it can be used as one of the strains that compose the elite germplasm for silkworm breeding programs. Additionally, genetic molecular markers were efficient in discriminating between B. mori strains that had been identified based on their geographical origin. We found that all Japanese strains produced a 400-bp molecular marker that has been associated with susceptibility to BmNPV.

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis.

PubMed

Kooke, Rik; Kruijer, Willem; Bours, Ralph; Becker, Frank; Kuhn, André; van de Geest, Henri; Buntjer, Jaap; Doeswijk, Timo; Guerra, José; Bouwmeester, Harro; Vreugdenhil, Dick; Keurentjes, Joost J B

2016-04-01

Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified. © 2016 American Society of Plant Biologists. All Rights Reserved.

gQTL: A Web Application for QTL Analysis Using the Collaborative Cross Mouse Genetic Reference Population.

PubMed

Konganti, Kranti; Ehrlich, Andre; Rusyn, Ivan; Threadgill, David W

2018-06-07

Multi-parental recombinant inbred populations, such as the Collaborative Cross (CC) mouse genetic reference population, are increasingly being used for analysis of quantitative trait loci (QTL). However specialized analytic software for these complex populations is typically built in R that works only on command-line, which limits the utility of these powerful resources for many users. To overcome analytic limitations, we developed gQTL, a web accessible, simple graphical user interface application based on the DOQTL platform in R to perform QTL mapping using data from CC mice. Copyright © 2018, G3: Genes, Genomes, Genetics.

[Ph-Sensor Properties of a Fluorescent Protein from Dendronephthya sp].

PubMed

Pakhomov, A A; Chertkova, R V; Martynov, V I

2015-01-01

Genetically encoded biosensors based on fluorescent proteins are now widely applicable for monitoring pH changes in live cells. Here, we have shown that a fluorescent protein from Dendronephthya sp. (DendFP) exhibits a pronounced pH-sensitivity. Unlike most of known genetically encoded pH-sensors, fluorescence of the protein is not quenched upon medium acidification, but is shifting from the red to green spectral range. Therefore, quantitative measurements of intracellular pH are feasible by ratiometric comparison of emission intensities in the red and green spectral ranges, which makes DendFP advantageous compared with other genetically encoded pH-sensors.

Endogenous Reference Genes and Their Quantitative Real-Time PCR Assays for Genetically Modified Bread Wheat (Triticum aestivum L.) Detection.

PubMed

Yang, Litao; Quan, Sheng; Zhang, Dabing

2017-01-01

Endogenous reference genes (ERG) and their derivate analytical methods are standard requirements for analysis of genetically modified organisms (GMOs). Development and validation of suitable ERGs is the primary step for establishing assays that monitoring the genetically modified (GM) contents in food/feed samples. Herein, we give a review of the ERGs currently used for GM wheat analysis, such as ACC1, PKABA1, ALMT1, and Waxy-D1, as well as their performances in GM wheat analysis. Also, we discussed one model for developing and validating one ideal RG for one plant species based on our previous research work.

Assessment on induced genetic variability and divergence in the mutagenized lentil populations of microsperma and macrosperma cultivars developed using physical and chemical mutagenesis

PubMed Central

2017-01-01

Induced mutagenesis was employed to create genetic variation in the lentil cultivars for yield improvement. The assessments were made on genetic variability, character association, and genetic divergence among the twelve mutagenized populations and one parent population of each of the two lentil cultivars, developed by single and combination treatments with gamma rays and hydrazine hydrates. Analysis of variance revealed significant inter-population differences for the observed quantitative phenotypic traits. The sample mean of six treatment populations in each of the cultivar exhibited highly superior quantitative phenotypic traits compared to their parent cultivars. The higher values of heritability and genetic advance with a high genotypic coefficient of variation for most of the yield attributing traits confirmed the possibilities of lentil yield improvement through phenotypic selection. The number of pods and seeds per plant appeared to be priority traits in selection for higher yield due to their strong direct association with yield. The cluster analysis divided the total populations into three divergent groups in each lentil cultivar with parent genotypes in an independent group showing the high efficacy of the mutagens. Considering the highest contribution of yield trait to the genetic divergence among the clustered population, it was confirmed that the mutagenic treatments created a wide heritable variation for the trait in the mutant populations. The selection of high yielding mutants from the mutant populations of DPL 62 (100 Gy) and Pant L 406 (100Gy + 0.1% HZ) in the subsequent generation is expected to give elite lentil cultivars. Also, hybridization between members of the divergent group would produce diverse segregants for crop improvement. Apart from this, the induced mutations at loci controlling economically important traits in the selected high yielding mutants have successfully contributed in diversifying the accessible lentil genetic base and will definitely be of immense value to the future lentil breeding programmes in India. PMID:28922405

The infinitesimal model: Definition, derivation, and implications.

PubMed

Barton, N H; Etheridge, A M; Véber, A

2017-12-01

Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Genomic scan as a tool for assessing the genetic component of phenotypic variance in wild populations.

PubMed

Herrera, Carlos M

2012-01-01

Methods for estimating quantitative trait heritability in wild populations have been developed in recent years which take advantage of the increased availability of genetic markers to reconstruct pedigrees or estimate relatedness between individuals, but their application to real-world data is not exempt from difficulties. This chapter describes a recent marker-based technique which, by adopting a genomic scan approach and focusing on the relationship between phenotypes and genotypes at the individual level, avoids the problems inherent to marker-based estimators of relatedness. This method allows the quantification of the genetic component of phenotypic variance ("degree of genetic determination" or "heritability in the broad sense") in wild populations and is applicable whenever phenotypic trait values and multilocus data for a large number of genetic markers (e.g., amplified fragment length polymorphisms, AFLPs) are simultaneously available for a sample of individuals from the same population. The method proceeds by first identifying those markers whose variation across individuals is significantly correlated with individual phenotypic differences ("adaptive loci"). The proportion of phenotypic variance in the sample that is statistically accounted for by individual differences in adaptive loci is then estimated by fitting a linear model to the data, with trait value as the dependent variable and scores of adaptive loci as independent ones. The method can be easily extended to accommodate quantitative or qualitative information on biologically relevant features of the environment experienced by each sampled individual, in which case estimates of the environmental and genotype × environment components of phenotypic variance can also be obtained.

A synthetic genetic edge detection program.

PubMed

Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D

2009-06-26

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

Defining the consequences of genetic variation on a proteome–wide scale

PubMed Central

Chick, Joel M.; Munger, Steven C.; Simecek, Petr; Huttlin, Edward L.; Choi, Kwangbom; Gatti, Daniel M.; Raghupathy, Narayanan; Svenson, Karen L.; Churchill, Gary A.; Gygi, Steven P.

2016-01-01

Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein–protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice. PMID:27309819

Looping Genomes: Diagnostic Change and the Genetic Makeup of the Autism Population.

PubMed

Navon, Daniel; Eyal, Gil

2016-03-01

This article builds on Hacking's framework of "dynamic nominalism" to show how knowledge about biological etiology can interact with the "kinds of people" delineated by diagnostic categories in ways that "loop" or modify both over time. The authors use historical materials to show how "geneticization" played a crucial role in binding together autism as a biosocial community and how evidence from genetics research later made an important contribution to the diagnostic expansion of autism. In the second part of the article, the authors draw on quantitative and qualitative analyses of autism rates over time in several rare conditions that are delineated strictly according to genomic mutations in order to demonstrate that these changes in diagnostic practice helped to both increase autism's prevalence and create its enormous genetic heterogeneity. Thus, a looping process that began with geneticization and involved the social effects of genetics research itself transformed the autism population and its genetic makeup.

A quantitative trait locus for recognition of foreign eggs in the host of a brood parasite.

PubMed

Martín-Gálvez, D; Soler, J J; Martínez, J G; Krupa, A P; Richard, M; Soler, M; Møller, A P; Burke, T

2006-03-01

Avian brood parasites reduce the reproductive output of their hosts and thereby select for defence mechanisms such as ejection of parasitic eggs. Such defence mechanisms simultaneously select for counter-defences in brood parasites, causing a coevolutionary arms race. Although coevolutionary models assume that defences and counter-defences are genetically influenced, this has never been demonstrated for brood parasites. Here, we give strong evidence for genetic differences between ejector and nonejectors, which could allow the study of such host defence at the genetic level, as well as studies of maintenance of genetic variation in defences. Briefly, we found that magpies, that are the main host of the great spotted cuckoo in Europe, have alleles of one microsatellite locus (Ase64) that segregate between accepters and rejecters of experimental parasitic eggs. Furthermore, differences in ejection rate among host populations exploited by the brood parasite covaried significantly with the genetic distance for this locus.

Motivations for genetic testing for lung cancer risk among young smokers.

PubMed

O'Neill, Suzanne C; Lipkus, Isaac M; Sanderson, Saskia C; Shepperd, James; Docherty, Sharron; McBride, Colleen M

2013-11-01

To examine why young people might want to undergo genetic susceptibility testing for lung cancer despite knowing that tested gene variants are associated with small increases in disease risk. The authors used a mixed-method approach to evaluate motives for and against genetic testing and the association between these motivations and testing intentions in 128 college students who smoke. Exploratory factor analysis yielded four reliable factors: Test Scepticism, Test Optimism, Knowledge Enhancement and Smoking Optimism. Test Optimism and Knowledge Enhancement correlated positively with intentions to test in bivariate and multivariate analyses (ps<0.001). Test Scepticism correlated negatively with testing intentions in multivariate analyses (p<0.05). Open-ended questions assessing testing motivations generally replicated themes of the quantitative survey. In addition to learning about health risks, young people may be motivated to seek genetic testing for reasons, such as gaining knowledge about new genetic technologies more broadly.

A Synthetic Genetic Edge Detection Program

PubMed Central

Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.

2009-01-01

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759

Standing variation in spatially growing populations

NASA Astrophysics Data System (ADS)

Fusco, Diana; Gralka, Matti; Kayser, Jona; Hallatschek, Oskar

Patterns of genetic diversity not only reflect the evolutionary history of a species but they can also determine the evolutionary response to environmental change. For instance, the standing genetic diversity of a microbial population can be key to rescue in the face of an antibiotic attack. While genetic diversity is in general shaped by both demography and evolution, very little is understood when both factors matter, as e.g. for biofilms with pronounced spatial organization. Here, we quantitatively explore patterns of genetic diversity by using microbial colonies and well-mixed test tube populations as antipodal model systems with extreme and very little spatial structure, respectively. We find that Eden model simulations and KPZ theory can remarkably reproduce the genetic diversity in microbial colonies obtained via population sequencing. The excellent agreement allows to draw conclusions on the resilience of spatially-organized populations and to uncover new strategies to contain antibiotic resistance.

Exploring how symptoms of attention-deficit/hyperactivity disorder are related to reading and mathematics performance: general genes, general environments.

PubMed

Hart, Sara A; Petrill, Stephen A; Willcutt, Erik; Thompson, Lee A; Schatschneider, Christopher; Deater-Deckard, Kirby; Cutting, Laurie E

2010-11-01

Children with attention-deficit/hyperactivity disorder (ADHD) tend to perform more poorly on tests of reading and mathematical performance than their typical peers. Quantitative genetic analyses allow for a better understanding of the etiology of ADHD and reading and mathematics outcomes, by examining their common and unique genetic and environmental influences. Analyses were conducted on a sample 271 pairs of 10-year-old monozygotic and dizygotic twins drawn from the Western Reserve Reading and Mathematics Project. In general, the results suggested that the associations among ADHD symptoms, reading outcomes, and math outcomes were influenced by both general genetic and general shared-environment factors. The analyses also suggested significant independent genetic effects for ADHD symptoms. The results imply that differing etiological factors underlie the relationships among ADHD and reading and mathematics performance. It appears that both genetic and common family or school environments link ADHD with academic performance.

Automated design of genetic toggle switches with predetermined bistability.

PubMed

Chen, Shuobing; Zhang, Haoqian; Shi, Handuo; Ji, Weiyue; Feng, Jingchen; Gong, Yan; Yang, Zhenglin; Ouyang, Qi

2012-07-20

Synthetic biology aims to rationally construct biological devices with required functionalities. Methods that automate the design of genetic devices without post-hoc adjustment are therefore highly desired. Here we provide a method to predictably design genetic toggle switches with predetermined bistability. To accomplish this task, a biophysical model that links ribosome binding site (RBS) DNA sequence to toggle switch bistability was first developed by integrating a stochastic model with RBS design method. Then, to parametrize the model, a library of genetic toggle switch mutants was experimentally built, followed by establishing the equivalence between RBS DNA sequences and switch bistability. To test this equivalence, RBS nucleotide sequences for different specified bistabilities were in silico designed and experimentally verified. Results show that the deciphered equivalence is highly predictive for the toggle switch design with predetermined bistability. This method can be generalized to quantitative design of other probabilistic genetic devices in synthetic biology.

An integrated approach to characterize genetic interaction networks in yeast metabolism

PubMed Central

Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs

2011-01-01

Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372

Population- and individual-specific regulatory variation in Sardinia.

PubMed

Pala, Mauro; Zappala, Zachary; Marongiu, Mara; Li, Xin; Davis, Joe R; Cusano, Roberto; Crobu, Francesca; Kukurba, Kimberly R; Gloudemans, Michael J; Reinier, Frederic; Berutti, Riccardo; Piras, Maria G; Mulas, Antonella; Zoledziewska, Magdalena; Marongiu, Michele; Sorokin, Elena P; Hess, Gaelen T; Smith, Kevin S; Busonero, Fabio; Maschio, Andrea; Steri, Maristella; Sidore, Carlo; Sanna, Serena; Fiorillo, Edoardo; Bassik, Michael C; Sawcer, Stephen J; Battle, Alexis; Novembre, John; Jones, Chris; Angius, Andrea; Abecasis, Gonçalo R; Schlessinger, David; Cucca, Francesco; Montgomery, Stephen B

2017-05-01

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Quantitative trait locus gene mapping: a new method for locating alcohol response genes.

PubMed

Crabbe, J C

1996-01-01

Alcoholism is a multigenic trait with important non-genetic determinants. Studies with genetic animal models of susceptibility to several of alcohol's effects suggest that several genes contributing modest effects on susceptibility (Quantitative Trait Loci, or QTLs) are important. A new technique of QTL gene mapping has allowed the identification of the location in mouse genome of several such QTLs. The method is described, and the locations of QTLs affecting the acute alcohol withdrawal reaction are described as an example of the method. Verification of these QTLs in ancillary studies is described and the strengths, limitations, and future directions to be pursued are discussed. QTL mapping is a promising method for identifying genes in rodents with the hope of directly extrapolating the results to the human genome. This review is based on a paper presented at the First International Congress of the Latin American Society for Biomedical Research on Alcoholism, Santiago, Chile, November 1994.

Phenotyping for drought tolerance of crops in the genomics era

PubMed Central

Tuberosa, Roberto

2012-01-01

Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognized obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different water regimes. This review provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars. PMID:23049510

Genetically Modified Foods and Consumer Perspective.

PubMed

Boccia, Flavio; Sarnacchiaro, Pasquale

2015-01-01

Genetically modified food is able to oppose the world's hunger and preserve the environment, even if the patents in this matter are symptomatic of several doubts. And also, transgenic consumption causes problems and skepticism among consumers in several European countries, but above all in Italy, where there is a strong opposition over recent years. So, the present study conducted a research to study the consumption of genetically modified food products by Italian young generation. This research presented the following purposes: firstly, to analyze genetically modified products' consumption among a particular category of consumers; secondly, to implement a quantitative model to understand behaviour about this particular kind of consumption and identify the factors that determine their purchase. The proposed model shows that transgenic consumption is especially linked to knowledge and impact on environment and mankind's health.

If I Could in a Small Way Help”: Motivations for and Beliefs about Sample Donation for Genetic Research

PubMed Central

Michie, Marsha; Henderson, Gail; Garrett, Joanne; Corbie-Smith, Giselle

2012-01-01

Human genome research depends upon participants who donate genetic samples, but few studies have explored in depth the motivations of genetic research donors. This mixed methods study examines telephone interviews with 752 sample donors in a U.S. genetic epidemiology study investigating colorectal cancer. Quantitative and qualitative results indicate that most participants wanted to help society, and that many also wanted information about their own health, even though such information was not promised. Qualitative analysis reveals that donors believed their samples contributed to a scientific “common good”; imagined samples as information rather than tissues; and often blurred distinctions between research and diagnostic testing of samples. Differences between African American and White perspectives were distinct from educational and other possible explanatory factors. PMID:21680977