scholarly journals Region-level epimutation rates in Arabidopsis thaliana

Heredity ◽  
2021 ◽  
Author(s):  
Johanna Denkena ◽  
Frank Johannes ◽  
Maria Colomé-Tatché
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Natural Populations ◽  
Genetic Mutation ◽  
Wide Scale ◽  
Functional Relevance ◽  
Genomic Regions ◽  
Methylation Patterns ◽  
Cg Dinucleotides ◽  
Gains And Losses

AbstractFailure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called “spontaneous epimutations”. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phenotypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutation events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as a way to identify the epigenetic basis of complex traits.

scholarly journals Region-level Epimutation Rates in Arabidopsis thaliana

2020 ◽  
Author(s):  
Johanna Denkena ◽  
Frank Johannes ◽  
Maria Colomé-Tatché
Keyword(s):  
Association Studies ◽  
Natural Populations ◽  
Genetic Mutation ◽  
Genome Wide ◽  
Wide Scale ◽  
Functional Relevance ◽  
Genomic Regions ◽  
Methylation Patterns ◽  
Cg Dinucleotides ◽  
Gains And Losses

AbstractFailure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called ‘spontaneous epimutations’. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phentoypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutational events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as away to identify the epigenetic basis of adaptive traits.

Complex Traits in Natural Populations

2020 ◽  
pp. 263-290
Author(s):  
Daniel L. Hartl
Keyword(s):  
Complex Traits ◽  
Population Genomics ◽  
Association Studies ◽  
Natural Populations ◽  
Complex Diseases ◽  
Stabilizing Selection ◽  
Phenotypic Evolution ◽  
Genetic Changes ◽  
Number Of Genes ◽  
Almost All

This chapter could as well be titled “Population Genomics,” although many aspects of population genomics are integrated throughout the other chapters. It includes estimates of mutational variance and standing variance, phenotypic evolution under directional selection as measured by the linear selection gradient, and phenotypic evolution under stabilizing selection. It explores the strengths and limitations of genome-wide association studies of quantitative trait loci (QTLs) and expression (eQTLs) to detect genetic influencing complex traits in natural populations and genetic risk factors for complex diseases such as heart disease or diabetes. The number of genes affecting complex traits is considered, as well as evidence bearing on the issue of whether complex diseases are primarily affected by a very large number of genes, almost all of small effect, and how this bears on direct-to-consumer and over-the-counter genetic testing. The population genomics of adaptation is considered, including drug resistance, domestication, and local selection versus gene flow. The chapter concludes with the population genomics of speciation as illustrated by reinforcement of mating barriers, the reproducibility of phenotypic and genetic changes, and the accumulation of genetic incompatibilities.

scholarly journals Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci

2011 ◽  
Vol 7 (6) ◽  
pp. 896-898 ◽  
Author(s):  
Alison G. Scoville ◽  
Young Wha Lee ◽  
John H. Willis ◽  
John K. Kelly
Keyword(s):  
Qtl Mapping ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Genetic Variance ◽  
Balancing Selection ◽  
Natural Populations ◽  
Population Based ◽  
Population Variation ◽  
Trait Locus ◽  
Genomic Regions

Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V Q , the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.

scholarly journals Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids

2017 ◽  
Author(s):  
Fanny Bonnafous ◽  
Ghislain Fievet ◽  
Nicolas Blanchet ◽  
Marie-Claude Boniface ◽  
Sébastien Carrère ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Flowering Time ◽  
Genetic Control ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Association Studies ◽  
Additive Models ◽  
Genome Wide Association Studies ◽  
Trait Loci ◽  
Genomic Regions

AbstractGenome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

scholarly journals Local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits

2020 ◽  
Author(s):  
Yiliang Zhang ◽  
Qiongshi Lu ◽  
Yixuan Ye ◽  
Kunling Huang ◽  
Wei Liu ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Genetic Correlation ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Autism Spectrum ◽  
Accurate Estimation ◽  
Genome Wide Association Studies ◽  
Unified Framework ◽  
Genomic Regions

AbstractLocal genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions, which could shed unique light on etiologic sharing and provide additional mechanistic insights into the genetic basis of complex traits compared to global genetic correlation. However, accurate estimation of local genetic correlation remains challenging, in part due to extensive linkage disequilibrium in local genomic regions and pervasive sample overlap across studies. We introduce SUPERGNOVA, a unified framework to estimate both global and local genetic correlations using summary statistics from genome-wide association studies. Through extensive simulations and analyses of 30 complex traits, we demonstrate that SUPERGNOVA substantially outperforms existing methods and identifies 150 trait pairs with significant local genetic correlations. In particular, we show that the positive, consistently-identified, yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically-distinct genetic signatures with bidirectional local genetic correlations. We believe that statistically-rigorous local genetic correlation analysis could accelerate progress in complex trait genetics research.

scholarly journals Quantifying the contribution of Neanderthal introgression to the heritability of complex traits

2020 ◽  
Author(s):  
Evonne McArthur ◽  
David Rinker ◽  
John A. Capra
Keyword(s):  
Complex Traits ◽  
Molecular Level ◽  
Association Studies ◽  
Modern Human ◽  
Modern Humans ◽  
Lung Capacity ◽  
Genome Wide ◽  
Anatomically Modern Humans ◽  
Estimate Heritability ◽  
Genomic Regions

ABSTRACTBackgroundNearly all Eurasians have ∼2% Neanderthal ancestry due to several events of inbreeding between anatomically modern humans and archaic hominins. Previous studies characterizing the legacy of Neanderthal ancestry in modern Eurasians have identified examples of both adaptive and deleterious effects of admixture. However, we lack a comprehensive understanding of the genome-wide influence of Neanderthal introgression on modern human diseases and traits.ResultsWe integrate recent maps of Neanderthal ancestry with well-powered association studies for more than 400 diverse traits to estimate heritability enrichment patterns in regions of the human genome tolerant of Neanderthal ancestry and in introgressed Neanderthal variants themselves. First, we find that variants in regions tolerant of Neanderthal ancestry are depleted of heritability for all traits considered, except skin and hair-related traits. Second, the introgressed variants remaining in modern Europeans are depleted of heritability for most traits; however, we discover that they are enriched for heritability of several traits with potential relevance to human adaptation to non-African environments, including hair and skin traits, autoimmunity, chronotype, bone density, lung capacity, and menopause age. To better understand the phenotypic consequences of these enrichments, we adapt recent methods to test for consistent directional effects of introgressed alleles, and we find directionality for several traits. Finally, we use a direction-of-effect-aware approach to highlight novel candidate introgressed variants that influence risk for disease.ConclusionOur results demonstrate that genomic regions retaining Neanderthal ancestry are not only less functional at the molecular-level, but are also depleted for variation influencing a diverse array of complex traits in modern humans. In spite of this depletion, we identify traits where introgression has an outsized effect. Integrating our results, we propose a framework for using quantification of trait heritability and direction of effect in introgressed regions to understand how Neanderthals were different from modern humans, how selection acted on different traits, and how introgression may have facilitated adaptation to non-African environments.

scholarly journals Targeted epigenomic changes to the maize methylome resulting from tissue culture

2018 ◽  
Author(s):  
Zhaoxue Han ◽  
Peter A. Crisp ◽  
Scott Stelpflug ◽  
Shawn M. Kaeppler ◽  
Qing Li ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Tissue Culture ◽  
Regulation Of Gene Expression ◽  
High Rate ◽  
Genome Integrity ◽  
Epigenetic State ◽  
Context Specific ◽  
Genomic Regions ◽  
Methylation Patterns ◽  
Gains And Losses

AbstractDNA methylation can contribute to the maintenance of genome integrity and regulation of gene expression. In most situations, DNA methylation patterns are inherited quite stably. However, changes in DNA methylation can occur at some loci as a result of tissue culture resulting in somaclonal variation. A sequence-capture bisulfite sequencing approach was implemented to monitor context-specific DNA methylation patterns in ~15Mb of the maize genome for a population of plants that had been regenerated from tissue culture. Plants that have been regenerated from tissue culture exhibit gains and losses of DNA methylation at a subset of genomic regions. There was evidence for a high rate of homozygous changes to DNA methylation levels that occur consistently in multiple independent tissue culture lines suggesting the existence of a targeted process for altering epigenetic state during tissue culture. The consistent changes induced by tissue culture include both gains and losses of DNA methylation and can affect CG, CHG or both contexts within a region. The majority of changes in DNA methylation exhibit stable inheritance although there is some evidence for stochastic reacquisition of the initial epigenetic state in some individuals. This study provides insights into the susceptibility of some loci and potential mechanisms that could contribute to altered DNA methylation and epigenetic state that occur during tissue culture in plant species.

A Haplotype-Based Algorithm for Multilocus Linkage Disequilibrium Mapping of Quantitative Trait Loci With Epistasis

Genetics ◽  
2003 ◽  
Vol 163 (4) ◽  
pp. 1533-1548 ◽  
Author(s):  
Xiang-Yang Lou ◽  
George Casella ◽  
Ramon C Littell ◽  
Mark C K Yang ◽  
Julie A Johnson ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Linkage Disequilibrium ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Association Studies ◽  
Natural Populations ◽  
Evolutionary Relationship ◽  
Linkage Disequilibrium Mapping ◽  
Trait Loci

AbstractFor tightly linked loci, cosegregation may lead to nonrandom associations between alleles in a population. Because of its evolutionary relationship with linkage, this phenomenon is called linkage disequilibrium. Today, linkage disequilibrium-based mapping has become a major focus of recent genome research into mapping complex traits. In this article, we present a new statistical method for mapping quantitative trait loci (QTL) of additive, dominant, and epistatic effects in equilibrium natural populations. Our method is based on haplotype analysis of multilocus linkage disequilibrium and exhibits two significant advantages over current disequilibrium mapping methods. First, we have derived closed-form solutions for estimating the marker-QTL haplotype frequencies within the maximum-likelihood framework implemented by the EM algorithm. The allele frequencies of putative QTL and their linkage disequilibria with the markers are estimated by solving a system of regular equations. This procedure has significantly improved the computational efficiency and the precision of parameter estimation. Second, our method can detect marker-QTL disequilibria of different orders and QTL epistatic interactions of various kinds on the basis of a multilocus analysis. This can not only enhance the precision of parameter estimation, but also make it possible to perform whole-genome association studies. We carried out extensive simulation studies to examine the robustness and statistical performance of our method. The application of the new method was validated using a case study from humans, in which we successfully detected significant QTL affecting human body heights. Finally, we discuss the implications of our method for genome projects and its extension to a broader circumstance. The computer program for the method proposed in this article is available at the webpage http://www.ifasstat.ufl.edu/genome/~LD.

scholarly journals SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiliang Zhang ◽  
Qiongshi Lu ◽  
Yixuan Ye ◽  
Kunling Huang ◽  
Wei Liu ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Autism Spectrum ◽  
Accurate Estimation ◽  
Genome Wide Association Studies ◽  
Statistical Framework ◽  
Genomic Regions ◽  
Genetic Signatures

AbstractLocal genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions. However, accurate estimation of local genetic correlation remains challenging, due to linkage disequilibrium in local genomic regions and sample overlap across studies. We introduce SUPERGNOVA, a statistical framework to estimate local genetic correlations using summary statistics from genome-wide association studies. We demonstrate that SUPERGNOVA outperforms existing methods through simulations and analyses of 30 complex traits. In particular, we show that the positive yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically distinct genetic signatures with bidirectional local genetic correlations.

scholarly journals GWAS Based on RNA-Seq SNPs and High-Throughput Phenotyping Combined with Climatic Data Highlights the Reservoir of Valuable Genetic Diversity in Regional Tomato Landraces

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1387
Author(s):  
Monica Rodriguez ◽  
Alessandro Scintu ◽  
Chiara M. Posadinu ◽  
Yimin Xu ◽  
Cuong V. Nguyen ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Complex Traits ◽  
Plant Traits ◽  
Association Studies ◽  
Climatic Data ◽  
Genome Wide Association Studies ◽  
Rna Seq ◽  
Adaptive Responses ◽  
Solanum Lycopersicum L ◽  
Genomic Regions

Tomato (Solanum lycopersicum L.) is a widely used model plant species for dissecting out the genomic bases of complex traits to thus provide an optimal platform for modern “-omics” studies and genome-guided breeding. Genome-wide association studies (GWAS) have become a preferred approach for screening large diverse populations and many traits. Here, we present GWAS analysis of a collection of 115 landraces and 11 vintage and modern cultivars. A total of 26 conventional descriptors, 40 traits obtained by digital phenotyping, the fruit content of six carotenoids recorded at the early ripening (breaker) and red-ripe stages and 21 climate-related variables were analyzed in the context of genetic diversity monitored in the 126 accessions. The data obtained from thorough phenotyping and the SNP diversity revealed by sequencing of ripe fruit transcripts of 120 of the tomato accessions were jointly analyzed to determine which genomic regions are implicated in the expressed phenotypic variation. This study reveals that the use of fruit RNA-Seq SNP diversity is effective not only for identification of genomic regions that underlie variation in fruit traits, but also of variation related to additional plant traits and adaptive responses to climate variation. These results allowed validation of our approach because different marker-trait associations mapped on chromosomal regions where other candidate genes for the same traits were previously reported. In addition, previously uncharacterized chromosomal regions were targeted as potentially involved in the expression of variable phenotypes, thus demonstrating that our tomato collection is a precious reservoir of diversity and an excellent tool for gene discovery.

Sign in / Sign up

Export Citation Format

Share Document