-
American Journal of Human Genetics Sep 2007Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to...
Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
Topics: Genetic Linkage; Genome, Human; Humans; Polymorphism, Single Nucleotide; Population; Software
PubMed: 17701901
DOI: 10.1086/519795 -
Heredity Jul 2014Adaptation is commonly a multidimensional problem, with changes in multiple traits required to match a complex environment. This is epitomized by balanced polymorphisms... (Review)
Review
Adaptation is commonly a multidimensional problem, with changes in multiple traits required to match a complex environment. This is epitomized by balanced polymorphisms in which multiple phenotypes co-exist and are maintained in a population by a balance of selective forces. Consideration of such polymorphisms led to the concept of the supergene, where alternative phenotypes in a balanced polymorphism segregate as if controlled by a single genetic locus, resulting from tight genetic linkage between multiple functional loci. Recently, the molecular basis for several supergenes has been resolved. Thus, major chromosomal inversions have been shown to be associated with polymorphisms in butterflies, ants and birds, offering a mechanism for localised reduction in recombination. In several examples of plant self-incompatibility, the functional role of multiple elements within the supergene architecture has been demonstrated, conclusively showing that balanced polymorphism can be maintained at multiple coadapted and tightly linked elements. Despite recent criticism, we argue that the supergene concept remains relevant and is more testable than ever with modern molecular methods.
Topics: Adaptation, Biological; Genetic Linkage; Genetic Loci; Genetics, Population; History, 20th Century; History, 21st Century; Models, Genetic; Phenotype; Polymorphism, Genetic; Selection, Genetic
PubMed: 24642887
DOI: 10.1038/hdy.2014.20 -
Molecular Biology and Evolution Oct 2022Epistasis refers to fitness or functional effects of mutations that depend on the sequence background in which these mutations arise. Epistasis is prevalent in nature,...
Epistasis refers to fitness or functional effects of mutations that depend on the sequence background in which these mutations arise. Epistasis is prevalent in nature, including populations of viruses, bacteria, and cancers, and can contribute to the evolution of drug resistance and immune escape. However, it is difficult to directly estimate epistatic effects from sampled observations of a population. At present, there are very few methods that can disentangle the effects of selection (including epistasis), mutation, recombination, genetic drift, and genetic linkage in evolving populations. Here we develop a method to infer epistasis, along with the fitness effects of individual mutations, from observed evolutionary histories. Simulations show that we can accurately infer pairwise epistatic interactions provided that there is sufficient genetic diversity in the data. Our method also allows us to identify which fitness parameters can be reliably inferred from a particular data set and which ones are unidentifiable. Our approach therefore allows for the inference of more complex models of selection from time-series genetic data, while also quantifying uncertainty in the inferred parameters.
Topics: Epistasis, Genetic; Genetic Fitness; Genetic Linkage; Models, Genetic; Mutation; Selection, Genetic
PubMed: 36130322
DOI: 10.1093/molbev/msac199 -
Nature Reviews. Genetics May 2015For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was... (Review)
Review
For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data.
Topics: Algorithms; Female; Genetic Linkage; Genome, Human; Genome-Wide Association Study; Genotyping Techniques; Humans; Lod Score; Male; Pedigree; Penetrance; Phenotype; Polymorphism, Single Nucleotide; Sequence Analysis, DNA; Software
PubMed: 25824869
DOI: 10.1038/nrg3908 -
Heredity Oct 2016Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics and plant and... (Review)
Review
Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces, such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating Ne for future research.
Topics: Biological Evolution; Gene Frequency; Genetic Drift; Genetic Linkage; Genetic Markers; Genetics, Population; Inbreeding; Linkage Disequilibrium; Models, Genetic; Mutation; Population Density; Reproduction; Selection, Genetic
PubMed: 27353047
DOI: 10.1038/hdy.2016.43 -
BMJ (Clinical Research Ed.) Aug 1993
Topics: Genetic Linkage; Homosexuality; Humans; Male; X Chromosome
PubMed: 8374408
DOI: 10.1136/bmj.307.6900.337 -
Genetics Mar 2023Genetic sequences collected over time provide an exciting opportunity to study natural selection. In such studies, it is important to account for linkage disequilibrium...
Genetic sequences collected over time provide an exciting opportunity to study natural selection. In such studies, it is important to account for linkage disequilibrium to accurately measure selection and to distinguish between selection and other effects that can cause changes in allele frequencies, such as genetic hitchhiking or clonal interference. However, most high-throughput sequencing methods cannot directly measure linkage due to short-read lengths. Here we develop a simple method to estimate linkage disequilibrium from time-series allele frequencies. This reconstructed linkage information can then be combined with other inference methods to infer the fitness effects of individual mutations. Simulations show that our approach reliably outperforms inference that ignores linkage disequilibrium and, with sufficient sampling, performs similarly to inference using the true linkage information. We also introduce two regularization methods derived from random matrix theory that help to preserve its performance under limited sampling effects. Overall, our method enables the use of linkage-aware inference methods even for data sets where only allele frequency time series are available.
Topics: Linkage Disequilibrium; Gene Frequency; Selection, Genetic; Mutation; High-Throughput Nucleotide Sequencing
PubMed: 36610715
DOI: 10.1093/genetics/iyac189 -
Journal of Evolutionary Biology Nov 2022Coupling of multiple barriers to gene-flow, such as divergent local adaptation and reproductive isolation, facilitates speciation. However, alleles at loci that...
Coupling of multiple barriers to gene-flow, such as divergent local adaptation and reproductive isolation, facilitates speciation. However, alleles at loci that contribute to barrier effects can be dissociated by recombination. Models of linkage between diverging alleles often consider elements that reduce recombination, such as chromosomal inversions and alleles that modify recombination rate between existing loci. In contrast, here, we consider the evolution of linkage due to the close proximity of loci on the same chromosome. Examples of such physical linkage exist in several species, but in other cases, strong associations are maintained without physical linkage. We use an individual-based model to study the conditions under which the physical linkage between loci controlling ecological traits and mating preferences might be expected to evolve. We modelled a single locus controlling an ecological trait that acts also as a mating cue. Mating preferences are controlled by multiple loci, formed by mutations that are randomly placed in the "genome", within varying distances from the ecological trait locus, allowing us to examine which genomic architectures spread across the population. Our model reveals that stronger physical linkage is favoured when mating preferences and selection are weaker. Under such conditions mating among divergent phenotypes is more frequent, and matching ecological trait and mating preference alleles are more likely to become dissociated by recombination, favouring the evolution of genetic linkage. While most theoretical studies on clustering of divergent loci focus on how physical linkage influences speciation, we show how physical linkage itself can arise, establishing conditions that can favour speciation.
Topics: Genetic Speciation; Genetic Linkage; Reproductive Isolation; Gene Flow; Phenotype
PubMed: 36196988
DOI: 10.1111/jeb.14105 -
Science (New York, N.Y.) Nov 2008Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We... (Review)
Review
Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead.
Topics: Chromosome Mapping; Cloning, Molecular; Disease; Genetic Linkage; Genome, Human; Genome-Wide Association Study; Genotype; Humans; Linkage Disequilibrium; Mutation; Physical Chromosome Mapping; Polymorphism, Single Nucleotide; Quantitative Trait, Heritable; Risk Factors; Selection, Genetic
PubMed: 18988837
DOI: 10.1126/science.1156409 -
Archives of Sexual Behavior Nov 2021Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors.... (Meta-Analysis)
Meta-Analysis
Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors. Individual genome-wide linkage studies (GWLS) have been conducted, but not jointly analyzed. Two main datasets account for > 90% of the published GWLS concordant sibling pairs on the trait and are jointly analyzed here: MGSOSO (Molecular Genetic Study of Sexual Orientation; 409 concordant sibling pairs in 384 families, Sanders et al. (2015)) and Hamer (155 concordant sibling pairs in 145 families, Mustanski et al. (2005)). We conducted multipoint linkage analyses with Merlin on the datasets separately since they were genotyped differently, integrated genetic marker positions, and combined the resultant LOD (logarithm of the odds) scores at each 1 cM grid position. We continue to find the strongest linkage support at pericentromeric chromosome 8 and chromosome Xq28. We also incorporated the remaining published GWLS dataset (on 55 families) by using meta-analytic approaches on published summary statistics. The meta-analysis has maximized the positional information from GWLS of currently available family resources and can help prioritize findings from genome-wide association studies (GWAS) and other approaches. Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait. Further increasing genetic knowledge about male sexual orientation, especially via large GWAS, should help advance our understanding of the biology of this important trait.
Topics: Female; Genetic Linkage; Genome, Human; Genome-Wide Association Study; Humans; Lod Score; Male; Sexual Behavior
PubMed: 34080073
DOI: 10.1007/s10508-021-02035-3