Dataset Information

Reconstructing the History of Polygenic Scores Using Coalescent Trees.

ABSTRACT: Genome-wide association studies (GWAS) have revealed that many traits are highly polygenic, in that their within-population variance is governed, in part, by small-effect variants at many genetic loci. Standard population-genetic methods for inferring evolutionary history are ill-suited for polygenic traits: when there are many variants of small effect, signatures of natural selection are spread across the genome and are subtle at any one locus. In the last several years, various methods have emerged for detecting the action of natural selection on polygenic scores, sums of genotypes weighted by GWAS effect sizes. However, most existing methods do not reveal the timing or strength of selection. Here, we present a set of methods for estimating the historical time course of a population-mean polygenic score using local coalescent trees at GWAS loci. These time courses are estimated by using coalescent theory to relate the branch lengths of trees to allele-frequency change. The resulting time course can be tested for evidence of natural selection. We present theory and simulations supporting our procedures, as well as estimated time courses of polygenic scores for human height. Because of its grounding in coalescent theory, the framework presented here can be extended to a variety of demographic scenarios, and its usefulness will increase as both GWAS and ancestral-recombination-graph inference continue to progress.

SUBMITTER: Edge MD

PROVIDER: S-EPMC6325695 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Reconstructing the History of Polygenic Scores Using Coalescent Trees.

Edge Michael D MD Coop Graham G

Genetics 20181102 1

Genome-wide association studies (GWAS) have revealed that many traits are highly polygenic, in that their within-population variance is governed, in part, by small-effect variants at many genetic loci. Standard population-genetic methods for inferring evolutionary history are ill-suited for polygenic traits: when there are many variants of small effect, signatures of natural selection are spread across the genome and are subtle at any one locus. In the last several years, various methods have em ...[more]

PMID: 30389808

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Project description:BACKGROUND: Overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, they are ubiquitous in microbial genomes and more conserved between species than non-overlapping genes. Based on this property, we have previously implemented a web server, named OGtree, that allows the user to reconstruct genome trees of some prokaryotes according to their pairwise OG distances. By analogy to the analyses of gene content and gene order, the OG distance between two genomes we defined was based on a measure of combining OG content (i.e., the normalized number of shared orthologous OG pairs) and OG order (i.e., the normalized OG breakpoint distance) in their whole genomes. A shortcoming of using the concept of breakpoints to define the OG distance is its inability to analyze the OG distance of multi-chromosomal genomes. In addition, the amount of overlapping coding sequences between some distantly related prokaryotic genomes may be limited so that it is hard to find enough OGs to properly evaluate their pairwise OG distances. RESULTS: In this study, we therefore define a new OG order distance that is based on more biologically accurate rearrangements (e.g., reversals, transpositions and translocations) rather than breakpoints and that is applicable to both uni-chromosomal and multi-chromosomal genomes. In addition, we expand the term "gene" to include both its coding sequence and regulatory regions so that two adjacent genes whose coding sequences or regulatory regions overlap with each other are considered as a pair of overlapping genes. This is because overlapping of regulatory regions of distinct genes suggests that the regulation of expression for these genes should be more or less interrelated. Based on these modifications, we have reimplemented our OGtree as a new web server, named OGtree2, and have also evaluated its accuracy of genome tree reconstruction on a testing dataset consisting of 21 Proteobacteria genomes. Our experimental results have finally shown that our current OGtree2 indeed outperforms its previous version OGtree, as well as another similar server, called BPhyOG, significantly in the quality of genome tree reconstruction, because the phylogenetic tree obtained by OGtree2 is greatly congruent with the reference tree that coincides with the taxonomy accepted by biologists for these Proteobacteria. CONCLUSIONS: In this study, we have introduced a new web server OGtree2 at http://bioalgorithm.life.nctu.edu.tw/OGtree2.0/ that can serve as a useful tool for reconstructing more precise and robust genome trees of prokaryotes according to their overlapping genes.

Project description:BackgroundEarly identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM-5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD.MethodsWe studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM-IV alcohol dependence or DSM-5 AUD and 1616 were alcohol-exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first-degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH-). PRS were derived from a meta-analysis of a genome-wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity.ResultsAUD cases had higher PRS than controls with PRS increasing as the number of DSM-5 diagnostic criteria increased (p-values ≤ 1.85E-05 ) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p-value = 7.57E-08 ) and 1.86 (95% CI: 1.35 to 2.56, p-value = 1.32E-04 ) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first-degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM-5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p-values ≤6.7E-11 ). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p-values ≤6.8E-10 ).ConclusionsBoth PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.

Dataset Information

Reconstructing the History of Polygenic Scores Using Coalescent Trees.

Publications

Reconstructing the History of Polygenic Scores Using Coalescent Trees.

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