scholarly journals Linkage disequilibrium–dependent architecture of human complex traits shows action of negative selection

2017 ◽  
Vol 49 (10) ◽  
pp. 1421-1427 ◽  
Author(s):  
Steven Gazal ◽  
Hilary K Finucane ◽  
Nicholas A Furlotte ◽  
Po-Ru Loh ◽  
Pier Francesco Palamara ◽  
...  
2019 ◽  
Vol 51 (8) ◽  
pp. 1295-1295
Author(s):  
Steven Gazal ◽  
Hilary K. Finucane ◽  
Nicholas A. Furlotte ◽  
Po-Ru Loh ◽  
Pier Francesco Palamara ◽  
...  

2016 ◽  
Author(s):  
Steven Gazal ◽  
Hilary K. Finucane ◽  
Nicholas A Furlotte ◽  
Po-Ru Loh ◽  
Pier Francesco Palamara ◽  
...  

AbstractRecent work has hinted at the linkage disequilibrium (LD) dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) have larger per-SNP heritability after conditioning on their minor allele frequency (MAF). However, this has not been formally assessed, quantified or biologically interpreted. Here, we analyzed summary statistics from 56 complex diseases and traits (average N = 101,401) by extending stratified LD score regression to continuous annotations. We determined that SNPs with low LLD have significantly larger per-SNP heritability. Roughly half of the LLD signal can be explained by functional annotations that are negatively correlated with LLD, such as DNase I hypersensitivity sites (DHS). The remaining signal is largely driven by our finding that common variants that are more recent tend to have lower LLD and to explain more heritability (P = 2.38 × 10−104); the youngest 20% of common SNPs explain 3.9x more heritability than the oldest 20%, consistent with the action of negative selection. We also inferred jointly significant effects of other LD-related annotations and confirmed via forward simulations that these annotations jointly predict deleterious effects. Our results are consistent with the action of negative selection on deleterious variants that affect complex traits, complementing efforts to learn about negative selection by analyzing much smaller rare variant data sets.


2017 ◽  
Author(s):  
Jian Zeng ◽  
Ronald de Vlaming ◽  
Yang Wu ◽  
Matthew R Robinson ◽  
Luke Lloyd-Jones ◽  
...  

AbstractEstimation of the joint distribution of effect size and minor allele frequency (MAF) for genetic variants is important for understanding the genetic basis of complex trait variation and can be used to detect signature of natural selection. We develop a Bayesian mixed linear model that simultaneously estimates SNP-based heritability, polygenicity (i.e. the proportion of SNPs with nonzero effects) and the relationship between effect size and MAF for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752), and show that on average across 28 traits, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (p < 0.05/28 =1.8×10−3) signatures of natural selection for 23 out of 28 traits including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. We further apply the method to 27,869 gene expression traits (N = 1,748), and identify 30 genes that show significant (p < 2.3×10−6) evidence of natural selection. All the significant estimates of the relationship between effect size and MAF in either complex traits or gene expression traits are consistent with a model of negative selection, as confirmed by forward simulation. We conclude that natural selection acts pervasively on human complex traits shaping genetic variation in the form of negative selection.


2018 ◽  
Vol 50 (5) ◽  
pp. 746-753 ◽  
Author(s):  
Jian Zeng ◽  
Ronald de Vlaming ◽  
Yang Wu ◽  
Matthew R. Robinson ◽  
Luke R. Lloyd-Jones ◽  
...  

Genetics ◽  
2001 ◽  
Vol 157 (2) ◽  
pp. 899-909
Author(s):  
Rongling Wu ◽  
Zhao-Bang Zeng

Abstract A new strategy for studying the genome structure and organization of natural populations is proposed on the basis of a combined analysis of linkage and linkage disequilibrium using known polymorphic markers. This strategy exploits a random sample drawn from a panmictic natural population and the open-pollinated progeny of the sample. It is established on the principle of gene transmission from the parental to progeny generation during which the linkage between different markers is broken down due to meiotic recombination. The strategy has power to simultaneously capture the information about the linkage of the markers (as measured by recombination fraction) and the degree of their linkage disequilibrium created at a historic time. Simulation studies indicate that the statistical method implemented by the Fisher-scoring algorithm can provide accurate and precise estimates for the allele frequencies, recombination fractions, and linkage disequilibria between different markers. The strategy has great implications for constructing a dense linkage disequilibrium map that can facilitate the identification and positional cloning of the genes underlying both simple and complex traits.


Author(s):  
Valentin Hivert ◽  
Julia Sidorenko ◽  
Florian Rohart ◽  
Michael E. Goddard ◽  
Jian Yang ◽  
...  

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