The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses

被引:50
作者
Caballero, Armando [1 ]
Tenesa, Albert [2 ,3 ,4 ]
Keightley, Peter D. [5 ]
机构
[1] Univ Vigo, Dept Bioquim Genet & Inmunol, Fac Biol, Vigo 36310, Spain
[2] Univ Edinburgh, Roslin Inst, Easter Bush EH25 9RG, Midlothian, Scotland
[3] Univ Edinburgh, Royal Dick Sch Vet Studies, Easter Bush EH25 9RG, Midlothian, Scotland
[4] Univ Edinburgh, MRC, HGU, Inst Genet & Mol Med,Western Gen Hosp, Edinburgh EH4 2XU, Midlothian, Scotland
[5] Univ Edinburgh, Inst Evolutionary Biol, Edinburgh EH9 3FL, Midlothian, Scotland
基金
英国生物技术与生命科学研究理事会;
关键词
quantitative trait variation; complex traits; missing heritability; fitness; additive genetic variance; MISSING HERITABILITY; HUMAN HEIGHT; ASSOCIATION; RARE; ARCHITECTURE; SELECTION; VARIANTS; FITNESS; EVOLUTION; DISEASE;
D O I
10.1534/genetics.115.177220
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (similar to 0.03-0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.
引用
收藏
页码:1601 / +
页数:32
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