Age- and gender-dependent heterogeneous proportion of variation explained by SNPs in quantitative traits reflecting human health

2018

Front. Genet.

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Expression quantitative trait loci (eQTLs) are important for understanding the genetic basis of cellular activities and complex phenotypes. Genome-wide eQTL analyses can be effectively conducted by employing a mixed model. The mixed model includes random polygenic effects with variability, which can be estimated by the covariance structure of pairwise genomic similarity among individuals based on genotype information for nucleotide sequence variants. This increases the accuracy of identifying eQTLs by avoiding population stratification. Its extensive use will accelerate our understanding of the genetics of gene expression and complex phenotypes. An overview of genome-wide eQTL analyses using mixed model methodology is provided, including discussions of both theoretical and practical issues. The advantages of employing mixed models are also discussed in this review.

Section: Closing Remarksmentioning

confidence: 99%

Genome-Wide Expression Quantitative Trait Loci Analysis Using Mixed Models

2018

Front. Genet.

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“…However, the homogeneity problem cannot be overcome by this approach for many sex-influenced traits. For example, heritability (a portion of phenotypic variance explained by genetic effects) of men was larger than that of women for body mass index and triglyceride level [ 10 ]. This heterogeneous heritability must be attributed to difference in individual genetic effects between women and men.…”

Section: Genetic Analysis Of Sex-influenced Traitsmentioning

confidence: 99%

Analytical Models For Genetics of Human Traits Influenced By Sex

2016

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Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of genetic variance by sex can be assessed employing a mixed model with genetic relationship matrix constructed from genome-wide nucleotide variant information. Estimating genetic architecture of each sex would help understand different prevalence, course, and severity of complex diseases between women and men in the era of personalized medicine.

Genome-wide association study reveals sex-specific selection signals against autosomal nucleotide variants

Ryu

2016

J Hum Genet

A genome-wide association study (GWAS) was conducted to examine genetic associations of common autosomal nucleotide variants with sex in a Korean population with 4183 males and 4659 females. Nine genetic association signals were identified in four intragenic and five intergenic regions (P<5 × 10(-8)). Further analysis with an independent data set confirmed two intragenic association signals in the genes encoding protein phosphatase 1, regulatory subunit 12B (PPP1R12B, intron 12, rs1819043) and dynein, axonemal, heavy chain 11 (DNAH11, intron 61, rs10255013), which are directly involved in the reproductive system. This study revealed autosomal genetic variants associated with sex ratio by GWAS for the first time. This implies that genetic variants in proximity to the association signals may influence sex-specific selection and contribute to sex ratio variation. Further studies are required to reveal the mechanisms underlying sex-specific selection.