Detection and quantification of inbreeding depression for complex traits from SNP data

Proc Natl Acad Sci U S A. 2017 Aug 8;114(32):8602-8607. doi: 10.1073/pnas.1621096114. Epub 2017 Jul 26.

Abstract

Quantifying the effects of inbreeding is critical to characterizing the genetic architecture of complex traits. This study highlights through theory and simulations the strengths and shortcomings of three SNP-based inbreeding measures commonly used to estimate inbreeding depression (ID). We demonstrate that heterogeneity in linkage disequilibrium (LD) between causal variants and SNPs biases ID estimates, and we develop an approach to correct this bias using LD and minor allele frequency stratified inference (LDMS). We quantified ID in 25 traits measured in [Formula: see text] participants of the UK Biobank, using LDMS, and confirmed previously published ID for 4 traits. We find unique evidence of ID for handgrip strength, waist/hip ratio, and visual and auditory acuity (ID between -2.3 and -5.2 phenotypic SDs for complete inbreeding; [Formula: see text]). Our results illustrate that a careful choice of the measure of inbreeding combined with LDMS stratification improves both detection and quantification of ID using SNP data.

Keywords: directional dominance; homozygosity; inbreeding depression; quantitative genetics; single-nucleotide polymorphism.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Consanguinity*
  • Databases, Nucleic Acid*
  • Female
  • Humans
  • Linkage Disequilibrium*
  • Male
  • Models, Genetic*
  • Polymorphism, Single Nucleotide*
  • Quantitative Trait, Heritable*