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

43Citations
Citations of this article
129Readers
Mendeley users who have this article in their library.

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 ~140,000 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; P < 0.001). 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.

Cite

CITATION STYLE

APA

Yengo, L., Zhu, Z., Wray, N. R., Weir, B. S., Yang, J., Robinson, M. R., & Visscher, P. M. (2017). Detection and quantification of inbreeding depression for complex traits from SNP data. Proceedings of the National Academy of Sciences of the United States of America, 114(32), 8602–8607. https://doi.org/10.1073/pnas.1621096114

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free