How to deal with genotype uncertainty in variance component quantitative trait loci analyses

Abstract

Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation-Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

Published in

Genetics Research
2011, Volume: 93, number: 5, pages: 333-342 Publisher: CAMBRIDGE UNIV PRESS

SLU Authors

• Rönnegård, Lars

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    
  • Dalarna University

• Carlborg, Örjan

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    
  • Uppsala University

UKÄ Subject classification

Animal and Dairy Science
Veterinary Science


Publication identifier

DOI: https://doi.org/10.1017/S0016672311000152

Permanent link to this page (URI)

https://res.slu.se/id/publ/57937