Differences between genomic-based and pedigree-based relationships in a chicken population, as a function of quality control and pedigree links among individuals

J Anim Breed Genet. 2014 Dec;131(6):445-51. doi: 10.1111/jbg.12109. Epub 2014 Jul 15.

Abstract

This work studied differences between expected (calculated from pedigree) and realized (genomic, from markers) relationships in a real population, the influence of quality control on these differences, and their fit to current theory. Data included 4940 pure line chickens across five generations genotyped for 57,636 SNP. Pedigrees (5762 animals) were available for the five generations, pedigree starting on the first one. Three levels of quality control were used. With no quality control, mean difference between realized and expected relationships for different type of relationships was ≤ 0.04 with standard deviation ≤ 0.10. With strong quality control (call rate ≥ 0.9, parent-progeny conflicts, minor allele frequency and use of only autosomal chromosomes), these numbers reduced to ≤ 0.02 and ≤ 0.04, respectively. While the maximum difference was 1.02 with the complete data, it was only 0.18 with the latest three generations of genotypes (but including all pedigrees). Variation of expected minus realized relationships agreed with theoretical developments and suggests an effective number of loci of 70 for this population. When the pedigree is complete and as deep as the genotypes, the standard deviation of difference between the expected and realized relationships is around 0.04, all categories confounded. Standard deviation of differences larger than 0.10 suggests bad quality control, mistakes in pedigree recording or genotype labelling, or insufficient depth of pedigree.

Keywords: Chicken; comparison; genomic relationship matrix; numerator relationship matrix; standard deviation.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Breeding*
  • Chickens / genetics*
  • Genetic Markers
  • Genome
  • Genomics
  • Genotype*
  • Pedigree*
  • Polymorphism, Single Nucleotide*
  • Quality Control

Substances

  • Genetic Markers