Genetic analysis of within-litter variation in piglets’ birth weight using genomic or pedigree relationship matrices

E.B. Sell, Q. Wang, H.A. Mulder, E.F. Knol

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

Abstract

The objective of this study was to estimate the genetic variance for within-litter variation of birth weight (BW0) using genomic (GRM) or pedigree relationship matrices (PRM) and to compare the accuracy of estimated breeding values (EBV) for within-litter variation of BW0 using GRM and PRM. The BW0 and residual variance of BW0 were modeled by the double hierarchical generalized linear model using GRM or PRM. Data came from 2 dam lines: Landrace and Large White. After editing, the data set in Landrace consisted of 748 sows with 1,938 litters and 29,430 piglets and in Large White of 989 sows with 3,320 litters and 51,818 piglets. To construct GRM, 46,466 (Landrace) and 44,826 (Large White) single nucleotide polymorphisms were used, whereas to construct PRM, 5 generations of pedigree were used. The accuracy of EBV with GRM was estimated with 8-fold cross-validation and compared to PRM. Estimated variance components were highly similar for GRM and PRM. The maternal genetic variance in residual variance of BW0 in Landrace was 0.05 with GRM and 0.06 with PRM. In Large White these were 0.04 with GRM and 0.05 with PRM. The genetic coefficient of variation (GCVSDe) was about 0.10 in both dam lines. This indicates a change of 10% in residual SD of BW0 when achieving a genetic response of 1 genetic standard deviation. The genetic correlation between birth weight and its residual variance was about 0.6 in both dam lines. The accuracies of selection for within-litter variation of birth weight were 0.35 with GRM and 0.23 with PRM in Landrace and 0.29 with GRM and 0.34 with PRM in Large White. In this case, using GRM did not significantly increase accuracies of selection. Results, however, show good opportunities to select for reduced within-litter variation of BW0. Genomic selection can increase accuracy of selection when reference populations contain at least 2,000 sows
Original languageEnglish
Pages (from-to)1471-1480
JournalJournal of Animal Science
Volume93
Issue number4
DOIs
Publication statusPublished - 2015

Keywords

  • generalized linear-models
  • single nucleotide polymorphism
  • environmental variance
  • broiler-chickens
  • residual variance
  • individual birth
  • breeding values
  • parameters
  • heterogeneity
  • selection

Fingerprint Dive into the research topics of 'Genetic analysis of within-litter variation in piglets’ birth weight using genomic or pedigree relationship matrices'. Together they form a unique fingerprint.

Cite this