Forskning ved Københavns Universitet - Københavns Universitet


Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

Publikation: KonferencebidragPaperForskningfagfællebedømt

  • Duy Ngoc Do
  • L. L. G. Janss
  • Anders Bjerring Strathe
  • J. Jensen
  • Haja Kadarmideen
Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of different power parameters had no effect on predictive ability. Partitioning of genomic variance showed that SNP groups either by position (intron, exon, downstream, upstream and 5’UTR) or by function (missense and protein-altering) had similar average explained variance per SNP, except that 3’UTR had a higher value.
Antal sider3
StatusUdgivet - 2014
BegivenhedThe 10th World Congress on Genetics Applied to Livestock Production - Vancouver, Canada
Varighed: 17 aug. 201422 aug. 2014


KonferenceThe 10th World Congress on Genetics Applied to Livestock Production

ID: 135537565