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The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs.

Amir AliakbariEmilie DelpuechYann LabruneJuliette RiquetHélène Gilbert
Published in: Genetics, selection, evolution : GSE (2020)
Our results show that genomic prediction using a training set that includes animals from genetically-related lines can be as accurate as genomic prediction using a training set from the target population. With combined reference sets, accuracy increased for traits that were highly affected by selection. Our results provide insights into the design of reference populations, especially to initiate genomic selection in small-sized lines, for which the number of historical samples is small and that are developed simultaneously. This applies especially to poultry and pig breeding and to other crossbreeding schemes.
Keyphrases
  • copy number
  • virtual reality
  • genome wide
  • gene expression
  • mass spectrometry
  • big data
  • machine learning
  • antimicrobial resistance
  • artificial intelligence
  • data analysis