Detecting effective starting point of genomic selection by divergent trends from best linear unbiased prediction and single-step genomic best linear unbiased prediction in pigs, beef cattle, and broilers.

Rostam Abdollahi-Arpanahi, Daniela Lourenco, Ignacy Misztal
Author Information
  1. Rostam Abdollahi-Arpanahi: Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. ORCID
  2. Daniela Lourenco: Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.
  3. Ignacy Misztal: Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. ORCID

Abstract

Genomic selection has been adopted nationally and internationally in different livestock and plant species. However, understanding whether genomic selection has been effective or not is an essential question for both industry and academia. Once genomic evaluation started being used, estimation of breeding values with pedigree best linear unbiased prediction (BLUP) became biased because this method does not consider selection using genomic information. Hence, the effective starting point of genomic selection can be detected in two possible ways including the divergence of genetic trends and Realized Mendelian sampling (RMS) trends obtained with BLUP and single-step genomic BLUP (ssGBLUP). This study aimed to find the start date of genomic selection for a set of economically important traits in three livestock species by comparing trends obtained using BLUP and ssGBLUP. Three datasets were used for this purpose: 1) a pig dataset with 117k genotypes and 1.3M animals in pedigree, 2) an Angus cattle dataset consisted of ~842k genotypes and 11.5M animals in pedigree, and 3) a purebred broiler chicken dataset included ~154k genotypes and 1.3M birds in pedigree were used. The genetic trends for pigs diverged for the genotyped animals born in 2014 for average daily gain (ADG) and backfat (BF). In beef cattle, the trends started diverging in 2009 for weaning weight (WW) and in 2016 for postweaning gain (PWG), with little divergence for birth weight (BTW). In broiler chickens, the genetic trends estimated by ssGBLUP and BLUP diverged at breeding cycle 6 for two out of the three production traits. The RMS trends for the genotyped pigs diverged for animals born in 2014, more for ADG than for BF. In beef cattle, the RMS trends started diverging in 2009 for WW and in 2016 for PWG, with a trivial trend for BTW. In broiler chickens, the RMS trends from ssGBLUP and BLUP diverged strongly for two production traits at breeding cycle 6, with a slight divergence for another trait. Divergence of the genetic trends from ssGBLUP and BLUP indicates the onset of the genomic selection. The presence of trends for RMS indicates selective genotyping, with or without the genomic selection. The onset of genomic selection and genotyping strategies agrees with industry practices across the three species. In summary, the effective start of genomic selection can be detected by the divergence between genetic and RMS trends from BLUP and ssGBLUP.

Keywords

References

J Dairy Sci. 2020 Jun;103(6):5291-5301 [PMID: 32331884]
J Dairy Sci. 2011 Feb;94(2):1011-20 [PMID: 21257070]
J Anim Sci. 2015 Jun;93(6):2653-62 [PMID: 26115253]
J Anim Sci. 2001 May;79(5):1166-72 [PMID: 11374535]
J Dairy Sci. 2018 Mar;101(3):2187-2198 [PMID: 29290441]
J Dairy Sci. 2018 Jun;101(6):5166-5176 [PMID: 29605309]
J Dairy Sci. 2014;97(6):3943-52 [PMID: 24679933]
J Dairy Sci. 2009 Sep;92(9):4656-63 [PMID: 19700729]
J Dairy Sci. 2018 Apr;101(4):3155-3163 [PMID: 29397162]
J Dairy Sci. 2017 Oct;100(10):8277-8281 [PMID: 28780113]
Genetics. 2016 May;203(1):573-81 [PMID: 26944916]
J Dairy Sci. 2021 Jan;104(1):662-677 [PMID: 33162076]
Genet Sel Evol. 2015 Jul 02;47:56 [PMID: 26133806]
J Anim Sci. 2020 Feb 1;98(2): [PMID: 31999338]
J Anim Sci. 2020 Jun 1;98(6): [PMID: 32374831]
J Dairy Sci. 2015 Jun;98(6):4090-4 [PMID: 25864050]
J Anim Sci. 2021 Jan 1;99(1): [PMID: 33313883]
Genet Res (Camb). 2011 Oct;93(5):357-66 [PMID: 21767459]
J Anim Breed Genet. 2013 Aug;130(4):252-8 [PMID: 23855627]
J Anim Sci. 2020 Apr 1;98(4): [PMID: 32267923]
J Dairy Sci. 2010 Feb;93(2):743-52 [PMID: 20105546]
Genet Sel Evol. 2011 Aug 18;43:30 [PMID: 21851619]
J Dairy Sci. 2018 Jun;101(6):5194-5206 [PMID: 29573806]
J Anim Breed Genet. 2007 Dec;124(6):342-55 [PMID: 18076471]
J Anim Breed Genet. 2018 Apr;135(2):107-115 [PMID: 29484731]
Genet Sel Evol. 2020 Jul 29;52(1):42 [PMID: 32727349]
J Anim Sci. 2016 Mar;94(3):909-19 [PMID: 27065253]
Genes (Basel). 2020 Jul 14;11(7): [PMID: 32674271]

Grants

  1. /Cobb-Vantress
  2. /Pig Improvement Company
  3. /Angus Genetics Inc.
  4. /U.S. Department of Agriculture
  5. 2020-67015-31030/National Institute of Food and Agriculture

MeSH Term

Animals
Cattle
Chickens
Genome
Genomics
Genotype
Models, Genetic
Pedigree
Phenotype
Swine

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