Evaluation of reduced subsets of single nucleotide polymorphisms for the prediction of age at puberty in sows

K. L. Lucot, M. L. Spangler, M. D. Trenhaile, S. D. Kachman, D. C. Ciobanu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Summary Genomic information could be used efficiently to improve traits that are expensive to measure, sex limited or expressed late in life. This study analyzed the phenotypic variation explained by major SNPs and windows for age at puberty in gilts, an indicator of reproductive longevity. A genome-wide association study using 56 424 SNPs explained 25.2% of the phenotypic variation in age at puberty in a training set (n = 820). All SNPs from the top 10% of 1-Mb windows explained 33.5% of the phenotypic variance compared to 47.1% explained by the most informative markers (n = 261). In an evaluation population, consisting of subsequent batches (n = 412), the predictive ability of all SNPs from the major 1-Mb windows was higher compared to the variance captured by the most informative SNP from each of these windows. The phenotypic variance explained in the evaluation population varied from 12.3% to 36.8% when all SNPs from major windows were used compared to 6.5-23.7% explained by most informative SNPs. The correlation between phenotype and genomic prediction values based on SNP effects estimated in the training population was marginal compared to their effects retrained in the evaluation population for all (0.46-0.81) or most informative SNPs (0.30-0.65) from major windows. An increase in genetic gain of 20.5% could be obtained if genomic selection included both sexes compared to females alone. The pleiotropic role of major genes such as AVPR1A could be exploited in selection of both age at puberty and reproductive longevity.

Original languageEnglish (US)
Pages (from-to)403-409
Number of pages7
JournalAnimal genetics
Volume46
Issue number4
DOIs
StatePublished - Aug 1 2015

Keywords

  • fertility
  • genomic prediction
  • swine

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Genetics

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