Genomic prediction using QTL derived from whole genome sequence data

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This study investigated the gain in accuracy of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k SNP data. Analyses were performed for Nordic Holstein and Danish Jersey animals, using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model, results showed increases in accuracy of up to two percentage points for production traits in both Holstein and Jersey animals by including the extra variants in the analysis, and an extra 1.5 percentage points for fertility in Jersey animals. When using a Bayesian model accuracies were generally higher, but only small increases in accuracy of up to 0.6 percentage points were observed for the Holstein animals when including the extra markers, while both increases and decreases were observed for Jersey
Original languageEnglish
Publication year17 Aug 2014
Number of pages3
Publication statusPublished - 17 Aug 2014
Event10th World Congress on Genetics Applied to Livestock Production (WCGALP) - The Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4, Vancouver, Canada
Duration: 17 Aug 201422 Aug 2014
Conference number: 10th

Conference

Conference10th World Congress on Genetics Applied to Livestock Production (WCGALP)
Number10th
LocationThe Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4
CountryCanada
CityVancouver
Period17/08/201422/08/2014

    Research areas

  • custom chip, genomic prediction, QTL

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