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Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 505311
Title Meta-analysis of GWAS of bovine stature with >50,000 animals imputed to whole-genome sequence
Author(s) Bouwman, A.C.; Pausch, H.; Govignon-Gion, A.; Hoze, C.; Sanchez, M.P.; Boussaha, M.; Boichard, D.A.; Sahana, G.; Brondum, R.F.; Guldbrandtsen, B.; Lund, M.; Vilkki, J.; Sargolzaei, M.; Schenkel, F.S.; Taylor, J.; Hoff, J.L.; Schnabel, R.D.; Veerkamp, R.F.; Goddard, M.E.; Hayes, B.J.
Event EAAP - 66th Annual Meeting 2015, Warsaw, 2015-08-31/2015-09-04
Department(s) LR - Animal Breeding & Genomics
Animal Breeding and Genetics
Publication type Abstract in scientific journal or proceedings
Publication year 2015
Abstract Extensive meta analysis of GWAS in humans has identified 697 significant SNP, however these SNP explain
only 20% the total genetic variation. In order to compare the genetic architecture of stature in humans to
stature in cattle, we performed a large meta-analysis using imputed sequence data. The 1000 Bull Genomes
project provided a multi-breed reference population of 1,147 sequenced animals to impute SNP-chip
genotypes up to whole genome sequence for 15 populations. The populations from Australia, Canada,
Denmark, Finland, France, Germany, the Netherlands, and the USA represented the Angus, Fleckvieh,
Holstein, Jersey, Montbeliarde, Normande, and Nordic Red Dairy Cattle breeds. Genome-wide association
studies were performed on stature phenotypes for each of the populations. Individual GWAS studies revealed
many QTL regions and several regions harboured good candidate genes, e.g. PLAG1, IGF2. Results from
these GWAS studies were combined in a meta-analysis to increase the power for QTL detection and to
refine QTL regions exploiting the different patterns of LD among the breeds. Results of this meta-analysis
will be validated in an independent population to determine how much of the variation in stature can be
explained by the significant SNP
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