Supplementary data to publication “An approximate Bayesian significance test for genomic evaluations” (Biom J)

DOI

A simulation study has been conducted to analyse the association between genetic and phenotypic variation in livestock. Following the density and distribution of single nucleotide polymorphisms (SNPs) on the Illumina BovineSNP50 chip, 52,773 SNPs were simulated on the cattle genome of 30 Morgan length. Several generations of random mating were executed in which random recombination events according to the genetic distance between SNPs and random mutation of SNP alleles were considered. In the most recent generations, 50 sires were mated to 20 dams in order to generate multiple half-sib families. The data were split into training (n=2,000) and validation/testing set (n=2,000). Twenty-three SNPs were randomly preselected to be the causative variants, and additive, dominance and epistatic effects were simulated. Two different traits were achieved by adding different residual error terms to the sum of genetic effects, such that the total genetic variation contributed either 30% or 50% to the phenotypic variation. Then, 5,227 SNPs (every 10-th SNP including the causative variants) were selected. The simulation was repeated 100 times. More details can be found in Wittenburg et al. (2011) Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers. BMC Genetics 12:74, https://doi.org/10.1186/1471-2156-12-74 SNP, dominance, epistasis, recombination, genetic variation

Identifier
DOI http://dx.doi.org/doi:10.1002/bimj.201700219
Metadata Access https://www.radar-service.eu/oai/provider?verb=GetRecord&metadataPrefix=oai_dc&identifier=1cedb20a-dfd9-5ccf-82be-e497d0d47eb5
Provenance
Creator Melzer, Nina;Wittenburg, Dörte
Publisher Leibniz Institute for Farm Animal Biology (FBN)
Publication Year 2018
Rights CC BY 4.0 Attribution;Leibniz Institute for Farm Animal Biology (FBN)
Contact Leibniz Institute for Farm Animal Biology (FBN)
Representation
Resource Type phenotypic and genetic data;Dataset
Format application/zip
Coverage
Discipline Biology