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Population parameters incorporated into genome-wide tagSNP selection

Published online by Cambridge University Press:  25 March 2013

A. P. Silesian  and
J. Szyda
A. P. Silesian*
Affiliation:
Institute of Genetics, Biostatistics Group, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland
J. Szyda
Affiliation:
Institute of Genetics, Biostatistics Group, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631 Wroclaw, Poland
*
†E-mail: ap.silesian@gmail.com
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Abstract

Single nucleotide polymorphisms (SNPs) are the most widespread source of variation in genomes. While the very large number of SNPs allows for a very precise description of genetic variation, it impedes data processing and significantly increases analysis time. Many of the SNPs located close to each other frequently carry the same or similar information. This problem can be solved by selecting the most informative SNPs (tagSNPs) using linkage disequilibrium information by identifying a set of tagSNPs representative for a chromosome fragment. The goal of this study is to check whether the genetic structure of a population, expressed by relationship and inbreeding coefficients, affects tagSNP selection. Six subsets of 450 bulls are selected out of the 1228 Polish Holstein-Friesian bulls genotyped by the Illumina BovineSNP50 Bead Chip. TagSNPs are selected for each of the subsets, as well as for the whole data set. The average reduction of the SNP number is 77.2% and is very similar in each sub-population. Differences in tagSNP selection between sub-populations are small. On average, 93.88% of the tagSNPs overlap between subsets. The study showed that differences in the genetic structure of the reference population have little influence on tagSNP selection.

Keywords

linkage disequilibriumreference population structuresingle nucleotide polymorphismstagSNP
Type
Breeding and genetics
Information
animal , Volume 7 , Issue 8 , August 2013 , pp. 1227 - 1230
Copyright
Copyright © The Animal Consortium 2013 

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