Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T05:20:04.176Z Has data issue: false hasContentIssue false
  • English
  • Français

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
Get access

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 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Banos, G, Coffey, MP 2010. Short communication: characterization of the genome-wide linkage disequilibrium in 2 divergent selection lines of dairy cows. Journal of Dairy Science 93, 2775–2778.Google Scholar
Barendse, W, Reverter, A, Bunch, RJ, Harrison, BE, Barris, W, Thomas, MB 2007. A validated whole-genome association study of efficient food conversion in cattle. Genetics 176, 1893–1905.CrossRefGoogle ScholarPubMed
Barrett, JC, Fry, B, Maller, J, Daly, MJ 2004. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265.Google Scholar
Boehnke, M 2000. A look at linkage disequilibrium. Nature Genetics 25, 246–247.CrossRefGoogle Scholar
Calus, MPL 2010. Genomic breeding value prediction: methods and procedures. Animal 4, 157–164.Google Scholar
Carlson, CS, Eberle, MA, Rieder, MJ, Quian, Y, Krygulak, L, Nickerson, DA 2004. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. American Journal of Human Genetics 74, 106–120.Google Scholar
de Bakker, PI, Yelensky, R, Pe'er, I, Gabriel, SB, Daly, MJ, Altshuler, D 2005. Efficiency and power in genetic association studies. Nature Genetics 37, 1217–1223.CrossRefGoogle ScholarPubMed
de Roos, APW, Hayes, BJ, Spelman, RJ, Goddard, ME 2008. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle. Genetics 179, 1503–1512.Google Scholar
Ding, K, Kullo, IJ 2007. Methods for the selection of tagging SNPs: a comparison of tagging efficiency and performance. European Journal of Human Genetics 15, 228–236.Google Scholar
Gabriel, SB, Schaffner, SF, Nguyen, H, Moore, JM, Roy, J, Blumenstiel, B, Higgins, J, DeFelice, M, Lochner, A, Faggart, M, Liu-Cordero, SN, Rotimi, C, Adeyemo, A, Cooper, R, Ward, R, Lander, ES, Daly, MJ, Altshuler, D 2002. The structure of haplotype blocks in the human genome. Science 296, 2225–2229.Google Scholar
Gautier, M, Faraut, T, Moazami-Goudarzi, K, Navratil, V, Foglio, M, Grohs, C, Boland, A, Garnier, JG, Boichard, D, Lathrop, GM, Gut, IG, Eggen, A 2007. Genetic and haplotypic structure in 14 European and African cattle breeds. Genetics 177, 1059–1070.Google Scholar
Ke, X, Miretti, MM, Broxholme, J, Hunt, S, Beck, S, Bentley, DR, Deloukas, P, Cardon, LR 2005. A comparison of tagging methods and their tagging space. Human Molecular Genetics 14, 2757–2767.Google Scholar
Khatkar, MS, Nicholas, FW, Collins, AR, Zenger, KR, Cavanagh, JAL, Barris, W, Schnabel, RD, Taylor, JF, Raadsma, HW 2008. Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC Genomics 9, 187.CrossRefGoogle ScholarPubMed
Khatkar, MS, Zenger, KR, Hobbs, M, Hawken, RJ, Cavanagh, JA, Barris, W, McClintock, AE, McClintock, S, Thomson, PC, Tier, B, Nicholas, FW, Raadsma, HW 2007. A primary assembly of a bovine haplotype block map based on a 15,036-single-nucleotide polymorphism panel genotyped in Holstein-Friesian cattle. Genetics 176, 763–772.Google Scholar
Kim, ES, Kirkpatrick, BW 2009. Linkage disequilibrium in the North American Holstein population. Animal Genetics 40, 279–288.Google Scholar
LaFramboise, T 2009. Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Research 37, 4181–4193.CrossRefGoogle ScholarPubMed
Marques, E, Schnabel, RD, Stothard, P, Kolbehdari, D, Wang, Z, Taylor, JF, Moore, SS 2008. High density linkage disequilibrium maps of chromosome 14 in Holstein and Angus cattle. BMC Genetics 9, 45, doi:10.1186/1471-2156-9-45, Published online by BioMed Central Ltd.Google Scholar
Matukumalli, LK, Lawley, CT, Schnabel, RD, Taylor, JF, Allan, MF, Heaton, MP, O'Conell, J, Moore, SS, Smith, TP, Sonstegard, TS, Van Tassell, CP 2009. Development and characterization of a high density SNP genotyping assay for cattle. PLoS ONE 4(4), e5350, doi:10.1371/journal.pone.0005350, Published online by PLoS ONE.Google Scholar
McKay, SD, Schnabel, RD, Murdoch, BM, Matukumalli, LK, Aerts, J, Coppieters, W, Crews, D, Neto, ED, Gill, CA, Gao, C, Mannen, H, Stothard, P, Wang, Z, Van Tassell, CP, Williams, JL, Taylor, JF, Moore, SS 2007. Whole genome linkage disequilibrium maps in cattle. BMC Genetics 8, 74, doi:10.1186/1471-2156-8-74, Published online by BioMed Central Ltd.Google Scholar
Prasad, A, Schnabel, RD, McKay, SD, Murdoch, B, Stothard, P, Kolbehdari, D, Wang, Z, Taylor, JF, Moore, SS 2008. Linkage disequilibrium and signatures of selection on chromosomes 19 and 29 in beef and dairy cattle. Animal Genetics 39, 597–605.Google Scholar
Qanbari, S, Pimentel, EC, Tetens, J, Thaller, G, Lichtner, P, Sharifi, AR, Simianer, H 2010. The pattern of linkage disequilibrium in German Holstein cattle. Animal Genetics 41, 346–356.Google Scholar
R Development Core Team 2010. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Sargolzaei, M, Schenkel, FS, Jansen, GB, Schaeffer, LR 2008. Extent of linkage disequilibrium in Holstein cattle in North America. Journal of Dairy Science 91, 2106–2117.Google Scholar
Schaeffer, LR 2006. Strategy for applying genome-wide selection in dairy cattle. Journal of Animal Breading and Genetics 123, 218–223.Google Scholar
Villa-Angulo, R, Matukumalli, LK, Gill, CA, Choi, J, Van Tassell, CP, Grefenstette, JJ 2009. High-resolution haplo-type block structure in the cattle genome. BMC Genetics 10, 19, doi:10.1186/1471-2156-10-19, Published online by BioMed Central Ltd.Google Scholar
Supplementary material: PDF

Silesian Supplementary Material

Silesian S1

Download Silesian Supplementary Material(PDF)
PDF 704 KB
Supplementary material: PDF

Silesian Supplementary Material

Silesian S2

Download Silesian Supplementary Material(PDF)
PDF 661.7 KB