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Tracing Cattle Breeds with Principal Components Analysis Ancestry Informative SNPs

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  • Jamey Lewis
  • Zafiris Abas
  • Christos Dadousis
  • Dimitrios Lykidis
  • Peristera Paschou
  • Petros Drineas

Abstract

The recent release of the Bovine HapMap dataset represents the most detailed survey of bovine genetic diversity to date, providing an important resource for the design and development of livestock production. We studied this dataset, comprising more than 30,000 Single Nucleotide Polymorphisms (SNPs) for 19 breeds (13 taurine, three zebu, and three hybrid breeds), seeking to identify small panels of genetic markers that can be used to trace the breed of unknown cattle samples. Taking advantage of the power of Principal Components Analysis and algorithms that we have recently described for the selection of Ancestry Informative Markers from genomewide datasets, we present a decision-tree which can be used to accurately infer the origin of individual cattle. In doing so, we present a thorough examination of population genetic structure in modern bovine breeds. Performing extensive cross-validation experiments, we demonstrate that 250-500 carefully selected SNPs suffice in order to achieve close to 100% prediction accuracy of individual ancestry, when this particular set of 19 breeds is considered. Our methods, coupled with the dense genotypic data that is becoming increasingly available, have the potential to become a valuable tool and have considerable impact in worldwide livestock production. They can be used to inform the design of studies of the genetic basis of economically important traits in cattle, as well as breeding programs and efforts to conserve biodiversity. Furthermore, the SNPs that we have identified can provide a reliable solution for the traceability of breed-specific branded products.

Suggested Citation

  • Jamey Lewis & Zafiris Abas & Christos Dadousis & Dimitrios Lykidis & Peristera Paschou & Petros Drineas, 2011. "Tracing Cattle Breeds with Principal Components Analysis Ancestry Informative SNPs," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.
    • Handle: RePEc:plo:pone00:0018007
    DOI: 10.1371/journal.pone.0018007
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    References listed on IDEAS

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    1. Christopher S. Troy & David E. MacHugh & Jillian F. Bailey & David A. Magee & Ronan T. Loftus & Patrick Cunningham & Andrew T. Chamberlain & Bryan C. Sykes & Daniel G. Bradley, 2001. "Genetic evidence for Near-Eastern origins of European cattle," Nature, Nature, vol. 410(6832), pages 1088-1091, April.
    2. Peristera Paschou & Petros Drineas & Jamey Lewis & Caroline M Nievergelt & Deborah A Nickerson & Joshua D Smith & Paul M Ridker & Daniel I Chasman & Ronald M Krauss & Elad Ziv, 2008. "Tracing Sub-Structure in the European American Population with PCA-Informative Markers," PLOS Genetics, Public Library of Science, vol. 4(7), pages 1-13, July.
    3. Peristera Paschou & Elad Ziv & Esteban G Burchard & Shweta Choudhry & William Rodriguez-Cintron & Michael W Mahoney & Petros Drineas, 2007. "PCA-Correlated SNPs for Structure Identification in Worldwide Human Populations," PLOS Genetics, Public Library of Science, vol. 3(9), pages 1-15, September.
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    1. Parthan Kasarapu & Laercio R Porto-Neto & Marina R S Fortes & Sigrid A Lehnert & Mauricio A Mudadu & Luiz Coutinho & Luciana Regitano & Andrew George & Antonio Reverter, 2017. "The Bos taurus–Bos indicus balance in fertility and milk related genes," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-20, August.

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