Article thumbnail
Location of Repository

Use of the canonical discriminant analysis to select SNP markers for bovine breed assignment and traceability purposes

By Corrado Dimauro, Massimo Cellesi, Roberto Steri, Giustino Gaspa, Silvia Sorbolini, Alessandra Stella and Nicolò Pietro Paolo Macciotta

Abstract

Several market research studies have shown that consumers are primarily concerned with the provenance of the food they eat. Among the available identification methods, only DNA-based techniques appear able to completely prevent frauds. In this study, a new method to discriminate among different bovine breeds and assign new individuals to groups was developed. Bulls of three cattle breeds farmed in Italy – Holstein, Brown, and Simmental – were genotyped using the 50K SNP Illumina BeadChip. Multivariate canonical discriminant analysis was used to discriminate among breeds, and discriminant analysis (DA) was used to assign new observations. This method was able to completely identify the three groups at chromosome level. Moreover, a genome-wide analysis developed using 340 linearly independent SNPs yielded a significant separation among groups. Using the reduced set of markers, the DA was able to assign 30 independent individuals to the proper breed. Finally, a set of 48 high discriminant SNPs was selected and used to develop a new run of the analysis. Again, the procedure was able to significantly identify the three breeds and to correctly assign new observations. These results suggest that an assay with the selected 48 SNP could be used to routinely track monobreed products

Topics: AGR/17 Zootecnica generale e miglioramento genetico, AGR/19 Zootecnica speciale
Publisher: Blackwell / Wiley
Year: 2013
DOI identifier: 10.1111/age.12021
OAI identifier: oai:eprints.uniss.it:9146
Provided by: UnissResearch
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://eprints.uniss.it/9146/ (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.