Background: SNP (single nucleotide polymorphisms) genotype data are increasingly available in cattle populations and, among other things, can be used to predict carriers of specific haplotypes. It is therefore convenient to have a practical statistical method for the accurate classification of individuals into carriers and non-carriers. In this paper, we present a procedure combining variable selection (i.e. the selection of predictive SNPs) and linear discriminant analysis for the identification of carriers of a haplotype on BTA19 (Bos taurus autosome 19) known to be associated with reduced cow fertility. A population of 3645 Brown Swiss cows and bulls genotyped with the 54K SNP-chip was available for the analysis. Results: The overall error rate for the prediction of haplotype carriers was on average very low (~<= 1%). The error rate was found to depend on the number of SNPs in the model and their density around the region of the haplotype on BTA19. The minimum set of SNPs to still achieve accurate predictions was 5, with a total test error rate of 1.59. Conclusions: The paper describes a procedure to accurately identify haplotype carriers from SNP genotypes in cattle populations. Very few misclassifications were observed, which indicates that this is a very reliable approach for potential applications in cattle breeding.

Predicting haplotype carriers from SNP genotypes in Bos taurus through linear discriminant analysis

Biffani S;Stella A;Biscarini F
2015

Abstract

Background: SNP (single nucleotide polymorphisms) genotype data are increasingly available in cattle populations and, among other things, can be used to predict carriers of specific haplotypes. It is therefore convenient to have a practical statistical method for the accurate classification of individuals into carriers and non-carriers. In this paper, we present a procedure combining variable selection (i.e. the selection of predictive SNPs) and linear discriminant analysis for the identification of carriers of a haplotype on BTA19 (Bos taurus autosome 19) known to be associated with reduced cow fertility. A population of 3645 Brown Swiss cows and bulls genotyped with the 54K SNP-chip was available for the analysis. Results: The overall error rate for the prediction of haplotype carriers was on average very low (~<= 1%). The error rate was found to depend on the number of SNPs in the model and their density around the region of the haplotype on BTA19. The minimum set of SNPs to still achieve accurate predictions was 5, with a total test error rate of 1.59. Conclusions: The paper describes a procedure to accurately identify haplotype carriers from SNP genotypes in cattle populations. Very few misclassifications were observed, which indicates that this is a very reliable approach for potential applications in cattle breeding.
2015
BIOLOGIA E BIOTECNOLOGIA AGRARIA
cattle; classification; error analysis; fertility; genotype; identification key; linear programing; statistical analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/340331
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