Standard statistical tools for the breed allocation problem

Abstract

Modern technologies are frequently used in order to deal with new genomic problems. For instance, the STRUCTURE software is usually employed for breed assignment based on genetic information. However, standard statistical techniques offer a number of valuable tools which can be successfully used for dealing with most problems. In this paper, we investigated the capability of microsatellite markers for individual identification and their potential use for breed assignment of individuals in seventy Lidia breed lines and breeders. Traditional binomial logistic regression is applied to each line and used to assign one individual to a particular line. In addition, the area under receiver operating curve (AUC) criterion is used to measure the capability of the microsatellite-based models to separate the groups. This method allows us to identify which microsatellite loci are related to each line. Overall, only one subject was misclassified or a 99.94% correct allocation. The minimum observed AUC was 0.986 with an average of 0.997. These results suggest that our method is competitive for animal allocation and has some interpretative advantages and a strong relationship with methods based on SNPs and related techniques.

Keywords:

• breed allocation
• microsatellite loci
• logistic regression
• ROC curves

Acknowledgements

This work was supported by the Grant MTM2011-23204 of the Spanish Ministry of Science and Innovation (FEDER support included).

Samples were provided by UCTL (Union de Criadores de Toros de Lidia) within the frame of a research project founded by the INIA and the European Regional Development Fund no: RZ2008-00005-C02-02. This study also received financial support of INIA, RTA2011-00060-C02-O2.