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

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.

Selection of discriminant SNP markers for breed and geographic assignment of Italian sheep

“…In OAR1 the number of selected SNPs was 418 whereas only 102 markers were used in OAR6. Dimauro et al (2013) reported a similar pattern in discriminating three bovine breeds. Unlike in Fig.…”

Combined use of principal component analysis and random forests identify population‐informative single nucleotide polymorphisms: application in cattle breeds

“…Application of RFs in a similar decision tree structure could help to solve the question related to the different levels of diversities among the investigated cattle breeds. Dimauro et al (2013) reported another approach in which they exploited canonical discriminant analysis (CDA) for the identification of informative SNPs to discriminate three breeds (Holstein, Brown and Simmental) that were included also in our study. In particular, they suggested to filter SNPs using arbitrary thresholds on the absolute values of the canonical coefficients (CC).…”

“…Again, it is not clear if LD among markers affected the CDA approach or not. It is interesting to note that Dimauro et al (2013) identified the largest number of discriminating SNP located on BTA6 (18 of 48 SNPs). BTA6 contained the largest number of selected SNPs also in our study.…”

Identification of Ancestry Informative Marker (AIM) Panels to Assess Hybridisation between Feral and Domestic Sheep

“…Small sets, or panels, of ancestry informative markers (AIMs) have been developed and used to infer population genetic parameters in several species. AIM panels have been used to estimate biogeographical ancestry and structure in human populations [19][20][21][22], to discriminate among breeds and geographical origin of Italian sheep breeds [23], to identify cattle breeds [24][25][26], to trace the origin of animal products [27,28], and for breed assignment and analysis of individual ancestry in cattle [29][30][31][32] and pig populations [33]. Moreover, AIM panels have been developed to identify hybrids in wildlife conservation projects on wolf [34], wild cat [9], and mule deer [35].…”