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On the way to functional agro biodiversity: coat colour gene variability in goats
L Nicoloso1, R Negrini, P Ajmone-Marsan
1Sezione di Zootecnica Agraria, Dipartimento di Scienze Animali, Università degli Studi, Milano, Italy. letizia.nicoloso@unimi.it
Abstract:
Functional agro biodiversity defines the exploitation of biodiversity to provide ecosystem services, support sustainable agricultural production and benefit the regional and global environment and the public at large (ELN-FAB, 2009; www.eln_fab.eu). Tracking of animal products back to the breed of origin based on their genetic make-up undoubtedly falls in this category. The aim of this paper was to identify and validate a set of single nucleotide polymorphisms (SNPs) in goat coat colour genes, most of which have not been investigated before, to trace five goat populations of the Italian Alps and their product. Several regions of 28 genes influencing coat colour pathways were amplified in eight animals (two per breed). Sequence comparison revealed 48 SNPs and three INDEL (INsertion DELetion). No breed-specific alleles were detected; however, several SNPs showed an uneven frequency distribution between breeds. In BIO, the genotype frequency distribution of a non-synonymous SNP suggested a possible role of TYRP1 in brown eumelanic goat coat colour. A total of 29 independent SNPs in 20 genes were selected and used to allocate 159 minimally related goat samples using STRUCTURE 2.2 and GeneClass 2 software. STRUCTURE 2.2 assigns 99% of individuals to the correct breed considering the prior information on putative breed of origin for each sample and 81% using only the genotypic data. The three algorithms available in GeneClass 2 performed with nearly equal efficiency, with 86% and 87% correct allocations. All the methods yielded an average probability of assignment >0.92 and a specificity index >0.86. Despite their coat colour variability, individuals belonging to ORO were fully assigned, showing that, in the absence of a breed-specific allele tied to coat colour, the best assignment resulted for the most genetically distinct breed. The lowest rate of correct assignment was observed in Verzaschese (73%), not ascertained in the breed panel used in the SNP discovery phase.
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