Patterns of genetic diversity of local pig populations in the State of Pernambuco, Brazil

• Autor(a) principal: Silva,Elizabete Cristina da
• Data de Publicação: 2011
• Outros Autores: Dutra Junior,Wilson Moreira, Ianella,Patrícia, Gomes Filho,Manoel Adrião, Oliveira,Cláudio José Parro de, Ferreira,Débora Nathália de Moura, Caetano,Alexandre Rodrigues, Paiva,Samuel Rezende
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Zootecnia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982011000800010
• topic: animal genetics resources; genetic variability; microsatellites loci; Sus Scrofa

This study estimated the genetic diversity and structure of 12 genetic groups (GG) of locally adapted and specialized pigs in the state of Pernambuco using 22 microsatellite markers. Nine locally adapted breeds (Baé, Caruncho, Canastra, Canastrão, Mamelado, Moura, Nilo, Piau and UDB (Undefined Breed)) and 3 specialized breeds (Duroc, Landrace and Large White), totaling 190 animals, were analyzed. The Analysis of Molecular Variance (AMOVA) showed that 3.2% of the total variation was due to differences between genetic groups, and 3.6% to differences between local and commercial pigs. One hundred and ninety eight alleles were identified and apart from the Large White breed, all GG presented Hardy-Weinberg Equilibrium deviations for some loci. The total and effective allele means were lower for Duroc (3.65 and 3.01) and higher for UDB (8.89 and 4.53) and Canastra (8.61 and 4.58). Using Nei's standard genetic distance and the UPGMA method, it was possible to observe that the Landrace breed was grouped with the local genetic groups Canastra, Moura, Canastrão, Baé and Caruncho. Due to the complex admixture pattern, the genetic variability of the 12 genetic groups can be analyzed by distributing the individuals into two populations as demonstrated by a Bayesian analysis, corroborating the results from AMOVA, which revealed a low level of genetic differentiation between the inferred populations.