Genome structure in Sicilian cattle breeds

Risultato della ricerca: Otherpeer review


Genomic technologies provide background information concerning genome structure in domestic animals. The aim of this work was to investigate the genetic structure and the patterns of linkage disequilibrium (LD) in two Sicilian local cattle breeds, Cinisara and Modicana. Genotypes from animals of Italian Holstein breed were also used to investigate the relationship among breeds. Structure software was used to analyze the genetic structure and assign the individuals to each cluster. The genetic relationship between individuals was estimated by Principal Components Analysis (PCA) of genetic distance. A standard descriptive LD parameter (r2) was obtained between adjacent SNPs and for all pairwise combinations of SNPs on each chromosome. PCA and Bayesian clustering algorithm showed that animals from the three breeds formed non-overlapping clusters and are clearly separated populations. Between the Sicilian cattle breeds, the Modicana was the most differentiated breed, whereas the Cinisara animals showed a lowest value of assignment, the presence of substructure and genetic links occurred between both breeds. Considering the levels of LD between adjacent markers, the average r2 in Modicana (0.200±0.247) was comparable to those reported for others cattle breeds, whereas Cinisara showed a low value (0.162±0.222). The results may be explained considering the influence of selection on LD; in fact the Cinisara breed is not subject to breeding programs whereas the Modicana breed is characterized by low selection pressure. Average r2 ranging from 0.192 and 0.234 for SNPs located up to 50 kb apart to 0.021 and 0.027 for SNPs separated more than 5000 kb, respectively for Cinisara and Modicana breeds. The information generated from this study has important implications for the design and applications of selection breeding programs in these two local cattle breeds
Lingua originaleEnglish
Numero di pagine0
Stato di pubblicazionePublished - 2014


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