3 years ago

Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups

Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
Jose Braccini, Jaime Araujo Cobuci, Samuel Rezende Paiva, Concepta Margaret McManus, Stéphane Joost, Robson Jose Cesconeto
Samples of 191 animals from 18 different Brazilian locally adapted swine genetic groups were genotyped using Illumina Porcine SNP60 BeadChip in order to identify selection signatures related to the monthly variation of Brazilian environmental variables. Using BayeScan software, 71 SNP markers were identified as FST outliers and 60 genotypes (58 markers) were found by Samβada software in 371 logistic models correlated with 112 environmental variables. Five markers were identified in both methods, with a Kappa value of 0.073 (95% CI: 0.011–0.134). The frequency of these markers indicated a clear north–south country division that reflects Brazilian environmental differences in temperature, solar radiation, and precipitation. Global spatial territory correlation for environmental variables corroborates this finding (average Moran's I = 0.89, range from 0.55 to 0.97). The distribution of alleles over the territory was not strongly correlated with the breed/genetic groups. These results are congruent with previous mtDNA studies and should be used to direct germplasm collection for the National gene bank. Understanding the adaptation process of livestock, as a swine, is important to make decisions in conservation genetics. Using two different approaches to detect signatures of natural selection, we explore the influence of different environment in the fixation of alleles in Brazilian locally adapted swine genetic groups. We used Porcine SNP60 BeadChip in order to identify selection signatures related to the Brazilian environmental variables. The distribution of SNP alleles over the Brazilian territory demonstrates a clear north–south orientation. Photo credit: José Diomedes Barbosa Neto

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/ece3.3323

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