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Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups.
Cesconeto, Robson Jose; Joost, Stéphane; McManus, Concepta Margaret; Paiva, Samuel Rezende; Cobuci, Jaime Araujo; Braccini, Jose.
Afiliação
  • Cesconeto RJ; Universidade Federal do Rio Grande do Sul Porto Alegre Rio Grande do Sul Brazil.
  • Joost S; Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland.
  • McManus CM; Universidade de Brasília (UnB) Brasilia DF Brazil.
  • Paiva SR; EMBRAPA Brasilia Brazil.
  • Cobuci JA; Universidade Federal do Rio Grande do Sul Porto Alegre Rio Grande do Sul Brazil.
  • Braccini J; Universidade Federal do Rio Grande do Sul Porto Alegre Rio Grande do Sul Brazil.
Ecol Evol ; 7(22): 9544-9556, 2017 11.
Article em En | MEDLINE | ID: mdl-29187988
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 Samßada 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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article