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

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 i...

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Autores principales: Cesconeto, Robson Jose, Joost, Stéphane, McManus, Concepta Margaret, Paiva, Samuel Rezende, Cobuci, Jaime Araujo, Braccini, Jose
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696410/
https://www.ncbi.nlm.nih.gov/pubmed/29187988
http://dx.doi.org/10.1002/ece3.3323
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author Cesconeto, Robson Jose
Joost, Stéphane
McManus, Concepta Margaret
Paiva, Samuel Rezende
Cobuci, Jaime Araujo
Braccini, Jose
author_facet Cesconeto, Robson Jose
Joost, Stéphane
McManus, Concepta Margaret
Paiva, Samuel Rezende
Cobuci, Jaime Araujo
Braccini, Jose
author_sort Cesconeto, Robson Jose
collection PubMed
description 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 F(ST) 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.
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spelling pubmed-56964102017-11-29 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 Ecol Evol Original Research 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 F(ST) 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. John Wiley and Sons Inc. 2017-10-12 /pmc/articles/PMC5696410/ /pubmed/29187988 http://dx.doi.org/10.1002/ece3.3323 Text en © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Cesconeto, Robson Jose
Joost, Stéphane
McManus, Concepta Margaret
Paiva, Samuel Rezende
Cobuci, Jaime Araujo
Braccini, Jose
Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title_full Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title_fullStr Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title_full_unstemmed Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title_short Landscape genomic approach to detect selection signatures in locally adapted Brazilian swine genetic groups
title_sort landscape genomic approach to detect selection signatures in locally adapted brazilian swine genetic groups
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5696410/
https://www.ncbi.nlm.nih.gov/pubmed/29187988
http://dx.doi.org/10.1002/ece3.3323
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