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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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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. |
format | Online Article Text |
id | pubmed-5696410 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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