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Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and hapl...

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Autores principales: Martínez-Montes, Ángel M., Fernández, Almudena, Muñoz, María, Noguera, Jose Luis, Folch, Josep M., Fernández, Ana I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844516/
https://www.ncbi.nlm.nih.gov/pubmed/29522525
http://dx.doi.org/10.1371/journal.pone.0190184
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author Martínez-Montes, Ángel M.
Fernández, Almudena
Muñoz, María
Noguera, Jose Luis
Folch, Josep M.
Fernández, Ana I.
author_facet Martínez-Montes, Ángel M.
Fernández, Almudena
Muñoz, María
Noguera, Jose Luis
Folch, Josep M.
Fernández, Ana I.
author_sort Martínez-Montes, Ángel M.
collection PubMed
description One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.
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spelling pubmed-58445162018-03-23 Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed Martínez-Montes, Ángel M. Fernández, Almudena Muñoz, María Noguera, Jose Luis Folch, Josep M. Fernández, Ana I. PLoS One Research Article One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed. Public Library of Science 2018-03-09 /pmc/articles/PMC5844516/ /pubmed/29522525 http://dx.doi.org/10.1371/journal.pone.0190184 Text en © 2018 Martínez-Montes et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Martínez-Montes, Ángel M.
Fernández, Almudena
Muñoz, María
Noguera, Jose Luis
Folch, Josep M.
Fernández, Ana I.
Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title_full Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title_fullStr Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title_full_unstemmed Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title_short Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed
title_sort using genome wide association studies to identify common qtl regions in three different genetic backgrounds based on iberian pig breed
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844516/
https://www.ncbi.nlm.nih.gov/pubmed/29522525
http://dx.doi.org/10.1371/journal.pone.0190184
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