Genome-wide interval mapping using SNPs identifies new QTL for growth, body composition and several physiological variables in an F-2 intercross between fat and lean chicken lines

Autor: Larry A. Cogburn, Michel J. Duclos, Jean Simon, Olivier Demeure, Sandrine Lagarrigue, Elisabeth Le Bihan-Duval, Nicola Bacciu, Frédérique Pitel, Pascale Le Roy, Guillaume Le Mignon, Olivier Filangi, Anne Boland
Přispěvatelé: Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité de Recherches Avicoles (URA), Institut National de la Recherche Agronomique (INRA), Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, IG, Centre National de Génotypage, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Department of Animal and Food Sciences, University of Delaware [Newark], USDA-IFAFS Animal Genome Program [00-52100-9614], Analyse du Genome des Animaux d'Elevage (AGENAE) program, INRA (France), European Animal Disease Genomics Network of Excellence for Animal Health and Food Safety (EADGENE) program, AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Recherches Avicoles (SRA), Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Genetics Selection Evolution
Genetics Selection Evolution, BioMed Central, 2013, 45, online (september), Non paginé. ⟨10.1186/1297-9686-45-36⟩
Genetics, Selection, Evolution : GSE
Genetics Selection Evolution september (45, online), Non paginé. (2013)
Genetics Selection Evolution, 2013, 45, online (september), Non paginé. ⟨10.1186/1297-9686-45-36⟩
ISSN: 0999-193X
1297-9686
DOI: 10.1186/1297-9686-45-36⟩
Popis: Chantier qualité GA; Background: For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F2 intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome.[br/] Results: Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.[br/] Conclusions: The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.
Databáze: OpenAIRE
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