Literature DB >> 22444650

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain-Large White backcross.

H Gilbert1, J Riquet, J Gruand, Y Billon, K Fève, P Sellier, J Noblet, J P Bidanel.   

Abstract

Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Piétrain (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW × PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P < 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P < 0.01 at the CW level) were mapped to chromosomes SSC6 - probably due to the halothane alleles - and SSC7, respectively. Three putative QTL for feed intake traits were detected (P < 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P < 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.

Entities:  

Year:  2010        PMID: 22444650     DOI: 10.1017/S1751731110000339

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  9 in total

1.  Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars.

Authors:  Jeremy T Howard; Shihui Jiao; Francesco Tiezzi; Yijian Huang; Kent A Gray; Christian Maltecca
Journal:  BMC Genet       Date:  2015-05-30       Impact factor: 2.797

2.  Novel insight into the genomic architecture of feed and nitrogen efficiency measured by residual energy intake and nitrogen excretion in growing pigs.

Authors:  Mahmoud Shirali; Carol-Anne Duthie; Andrea Doeschl-Wilson; Pieter W Knap; Egbert Kanis; Johan A M van Arendonk; Rainer Roehe
Journal:  BMC Genet       Date:  2013-12-20       Impact factor: 2.797

3.  Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake.

Authors:  Duy N Do; Anders B Strathe; Tage Ostersen; Sameer D Pant; Haja N Kadarmideen
Journal:  Front Genet       Date:  2014-09-09       Impact factor: 4.599

4.  Exploring the genetics of feed efficiency and feeding behaviour traits in a pig line highly selected for performance characteristics.

Authors:  Henry Reyer; Mahmoud Shirali; Siriluck Ponsuksili; Eduard Murani; Patrick F Varley; Just Jensen; Klaus Wimmers
Journal:  Mol Genet Genomics       Date:  2017-05-12       Impact factor: 3.291

5.  Quantitative trait loci mapping for feed conversion efficiency in crucian carp (Carassius auratus).

Authors:  Meixia Pang; Beide Fu; Xiaomu Yu; Haiyang Liu; Xinhua Wang; Zhan Yin; Shouqi Xie; Jingou Tong
Journal:  Sci Rep       Date:  2017-12-05       Impact factor: 4.379

6.  Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs.

Authors:  Xiao Wang; Haja N Kadarmideen
Journal:  Metabolites       Date:  2020-05-15

7.  Statistical method for mapping QTLs for complex traits based on two backcross populations.

Authors:  Zhu Zhihong; Hayart Yousaf; Yang Jian; Cao Liyong; Lou Xiangyang; Xu Haiming
Journal:  Chin Sci Bull       Date:  2012-07

8.  Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs.

Authors:  Duy Ngoc Do; Tage Ostersen; Anders Bjerring Strathe; Thomas Mark; Just Jensen; Haja N Kadarmideen
Journal:  BMC Genet       Date:  2014-02-17       Impact factor: 2.797

9.  Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin.

Authors:  Claudia A Sevillano; Jan Ten Napel; Simone E F Guimarães; Fabyano F Silva; Mario P L Calus
Journal:  BMC Genomics       Date:  2018-10-11       Impact factor: 3.969

  9 in total

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