Literature DB >> 18366476

A muscle transcriptome analysis identifies positional candidate genes for a complex trait in pig.

V Lobjois1, L Liaubet, M SanCristobal, J Glénisson, K Fève, J Rallières, P Le Roy, D Milan, P Cherel, F Hatey.   

Abstract

Muscle tenderness is an important complex trait for meat quality and thus for genetic improvement through animal breeding. However, the physiological or genetic control of tenderness development in muscle is still poorly understood. In this work, using transcriptome analysis, we found a relationship between gene expression variability and tenderness. Muscle (longissimus dorsi) samples from 30 F(2) pigs were characterized by Warner-Bratzler Shear Force (WBSF) on cooked meat as a measurement of muscle tenderness. Gene expression levels were measured using microarrays for 17 muscle samples selected to represent a range of WBSF values. Using a linear regression model, we determined that samples with WBSF values above 30 N could be effectively analysed for genes exhibiting a significant association of their expression level on shear force (false discovery rate <0.05). These genes were shown to be involved in three functional networks: cell cycle, energy metabolism and muscle development. Twenty-two genes were mapped on the pig genome and 12 were found to be located in regions previously reported to contain quantitative trait loci (QTL) affecting pig meat tenderness (chromosomes 2, 6 and 13). Some genes appear therefore as positional candidate genes for QTL.

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Year:  2008        PMID: 18366476     DOI: 10.1111/j.1365-2052.2007.01695.x

Source DB:  PubMed          Journal:  Anim Genet        ISSN: 0268-9146            Impact factor:   3.169


  18 in total

1.  A genetical genomics approach reveals new candidates and confirms known candidate genes for drip loss in a porcine resource population.

Authors:  Hanna Heidt; Mehmet Ulas Cinar; Muhammad Jasim Uddin; Christian Looft; Heinz Jüngst; Dawit Tesfaye; Astrid Becker; Andreas Zimmer; Siriluck Ponsuksili; Klaus Wimmers; Ernst Tholen; Karl Schellander; Christine Große-Brinkhaus
Journal:  Mamm Genome       Date:  2013-09-12       Impact factor: 2.957

2.  Additive effects of 19 porcine SNPs on growth rate, meat content and selection index.

Authors:  S Kaminski; H Help; T Suchocki; J Szyda
Journal:  J Appl Genet       Date:  2009       Impact factor: 3.240

3.  Transcriptome analysis reveals that constant heat stress modifies the metabolism and structure of the porcine longissimus dorsi skeletal muscle.

Authors:  Yue Hao; Yuejin Feng; Peige Yang; Yanjun Cui; Jiru Liu; Chunhe Yang; Xianhong Gu
Journal:  Mol Genet Genomics       Date:  2016-08-25       Impact factor: 3.291

4.  Molecular characterization and expression analysis of NDUFS4 gene in m. longissimus dorsi of Laiwu pig (Sus scrofa).

Authors:  Qimei Chen; Yongqing Zeng; Hui Wang; Lun Yang; Yun Yang; Honglei Zhu; Yuan Shi; Wei Chen; Yanxia Hu
Journal:  Mol Biol Rep       Date:  2012-10-18       Impact factor: 2.316

5.  Identification of differentially expressed genes in chickens differing in muscle glycogen content and meat quality.

Authors:  Vonick Sibut; Christelle Hennequet-Antier; Elisabeth Le Bihan-Duval; Sylvain Marthey; Michel J Duclos; Cécile Berri
Journal:  BMC Genomics       Date:  2011-02-16       Impact factor: 3.969

6.  Gene expression profiling of skeletal muscle of nursing piglets.

Authors:  Caode Jiang; Ping Shi; Shun Li; Ranran Dong; Jiawei Tian; Jin Wei; Shuang Luo
Journal:  Int J Biol Sci       Date:  2010-10-11       Impact factor: 6.580

7.  Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism.

Authors:  Laurence Liaubet; Valérie Lobjois; Thomas Faraut; Aurélie Tircazes; Francis Benne; Nathalie Iannuccelli; José Pires; Jérome Glénisson; Annie Robic; Pascale Le Roy; Magali Sancristobal; Pierre Cherel
Journal:  BMC Genomics       Date:  2011-11-04       Impact factor: 3.969

8.  Identification of the novel candidate genes and variants in boar liver tissues with divergent skatole levels using RNA deep sequencing.

Authors:  Asep Gunawan; Sudeep Sahadevan; Mehmet Ulas Cinar; Christiane Neuhoff; Christine Große-Brinkhaus; Luc Frieden; Dawit Tesfaye; Ernst Tholen; Christian Looft; Dessie Salilew Wondim; Michael Hölker; Karl Schellander; Muhammad Jasim Uddin
Journal:  PLoS One       Date:  2013-08-26       Impact factor: 3.240

9.  Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

Authors:  Vincent Jouffe; Suzanne Rowe; Laurence Liaubet; Bart Buitenhuis; Henrik Hornshøj; Magali SanCristobal; Pierre Mormède; D J de Koning
Journal:  BMC Proc       Date:  2009-07-16

10.  The structure of a gene co-expression network reveals biological functions underlying eQTLs.

Authors:  Nathalie Villa-Vialaneix; Laurence Liaubet; Thibault Laurent; Pierre Cherel; Adrien Gamot; Magali SanCristobal
Journal:  PLoS One       Date:  2013-04-05       Impact factor: 3.240

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