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Title: Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism.      
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available
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instance of dataset
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not applicable
refinement:
curated
dateReleased:
06-26-2012
ID:
E-GEOD-26924
description:
BACKGROUND: The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. RESULTS: QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). CONCLUSION: Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential. A wide genomic project was designed to combine genetic and transcriptome analysis. This project involved about 1,000 F2 pigs from 15 half-sib families to identify QTL for meat quality traits (Cherel et al., unpublished data). In this study, we focused on one family of 57 half sib F2 pigs. Total RNA was isolated from each of the 57 muscle samples using a commercial kit, and controlled for quality and concentration using an AGILENT 2100 bioanalyzer. cDNA was synthesized and labelled from 5 µg total RNA by simultaneous reverse transcription of mRNA using SuperScriptTM II RNase H- Reverse Transcriptase and 33P-deoxy-CTP. Each muscle sample mRNA was hybridized at 68°C during 24 h to one array. The arrays were then exposed to radioisotopic-sensitive imaging plates that were scanned thereafter with a phosphor imaging system at a 25 µm resolution. Hybridization images were quantified using a semi-automated software through a grid process with a fixed spot diameter. The output was then subjected to the data analysis process.
keywords:
transcription profiling by array
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storedIn:
Array Express
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accessURL: https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-26924
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OmicsDI
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accessType:
download
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accessURL: www.omicsdi.org/ws/dataset/arrayexpress-repository/E-GEOD-26924.json
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OmicsDI
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accessType:
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accessURL: http://www.omicsdi.org/ws/dataset/arrayexpress-repository/E-GEOD-26924.xml
ID:
SCR:014747
name:
Omics Discovery Index
abbreviation:
OmicsDI
homePage: http://www.omicsdi.org/