Project 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 Âµg 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 68Â°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 Âµm 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.

Project description:Analyses of QTLs for expression levels (eQTLs) of the genes reveal genetic relationship between expression variation and the regulator, thus unlocking the information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. Totally 1,632 single feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1,459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hotspots among rice genome, each of which controls transcript variations of many e-traits. Gene Ontology analysis revealed enrichment of certain functional categories of genes in some of the eQTL hotspots. In particular, eQTLs for e-traits involving DNA metabolic process was significantly enriched in several eQTL hotspots on chromosomes 3, 5 and 10. Several transcription factors colocalizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between the QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided the clues for identification and characterization of regulatory network in the whole genome at the transcriptional level. To dissect the genetic variation between the two rice indica varieties Minghui 63 and Zhenshan 97, a total of 110 RILs from Minghui 63 and Zhenshan 97 and parents were sampled. And the Affymetrix Genechip rice Genome Array was used to investigate their dynamic transcript levels. Two independent biological replicates were sampled from each RIL, and three replicates for each parent.resulting in a dataset of 226 microarrays.

Project description:In the last 20 years, there has been significant research towards defining the genetic basis of lipid metabolism and meat quality related traits in pigs. Nowadays, the study of the transcriptome and its regulatory mechanisms allows going far beyond in the genetic dissection of these complex traits. In present study, a genome-wide eQTL scan aiming to detect pig genome regions regulating levels of skeletal muscle mRNA expression has been performed. This study has been conducted on a commercial Duroc population where a number of QTL for muscle fat deposition and fatty acid composition had been detected. GeneChip Porcine Genome® arrays (Affymetrix) were used to determine the gene expression levels of gluteus medius samples from 105 Duroc pigs belonging to two groups with divergent phenotypes for fatness traits. This experimental design aimed to favour detection of eQTL affecting genes related to lipid metabolism and meat quality traits. The whole genome scan with a panel of 110 microsatellites allowed us detecting 613 genome-wide significant eQTL unequally distributed across the pig genome, SSC5 and SSC3 harbouring the highest number of eQTL. Moreover, 11 genome regions with eQTL affecting the expression levels of a high number of genes (eQTL hot spots) have been described. After mapping target probes and discarding low quality probes, a total of 59 cis- and 396 trans-acting eQTL were retained for further analyses. The functional classification showed that lipid-related GO terms were not the most enriched by the list of eQTL-regulated genes. However, a number of regulated genes functionally related to lipid metabolism and fat deposition traits were identified, and their functional relationship with these phenotypes were further investigated. With this purpose, eQTL results were integrated with 1) QTL linkage maps and 2) correlation data between phenotypes and gene expression levels. As a result, a comprehensive list of 29 positional and functional candidate genes was elaborated. These results represent a valuable contribution to the comprehension of genetic regulation of skeletal muscle individual gene expression in swine species, and a first step towards disentangling gene networks and molecular mechanisms involved in lipid metabolism and meat quality traits. 105 gluteus medius samples from 105 animals belonging to two groups of 53 and 52 animals each: HIGH group had higher carcass, plasma and muscle fat content; LOW group had lower carcass, plasma and muscle fat content

Project description:In the last 20 years, there has been significant research towards defining the genetic basis of lipid metabolism and meat quality related traits in pigs. Nowadays, the study of the transcriptome and its regulatory mechanisms allows going far beyond in the genetic dissection of these complex traits. In present study, a genome-wide eQTL scan aiming to detect pig genome regions regulating levels of skeletal muscle mRNA expression has been performed. This study has been conducted on a commercial Duroc population where a number of QTL for muscle fat deposition and fatty acid composition had been detected. GeneChip Porcine Genome® arrays (Affymetrix) were used to determine the gene expression levels of gluteus medius samples from 105 Duroc pigs belonging to two groups with divergent phenotypes for fatness traits. This experimental design aimed to favour detection of eQTL affecting genes related to lipid metabolism and meat quality traits. The whole genome scan with a panel of 110 microsatellites allowed us detecting 613 genome-wide significant eQTL unequally distributed across the pig genome, SSC5 and SSC3 harbouring the highest number of eQTL. Moreover, 11 genome regions with eQTL affecting the expression levels of a high number of genes (eQTL hot spots) have been described. After mapping target probes and discarding low quality probes, a total of 59 cis- and 396 trans-acting eQTL were retained for further analyses. The functional classification showed that lipid-related GO terms were not the most enriched by the list of eQTL-regulated genes. However, a number of regulated genes functionally related to lipid metabolism and fat deposition traits were identified, and their functional relationship with these phenotypes were further investigated. With this purpose, eQTL results were integrated with 1) QTL linkage maps and 2) correlation data between phenotypes and gene expression levels. As a result, a comprehensive list of 29 positional and functional candidate genes was elaborated. These results represent a valuable contribution to the comprehension of genetic regulation of skeletal muscle individual gene expression in swine species, and a first step towards disentangling gene networks and molecular mechanisms involved in lipid metabolism and meat quality traits.

Dataset Information

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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