12 research outputs found
Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism
<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <it>cis</it>-drivers of gene expression programs in skeletal muscle as <it>COQ4 </it>(SSC1), <it>LOC100513192 </it>(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 <it>cis</it>-causing genetic polymorphims affecting gene expression levels, with (e.g. <it>COQ4</it>) or without (e.g. <it>LOC100513192</it>) potential pleiotropic effects that affect the expression of other genes (cluster of <it>trans</it>-eQTLs).</p> <p>Conclusion</p> <p>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.</p
Pyroséquençage pour le développement d'EST et de SNP aviaires
Le but du programme est de combler les dĂ©ficits en marqueurs observĂ©s pour trois espĂšces aviaires : la caille, le canard et la poule. La stratĂ©gie choisie est l'obtention, Ă partir de plusieurs individus de lignĂ©es d'intĂ©rĂȘt, de SNP (Single Nucleotide Polymorphism, polymorphisme d'un nuclĂ©otide) par une nouvelle technologie de sĂ©quençage Ă haut dĂ©bit (sĂ©quenceur 454 GS-FLX, Roche). Nous sĂ©quençons des reprĂ©sentations rĂ©duites du gĂ©nome, en sĂ©lectionnant d'une part des fragments de restriction d'ADN gĂ©nomique - les mĂȘmes chez tous les individus - et d'autre part les transcrits qui reprĂ©sentent globalement la partie du gĂ©nome correspondant aux gĂšnes exprimĂ©s. Ces expĂ©rimentations sont rĂ©alisĂ©es Ă partir d'Ă©chantillons d'ADN ou d'ARN issus d'individus de lignĂ©es Ă l'origine de croisements existants, pour chacune des trois espĂšces. Les donnĂ©es gĂ©nĂ©rĂ©es par plusieurs "runs" de sĂ©quence seront traitĂ©es in silico : contigage Ă haut dĂ©bit, recherche de SNP, comparaison avec les banques de sĂ©quences connues...En plus de l'intĂ©rĂȘt que reprĂ©sente la production d'un trĂšs grand nombre de SNP nouveaux, cette technologie devrait permettre de mieux sĂ©quencer les rĂ©gions riches en (G+C) correspondant aux plus petits des microchromosomes pour lesquels il n'y a pas de sĂ©quence chez la poule. La comparaison des sĂ©quences des transcrits obtenues chez la caille et le canard avec la sĂ©quence du gĂ©nome de la poule permettra d'Ă©tablir une "cartographie virtuelle" des SNP obtenus, grĂące Ă la grande conservation de syntĂ©nie existant entre ces trois espĂšces
Design and Characterization of a 52K SNP Chip for Goats
The success of Genome Wide Association Studies in the discovery of sequence variation linked to complex traits in humans has increased interest in high throughput SNP genotyping assays in livestock species. Primary goals are QTL detection and genomic selection. The purpose here was design of a 50-60,000 SNP chip for goats. The success of a moderate density SNP assay depends on reliable bioinformatic SNP detection procedures, the technological success rate of the SNP design, even spacing of SNPs on the genome and selection of Minor Allele Frequencies (MAF) suitable to use in diverse breeds. Through the federation of three SNP discovery projects consolidated as the International Goat Genome Consortium, we have identified approximately twelve million high quality SNP variants in the goat genome stored in a database together with their biological and technical characteristics. These SNPs were identified within and between six breeds (meat, milk and mixed): Alpine, Boer, Creole, Katjang, Saanen and Savanna, comprising a total of 97 animals. Whole genome and Reduced Representation Library sequences were aligned on >10 kb scaffolds of the de novo goat genome assembly. The 60,000 selected SNPs, evenly spaced on the goat genome, were submitted for oligo manufacturing (Illumina, Inc) and published in dbSNP along with flanking sequences and map position on goat assemblies (i.e. scaffolds and pseudo-chromosomes), sheep genome V2 and cattle UMD3.1 assembly. Ten breeds were then used to validate the SNP content and 52,295 loci could be successfully genotyped and used to generate a final cluster file. The combined strategy of using mainly whole genome Next Generation Sequencing and mapping on a contig genome assembly, complemented with Illumina design tools proved to be efficient in producing this GoatSNP50 chip. Advances in use of molecular markers are expected to accelerate goat genomic studies in coming years
SNPs by category in final design.
<p>The number of selected SNPs is indicated for each of the following categories. 1: SNP detected in an EST. 2: two alleles detected in the five considered breeds. 3: two alleles detected in Alpine and Saanen and Creole and (Boer or Savanna). 4: two alleles detected in two of the three milk and mixed breeds (Alpine, Saanen, Creole) and in Boer and Savanna. 5: two alleles detected in Alpine and Saanen and Creole. 6: two alleles detected in three out of the five breeds. 10: two alleles detected in each of the two milk breeds (Saanen and Alpine). 11: two alleles detected in one milk breed (Saanen or Alpine) and one meat breed (Creole or Boer or Katjang/Savanna). 12: two alleles detected in at least two meat breeds (Creole and Boer or Katjang/Savanna). 13: two alleles detected in one milk breed (Saanen or Alpine).</p
Average call rate and >5%MAF SNPs for the cluster file breeds.
<p>For each breed used for the chip validation and cluster file definition, the number of samples, the number of >5%MAF SNPs and the average call rate are indicated.</p
SNP identified in the five breeds or breed pool and in ESTs.
<p>The number on the diagonal is the number of SNPs found in a breed (Alpine, Boer, Creole, Saanen), breed pool (Katjang/Savanna) or in ESTs. Off diagonals are the number of SNPs shared between the two respective breeds.</p
Goat Genome scaffolds assembly.
<p>The goat genome scaffolds were sorted by decreasing size (x-axis) and the cumulative proportion of the assembled genome was plotted on the y-axis for all the scaffolds. The vertical line shows that >10kb scaffolds represent 97.2% of the assembled goat genome.</p
SNP spacing on the goat scaffolds.
<p>Spacing between the selected SNPs was calculated and the percentage of gaps (total number of gaps is 59,030 on goat scaffolds and 62,693 on UMD3.1 cattle assembly) is shown (y-axis) in each 5kb class ranging from 5 to 150kb (x-axis).</p