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| Framework for Studies of Population Variation in Gene Activity |
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| SciMed - Genetics & Genome | |||
| TS-Si News Service | |||
| Sunday, 14 March 2010 16:00 | |||
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Geneva, Switzerland. A report in the journal Nature provides a framework for understanding of the impact of genetic variations in cellular interactions. This approach has important implications for the understanding of human disorders and wide implications for human health. It is well known that Our DNA contains the information needed to produce the different proteins that are the building blocks and key components of cells. DNA sequences, defined as genes, carry the instructions to synthesize such proteins. This genetic material, however, never leaves the stronghold nucleus of the cell. Instead, copies called RNA messengers are made and sent out to the tiny cell’s protein factories located outside of the nucleus. Mutations in genes lead to a variation in the abundance or structure of these RNA messengers. This in turn is associated with changes in the protein content of cells, thereby influencing the way certain cellular processes are executed. Such DNA variations thus may contribute to differences in characteristics between individuals and may also cause or predispose to various diseases. To elucidate the genetic nature of this Previous studies provided information about rough individual differences in the quantity of RNA from each gene in the cell. This was sufficient for identification, but could not define the exact molecular consequences. In this new research project, conducted using blood cells of 60 individuals of European descent, the scientists have obtained a much higher resolution of such processes. This allow a more detailed description of the molecular differences in RNA among individuals. “For the first time we are able to “read” the sequence of almost all the RNA molecules in the cell and compare them among individuals” says Dr. Stephen Montgomery from the University of Geneva (UNIGE). The ability to read the RNA sequence in so many individuals is of unprecedented scale and brings the understanding of genetic variation to a new level. “The Professor Emmanouil Dermitzakis from the FundingThe Ministry of Science and Innovation, the Ingenio Consolider 2010 Programme, the Wellcome Trust, the Louis-Jeantet Foundation and Swiss NSF Frontiers in Genetics have funded the project.
CitationTranscriptome genetics using second generation sequencing in a Caucasian population. Stephen B. Montgomery, Micha Sammeth, Maria Gutierrez-Arcelus, Radoslaw P. Lach, Catherine Ingle, James Nisbett, Roderic Guigó and Emmanouil T. Dermitzakis. Nature 2010; ePub ahead of print. doi:10.1038/nature08903
Abstract Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.Quote this article on your site To create link towards this article on your website, copy and paste the text below in your page. Preview : ![]()
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| Last Updated on Saturday, 13 March 2010 10:57 |




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