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 DNA variants affecting gene activity may be responsible for disease susceptibility, primarily to common pathologies such as diabetes, cardiovascular diseases and asthma. Understanding of how such subtle differences modulate gene expression is bound to accelerate the understanding of all cellular mechanisms, enabling faster and more focused development of treatments.

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.

To elucidate the genetic nature of this variability, an international collaboration of researchers have used novel technology to study RNA messengers. This cutting edge procedure, called second generation sequencing, allows an unprecedented level of resolution to determine the abundance and structure of RNA messengers.

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 genome sequencing provided us with information to understand basic processes within the cell but the new mRNA study allows us to reach a new level on the understanding of variability between individuals” says Roderic Guigó, coordinator of the Bioinformatics and Genomics Programme at the CRG.

Professor Emmanouil Dermitzakis from the Genetics Department of the Faculty of medicine of the UNIGE and the Frontiers in Genetics program states “Obviously, such an increase in resolution provides us with a major advance in understanding of cellular processes and the fine detail of differences between humans”.

Citation Transcriptome 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.

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