Saturday, February 27, 2010

Scientists at the University of Essex have a greater understanding of how our genes are controlled following a major research project.

ScienceDaily (Feb. 26, 2010) — Scientists at the University of Essex have a greater understanding of how our genes are controlled following a major research project.


The findings of the study, which looked at how proteins work as teams to control genes in the cells, could also help to unravel the mechanisms of disease such as cancer.

The five-year research, funded by the Medical Research Council, has been published in Molecular and Cellular Biology.

The research team, led by Dr Elena Klenova from the Department of Biological Sciences, looked at the protein called CTCF, which was previously identified as a key 'controller' of many of our genes, making them either active or inactive.

However, the scientists at Essex have discovered that other proteins were working with CTCF for fine tuning of the genes. This collaboration between CTCF and its neighbours at the molecular level provides the mechanism by which CTCF's function as a gene regulator is controlled.

Dr Dawn Farrar, the principal researcher on the project, said the discovery of the link between CTCF and other proteins was a 'fascinating example of molecular teamwork'.

Dr Klenova, said: 'Understanding the factors responsible for the regulation of our genes, and how, why and when particular genes are switched on and off may give us a greater understanding of general biological systems. It also helps us to unravel the mechanisms of disease such as cancer. We believe that our published study has contributed to present knowledge of gene regulation.'

It is hoped scientists will be able to build on this research -- which was undertaken in collaboration with the Cancer Research UK Cambridge Research Institute and Karolinska Institute in Sweden -- to further understand the factors responsible for the regulation of our genes, and how this can lead to disease.

Friday, February 26, 2010

Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments

Published in Bioinformatics Journal


Hugues Richard1,*, Marcel H. Schulz1,2, Marc Sultan3, Asja N├╝rnberger3, Sabine Schrinner3, Daniela Balzereit3, Emilie Dagand3, Axel Rasche3, Hans Lehrach3, Martin Vingron1, Stefan A. Haas1 and Marie-Laure Yaspo3

1Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestr. 73, 2International Max Planck Research School for Computational Biology and Scientific Computing, and 3Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany

*To whom correspondence should be addressed. Tel: ; Fax: +493084131152; Email: hugues.richard@molgen.mpg.de

Received July 26, 2009. Revised November 26, 2009. Accepted January 17, 2010.


 ABSTRACT
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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 SUPPLEMENTARY DATA
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 REFERENCES

Alternative splicing, polyadenylation of pre-messenger RNA molecules and differential promoter usage can produce a variety of transcript isoforms whose respective expression levels are regulated in time and space, thus contributing specific biological functions. However, the repertoire of mammalian alternative transcripts and their regulation are still poorly understood. Second-generation sequencing is now opening unprecedented routes to address the analysis of entire transcriptomes. Here, we developed methods that allow the prediction and quantification of alternative isoforms derived solely from exon expression levels in RNA-Seq data. These are based on an explicit statistical model and enable the prediction of alternative isoforms within or between conditions using any known gene annotation, as well as the relative quantification of known transcript structures. Applying these methods to a human RNA-Seq dataset, we validated a significant fraction of the predictions by RT-PCR. Data further showed that these predictions correlated well with information originating from junction reads. A direct comparison with exon arrays indicated improved performances of RNA-Seq over microarrays in the prediction of skipped exons. Altogether, the set of methods presented here comprehensively addresses multiple aspects of alternative isoform analysis. The software is available as an open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/
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Regulation of Alternative Splicing by Histone Modifications

Published in Science

Reini F. Luco,1 Qun Pan,2 Kaoru Tominaga,3 Benjamin J. Blencowe,2 Olivia M. Pereira-Smith,3 Tom Misteli1,*

Alternative splicing of pre-mRNA is a prominent mechanism to generate protein diversity, yet its regulation is poorly understood. We demonstrated a direct role for histone modifications in alternative splicing. We found distinctive histone modification signatures that correlate with the splicing outcome in a set of human genes, and modulation of histone modifications causes splice site switching. Histone marks affect splicing outcome by influencing the recruitment of splicing regulators via a chromatin-binding protein. These results outline an adaptor system for the reading of histone marks by the pre-mRNA splicing machinery.