Public Release:  A new method to identify mutated genes in human diseases

PLOS

Researchers from the University of Turin, Italy and the University of Nijmegen, The Netherlands, have devised a new method that may help the medical community to determine the genetic basis of many common diseases. Their findings are described in an article published March 21st in the open-access journal PLoS Computational Biology.

Thousands of human diseases originate from mutations in one or more genes. Identification of mutated genes is a crucial first step towards understanding the molecular mechanisms at the origin of diseases and devising a treatment. In many cases, we do not know the identity of the affected gene, only a chromosomal region (typically containing hundred of genes) in which the mutation is located.

The research group, led by Ferdinando Di Cunto and Paolo Provero, analyzed gene expression data (patterns of gene activity in tissues and cell lines) from thousands of published experiments to identify genes showing patterns comparable to the ones of mutated genes in similar diseases. The study identified candidate genes for 81 diseases, including various forms of epilepsy and muscular dystrophy

As in all such analyses, the results must be verified experimentally. However, the task of understanding the molecular basis of many diseases could be significantly simplified by the results of this work.

###

PLEASE ADD THIS LINK TO THE PUBLISHED ARTICLE IN ONLINE VERSIONS OF YOUR REPORT: http://www.ploscompbiol.org/doi/pcbi.1000043 (link will go live on Friday, March 21)

CITATION: Ala U, Piro RM, Grassi E, Damasco C, Silengo L, et al. (2008) Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis. PLoS Comput Biol 4(3): e1000043. doi:10.1371/journal.pcbi.1000043

CONTACT:

Ferdinando Di Cunto
University of Turin
+39-011-670-6409
ferdinando.dicunto@unito.it

Paolo Provero
University of Turin
+39-011-670-6438
paolo.provero@unito.it

Disclaimer

This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by the article authors. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.

About PLoS Computational Biology

PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.

About the Public Library of Science

The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource. For more information, visit http://www.plos.org.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.