Genome bioinformatic analysis of nonsynonymous SNPs

Background: Genome-wide association studies of common diseases for common, low penetrance causal variants are underway. A proportion of these will alter protein sequences, the most common of which is the non-synonymous single nucleotide polymorphism (nsSNP). It would be an advantage if the functional effects of an nsSNP on protein structure and function could be predicted, both for the final identification process of a causal variant in a disease-associated chromosome region, and in further functional analyses of the nsSNP and its disease-associated protein. Results: In the present report we have compared and contrasted structure- and sequence-based methods of prediction to over 5500 genes carrying nearly 24,000 nsSNPs, by employing an automatic comparative modelling procedure to build models for the genes. The nsSNP information came from two sources, the OMIM database which are rare (minor allele frequency, MAF, < 0.01) and are known to cause penetrant, monogenic diseases. Secondl...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: David F. Burke, Catherine L. Worth, Eva-Maria Priego, Tammy M. K. Cheng, Luc J. Smink, John A. Todd, Tom L. Blundell
• Keywords: BMCBI 2007, Causal Variant, Disease, Protein