Compugen Ltd. has announced at the 2006 Cold Spring Harbor Meeting on Pharmacogenomics the launch of its GeneVa structural genomic variations platform providing predicted non-SNP (Single Nucleotide Polymorphism), medium and large-scale genetic variations in the human genome.
The important role of non-SNP, medium and large-scale genetic variations, has recently become increasingly apparent. SNPs are genomic locations where a single nucleotide can differ between individuals.
Due to their high frequency in the human genome, a large number of techniques are used today to exploit SNP information for genotyping efforts.
Recent reports show that medium and large-scale insertions and deletions are also a substantial source of polymorphism in humans and it is expected they will facilitate theranostic and disease predisposition studies with a higher degree of success than current SNP only approaches.
The GeneVa platform, which was announced today, currently incorporates a database - developed during the past year - of approximately 200,000 novel predicted insertions, deletions and copy-number variations in the human genome.
This database was created by analyzing genomic, EST (Expressed Sequence Tag), disease related and other databases.
A specialized computational biology analysis platform was developed to handle and integrate these disparate data sources, identify possible genomic structural variations and predict their association with specific disease pathways such as those associated with breast and colon cancer, diabetes type II and Parkinson’s disease.
Yossi Cohen, MD, VP Research and Discovery said, “This is another example of how the capabilities that have been developed over the past decade at Compugen now allow us to quickly address important unmet clinical needs with unique predictive platforms. In this case, we are confident that in less than a year from project initiation we have developed the largest structural non-SNP genomic variations database available today."
“We intend to utilize the GeneVa platform, on our own and with partners, to correlate patients’ genetic profiles with clinical data such as drug response or disease predisposition and to identify novel biomarkers for drug development. We are also developing an experimental protocol that will enable such studies to be performed efficiently and cost effectively, handling thousands of variants and hundreds of patients at a fraction of the cost of generic techniques such as sequencing”.