Scientists working on the International Genome Structural Variation Consortium’s Copy Number Variation Project have generated the first comprehensive copy number variation (CNV) map of the human genome. The team says the discovery of hundreds of CNVs will enable researchers to perform more powerful association studies on diseases, such as cancer, Parkinson’s and Alzheimer’s.
“Our results suggest that submicroscopic structural variants along chromosomes are more widespread than previously thought and that researchers should study both SNPs and CNVs when undertaking disease research,” says Stephen Scherer, Ph.D., senior scientist in Genetics & Genome Biology at The Hospital for Sick Children, director of The Center for Applied Genomics. The study showed that CNV regions were found to comprise about 360 megabases, or around 12% of the human genome.
The researchers used Affymetrix’ 500K Array. The study, published in the November 23, 2006 issue of Nature along with a supporting paper in Genome Research, is the first publication to demonstrate the performance of whole-genome SNP arrays in detecting CNVs in the general population.
“Our new approach will be useful in understanding the role of copy number alteration in disease pathology,” points out Hiroyuki Aburatani, M.D., Ph.D., professor at the University of Tokyo and one of the lead researchers. “This information should lead to the development of diagnostic tests with submicroscopic resolution that can detect not only mutations in cancer but other genetic variations associated with common diseases.”
Researchers in the study constructed the CNV map of the human genome by analyzing samples from 270 people of European, Asian, or African descent, who were originally included in the International HapMap Project. The DNA from these individuals was scanned using the Affymetrix 500K Array and a BAC array platform developed by the Wellcome Trust Sanger Institute. The researchers discovered 1,447 CNV regions containing hundreds of genes, disease loci, functional elements and segmental duplications.