California researchers help map human genetic variation across populations

Computer scientists at two research centers affiliated with the University of California have teamed with biologists from Perlegen Sciences, Inc., to map key genetic signposts across three human populations. Their study - published in the Feb. 18 issue of Science - could make widely accessible the analysis of human variation based on whole-genome data, and speed efforts to pinpoint DNA variations that are associated with disease or with how patients respond differently to drugs.

"This project sets a new milestone in the search for genetic elements linked to complex genetic diseases such as Alzheimer's, cancer and multiple sclerosis," said co-author David R. Cox, Chief Scientific Officer at Mountain View, CA-based Perlegen.

"Genome-wide analysis may soon become a standard methodology in the search for more effective, individualized treatments."

Researchers at Perlegen sequenced the single-letter variations (called single-nucleotide polymorphisms, or SNPs) in the DNA of 71 individuals of European American, African American, and Han Chinese American ancestry. Subsequently, scientists at the California Institute for Telecommunications and Information Technology (Calit2) at the University of California, San Diego, and the UC Berkeley-affiliated International Computer Science Institute (ICSI) helped analyze the set of over 100 million genotypes from the over 1.5 million SNPs sequenced in each sample by Perlegen.

Halperin and Calit2 researcher Eleazar Eskin, who co-authored the study with Perlegen scientists, have pioneered a method for translating genotypes into haplotypes, using the HAP software tool they co-developed For this study, the bioinformatics researchers had to process more than 190 million data points. "Using other programs, haplotyping would require at least a few months of CPU time," said Eskin, an assistant professor in Computer Science and Engineering at UC San Diego's Jacobs School of Engineering. "Using HAP on a regular laptop, this work would take only 200 CPU hours. But we were able to use a cluster of computers from Calit2's OptIPuter project, and that allowed us to perform our final entire analysis in less than 12 hours." Eskin recently received a grant from the Jacobs School's von Liebig Center for Entrepreneurism and Technology Advancement to work on potential commercial uses of the HAP software.

Until now, due to the high cost of sequencing technology, disease association studies have traditionally been performed over short genomic regions. The Science study indicates that genome-wide association studies will now be possible for a considerably reduced budget, as scientists build on the publicly-available data and tools made available by Perlegen, ICSI and Calit2.

The researchers in San Diego and Berkeley also used the HAP tool to partition the human genome into 'blocks', or regions, of limited diversity. These are regions where only a few common patterns account for the majority of the variation in the population. The resulting haplotype 'maps' across the three populations appeared qualitatively similar to the maps compiled by Perlegen using a different technique called 'linkage disequilibrium' (LD). LD involves correlations of DNA variants in physical proximity along a chromosome, and results from a combination of processes including mutation, natural selection, and genetic drift. Linkage disequilibrium is complex and varies from one region of the genome to another, as well as between different populations. According to the study, "LD maps and haplotype maps represent somewhat different aspects of the local structure of genetic variation."