With HapMap, one size fits many
Photo courtesy of Emrah Turudu, iStockphoto
As a postscript to the International HapMap Project, scientists have examined whether the effort — a genetic analysis of individuals from a handful of geographic areas — accurately reflects the genetic differences commonly found in other worldwide populations. In a paper appearing in the October 22 advance online edition of Nature Genetics, the researchers selected genetic markers based on the HapMap's reference samples and found that these markers could be used to detect key genetic differences in eleven other sample populations. The work serves as an important validation of the HapMap as a resource for genome-wide analyses of several different geographic populations.
With the recent completion of the HapMap Project, the scientific community gained access to a catalogue of more than 3 million single-letter variations in the human genetic code. These differences, called single nucleotide polymorphisms (SNPs), were originally "read" from the DNA of 270 individuals from just four geographic regions. As researchers now rely on the HapMap to pinpoint special "tag" SNPs, which act as proxies for long stretches of the human genome and represent the scientific cornerstone of current efforts to systematically correlate genetic variants with human disease, it is important for researchers to determine how broadly these tags can be applied.
In an effort led by David Altshuler, director of the Program in Medical and Population Genetics at the Broad Institute and an associate professor at Massachusetts General Hospital and Harvard Medical School, and involving co-first authors Paul de Bakker, Noël Burtt and Robert Graham, the scientists focused on human genes involved in steroid hormone and growth factor biology. They first identified SNPs in these genes by searching both HapMap samples and DNA samples collected from eleven other populations. These additional populations include that of the Multiethnic Cohort study, which focuses on the relationship between cancer and diet in individuals living in Hawaii and Los Angeles and comprises African American, Japanese, Latino, Native Hawaiian and Caucasian populations not surveyed in the HapMap effort.
Using the SNP data collected from HapMap samples, the scientists selected the appropriate tag SNPs within the chosen genes. Then, using statistical methods as well as a mock disease association study, they determined how well these tag SNPs describe common variation in the same genes of the non-HapMap samples. Their findings reveal that HapMap data serve as good guides for conducting genome-wide studies in a variety of human populations.
Other Broad scientists who participated in this work include Candace Guiducci, Roman Yelensky, Jared Drake, Todd Bersaglieri, Johannah Butler, Robert Onofrio, Helen Lyon, Matthew Freedman, Mark Daly and Joel Hirschhorn.