Previous research has indicated that chromatin--a chromosome's substance consisting of histone proteins and DNA--exhibits salt-dependent conformations. Specifically, chains of nucleosomes, the building blocks of chromatin that appear as bead-like structures along DNA, fold into a condensed fiber as salt increases. This folding and the interplay between chromatin structures regulate fundamental gene expression. However, the molecular mechanism underlying this process remains unclear.
The research team, which included NYU chemists Tamar Schlick, Jian Sun (now at the Cornell Medical School), and Qing Zhang, analyzed a 12-nucleosome array. Using a variety of salt conditions, the researchers found that the nucleosomal array formed irregular three-dimensional zig-zag structures at high salt concentrations and "beads-on-a-string" structures at low salt, demonstrating that the structure of chromatin strongly depends on its salt environment.
To Schlick and her colleagues, these results revealed that in a low-salt environment, linker DNAs in the array were repelled, preventing array folding and resulting in a bead-like structure. However, under high-salt conditions, screening of linker DNA repulsion allows close contacts and attraction between nucleosomes, allowing the array to fold. As chromatin folding or unfolding prevents or allows the transcriptional machinery's access to the DNA in a chromosome, this computer simulation study helps to understand the mechanism of gene expression and silencing.
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The new HSPH analysis method, which uses just one dataset, bypasses the multiple comparison problem altogether by first estimating how much genetics can explain a specific trait within a population, and then tracing the roots of the trait back to candidate SNPs that would explain that "genetic effect size." To test their methodology, the research team ran simulation studies using data from the Childhood Asthma Management Program (CAMP) Genetics Ancillary Study based at Channing Laboratory, Brigham and Women's Hospital, in Boston and data from a joint study conducted by the Mayo Clinic College of Medicine and Affymetrix. The results of the simulation studies suggested that the new approach outperformed the traditional approach by factors up to 100.
Besides dealing away with the multiple comparison problem, the HSPH technique offers another feature that is highly attractive to geneticists-the methodology appears to be able to find multiple SNPs involved in a single disease or trait.
"Many biomedical scientists today are interested in complex phenotypes, such as risk for unhealthy levels of body mass index, blood pressure, or cholesterol," said HSPH Assistant Professor of Biostatistics Christoph Lange, who is senior author on the paper. "Yet until now, no statistical tool existed that would allow researchers to look at several thousand disease genes and successfully identify those small number of genes that influence such complex traits."
The HSPH methodology is part of an analysis software program called PBAT, freely available at biostat.harvard/~clange/default.htm. The program was developed by Lange and HSPH Professor Nan Laird.
The CAMP Genetics Ancillary Study is supported by the National Heart, Lung, and Blood Institute. The joint study conducted by the Mayo Clinic College of Medicine and Affymetrix was supported by the Mayo Clinic Genomic Center and Comprehensive Cancer Center and by the National Institutes of Health (NIH). The NIH provided additional funding for the HSPH research.
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