Their work will appear in an upcoming issue of the journal Gene and is currently available online.
Dr. Harold "Skip" Garner, professor of biochemistry and internal medicine, and his colleagues made their discovery while mining databases of coding single nucleotide polymorphisms (cSNPs) held by the National Center for Biotechnology Information, the SNP Consortium, the National Cancer Institute and the Institute of Medical Genetics at Cardiff, Wales. Single nucleotide polymorphisms (SNPs) are the most common and simplest form of genetic mutation in the human genome.
In their analysis, the researchers showed that a large fraction of human cSNPs occur at only a few distinctive and usually recurrent DNA sequence patterns. However, such events within the genome account for a disproportionate amount of all gene point mutations.
Developing an association between phenotype (the outward, physical manifestation) and genotype (the internally coded, inheritable information) is vital toward understanding and identifying indications of disease.
"This discovery can be used to essentially define the likelihood of one gene to mutate relative to others as a function of both time and environment," said Monica M. Horvath, molecular biophysics graduate student and co-author. "cSNP trends are critical to quantify in order to develop hypotheses regarding the complexity and range of mutational mechanisms that generate both genome diversity and disease."
The next phase, Ms. Horvath said, is to employ both experimental and computational tests to benchmark how well these trends can predict mutations not yet found in the human genome.