In Nature this week, researchers from the Broad Institute and elsewhere describe a new method for determining the genetic changes that might contribute to autoimmune disease. While large-scale genetic studies can identify areas in the genome that are associated with autoimmune disorders, the existence of multiple base-pair changes makes it difficult to tease out which ones are actually disease causing. With their new fine-mapping algorithm, the researchers are able to examine both genetic and epigenetic influences on gene activity. Using the approach, they found that most causal variants are located in non-coding genetic regions and conclude that disease risk tends to be linked to variations in cell-type-specific enhancers involved in the stimulation of immune cells. GenomeWeb Daily News has more on this study here.
Meanwhile, in Nature Biotechnology, a team of Spanish researchers report on the characterization of structural variations in cancer by comparing genome sequence reads. They used a program called SMUFIN to directly compare sequence reads from normal and tumor genomes to identify and characterize a range of somatic sequence variation, from single-nucleotide variants to large structural variants at base pair resolution. On modeled tumor genomes, the approach proved to have an average sensitivity of 92 percent and 74 percent for SNVs and structural variants, with specificities of 95 percent and 91 percent, respectively. SMUFIN was also able to identify breakpoints associated with chromothripsis and chromoplexy with high specificity for aggressive forms of solid and hematological tumors.