A Harvard University and Broad Institute-led team tapped genome sequence data generated through the 1000 Genomes Project in its search for variants involved in recent human adaptations. As they write in Cell, the researchers used a genome-wide version of their "composite of multiple signals," or CMS method to help find regions of the genome suspected of being subject to selection. From there, they fine mapped more than 400 candidate regions, uncovering potential causal SNPs in recent human adaptation. Along with several SNPs contributing to infectious disease response, for instance, the team tracked down almost three-dozen non-synonymous variants and 59 SNPs that appear to influence the expression of nearby RNA or protein-coding sequences.
Using whole-exome sequence data, researchers from the Broad Institute, Massachusetts General Hospital, Brigham and Women's Hospital, and elsewhere identified mutations within different tumor sub-populations in chronic lymphocytic leukemia — information that proved useful for tracking clonal evolution within the cancer. By using a sensitive mutation caller to consider exome sequence data for matched tumor and normal samples from 149 individuals with CLL, they say, the researchers saw that apparent driver mutations tended to turn up in tumor clones or sub-clones. Meanwhile, data from 18 individuals whose CLL tumors sampled more than once indicated that driver mutation-containing sub-clones can expand with time, fueling CLL progression.
Finally, an international team led by investigators at the University of California, San Francisco, describes a two-stage method for exploring biological pathways behind various processes or diseases using genetic interaction maps of mammalian cells. In that study, researchers demonstrated the feasibility of the approach — which relies on genome-wide RNA interference screening followed by genetic interaction analyses using double short hairpin libraries — by mapping genetic interactions related to ricin susceptibility. In addition to genes already known for bumping the toxin's effects up or down, the investigators saw previously unappreciated contributors to the process. And, they say, the genetic interaction mapping strategy itself "provides a potentially transformative tool for defining gene function and designing combination therapies based on synergistic pairs."