The University of Geneva Medical School's Emmanouil Dermitzakis led an international team to look at differences in expression quantitative trait loci between men and women in Genome Research. Based on analyses of autosomal eQTLs using data on males and females from four populations sampled through the HapMap study, they determined that some 12 percent to 15 percent of these gene expression-regulating variants show sex-biased function. In some instances regulatory variants differed between males and females. In other cases, the same eQTL seemed to have different effects on expression of the associated gene. "Sex-related effects can impact traits where no sexual dimorphism has been observed," the team concludes. "Given the prominence of sex-biased effects, this study emphasizes the importance of considering each sex separately in genomic studies to uncover new disease and trait variants."
Korean researchers performed RNA sequencing on tumor samples from 87 Korean individuals with lung adenocarcinoma samples for another Genome Research study. For the majority of these cases, they were also able to do transcriptome and exome sequencing analyses on matched normal samples. Coupled with screening tests for a few known driver mutations or fusions in more than 100 other lung tumors, these sequences helped the team track down candidate driver mutations in new and known lung cancer genes. The analysis also identified dozens of gene fusions as well as new lung adenocarcinoma-related alternative splicing events and copy number changes. "The successful discovery of many aberrations in cancer genes, such as somatic mutations, gene fusion, alternative splicing events, and cancer outliers, is most likely due to the strong power and comprehensive nature of whole-transcriptome sequencing," authors of the study say.
In the early online edition of Genome Research, a group led by investigators at the University of Texas MD Anderson Cancer Center outlines findings from a systems biology study of endometrial cancer. After sequencing coding regions 13 tumor-normal pairs, the team brought together mutation data from those exomes with screens and functional studies of endometrial cancer. Together, the approaches uncovered a dozen genes containing mutations suspected to drive development of the cancer. The team went on to more fully characterize one of these genes, an apparent tumor suppressor called ARID1A, using a combination of mutational and proteomic analyses in hundreds more endometrial cancers. "Our study presents the first unbiased view of somatic coding mutations in endometrial cancer," the group writes, "and provides functional evidence for diverse driver genes and mutations in this disease."