Researchers from Case Western Reserve University report in the early edition of the Proceedings of the National Academy of Sciences this week that they've uncovered mutations linked to colorectal cancer that seem to be specific to African-American patients. The investigators performed exome sequencing on a discovery set of 31 African-American patients with colorectal cancer. After re-sequencing and validating in a separate cohort, the researchers came up with a set of 20 genes that were mutated in more than one patient and that hadn't been linked to colorectal cancer before. The researchers then examined whether these mutations were also present in a Caucasian patient cohort, finding that mutations in these genes — which included EPHA6 and FLCN — were more likely to affect African-American colorectal cancer patients. This suggested to the investigators that there could be differences in "colon carcinogenesis between the different ethnic groups and [that] also may have implications for the ethnicity associated differences in tumor incidence and outcome." GenomeWeb has more on this study here.
Researchers from China and elsewhere report in PNAS that they've developed a draft assembly of the Tibetan hulless barley (Hordeum vulgare L. var. nudum) genome. This 3.89-Gb draft assembly includes more than 36,150 predicted protein-coding genes and by comparing it to other Poaceae species, they traced the divergence time between barley and Aegilops tauschii, Triticum urartu, and T. aestivum to about 17 million years ago. Additionally, re-sequencing of 10 more barley accessions, both wild and cultivated, revealed high levels of genetic variations in Tibetan hulless barley and between it and other types of barley. A selective sweep analysis further uncovered a link between genes under selection and the environmental stresses of the Tibetan plateau.
Finally, the University of North Carolina-Chapel Hill's Dan-Yu Lin and his colleagues present an integrative analysis to get at rare mutations associated with disease. Rather than sequencing an entire large cohort, Lin and his colleagues say that another approach is to only sequence those individual with extreme traits or specific disease. The genome-wide association data from the members of the cohort who are not selected for sequencing can then be used to impute sequencing data and thus bolster the number of patients on which they have information about rare variants. "This integrative analysis is substantially more powerful than the use of sequencing data alone and can accelerate the search for disease-causing mutations," the researchers write.