In PLOS Genetics, researchers from the University of Helsinki and elsewhere report on findings from an exome sequencing analysis of small bowel adenocarcinoma. The team used a combination of exome sequencing and OncodriveFML driver mutation detection analysis to profile more than 100 primary small bowel adenocarcinoma samples archived over several years, from 2003 to 2011. Along with apparent driver mutations in genes such as SOX9, ATM, and ARID2, for example, the analyses uncovered recurrent gene mutations, mutation hotspots, sites of allelic imbalance, and small bowel adenocarcinoma mutation signatures. "This comprehensive work unveils the mutational landscape and most frequently affected genes and pathways in [small bowel adenocarcinoma], providing potential therapeutic targets, and novel and more thorough insights into the genetic background of this tumor type," the authors note.
A Brown University-led team took a closer look at pre-messenger RNA splicing patterns in the Lynch syndrome-related gene MLH1 and other hereditary cancer genes for another PLOS Genetics paper. Using in vivo and in vitro reporter assays, the researchers searched for altered splicing events at known MLH1 variants, identifying 11 such changes across three dozen pathogenic mutation sites. An expanded analysis of splice site mutations in thousands of genes from the Human Gene Mutation Database highlighted 86 disease genes with higher-than-usual splicing mutation burdens, including MLH1 and two additional Lynch syndrome genes, MSH2 and PMS2. "Our findings strongly argue for additional clinical sequencing prioritization in both cancer genes and genes prone to splice site mutations," they say.
For a paper in PLOS Pathogens, researchers from the Harvard T.H. Chan School of Public Health and other centers explore strain variation and potential vulnerabilities in the tuberculosis-causing pathogen Mycobacterium tuberculosis. The team turned to whole-genome sequencing, genome-wide transposon mutagenesis sequencing (TnSeq), in vitro growth analyses, and other approaches to assess eight clinical isolates and an M. tuberculosis reference strain, uncovering strain-specific differences in genes required for growth under various conditions, including the presence of antibiotics. "Our results provide novel insight into the basis of variation among [M. tuberculosis] strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among [M. tuberculosis] strains," the team writes.