Polish Academy of Sciences researchers report on a pan-cancer atlas spanning somatic mutations in dozens of microRNA biogenesis genes. Using exome sequence data for more than 10,200 matched tumor and normal pairs, the team tallied some 3,600 somatic mutations in 29 miRNA biogenesis genes across 33 cancer types profiled for the Cancer Genome Atlas, uncovering recurrent mutations that appeared to correspond with specific cancer types and/or patient outcomes. "We identified a list of miRNAs whose level is affected by particular types of mutations in either SMAD4, SMAD2, or DICER1, and showed that hotspot mutations in the RNase domains in DICER1 not only decrease the level of 5p-miRNAs but also increase the level of 3p-miRNAs, including many well-known cancer-related miRNAs," the authors report, adding that "we created an atlas/compendium of miRNA biogenesis alterations providing a useful resource for different aspects of biomedical research."
A team from the Chinese Academy of Agricultural Sciences shares findings from a DNA methylation and gene expression analysis of skeletal muscle samples from Landrace pigs at 27 stages of development. By generating whole-genome bisulfite sequencing and RNA sequencing profiles for skeletal samples collected from pigs at 15 prenatal and a dozen post-natal points along the porcine developmental pathway, the researchers saw a broad decline in DNA methylation levels as pigs transitioned from embryonic to adult stages. They noted that differentially methylated cytosines tended to fall at enhancer histone markers and chromatin-accessible sites in the genome, for example, but occurred far less at promoter regulatory sites — methylation shifts that they set against muscle-related gene expression. "These data have important value for understanding the molecular regulation of skeletal muscle development in mammals," they write, "and provide an invaluable resource for [studies] on animal breeding, muscle biology, and related diseases."
Finally, investigators in Singapore and China introduce a virus integration caller known as SurVirus that takes repeat regions in the host genome into account. "Given a second-generation, paired-end dataset, a host genome, and a database of viruses, SurVirus predicts the integration events that occurred, providing the precise integration loci on the host genome as well as which segments of which viruses integrated," they say. The team applied SurVirus to available sequence data from hepatocellular carcinoma and cervical cancer samples, uncovering related hepatitis B virus (HBV) or human papillomavirus (HPV) integrations, respectively. "Using SurVirus, we find that HPV and HBV integrations are enriched in LINE and satellite regions which had been overlooked," the authors write, as well as discover recurrent HBV and HPV breakpoints in human genome-virus fusion transcripts."