A University of Pennsylvania-led team introduces software for teasing out the effects of non-coding variants found in genome-wide association studies. The approach — called "Inferring the molecular mechanisms of noncoding genetic variants," or INFERNO — quantifies tissue-specific enhancers and other regulatory features using statistical methods informed by transcription factor, expression quantitative trait locus, and other functional genomic datasets, the researchers explain. When they applied INFERNO to schizophrenia and inflammatory bowel disease GWAS data, for example, the investigators identified causal variants at brain and immune enhancers, respectively.
University of Groningen and University of Lausanne researchers present an annotated genome sequence for a strain of Streptococcus pneumoniae called D39 that's commonly used in pneumococcal research. The team did de novo genome sequencing on a D39 isolate from serotype 2, putting together a genome assembly based on long reads that were polished with short read data. A deep annotation of the S. pneumoniae genome and transcriptome led to new genes, more than 1,000 transcription start sites, and nearly 750 termination sites, the authors report, noting that they developed a genome browser called PneumoBrowse to delve into the genetic and regulatory features of the opportunistic pathogen.
For a related study, members of the same Groningen and Lausanne team dig into the transcriptional features found in S. pneumoniae grown in infection-relevant settings. For that analysis, the researchers used RNA sequence data for S. pneumoniae isolates grown in nearly two dozen growth conditions. "The data demonstrated a high level of dynamic expression and, strikingly, all annotated pneumococcal genomic features were expressed in at least one of the studied conditions," the authors report. In addition to exploring co-expression and regulation of the S. pneumoniae genes, they brought the expression data together with an interactive tool dubbed PneumoExpress.