Researchers in the US and Australia depict their integrated gene coexpression network analysis of brain gene data sets from prefrontal cortex samples of people with and without schizophrenia. “Significant overlap of ‘case’ and ‘control’ module composition was observed, indicating that extensive differences in underlying molecular connectivity are not likely driving pathology in schizophrenia,” the authors write, adding that their findings provide a novel mechanism for the ‘development’ of schizophrenia on a molecular level, and support the concept that the pathogenesis begins early in life.
In an advance, online publication of Genome Research, a pair of researchers at the European Bioinformatics Institute describe their creation of an effective model for natural selection in promoters. Their model, Sunflower, “predicts a binding profile of transcription factors to DNA sequence, in which different factors compete for the same potential binding sites,” the authors write, adding that different classes of promoters display different sensitivity to mutations; they found that phosphorylation-related genes have promoters which are more sensitive to mutations than immune genes.
Also published online is research out of the University of Pennsylvania, reporting on a genome-wide analysis of histone modifications in human pancreatic islets. The researchers identified global relationships between promoter structure, histone modifications, and gene expression. They utilized their histone marks to determine diabetes-associated SNPs that are likely to be part of regulatory elements. “Our global map of histone marks will serve as an important resource for understanding the epigenetic basis of type 2 diabetes,” the team suggests.
Researchers describe their global study of the melanoma transcriptome in an advance, online publication in Genome Research this week. Michael Berger of the Broad Institute and his colleagues have “developed a systematic approach to characterize the spectrum of cancer-associated mRNA alterations through integration of transcriptomic and structural genomic data, and we applied this approach to generate new insights into melanoma biology.” By performing paired-end massively parallel sequencing of cDNA and chromosomal copy number data analyses, the team mapped chimeric transcripts and traced them to their genomic origins. Their investigation revealed a high rate of somatic mutations, supporting the idea that point mutations are the major driver in the progression of melanoma.