In this week's Nature Genetics, a team led by researchers from the Medical University of Graz publishes a study describing the use of whole-genome sequencing of plasma DNA to study cancer gene expression. The investigators sequenced cell-free DNA in blood samples from both healthy donors and metastatic cancer patients, and identified two separate regions at transcription start sites where nucleosome occupancy results in different read depth coverage patterns for expressed and silent genes. Using a machine learning technique for gene classification, they found that the plasma DNA read depth patterns from healthy individuals reflected the expression signature of hematopoietic cells. For cancer patients, they were able to accurately classify expressed cancer driver genes in regions with somatic copy number gains. The researchers were also able to determine the expressed isoform of genes with several transcription start sites. GenomeWeb has more on this study here.
And in Nature Neuroscience, a group from the University of California, Los Angeles, presents the results of a genome-wide analysis of microRNA expression in post-mortem brains of individuals with autism spectrum disorder, identifying several non-coding RNAs that are dysregulated in the condition. Within the targets of these miRNAs, the researchers found an enrichment of autism risk genes, and they confirmed regulator relationships between several miRNAs and their putative target mRNAs in primary human neural progenitors. The results point to a role for miRNA dysfunction in autism and, potentially, other neuropsychiatric diseases.