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This Week in Genome Biology: Jan 25, 2017

Researchers at Stanford University, the Broad Institute, and Harvard outline epigenetic differences from one cell to the next in chronic myeloid leukemia. The team used single-cell ATAC sequencing and RNA sequencing to profile single-cell chromatin accessibility and expression in K562 chronic myeloid leukemia cells. Results from the analysis hint that chromatin accessibility shifts are accompanied by shifts in representation by the cell surface marker CD24 and in GATA transcription factor activity, for example, prompting the authors to note that "[s]ingle-cell chromatin accessibility can guide prospective characterization of cancer heterogeneity."

A UK- and US-led team describes transcriptional differences in blood samples from Ebola virus-infected individuals with better or worse infection outcomes. The researchers used RNA sequencing to profile transcriptional patterns in peripheral blood samples obtained from 138 individuals tested at a mobile lab in Guinea in 2014 or 2015. The 112 sequenced samples remaining after quality control steps represented two-dozen Ebola virus survivors and 88 individuals with fatal infections. Their results revealed gene expression differences during acute infection in individuals who did not survive, particularly a jump in liver-related genes and immune genes from the interferon signaling pathway. GenomeWeb has more on this, here.

Researchers from the University of Southern California and elsewhere search for methylation-based tools for predicting particularly aggressive prostate cancer cases. Using array-based methylation profiling, the team looked at DNA methylation patterns in samples from multiple tumor foci per person in 14 men with prostate cancer, uncovering prostate cancer sub-clones with distinct epigenetic features in more than half of the individuals. In addition to analyses focused on identifying primary sub-clones sources for subsequent metastatic tumors, the investigators narrowed in on a set of 25 DNA methylation probes that seemed to predict prostate cancer aggressiveness.