Editor's Note: Some of the articles described below are not yet available at the PNAS site, but they are scheduled to be posted some time this week.
In a paper scheduled to appear in PNAS this week, researchers from the University of Southern California and elsewhere present findings from an epigenetic analysis of lymphoma cases related to oncogenic Kaposi's sarcoma-associated herpesvirus (KSHV) infections. The team relied on global run-on sequencing, chromatin immunoprecipitation sequencing, RNA interference, gene editing, and other approaches to track host regulatory element patterns over time in a primary effusion lymphoma cells, identifying super-enhancers influencing the activity of host genes involved in KSHV latency or reactivation. "During KSHV latency, expression levels of several key transcription factors and oncogenes are elevated by clusters of enhancers," the authors report. "Upon virus reactivation, global host enhancer activities are suppressed in order to facilitate viral replication."
A team from the US and China introduces a variant prioritization tool and scoring strategy aimed at characterizing non-coding variant effects on chromatin accessibility in individual genomes. The OpenCausal tool hinges on data from personal genomes and reference transcription factor expression features, the researchers write, producing a set of chromatin accessibility-affecting non-coding variants. Building on a prediction model called Ropen, the authors came up with OpenCausal to spit out causal scores for quantifying non-coding variant effects on regulatory element openness. In more than 6,400 GTEx samples spanning 18 tissue types, for example, they found that the OpenCausal tool prioritized non-coding variants at quantitative trait loci known for influencing expression or chromatin accessibility, while a proof-of-concept analysis on data from a genome-wide association study for height highlighted the possibility of using OpenCausal to prioritize GWAS variants.
Investigators in Germany, Canada, the UK, and Netherlands describe peripheral immune signatures found in dozens of multiple sclerosis-discordant identical twin pairs with a systems biology approach. Using fluorescent markers, flow cytometry-based cell sorting, machine learning, and other approaches, the team identified adaptive and innate immune cell clusters in peripheral blood mononuclear cell samples from 22 individuals with multiple sclerosis and their unaffected twins. Overall, the authors note, immune features were comparable between monozygotic twins with or without multiple sclerosis, though they unearthed a memory T cell signature in blood samples from a subset of multiple sclerosis-free siblings showing other signs of subclinical, pre-symptomatic multiple sclerosis. "Some of these early-disease immune traits were confirmed in a second independent cohort of untreated early relapsing-remitting [multiple sclerosis] patients," they write, pointing to an apparent T cell role in early disease stages.