News and insights

Subscribe to our newsletter

What: A team of researchers from the Massachusetts General Hospital, ӳý of MIT and Harvard, and the University of North Carolina has identified an inflammatory molecule that may play an essential role in the development of lupus—a chronic, painful autoimmune disease affecting more than 1.5 million Americans.

A  by ӳý associate member Gökhan Hotamisligil, first author Takahisa Nakamura of Harvard T.H. Chan School of Public Health and Cincinnati Children’s Hospital Medical Center, and colleagues identifies components of a pathway— including a complex between double-stranded RNA-dependent kinase (PKR) and TAR RNA-binding protein (TRBP)—that integrates metabolic cues, stress signals, translational regulation, and the metabolically driven inflammatory response in obesity-related pathogenesis. These findings uncover a potential link between RNA metabolism and endogenous dsRNA-mediated signaling in the initiation and maintenance of a metabolic inflammatory state and provide potential targets for the treatment of chronic stress-related diseases including obesity-induced metabolic diseases. Their paper can be found online in Cell Reports.

In , a team led by researchers from the ӳý, MIT, and Dana-Farber Cancer Center describes new statistical methods that account for artifacts introduced by whole-genome amplification of single-cell genomic DNA. Their approach establishes a system for characterizing amplification bias and provides a framework for quality assurance in single-cell DNA libraries. ӳý associate member J. Christopher Love and institute member Matthew Meyerson were senior authors of the study; ӳý researchers Cheng-Zhong Zhang and Viktor Adalsteinsson were first authors.

For cells, location is key to their fate and behavior, but studying expression patterns across complex tissues is difficult. A team led by ӳý visiting scientist Rahul Satija (of ӳý core member Aviv Regev's lab) and Jeff Farrell (a postdoc in associate member Alex Schier's lab) recently reported on Seurat, their new computational strategy to map single cells by integrating single-cell RNA-seq data with RNA patterns from tissues. Their team used the tool, named after the 19th century pointillist painter, to generate a transcriptome-wide map of spatial patterning in zebrafish embryos, demonstrating Seurat's utility for mapping cells within complex patterned tissues. Their paper appears online in .

A in this month’s issue of the journal Nature Methods discusses the exponential growth of cancer “omics” data, the need for interoperability between data integration tools, and the approaches researchers are taking to address these issues. One of the helpful technologies highlighted in the piece is , a platform that bridges commonly used bioinformatics tools, facilitating interoperability for biomedical investigators with little to no computer programming experience.