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This Week in PNAS: Aug 27, 2013

In the early, online edition of the Proceedings of the National Academy of Sciences, a University of Freiburg-led team describes a bioinformatics strategy for deciphering small RNA targets in bacterial genomes. The approach — called "comparative prediction algorithm for sRNA targets," or CopraRNA — predicts sRNA targets across the genome with the help of phylogenetic information, the study authors explain, while providing a peek at networks regulating gene expression as well as the sRNA domains interacting with their messenger RNA targets. For instance, their CopraRNA analysis of several characterized bacterial sRNAs dug up both new and known mRNA interactions, along with related mRNA hubs.

Researchers from Germany and Israel report on sets of genes that are co-expressed in human thymus cells tasked with helping immune cells established self-tolerance, among other things. By focusing on array-based gene expression patterns in medullary thymic epithelial cells that produce particular types of tissue-restricted self-antigens, the team uncovered three groups of co-expressed gene clusters. "Our data suggest that single [medullary thymic epithelial cells] shift through distinct gene pools," the study's authors say, "thus scanning a sizeable fraction of the overall repertoire of promiscuously expressed self-antigens."

Using a combination of high-throughput sequencing and in vitro selection in the lab, a group from Harvard University and the University of California, Santa Barbara, explored fitness differences between short RNAs — information used to take a look at the RNA fitness landscape. "Our results give an experimental determination of a comprehensive fitness landscape," the study's authors write. "A limited neutral network is present, but most fitness peaks are evolutionarily isolated from one another."