Published yesterday in Genome Biology, Chad Nusbaum at the Broad Institute is the lead author on a paper describing a novel method for closing non-structural gaps in the human genome. Even though the human genome is "finished," the most recent release contains 260 euchromatic gaps. In this work, they present an approach for closing these gaps using 454 sequencing, and as proof of principle, apply it to closing all three remaining non-structural gaps in chromosome 15.
Yale's Frank Slack led work looking at the changeable expression of small noncoding RNAs, especially miRNAs and piRNAs, during development in C. elegans. Using deep sequencing to analyze small RNA expression, they found that "a significant number of known miRNAs showed major changes in expression during development and between males and hermaphrodites." They also identified 66 novel miRNA candidates and hundreds of novel piRNA/21U-RNAs.
Merck scientists have built tissue-to-tissue co-expression networks between genes in the hypothalamus, liver, or adipose tissue to model a framework of gene networks in obesity. This is the first systematic effort to study inter-tissue relationships in obese mice, they say, and "the subnetworks identified as specific to tissue-to-tissue interactions are enriched in genes that have obesity-relevant biological functions such as circadian rhythm, energy balance, stress response, or immune response."
Audrey Gasch from the University of Wisconsin studied what might cause the different gene expression patterns in yeast under stress. She and her team found that the histone deacetylase Rpd3-Large complex is required for expression of both induced and repressed environmental stress response genes, of which there are about 600 repressed and 300 induced genes. ChIP and computational analysis showed "a direct role for Rpd3-Large at representative genes" and that regulators could act with Rpd3p at ESR genes.
Finally, Genome Biology reports on two new software tools. MotifAdjuster helps detect and resolve errors in transcription factor binding site annotation data, while Cell Cycle Ontology is a semantic Web-enabled application ontology that integrates information on the cell cycle process.