Investigators at the Broad Institute led by Chad Nusbaum describe in an advance online publication of Genome Biology an automated, scalable approach to Solution Hybrid Selection capture, which they say "provides a dramatic increase in scale and throughput of sequence-ready libraries produced." Nusbaum et al. have also injected "a series of in-process quality control checkpoints" into their protocol, which they add, can be useful for the standard, manual method.
In the current issue of Genome Biology, researchers at the Wellcome Trust Sanger Institute present SVMerge, a package to "detect structural variants by integrating calls from several existing structural variant callers, which are then validated and the breakpoints refined using local de novo assembly." SVMerge, which is available for public download, is also capable of adding new callers as they become available. When the Sanger Institute researchers applied the program to data from a HapMap trio, they found that SVMerge enabled "enhanced structural variant detection, breakpoint refinement, and a lower false discovery rate."
Researchers at the University of California, San Francisco, and Princeton propose that there exists a "strong relationship between how and when genes are created and the roles they play in the cell." More specifically, in its evolutionary and functional analyses of new Saccharomyces cerevisiae genes, the UCSF-Princeton team observed "significant differences in the functional attributes and interactions of genes created at different times and by different mechanisms," such that "novel genes are initially less integrated into cellular networks than duplicate genes, but they appear to gain functions and interactions more quickly than duplicates." In addition, the researchers found an apparent preference among S. cerevisiae genes "to interact with other genes of similar age and origin."
In another paper appearing in the current issue of Genome Biology, investigators at the European Bioinformatics Institute present a "large scale comparison of global gene expression patterns in human and mouse." In their principal components analysis of the two, the EBI researchers found orthologous probesets between human and mouse; the most prominent of these principal component clusters "are the nervous system, muscle/heart tissues, liver and cell lines," the authors write, adding that "the most variable genes in each tissue are highly enriched with human-mouse tissue-specific orthologs and the least variable genes in each tissue are enriched with human-mouse housekeeping orthologs."