Based on a systematic analysis of the mitochondrial genome, Radek Szklarczyk and Martijn Huynen at Radboud University Medical Center in The Netherlands were able to estimate that "the mitochondrial proteome expanded at least 50% since the common ancestor of human and yeast." The authors' work, which appears this week in Genome Biology, found that gene duplications led to the expansion in humans, and that the most common of these are intra-mitochondrial and inter-compartmental.
Researchers led by Ben Langmead and Steven Salzberg at the University of Maryland have combined Bowtie and SOAPsnp to create Crossbow, an aligner and SNP caller that runs off of the cloud. "Executing in parallel using Hadoop," they say, "Crossbow analyzes data comprising 38-fold coverage of the human genome in three hours using a 320-CPU cluster rented from a cloud computing service for about $85." In a methods paper, scientists at Boston College present the Coding Motif Identification Tool, or COMIT, algorithm, which detects functional noncoding motifs in coding regions "using sequence conservation, explicitly separating nucleotide from amino acid effects," they write in the abstract.
Anna De Grassi and Francesca Ciccarelli from the European Institute of Oncology in Milan show that internal tandem repeats within human primate-specific paralogs alter the structure of the gene. They found that about 7 percent of primate paralogous genes in the human genome contain variable tandem repeats and that half of these repeats are within coding exons. When these repeats are inside exons, they say, "they encode variable amino acid repeats. When located at exon-intron boundaries, ITRs can generate alternative splicing pattern through the formation of novel introns."
Plant biologists at CNRS and INRA in France have studied miRNAs and their patterns of expression in a paper appearing this week. Performing a comparative genomic analysis in rice, poplar, and Arabidopsis, they identified miRNA clusters encoding miRNAs of the same family and clusters expressing miRNAs with unrelated sequences that are typically not evolutionarily conserved. "Strikingly, non-homologous miRNAs from the same cluster were predicted to target transcripts encoding related proteins," they write, and they predict being able to use this knowledge as a tool to "simultaneously control the expression of different genes."