Scientists at the University of Dundee in the UK have used computational analysis to study small, noncoding RNAs, particularly to determine whether miRNAs and small nucleolar RNAs are evolutionarily related. In their work, they found twenty snoRNA-like miRNA precursors whose surrounding genomic regions are very similar to those of snoRNAs. They also show that five sno-like miRNAs, miR-151, miR-605, mir-664, miR-215, and miR-140, bind to dyskerin, a component of the small nucleolar ribonucleoprotein complexes, "suggesting that these molecules have retained some H/ACA snoRNA functionality." Their work was published this week in PLoS Computational Biology.
The University of Pennsylvania's Vivian Cheung and Emory University's Stephanie Sherman studied genome-wide recombination rates using high-density SNP arrays in a study appearing in PLoS Genetics. Looking at 2,315 Caucasian individuals and their children, they found six genetic loci associated with recombination phenotypes, three of which influence female recombination and three different loci that influence male recombination. Each of the variants explains about 10 percent of the variation, they say, which "suggests a mechanism for variability in recombination that is essential for genetic diversity while maintaining the number of recombinations within a range to ensure proper chromosome segregation."
In other work in PLoS Genetics, French scientists at INRA in Marseille studied meiotic recombination in Arabidopsis thaliana. In order to identify proteins involved in the first step of meiotic recombination — the formation of DNA double-strand breaks — they performed a high-throughput meiotic mutant screen on over 55,000 mutant lines, finding that there are at least five proteins necessary for the formation of double-strand breaks. The new proteins, they say, are poorly conserved among species, "suggesting that the DSB formation mechanism, but not its regulation, is conserved among eukaryotes."
Finally, a study from researchers at the Swiss Federal Institute of Technology's Brain Mind Institute appearing in PLoS One looked at which genes are transcriptionally affected by γ-secretase activity. After up- or down-regulating γ-secretase in Chinese hamster ovary cells, they compared the two transcriptomes by microarray analysis. They identified 21 genes that were particularly affected, including PTPRG and AMN1, where transcription was decreased, and UPP1, where it was increased. These findings, they say, "support data on cell cycle disturbances relevant to cancer, stem cell and neurodegenerative diseases' research."