In the early, online edition of the Proceedings of the National Academy of Science, Indiana University biologist Michael Lynch and his colleagues peek at the base substitution mutation rate in Paramecium tetraurelia, a freshwater ciliate. From genome sequence data from seven so-called "mutation accumulation" lines, which had been started with individual cells and grown for thousands of generations, the team saw pronounced genome stability in P. tetraurelia. Indeed, they report, the base substitution mutation rate in the ciliate is estimated to be an order of magnitude lower than that of most other eukaryotes — a pattern suspected to stem from selection pressures related to the ciliate's complex life cycle, which involves both vegetative and sexual reproduction stages.
Uppsala University's Leif Andersson leads a team Swedish researchers looking at population structure in Atlantic herring, Clupea harengus, for another study slated to appear in the PNAS online this week. The team's reference genome-free strategy relied on transcriptome sequence data generated for muscle tissue from a Baltic herring caught near Sweden. Using that sequence data, the investigators produced an exome sequence resource representing the exons of genes expressed in these tissues and sequences surrounding them. And by resequencing pooled genomic DNA for 50 herring representatives each from eight populations in the Baltic Sea, Atlantic Ocean, and North Sea and comparing this data to the exome reference, the team uncovered hundreds of thousands of SNPs, including a small subset that proved useful for discerning herring population structure and for finding signs of selection in the fish.
Researchers from the University of California at San Diego described the bioinformatics-based approach that they used to find genome instability suppressor genes in Saccharomyces cerevisiae. By bringing together information from protein interaction, genetic interaction, and drug sensitivity studies, they identified more than 1,000 mutations suspected influencing gross chromosomal rearrangement events in the yeast model organism. Follow-up experiments on 87 of the candidate genes identified through that analysis led to dozens of verified new suppressor genes, bringing the tally to 110 so far. "We designed a bioinformatic protocol for identifying unanticipated genes involved in suppressing [gross chromosomal rearrangements]," UCSD researcher Richard Kolodner and colleagues say, "which involved handling numerous genome-wide datasets affected by both false-positive and false-negative errors."