In a study scheduled to appear online this week in the Proceedings of the National Academy of Sciences, the University of Illinois at Urbana-Champaign's Gene Robinson and colleagues look at the relationship between gene body methylation and alternative gene splicing in the honey bee, Apis mellifera. After using RNA interference to specifically curb levels of a DNA methyltransferase enzyme encoded by a gene called dnmt3 in honey bees' abdominal fat tissue, the team tracked gene and methylation profiles splicing patterns by RNA sequencing and bisulfite sequencing, respectively. Indeed, the resulting shifts in DNA methylation profiles in the bee tissue did coincide with changes to gene splicing patterns, the study authors note, explaining that "[f]our different types of splicing events were affected by dnmt3 gene knockdown and change in two types, exon skipping and intron retention, was directly related to decreased methylation."
The male-specific region of the bovine Y chromosome is unexpectedly replete with gene coding sequences, according to a study by researchers based at Pennsylvania State University and the National Center for Genome Resources in Santa Fe. In contrast to the sparse gene-coding sequences previously described in the male-specific portion of the primate Y chromosome, group found nearly 1,300 genes coding for members of dozens of protein families when they sequenced male-specific Y chromosome transcripts from bovine testis tissue. The set of male-specific genes may have a role in bovine testis development, too, the researchers report, since their expression appears to be particularly pronounced during that process.
For another study slated for the online edition of PNAS this week, biostatistics researchers with the University of North Carolina at Chapel Hill and National Heart, Lung, and Blood Institute's GO Exome Sequencing Project outline analytical approaches for doing quantitative trait analysis using sequence data representing individuals selected through trait-dependent sampling — for instance, for individuals from the opposite, extreme ends of the spectrum for a traits such as body mass index or blood pressure. The investigators' statistical schemes "can be used to perform quantitative trait analysis not only for the trait that is used to select subjects for sequencing," they say, "but for any other traits that are measured."