Researchers at the University of California, San Diego, discuss in a Nucleic Acids Research paper published online in advance this week the Saccharomyces cerevisiae gene SUS1 and, in particular, how its splicing pattern changes in response to environmental stimuli. "Unexpectedly, removal of the 3' intron is affected by splicing of the upstream intron, suggesting that cross-exon interactions influence intron removal," the UCSD researchers write. Further, the team presents evidence to suggest "a role for S. cerevisiae alternative splicing in histone modification and cellular function."
In a related paper published online in advance this week, investigators in Spain show that the S. cerevisiae "Sus1/ENY2 ... is involved in both transcription and mRNA export," and further, that as it responds to cellular conditions, "SUS1 splicing is inefficient ... and intronic mutations either promoting or blocking splicing lead to defects in mRNA export and cell growth." Taken together with the UCSD team's results, the authors say that the results of their SUS1 investigation "provide evidence of the involvement of splicing, translation, and decay in the regulation of early events in mRNP biogenesis; and imply the additional requirement for a balance in splicing isoforms from a single gene."
Researchers at the University of Helsinki this week present an approach for quantitative analysis of alternative spliced variants via multiple exon array data processing, or MEAP. In comparing MEAP against other pre-processing methods, the Helsinki team found it "produces reliable expression values at exon, alternatively spliced variant and gene levels, which allows generating novel experimentally testable predictions."
In another Nucleic Acids Research methods paper recently published online, a public-private team of researchers in Germany discuss "quantification noise in single-cell experiments," and how best to "make quantitative single-cell studies more transparent and reliable in order to fulfill the MIQE [minimum information for publication of quantitative, real-time PCR experiments] guidelines at the single-cell level." In its paper, the team also discusses the extent to which each experimental step produces variability, presenting two studies that they say "impressively demonstrate the heterogeneity of expression patterns in individual cells and showed clearly today's limitation in quantitative single-cell expression analysis."