Changes in gene expression associated with developmental arrest and longevity in Caenorhabditis elegans

Gene expression in a developmentally arrested, long-lived dauer population of Caenorhabditis elegans was compared with a nondauer (mixed-stage) population by using serial analysis of gene expression (SAGE). Dauer (152,314) and nondauer (148,324) SAGE tags identified 11,130 of the predicted 19,100 C. elegans genes. Genes implicated previously in longevity were expressed abundantly in the dauer library, and new genes potentially important in dauer biology were discovered. Two thousand six hundred eighteen genes were detected only in the nondauer population, whereas 2016 genes were detected only in the dauer, showing that dauer larvae show a surprisingly complex gene expression profile. Evidence for differentially expressed gene transcript isoforms was obtained for 162 genes. H1 histones were differentially expressed, raising the possibility of alternative chromatin packaging. The most abundant tag from dauer larvae (20-fold more abundant than in the nondauer profile) corresponds to a new, unpredicted gene we have named tts-1 (transcribed telomere-like sequence), which may interact with telomeres or telomere-associated proteins. Abundant antisense mitochondrial transcripts (2% of all tags), suggest the existence of an antisense-mediated regulatory mechanism in C. elegans mitochondria. In addition to providing a robust tool for gene expression studies, the SAGE approach already has provided the advantage of new gene/transcript discovery in a metazoan.

Discovering common stem-loop motifs in unaligned RNA sequences

Post-transcriptional regulation of gene expression is often accomplished by proteins binding to specific sequence motifs in mRNA molecules, to affect their translation or stability. The motifs are often composed of a combination of sequence and structural constraints such that the overall structure is preserved even though much of the primary sequence is variable. While several methods exist to discover transcriptional regulatory sites in the DNA sequences of coregulated genes, the RNA motif discovery problem is much more difficult because of covariation in the positions. We describe the combined use of two approaches for RNA structure prediction, FOLDALIGN and COVE, that together can discover and model stem-loop RNA motifs in unaligned sequences, such as UTRs from post-transcriptionally coregulated genes. We evaluate the method on two datasets, one a section of rRNA genes with randomly truncated ends so that a global alignment is not possible, and the other a hyper-variable collection of IRE-like elements that were inserted into randomized UTR sequences. In both cases the combined method identified the motifs correctly, and in the rRNA example we show that it is capable of determining the structure, which includes bulge and internal loops as well as a variable length hairpin loop. Those automated results are quantitatively evaluated and found to agree closely with structures contained in curated databases, with correlation coefficients up to 0.9. A basic server, Stem-Loop Align SearcH (SLASH), which will perform stem-loop searches in unaligned RNA sequences, is available at http://www.bioinf.au.dk/slash/.