The significance of alternative transcripts for Caenorhabditis elegans transcription factor genes, based on expression pattern analysis.

BACKGROUND: Sequence-specific DNA-binding proteins, with their paramount importance in the regulation of expression of the genetic material, are encoded by approximately 5% of the genes in an animal's genome. But it is unclear to what extent alternative transcripts from these genes may further increase the complexity of the transcription factor complement. RESULTS: Of the 938 potential C. elegans transcription factor genes, 197 were annotated in WormBase as encoding at least two distinct isoforms. Evaluation of prior evidence identified, with different levels of confidence, 50 genes with alternative transcript starts, 23 with alternative transcript ends, 35 with alternative splicing and 34 with alternative transcripts generated by a combination of mechanisms, leaving 55 that were discounted. Expression patterns were determined for transcripts for a sample of 29 transcription factor genes, concentrating on those with alternative transcript starts for which the evidence was strongest. Seamless fosmid recombineering was used to generate reporter gene fusions with minimal modification to assay expression of specific transcripts while maintaining the broad genomic DNA context and alternative transcript production. Alternative transcription factor gene transcripts were typically expressed with identical or substantially overlapping distributions rather than in distinct domains. CONCLUSIONS: Increasingly sensitive sequencing technologies will reveal rare transcripts but many of these are clearly non-productive. The majority of the transcription factor gene alternative transcripts that are productive may represent tolerable noise rather than encoding functionally distinct isoforms.

Expression pattern analysis of regulatory transcription factors in Caenorhabditis elegans.

Expression pattern data are fundamental to understanding transcriptional regulatory networks and the biological significance of such networks. For Caenorhabditis elegans, expression pattern analysis of transcription factor genes, with cellular resolution, typically involves generation of transcription factor gene/reporter gene fusions. This is followed by the creation of C. elegans strains transgenic for, and determination of expression patterns driven by, these fusions. Physiologically relevant regulatory relationships between transcription factors are both inferred from their expression patterns, in combination with protein-DNA interaction data, and evidenced from alterations of expression patterns when networks are disturbed.