A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

Abstract

Background: Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes.

Results: By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks.

Conclusion: wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

Figure 1

Transcription regulatory networks provide models to understand differential gene expression at a systems level. Transcription regulatory networks are composed of two types of components, or nodes: the genes involved in the system and the TFs that regulate their expression. Protein-protein interactions between TFs and protein-DNA interactions between TFs and their target genes can be visualized in transcription regulatory networks. The dashed line represents TF-TF protein-protein interaction (heterodimer). Arrows represent protein DNA interactions that result in transcription activation; the blunt 'arrow' represents protein-DNA interaction that results in repression of transcription.

Figure 2

Generation of wTF2.0, a comprehensive compendium of C. elegans TFs. Schematic overview of the wTF2.0 generation pipeline. See main text for details.

Figure 3

Venn diagram presenting the results of the GO term-based bioinformatic identification of putative TFs in WormBase 140. GO terms are indicated in each Venn diagram set. Numbers between parentheses represent the number of putative TFs retained in wTF2.0 after manual curation or DNA binding domain identification using InterPro v. 10.0.

Figure 4

Protein-protein interaction network of worm TFs. Blue rectangles indicate homodimers. Different colors identify different TF families as indicated. Interactions were obtained from Worm Interactome version 5 (WI5) [32] and visualized using Cytoscape [59].

Figure 5

wTF2.0 can be used to create clone resources that can be used to study the transcription regulatory networks controlling metazoan gene expression. TAG, epitope or purification tag; Y1H, yeast one-hybrid; Y2H, yeast two-hybrid.