GSBS Student Publications

UMMS Affiliation

Graduate School of Biomedical Sciences; Program in Gene Function and Expression; Program in Molecular Medicine

Date

1-20-2006

Document Type

Article

Medical Subject Headings

Animals; Caenorhabditis elegans; Computational Biology; Databases, Genetic; Dimerization; Genes, Helminth; Genes, Regulator; Helminth Proteins; Humans; Open Reading Frames; Promoter Regions (Genetics); Protein Interaction Mapping; Protein Structure, Tertiary; RNA Splicing; Transcription Factors; *Transcription, Genetic

Disciplines

Life Sciences | Medicine and Health Sciences

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.

Rights and Permissions

Citation: Genome Biol. 2005;6(13):R110. Epub 2005 Dec 30. Link to article on publisher's site

Related Resources

Link to article in PubMed

Journal Title

Genome biology

PubMed ID

16420670

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.