4.8 Article

Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity

Journal

CELL
Volume 158, Issue 6, Pages 1431-1443

Publisher

CELL PRESS
DOI: 10.1016/j.cell.2014.08.009

Keywords

-

Funding

  1. Canadian Institutes of Health Research [MOP-77721, MOP-111007]
  2. CIHR
  3. Canadian Institute for Advanced Research (CIFAR) Junior Fellows Genetic Networks Program
  4. NIH/NICHD [P01 HD39691]
  5. NIH [GM082971]
  6. EU Marie Curie International Outgoing Fellowship [252475]
  7. National Science Foundation (NSF) [MCB-1024999]
  8. Howard Hughes Medical Institute
  9. Gordon and Betty Moore Foundation [GBMF 3034]
  10. Millennium Nucleus for Fungal Integrative and Synthetic Biology [NC120043]
  11. Fondo Nacional de Desarrollo Cientifico y Tecnologico [FONDECYT 1131030]
  12. Direct For Biological Sciences
  13. Div Of Molecular and Cellular Bioscience [1024999] Funding Source: National Science Foundation

Ask authors/readers for more resources

Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only similar to 1% of eukaryotic TFs. Broadly sampling DNA-binding domain (DBD) types from multiple eukaryotic clades, we determined DNA sequence preferences for >1,000 TFs encompassing 54 different DBD classes from 131 diverse eukaryotes. We find that closely related DBDs almost always have very similar DNA sequence preferences, enabling inference of motifs for similar to 34% of the similar to 170,000 known or predicted eukaryotic TFs. Sequences matching both measured and inferred motifs are enriched in chromatin immunoprecipitation sequencing (ChIP-seq) peaks and upstream of transcription start sites in diverse eukaryotic lineages. SNPs defining expression quantitative trait loci in Arabidopsis promoters are also enriched for predicted TF binding sites. Importantly, our motif library can be used to identify specific TFs whose binding may be altered by human disease risk alleles. These data present a powerful resource for mapping transcriptional networks across eukaryotes.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available