ArticleCell2014
Determination and inference of eukaryotic transcription factor sequence specificity.
Article in Cell, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,190 papers.
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Who cites it
1,190 citing papers in PubMed, 2,002 citations in OpenAlex.
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- GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors.Nature methods · 2026Article
- Base-pair resolution conservation data improves cell type specific sequence-to-expression prediction.Bioinformatics (Oxford, England) · 2026Article
- Deep Learning for Deciphering the Plant Cis-Regulatory Code.Plants (Basel, Switzerland) · 2026Review
- Multi-omics dissection of FOXA1 reveals cancer-type-specific transcriptional networks and functional risk variants.iScience · 2026Article
1,130 more citing papers are in PubMed but not listed here.
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Authors and funding
28 authors at 10 institutions in 4 countries.
Funding
Abstract
Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only ∼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 ∼34% of the ∼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.
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