CoChat
Sign Up
Cited by 3,399Genomics and Chromatin DynamicsGene Regulatory Network AnalysisGenetic Associations and Epidemiology

The Human Transcription Factors

Open access
Lambert, Samuel A., Jolma, Arttu, Campitelli, Laura F., Das, Pratyush K., Yin, Yimeng, Albu, Mihai, Chen, Xiaoting, Taipale, Jussi +2 more·2018·Cell
DOI 10.1016/j.cell.2018.01.029PMC PMC12908702
Open this paper in CoChat — free accountOpen PDF

Abstract

Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them. Major classes of human TFs differ markedly in their evolutionary trajectories and expression patterns, underscoring distinct functions. TFs likewise underlie many different aspects of human physiology, disease, and variation, highlighting the importance of continued effort to understand TF-mediated gene regulation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cell.2018.01.029

Cites

128 of 141 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • More than 2000 transcription factors, and 1600 in humans, have been characterized in cells.

    “Nevertheless, on the other hand, since the first discovery of the Retinoblastoma tumor suppressor gene 1 (RB1), a transcriptional factor with demethylation capacities, if we consider that to date, more than 2000 transcription factors and 1600 in humans [60] have been characterized in cells, only a small number of them have been related with demethylation or methylation.”

    From Revisiting Epigenetics Fundamentals and Its Biomedical Implications (2024) · cites this paper as [60]

    The human TF repertoire section reports 1,639 known or likely human transcription factors, supporting the approximate figure of 1,600. It does not establish the claim of more than 2,000 transcription factors overall, and its 'known or likely' tally does not mean every factor has been characterized in cells. No page number is available in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Only a small number of characterized transcription factors have been related to demethylation or methylation.

    “Nevertheless, on the other hand, since the first discovery of the Retinoblastoma tumor suppressor gene 1 (RB1), a transcriptional factor with demethylation capacities, if we consider that to date, more than 2000 transcription factors and 1600 in humans [60] have been characterized in cells, only a small number of them have been related with demethylation or methylation.”

    From Revisiting Epigenetics Fundamentals and Its Biomedical Implications (2024) · cites this paper as [60]

    The human TF repertoire section reports 1,639 known or likely human transcription factors, supporting the approximate human count beside the citation. It does not say that only a small number have been related to methylation or demethylation; searches for those terms found no such comparison in the paper’s discussion. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Transcription factors play crucial roles in regulating gene expression.

    “Transcription factors play crucial roles in regulating gene expression, a fundamental process essential for all cellular functions [12].”

    From Targeting Microglial Transcriptional Reprogramming as a Therapy Strategy for Alzheimer's Disease (2026) · cites this paper as [12]

  • Transcription factors modulate the expression of multiple downstream targets in intricately coordinated and co-regulated pathways.

    “Transcription factors by nature modulate the expression of multiple downstream targets in intricately coordinated and co‐regulated pathways [12, 14].”

    From Targeting Microglial Transcriptional Reprogramming as a Therapy Strategy for Alzheimer's Disease (2026) · cites this paper as [12]

  • The natural genome contains only few instances of many TF combinations and binding site arrangements and is statistically underpowered to learn the rules by which it is decoded.

    “it has been argued that the natural genome contains only few instances of many TF combinations and binding site arrangements, and it is in a statistical sense underpowered to “learn the rules by which it is decoded.”28,29”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [28]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 21

  1. Hu S, Xie Z, Onishi A, Yu X, Jiang L, Lin J, Rho HS, Woodard C, Wang H, Jeong JS, (2009). Profiling the human protein-DNA interactome reveals ERK2 as a transcriptional repressor of interferon signaling. Cell 139, 610– 622. 19879846 PMC2774939
  2. Johnson DS, Mortazavi A, Myers RM, and Wold B (2007). Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497– 1502. 17540862
  3. Najafabadi HS, Mnaimneh S, Schmitges FW, Garton M, Lam KN, Yang A, Albu M, Weirauch MT, Radovani E, Kim PM, (2015). C2H2 zinc finger proteins greatly expand the human regulatory lexicon. Nat Biotechnol. 25690854
  4. Reece-Hoyes JS, and Walhout AJ (2012). Yeast one-hybrid assays: a historical and technical perspective. Methods 57, 441– 447. 22884952 PMC3448804
  5. Rhee HS, and Pugh BF (2011). Comprehensive Genome-wide Protein-DNA Interactions Detected at Single-Nucleotide Resolution. Cell 147, 1408– 1419. 22153082 PMC3243364
  6. Slattery M, Riley T, Liu P, Abe N, Gomez-Alcala P, Dror I, Zhou T, Rohs R, Honig B, Bussemaker HJ, (2011). Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins. Cell 147, 1270– 1282. 22153072 PMC3319069
  7. Wei GH, Badis G, Berger MF, Kivioja T, Palin K, Enge M, Bonke M, Jolma A, Varjosalo M, Gehrke AR, (2010). Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo. EMBO J. PMC2905244 20517297
  8. Yin Y, Morgunova E, Jolma A, Kaasinen E, Sahu B, Khund-Sayeed S, Das PK, Kivioja T, Dave K, Zhong F, (2017). Impact of cytosine methylation on DNA binding specificities of human transcription factors. Science 356. PMC8009048 28473536
  9. [1]Fried M & Crothers DM Equilibria and kinetics of lac repressor-operator interactions by polyacrylamide gel electrophoresis. Nucleic acids research 9, 6505– 6525 (1981). 6275366 PMC327619
  10. [2]Oliphant AR, Brandl CJ & Struhl K Defining the sequence specificity of DNA-binding proteins by selecting binding sites from random-sequence oligonucleotides: analysis of yeast GCN4 protein. Mol Cell Biol 9, 2944– 2949 (1989). 2674675 PMC362762
  11. [3]Tuerk C & Gold L Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249, 505– 510 (1990). 2200121
  12. [5]Galas DJ & Schmitz A DNAse footprinting: a simple method for the detection of protein-DNA binding specificity. Nucleic acids research 5, 3157– 3170 (1978). 212715 PMC342238
  13. [6]Tullius TD, Dombroski BA, Churchill ME & Kam L Hydroxyl radical footprinting: a high-resolution method for mapping protein-DNA contacts. Methods Enzymol 155, 537– 558 (1987). 2828876
  14. [7]Kadonaga JT & Tjian R Affinity purification of sequence-specific DNA binding proteins. Proceedings of the National Academy of Sciences of the United States of America 83, 5889– 5893 (1986). 3461465 PMC386402
  15. [8]Liang Y Applications of isothermal titration calorimetry in protein science. Acta biochimica et biophysica Sinica 40, 565– 576 (2008). 18604448
  16. [9]Majka J & Speck C Analysis of protein-DNA interactions using surface plasmon resonance. Advances in biochemical engineering/biotechnology 104, 13– 36 (2007). 17290817
  17. [10]Zhang W, Duhr S, Baaske P & Laue E Microscale thermophoresis for the assessment of nuclear protein-binding affinities. Methods Mol Biol 1094, 269– 276, doi: 10.1007/978-1-62703-706-8_21 (2014). 24162995 · DOI
  18. [14]Wu F, Olson BG & Yao J DamID-seq: Genome-wide Mapping of Protein-DNA Interactions by High Throughput Sequencing of Adenine-methylated DNA Fragments. Journal of visualized experiments: JoVE, e53620, doi: 10.3791/53620 (2016). 26862720 PMC4781701 · DOI
  19. [17]Noyes MB Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites. Cell 133, 1277– 1289 (2008). 18585360 PMC2478728
  20. [33]Hallikas O Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity. Cell 124, 47– 59 (2006). 16413481
  21. [34]Hallikas O & Taipale J High-throughput assay for determining specificity and affinity of protein-DNA binding interactions. Nat Protoc 1, 215– 222 (2006). 17406235

Cited by

Sorted by citations

Related

Authors
Lambert, S. A., Jolma, A., Campitelli, L. F., Das, P. K., Yin, Y., Albu, M., Chen, X., Taipale, J., Hughes, T. R., & Weirauch, M. T.
Affiliations
  • University of Toronto (CA)
  • University of Helsinki (FI)
  • Karolinska Institutet (SE)
  • Cincinnati Children's Hospital Medical Center (US)
Corresponding author
  • Taipale, Jussi
  • Hughes, Timothy R.
  • Weirauch, Matthew T.
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2018-02
Volume
172
Issue
4
Pages
650-665
ISSN
0092-8674 (ISSN-L)
DOI
10.1016/j.cell.2018.01.029
PMC
PMC12908702
OpenAlex
W2785792383
Cited by
3,399
References
129
Citations by year
2026: 341 · 2025: 508 · 2024: 576 · 2023: 521 · 2022: 493 · 2021: 410 · 2020: 282 · 2019: 190 · 2018: 72 · 2017: 1 · 2016: 1 · 2013: 1
FWCI
23.47
Type
journal article
Language
en
Update notices
erratum (2018-10-04)
Open access
Licence
Locations
  • Cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion)
Funders
  • NIH (R01 NS099068-01A1)
  • Lupus Research Alliance
  • Cincinnati Children’s Hospital
  • CIHR Foundation
  • Swedish Research Council (2016-00158)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
transcription factors, transcription factor binding motifs, DNA binding specificity, gene expression regulation, chromatin regulation, transcription factor evolution
MeSH terms
Gene Expression Regulation, Humans, Transcription Factors, Evolution, Molecular, Response Elements, Amino Acid Motifs

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review