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| Title |
Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity
|
|---|---|
| Published in |
Cell, September 2014
|
| DOI | 10.1016/j.cell.2014.08.009 |
| Pubmed ID | |
| Authors |
Matthew T. Weirauch, Ally Yang, Mihai Albu, Atina G. Cote, Alejandro Montenegro-Montero, Philipp Drewe, Hamed S. Najafabadi, Samuel A. Lambert, Ishminder Mann, Kate Cook, Hong Zheng, Alejandra Goity, Harm van Bakel, Jean-Claude Lozano, Mary Galli, Mathew G. Lewsey, Eryong Huang, Tuhin Mukherjee, Xiaoting Chen, John S. Reece-Hoyes, Sridhar Govindarajan, Gad Shaulsky, Albertha J.M. Walhout, François-Yves Bouget, Gunnar Ratsch, Luis F. Larrondo, Joseph R. Ecker, Timothy R. Hughes |
| 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. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 15% |
| Canada | 3 | 7% |
| Ireland | 1 | 2% |
| Switzerland | 1 | 2% |
| Belgium | 1 | 2% |
| Hungary | 1 | 2% |
| Comoros | 1 | 2% |
| Denmark | 1 | 2% |
| United Kingdom | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 23 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 26 | 63% |
| Members of the public | 13 | 32% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,151 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | <1% |
| France | 6 | <1% |
| Germany | 4 | <1% |
| Spain | 4 | <1% |
| Chile | 2 | <1% |
| Sweden | 2 | <1% |
| Mexico | 2 | <1% |
| United Kingdom | 2 | <1% |
| Brazil | 1 | <1% |
| Other | 10 | <1% |
| Unknown | 1107 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 306 | 27% |
| Researcher | 216 | 19% |
| Student > Master | 109 | 9% |
| Student > Bachelor | 101 | 9% |
| Professor > Associate Professor | 47 | 4% |
| Other | 168 | 15% |
| Unknown | 204 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 450 | 39% |
| Biochemistry, Genetics and Molecular Biology | 345 | 30% |
| Computer Science | 40 | 3% |
| Medicine and Dentistry | 25 | 2% |
| Neuroscience | 14 | 1% |
| Other | 66 | 6% |
| Unknown | 211 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 58. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2023.
All research outputs
#770,027
of 26,378,648 outputs
Outputs from Cell
#3,331
of 17,480 outputs
Outputs of similar age
#7,194
of 249,675 outputs
Outputs of similar age from Cell
#47
of 149 outputs
Altmetric has tracked 26,378,648 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,480 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 60.9. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 249,675 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 149 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.