Determination and inference of eukaryotic transcription factor sequence specificity.

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

doi:10.1016/j.cell.2014.08.009

Determination and inference of eukaryotic transcription factor sequence specificity.

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-HoyesSridhar Govindarajan, Gad Shaulsky, Albertha J.M. Walhout, François Yves Bouget, Gunnar Ratsch, Luis F. Larrondo, Joseph R. Ecker, Timothy R. Hughes

Research output: Contribution to journal › Article › peer-review

1180 Scopus citations

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.

Original language	English
Pages (from-to)	1431-1443
Number of pages	13
Journal	Cell
Volume	158
Issue number	6
DOIs	https://doi.org/10.1016/j.cell.2014.08.009
State	Published - 2014
Externally published	Yes

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Weirauch, M. T., Yang, A., Albu, M., Cote, A. G., Montenegro-Montero, A., Drewe, P., Najafabadi, H. S., Lambert, S. A., Mann, I., Cook, K., Zheng, H., Goity, A., van Bakel, H., Lozano, J. C., Galli, M., Lewsey, M. G., Huang, E., Mukherjee, T., Chen, X., ... Hughes, T. R. (2014). Determination and inference of eukaryotic transcription factor sequence specificity. Cell, 158(6), 1431-1443. https://doi.org/10.1016/j.cell.2014.08.009

@article{e3503716df6947fcaa58b04654ec0971,

title = "Determination and inference of eukaryotic transcription factor sequence specificity.",

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.",

author = "Weirauch, {Matthew T.} and Ally Yang and Mihai Albu and Cote, {Atina G.} and Alejandro Montenegro-Montero and Philipp Drewe and Najafabadi, {Hamed S.} and Lambert, {Samuel A.} and Ishminder Mann and Kate Cook and Hong Zheng and Alejandra Goity and {van Bakel}, Harm and Lozano, {Jean Claude} and Mary Galli and Lewsey, {Mathew G.} and Eryong Huang and Tuhin Mukherjee and Xiaoting Chen and Reece-Hoyes, {John S.} and Sridhar Govindarajan and Gad Shaulsky and Walhout, {Albertha J.M.} and Bouget, {Fran{\c c}ois Yves} and Gunnar Ratsch and Larrondo, {Luis F.} and Ecker, {Joseph R.} and Hughes, {Timothy R.}",

year = "2014",

doi = "10.1016/j.cell.2014.08.009",

language = "English",

volume = "158",

pages = "1431--1443",

journal = "Cell",

issn = "0092-8674",

publisher = "Elsevier B.V.",

number = "6",

}

Weirauch, MT, Yang, A, Albu, M, Cote, AG, Montenegro-Montero, A, Drewe, P, Najafabadi, HS, Lambert, SA, Mann, I, Cook, K, Zheng, H, Goity, A, van Bakel, H, Lozano, JC, Galli, M, Lewsey, MG, Huang, E, Mukherjee, T, Chen, X, Reece-Hoyes, JS, Govindarajan, S, Shaulsky, G, Walhout, AJM, Bouget, FY, Ratsch, G, Larrondo, LF, Ecker, JR & Hughes, TR 2014, 'Determination and inference of eukaryotic transcription factor sequence specificity.', Cell, vol. 158, no. 6, pp. 1431-1443. https://doi.org/10.1016/j.cell.2014.08.009

TY - JOUR

T1 - Determination and inference of eukaryotic transcription factor sequence specificity.

AU - Weirauch, Matthew T.

AU - Yang, Ally

AU - Albu, Mihai

AU - Cote, Atina G.

AU - Montenegro-Montero, Alejandro

AU - Drewe, Philipp

AU - Najafabadi, Hamed S.

AU - Lambert, Samuel A.

AU - Mann, Ishminder

AU - Cook, Kate

AU - Zheng, Hong

AU - Goity, Alejandra

AU - van Bakel, Harm

AU - Lozano, Jean Claude

AU - Galli, Mary

AU - Lewsey, Mathew G.

AU - Huang, Eryong

AU - Mukherjee, Tuhin

AU - Chen, Xiaoting

AU - Reece-Hoyes, John S.

AU - Govindarajan, Sridhar

AU - Shaulsky, Gad

AU - Walhout, Albertha J.M.

AU - Bouget, François Yves

AU - Ratsch, Gunnar

AU - Larrondo, Luis F.

AU - Ecker, Joseph R.

AU - Hughes, Timothy R.

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84907413210&partnerID=8YFLogxK

U2 - 10.1016/j.cell.2014.08.009

DO - 10.1016/j.cell.2014.08.009

M3 - Article

C2 - 25215497

AN - SCOPUS:84907413210

SN - 0092-8674

VL - 158

SP - 1431

EP - 1443

JO - Cell

JF - Cell

IS - 6

ER -

Determination and inference of eukaryotic transcription factor sequence specificity.

Abstract

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