Dataset Information

Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

ABSTRACT: The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-seq data from Phase II of the ENCODE Project. Here we present an update to Factorbook which significantly expands the breadth of cell type and TF coverage. The update includes an expanded motif catalog derived from thousands of ENCODE Phase II and III ChIP-seq experiments and HT-SELEX experiments; this motif catalog is integrated with the ENCODE registry of candidate cis-regulatory elements to annotate a comprehensive collection of genome-wide candidate TF binding sites. The database also offers novel tools for applying the motif models within machine learning frameworks and using these models for integrative analysis, including annotation of variants and disease and trait heritability. Factorbook is publicly available at www.factorbook.org; we will continue to expand the resource as ENCODE Phase IV data are released.

SUBMITTER: Pratt HE

PROVIDER: S-EPMC8728199 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

Pratt Henry E HE Andrews Gregory R GR Phalke Nishigandha N Huey Jack D JD Purcaro Michael J MJ van der Velde Arjan A Moore Jill E JE Weng Zhiping Z

Nucleic acids research 20220101 D1

The human genome contains ∼2000 transcriptional regulatory proteins, including ∼1600 DNA-binding transcription factors (TFs) recognizing characteristic sequence motifs to exert regulatory effects on gene expression. The binding specificities of these factors have been profiled both in vitro, using techniques such as HT-SELEX, and in vivo, using techniques including ChIP-seq. We previously developed Factorbook, a TF-centric database of annotations, motifs, and integrative analyses based on ChIP-s ...[more]

PMID: 34755879

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Project description:BackgroundClassically, models of DNA-transcription factor binding sites (TFBSs) have been based on relatively few known instances and have treated them as sites of fixed length using position weight matrices (PWMs). Various extensions to this model have been proposed, most of which take account of dependencies between the bases in the binding sites. However, some transcription factors are known to exhibit some flexibility and bind to DNA in more than one possible physical configuration. In some cases this variation is known to affect the function of binding sites. With the increasing volume of ChIP-seq data available it is now possible to investigate models that incorporate this flexibility. Previous work on variable length models has been constrained by: a focus on specific zinc finger proteins in yeast using restrictive models; a reliance on hand-crafted models for just one transcription factor at a time; and a lack of evaluation on realistically sized data sets.ResultsWe re-analysed binding sites from the TRANSFAC database and found motivating examples where our new variable length model provides a better fit. We analysed several ChIP-seq data sets with a novel motif search algorithm and compared the results to one of the best standard PWM finders and a recently developed alternative method for finding motifs of variable structure. All the methods performed comparably in held-out cross validation tests. Known motifs of variable structure were recovered for p53, Stat5a and Stat5b. In addition our method recovered a novel generalised version of an existing PWM for Sp1 that allows for variable length binding. This motif improved classification performance.ConclusionsWe have presented a new gapped PWM model for variable length DNA binding sites that is not too restrictive nor over-parameterised. Our comparison with existing tools shows that on average it does not have better predictive accuracy than existing methods. However, it does provide more interpretable models of motifs of variable structure that are suitable for follow-up structural studies. To our knowledge, we are the first to apply variable length motif models to eukaryotic ChIP-seq data sets and consequently the first to show their value in this domain. The results include a novel motif for the ubiquitous transcription factor Sp1.

Dataset Information

Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

Publications

Factorbook: an updated catalog of transcription factor motifs and candidate regulatory motif sites.

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