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The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation

BACKGROUND: A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. An empirical approach in this regard is to compare the expression profiles of cells under two conditions or tissues from two phenotypes and to unravel the underlying transcript...

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Autores principales: Feng, Yance, Zhang, Sheng, Li, Liang, Li, Lei M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509875/
https://www.ncbi.nlm.nih.gov/pubmed/31074378
http://dx.doi.org/10.1186/s12859-019-2732-6
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author Feng, Yance
Zhang, Sheng
Li, Liang
Li, Lei M.
author_facet Feng, Yance
Zhang, Sheng
Li, Liang
Li, Lei M.
author_sort Feng, Yance
collection PubMed
description BACKGROUND: A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. An empirical approach in this regard is to compare the expression profiles of cells under two conditions or tissues from two phenotypes and to unravel the underlying transcriptional regulation. We have proposed the method BASE to statistically infer the effective regulatory factors that are responsible for the gene expression differentiation with the help from the binding data between factors and genes. Usually the protein-DNA binding data are obtained by ChIP-seq experiments, which could be costly and are condition-specific. RESULTS: Here we report a definition of binding strength based on a probability model. Using this condition-free definition, the BASE method needs only the frequencies of cis-motifs in regulatory regions, thereby the inferences can be carried out in silico. The directional regulation can be inferred by considering down- and up-regulation separately. We showed the effectiveness of the approach by one case study. In the study of the effects of polyunsaturated fatty acids (PUFA), namely, docosahexaenoic (DHA) and eicosapentaenoic (EPA) diets on mouse small intestine cells, the inferences of regulations are consistent with those reported in the literature, including PPARα and NFκB, respectively corresponding to enhanced adipogenesis and reduced inflammation. Moreover, we discovered enhanced RORA regulation of circadian rhythm, and reduced ETS1 regulation of angiogenesis. CONCLUSIONS: With the probabilistic definition of cis-trans binding affinity, the BASE method could obtain the significances of TF regulation changes corresponding to a gene expression differentiation profile between treatment and control samples. The landscape of the inferred cis-trans regulations is helpful for revealing the underlying molecular mechanisms. Particularly we reported a more comprehensive regulation induced by EPA&DHA diet. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2732-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-65098752019-06-05 The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation Feng, Yance Zhang, Sheng Li, Liang Li, Lei M. BMC Bioinformatics Research BACKGROUND: A key problem in systems biology is the determination of the regulatory mechanism corresponding to a phenotype. An empirical approach in this regard is to compare the expression profiles of cells under two conditions or tissues from two phenotypes and to unravel the underlying transcriptional regulation. We have proposed the method BASE to statistically infer the effective regulatory factors that are responsible for the gene expression differentiation with the help from the binding data between factors and genes. Usually the protein-DNA binding data are obtained by ChIP-seq experiments, which could be costly and are condition-specific. RESULTS: Here we report a definition of binding strength based on a probability model. Using this condition-free definition, the BASE method needs only the frequencies of cis-motifs in regulatory regions, thereby the inferences can be carried out in silico. The directional regulation can be inferred by considering down- and up-regulation separately. We showed the effectiveness of the approach by one case study. In the study of the effects of polyunsaturated fatty acids (PUFA), namely, docosahexaenoic (DHA) and eicosapentaenoic (EPA) diets on mouse small intestine cells, the inferences of regulations are consistent with those reported in the literature, including PPARα and NFκB, respectively corresponding to enhanced adipogenesis and reduced inflammation. Moreover, we discovered enhanced RORA regulation of circadian rhythm, and reduced ETS1 regulation of angiogenesis. CONCLUSIONS: With the probabilistic definition of cis-trans binding affinity, the BASE method could obtain the significances of TF regulation changes corresponding to a gene expression differentiation profile between treatment and control samples. The landscape of the inferred cis-trans regulations is helpful for revealing the underlying molecular mechanisms. Particularly we reported a more comprehensive regulation induced by EPA&DHA diet. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2732-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-01 /pmc/articles/PMC6509875/ /pubmed/31074378 http://dx.doi.org/10.1186/s12859-019-2732-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Feng, Yance
Zhang, Sheng
Li, Liang
Li, Lei M.
The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title_full The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title_fullStr The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title_full_unstemmed The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title_short The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
title_sort cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509875/
https://www.ncbi.nlm.nih.gov/pubmed/31074378
http://dx.doi.org/10.1186/s12859-019-2732-6
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