Total Binding Affinity Profiles of Regulatory Regions Predict Transcription Factor Binding and Gene Expression in Human Cells

Grassi, Elena; Zapparoli, Ettore; Molineris, Ivan; Provero, Paolo

doi:10.1371/journal.pone.0143627

Cited by 18 publications

(18 citation statements)

References 28 publications

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“…Another way to characterize binding sites is through their Total Binding Affinity (TBA; [19,20]), scanning each binding region to produce a cumulative score based on the quality of motif match and the number of motif matches. Similar to the situation with motif enrichment, we see a clear correspondence between TBA and chromatin accessibility distribution.…”

Section: Resultsmentioning

confidence: 99%

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Chromatin Accessibility Plays a Key Role in Selective Targeting of Hox Proteins

Porcelli

Fischer

Russell

et al. 2018

Preprint

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Hox protein transcription factors specify segmental diversity along the anterior-posterior body axis in metazoans. Understanding the basis of Hox function has long faced the problem that, while the different members of the Hox family show clear functional specificity in vivo, they all show very similar binding specificity in vitro. Based on in vitro studies, cofactors may increase Hox binding selectivity however a satisfactory understanding of in vivo Hox target selectivity is still lacking. We have carried out a systematic analysis of the in vivo genomic binding profiles of all eight Drosophila Hox proteins using transient transfection in Kc167 cells to examine Hox protein targeting. We find that Hox proteins show considerable binding selectivity in vivo in the absence of the canonical Hox cofactors Extradenticle and Homothorax. Hox binding selectivity is strongly associated with chromatin accessibility; binding sites in less accessible chromatin show the highest selectivity and the different Hox proteins exhibit different propensities to bind less accessible chromatin. High Hox binding selectivity is also associated with high affinity binding regions, leading to a model where Hox proteins derive binding selectivity through an affinity-based competition with nucleosomes. Provision of the Extradenticle/Homothorax cofactors generally leads to an increase in the number of Hox binding regions and promotes the binding to regions in less accessible chromatin, however the provision of these cofactors has little effect on the overall selectivity of Hox targeting. These studies indicate that chromatin accessibility plays a key role in Hox selectivity and we propose that relative chromatin accessibility provides a basis for subtle differences in binding specificity and affinity to generate significantly different sets of genomic targets for different Hox proteins. We suggest that this mechanism may also be relevant to other transcription factor families.

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Section: Resultsmentioning

confidence: 99%

“…Jaspar Hox PWMs were truncated to 7-mers for Total Binding Affinity (TBA; [20]), Hox site counting and maxScore analysis. We then combined the PWMs of Lab, Pb, Dfd, Scr, Antp, Ubx, Abd-A to a new PWM HoxA and renamed Abd-B to HoxB.…”

Section: Methodsmentioning

confidence: 99%

Chromatin Accessibility Plays a Key Role in Selective Targeting of Hox Proteins

Porcelli

Fischer

Russell

et al. 2018

Preprint

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“…Several of the identified non-coding driver candidates are associated with chromatin regulation, either through association to regulatory genes (e.g., TOX3 intronic enhancer) or as binding sites for chromatin regulators (e.g., both PAX5 enhancers and CTCF TFBS near MAPRE3). In addition, the full set of cohesin binding sites show elevated mutation rates 34 , though micro-environment specific mutational processes may potentially underlie most of these 66 . This could suggest a potential role of non-coding mutations in shaping chromatin structure during cancer development, which is supported by the recent finding of chromatin-affecting non-coding mutations that create a superenhancer in lymphoblastic leukemia 42 .…”

Section: Discussionmentioning

confidence: 99%

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival

Hornshøj

Nielsen

Sinnott‐Armstrong

et al. 2017

Preprint

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Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Noncoding mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC wholegenomes from ten cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g. TERT and CDH10) and survival (e.g. CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4,128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217 and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. This screen for significant mutation patterns followed by correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

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“…We assembled a comprehensive set of putative regulators for each gene by compiling TF binding information in human cells from seven different data repositories comprising (i) MetaCore TM [41] with annotated "direct", "indirect" and "unspecific" interactions, (ii) the ChIP Enrichment Analysis (ChEA) database [42] Binding Affinity (TBA) [46]. TBA estimates the binding probability of a TF to the whole range of a gene's promoter.…”

Section: Assembling Transcription Factor Binding Information Into a Gmentioning

confidence: 99%

Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach

Poos

Kordaß

Kolte

et al. 2019

Preprint

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Background: Reactivation of the telomerase reverse transcriptase gene TERT is a central feature for the unlimited proliferation potential of the majority of cancers but the underlying regulatory processes are only partly understood. Results:We assembled regulator binding information from different sources to construct a generic human and mouse regulatory network. Advancing our "Mixed Integer linear Programming based Regulatory Interaction Predictor" (MIPRIP) approach, we identified the most common and cancer-type specific regulators of TERT across 19 different human cancers. The results were validated by using the wellknown TERT regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the TERT promoter. Conclusion:Our improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at https://github.com/networkmodeling/MIPRIP. MIPRIP 2.0 identified both common as well as tumor type specific regulators of TERT. The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease/condition under investigation.

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Total Binding Affinity Profiles of Regulatory Regions Predict Transcription Factor Binding and Gene Expression in Human Cells

Cited by 18 publications

References 28 publications

Chromatin Accessibility Plays a Key Role in Selective Targeting of Hox Proteins

Chromatin Accessibility Plays a Key Role in Selective Targeting of Hox Proteins

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival

Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach

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