RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

AbstractSeveral studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that are affected by DNA methylation. Overall, we find that CpG methylation decreases the likelihood of binding for the majority of TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding.

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Evaluating the impact of single nucleotide variants on transcription factor binding

Nucleic Acids Research ◽

10.1093/nar/gkw691 ◽

2016 ◽

pp. gkw691 ◽

Cited By ~ 13

Author(s):

Wenqiang Shi ◽

Oriol Fornes ◽

Anthony Mathelier ◽

Wyeth W. Wasserman

Keyword(s):

Transcription Factor ◽

Transcription Factor Binding ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Factor Binding ◽

The Impact

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BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes

10.1101/093393 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ines de Santiago ◽

Wei Liu ◽

Martin O’Reilly ◽

Ke Yuan ◽

Chandra Sekhar Reddy Chilamakuri ◽

...

Keyword(s):

Transcription Factor ◽

Copy Number ◽

Phenotypic Diversity ◽

Transcription Factor Binding ◽

Joint Analysis ◽

Factor Binding ◽

Regulatory Variants ◽

Cancer Genomes ◽

Allele Specific ◽

Copy Number Changes

AbstractAllele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods to detect allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and 6 targeted FAIRE-seq samples we show that BaalChIP effectively corrects allele-specific analysis for copy number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.

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Uncovering divergence in gene expression regulation in the adaptation of yeast to nitrogen scarcity

10.1101/2021.04.15.440091 ◽

2021 ◽

Author(s):

Carlos A. Villarroel ◽

Paulo Canessa ◽

Macarena Bastias ◽

Francisco A Cubillos

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Gene Expression Regulation ◽

Transcription Factor Binding ◽

Chromatin Accessibility ◽

Expression Regulation ◽

Factor Binding ◽

Allele Specific ◽

The Impact ◽

Allelic Bias

Saccharomyces cerevisiae rewires its transcriptional output to survive stressful environments, such as nitrogen scarcity under fermentative conditions. Although divergence in nitrogen metabolism has been described among natural yeast populations, the impact of regulatory genetic variants modulating gene expression and nitrogen consumption remains to be investigated. Here, we employed an F1 hybrid from two contrasting S. cerevisiae strains, providing a controlled genetic environment to map cis factors involved in the divergence of gene expression regulation in response to nitrogen scarcity. We used a dual approach to obtain genome-wide allele-specific profiles of chromatin accessibility, transcription factor binding, and gene expression through ATAC-seq and RNA-seq. We observed large variability in allele-specific expression and accessibility between the two genetic backgrounds, with a third of these differences specific to a deficient nitrogen environment. Furthermore, we discovered events of allelic bias in gene expression correlating with allelic bias in transcription factor binding solely under nitrogen scarcity, where the majority of these transcription factors orchestrates the Nitrogen Catabolite Repression regulatory pathway and demonstrates a cis x environment-specific response. Our approach allowed us to find cis variants modulating gene expression, chromatin accessibility and allelic differences in transcription factor binding in response to low nitrogen culture conditions.

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Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

Genome Research ◽

10.1101/gr.220202.117 ◽

2017 ◽

Vol 27 (10) ◽

pp. 1730-1742 ◽

Cited By ~ 13

Author(s):

Ron Schwessinger ◽

Maria C. Suciu ◽

Simon J. McGowan ◽

Jelena Telenius ◽

Stephen Taylor ◽

...

Keyword(s):

Transcription Factor ◽

Transcription Factor Binding ◽

Tissue Specific ◽

Factor Binding ◽

The Impact ◽

Regulatory Snps

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Plasticity of Naturally Occurring Regulatory T Cells in Allergic Airway Disease Is Modulated by the Transcriptional Activity of Il-6

International Journal of Molecular Sciences ◽

10.3390/ijms22094582 ◽

2021 ◽

Vol 22 (9) ◽

pp. 4582

Author(s):

Morgan MacBeth ◽

Anthony Joetham ◽

Erwin W. Gelfand ◽

Michaela Schedel

Keyword(s):

T Cells ◽

Transcription Factor ◽

Regulatory T Cells ◽

Molecular Mechanisms ◽

Transcription Factor Binding ◽

Allergic Airway Disease ◽

Luciferase Reporter ◽

Factor Binding ◽

Naturally Occurring ◽

The Impact

The impact of naturally occurring regulatory T cells (nTregs) on the suppression or induction of lung allergic responses in mice depends on the nuclear environment and the production of the pro-inflammatory cytokine interleukin 6 (IL-6). These activities were shown to be different in nTregs derived from wild-type (WT) and CD8-deficient mice (CD8−/−), with increased IL-6 levels in nTregs from CD8−/− mice in comparison to WT nTregs. Thus, identification of the molecular mechanisms regulating IL-6 production is critical to understanding the phenotypic plasticity of nTregs. Electrophoretic mobility shift assays (EMSA) were performed to determine transcription factor binding to four Il-6 promoter loci using nuclear extracts from nTregs of WT and CD8−/− mice. Increased transcription factor binding for each of the Il-6 loci was identified in CD8−/− compared to WT nTregs. The impact of transcription factor binding and a novel short tandem repeat (STR) on Il-6 promoter activity was analyzed by luciferase reporter assays. The Il-6 promoter regions closer to the transcription start site (TSS) were more relevant to the regulation of Il-6 depending on NF-κB, c-Fos, and SP and USF family members. Two Il-6 promoter loci were most critical for the inducibility by lipopolysaccharide (LPS) and tumor necrosis factor α (TNFα). A novel STR of variable length in the Il-6 promoter was identified with diverging prevalence in nTregs from WT or CD8−/− mice. The predominant GT repeat in CD8−/− nTregs revealed the highest luciferase activity. These novel regulatory mechanisms controlling the transcriptional regulation of the Il-6 promoter are proposed to contribute to nTregs plasticity and may be central to disease pathogenesis.

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Positional weight matrices have sufficient prediction power for analysis of noncoding variants

F1000Research ◽

10.12688/f1000research.75471.1 ◽

2022 ◽

Vol 11 ◽

pp. 33

Author(s):

Alexandr Boytsov ◽

Sergey Abramov ◽

Vsevolod J. Makeev ◽

Ivan V. Kulakovskiy

Keyword(s):

Transcription Factor ◽

Transcription Factor Binding ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Factor Binding ◽

Regulatory Variants ◽

Scoring Matrix ◽

Regulatory Potential ◽

The Rich ◽

Positional Weight

The commonly accepted model to quantify the specificity of transcription factor binding to DNA is the position weight matrix, also called the position-specific scoring matrix. Position weight matrices are used in thousands of projects and computational tools in regulatory genomics, including prediction of the regulatory potential of single-nucleotide variants. Yet, recently Yan et al. presented new experimental method for analysis of regulatory variants and, based on its results, reported that "the position weight matrices of most transcription factors lack sufficient predictive power". Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can successfully quantify transcription factor binding to alternative alleles.

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Interplay of cis and trans mechanisms driving transcription factor binding and gene expression evolution

10.1101/059873 ◽

2016 ◽

Author(s):

Emily S Wong ◽

Bianca M Schmitt ◽

Anastasiya Kazachenka ◽

David Thybert ◽

Aisling Redmond ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Inbred Mouse ◽

Transcription Factor Binding ◽

Regulatory Mechanisms ◽

Mouse Strains ◽

Cis Acting ◽

Factor Binding ◽

Regulatory Variants ◽

Transcription Factor Occupancy

AbstractNoncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states.

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