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BANCseq for determination of genome-wide apparent transcription factor binding affinities

ABSTRACT: BANCseq for determination of genome-wide apparent transcription factor binding affinities

PROVIDER: PRJNA906616 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17587600_1.fastq.gz	Fastqsanger.gz
	SRR17587600_2.fastq.gz	Fastqsanger.gz
	SRR17587601_1.fastq.gz	Fastqsanger.gz
	SRR17587601_2.fastq.gz	Fastqsanger.gz
	SRR17587602_1.fastq.gz	Fastqsanger.gz

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BANCseq for determination of genome-wide apparent transcription factor binding affinities

Project description:This SuperSeries is composed of the SubSeries listed below. In vivo transcription factor binding is regulated by DNA sequence and chromatin features. However, the impact of chromatin context on genome-wide transcription factor binding affinities have not yet been characterized. Here we report the establishment of a quantitative protein-DNA binding assay to determine genome-wide binding affinities to native chromatinized DNA. We use this method to quantify apparent genome-wide binding affinities of both pioneering and non-pioneering transcription factors to uncover the regulatory role of chromatin on transcription factor binding. This revealed that DNA accessibility is the main determinant of transcription factor binding, which restricts nanomolar binding of non-pioneering factors to promoters. DNA binding motifs only appear to be important for very high-affinity binding, but are not essential for nanomolar binding. We uncover numerous biological processes enriched at specific binding affinities, suggesting they are regulated at defined transcription factor concentrations. Importantly, our method adds a new quantitative layer of transcription factor biology, enabling stratification of genomic targets based on transcription factor expression and prediction of transcription factor binding sites under non-physiological conditions, such as disease associated elevated expression of (onco)genes.

2023-02-09 | GSE219035 | GEO

BANCseq for determination of genome-wide apparent transcription factor binding affinities [ATAC-Seq]

Project description:BANCseq for determination of genome-wide apparent transcription factor binding affinities [ATAC-Seq]

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BANCseq for determination of genome-wide apparent transcription factor binding affinities [CUT&Run]

Project description:BANCseq for determination of genome-wide apparent transcription factor binding affinities [CUT&Run]

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BANCseq for determination of genome-wide apparent transcription factor binding affinities [CUT&Run]

Project description:In vivo transcription factor binding is regulated by DNA sequence and chromatin features. However, the impact of chromatin context on genome-wide transcription factor binding affinities have not yet been characterized. Here we report the establishment of a quantitative protein-DNA binding assay to determine genome-wide binding affinities to native chromatinized DNA. We use this method to quantify apparent genome-wide binding affinities of both pioneering and non-pioneering transcription factors to uncover the regulatory role of chromatin on transcription factor binding. This revealed that DNA accessibility is the main determinant of transcription factor binding, which restricts nanomolar binding of non-pioneering factors to promoters. DNA binding motifs only appear to be important for very high-affinity binding, but are not essential for nanomolar binding. We uncover numerous biological processes enriched at specific binding affinities, suggesting they are regulated at defined transcription factor concentrations. Importantly, our method adds a new quantitative layer of transcription factor biology, enabling stratification of genomic targets based on transcription factor expression and prediction of transcription factor binding sites under non-physiological conditions, such as disease associated elevated expression of (onco)genes.

2023-02-09 | GSE193553 | GEO

BANCseq for determination of genome-wide apparent transcription factor binding affinities [ATAC-Seq]

2023-02-09 | GSE219034 | GEO

BANC-seq to identify genome-wide transcription factor binding affinities to native chromatin

Project description:BANC-seq (Binding Affinities to Native Chromatin by sequencing) allows determination of absolute apparent binding affinites of transcription factors to native chromatin in a genome-wide manner. In this study, we establish the method and show that chromatin and DNA sequence define binding affinites of FOXA1, SP1, YY1 and MYC/MAX complex. To relate the identified binding affinities to the actual transcriptional levels of these transcription factors in the cells used in this study, and to confirm that the nuclear isolation protocol used in the study does not lead to loss of nuclear proteins, we have generated whole proteomes including proteomics standards for absolute quantification of proteins. In addition, to validate some of the findings of the study, we have performed PAQMAN (Protein-nucleic acid affinity quantification by MAss spectrometry in nuclear extracts), as well as DNA pulldowns followed by mass spec.

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Project description:Interaction proteomics studies have provided fundamental insights into multimeric biomolecular assemblies and cell-scale molecular networks. Significant recent developments in mass spectrometry-based interaction proteomics have been fueled by rapid advances in label-free, isotopic, and isobaric quantitation workflows. Here, we report a quantitative protein-DNA and protein-nucleosome binding assay that uses affinity purifications from nuclear extracts coupled with isobaric chemical labeling and mass spectrometry to quantify apparent binding affinities proteome-wide. We use this assay with a variety of DNA and nucleosome baits to quantify apparent binding affinities of monomeric and multimeric transcription factors and chromatin remodeling complexes.

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Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

Project description:The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

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