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Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [GP5d/siRAD21 ChIP-Seq experiments]

ABSTRACT: During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis, and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered, and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M-phase. These results suggest that cohesin binding functions as a cellular memory that promotes re- stablishment of TF clusters after DNA replication and chromatin condensation. Examination of TF binding by ChIP-seq in a CRC cell-line treated with non-targeting siRNA, or siRNA specific to the cohesin subunit RAD21.

ORGANISM(S): Homo sapiens

SUBMITTER: Martin Enge

PROVIDER: E-GEOD-51234 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

Project description:During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis, and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered, and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M-phase. These results suggest that cohesin binding functions as a cellular memory that promotes re- stablishment of TF clusters after DNA replication and chromatin condensation. Examination of TF binding by ChIP-seq in LoVo CRC cell-lines.

2013-08-15 | E-GEOD-49402 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [Validation Set]

2013-09-25 | E-GEOD-51142 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [S-phase/M-phase synchronized cells]

2013-10-01 | E-GEOD-51290 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [GP5d/siRAD21 ChIP-Seq experiments]

2013-09-28 | GSE51234 | GEO

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

2013-08-15 | GSE49402 | GEO

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [Validation Set]

2013-09-25 | GSE51142 | GEO

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [S-phase/M-phase synchronized cells]

2013-10-01 | GSE51290 | GEO

Transcription factors harbor functional RNA-binding domains

Project description:Transcription factors (TFs) orchestrate the gene expression programs that define each cell’s identity, and the canonical TF accomplishes this with two functional domains1–7. The DNA-binding domain interacts with specific genomic sequences, and the effector domain binds coactivators or co-repressors that contribute to transcriptional regulation. We report here that TFs also frequently contain an RNA-binding domain and that this also contributes to gene regulation. Nearly half of TFs in human cells show evidence of RNA-binding and their affinities for RNA are similar to those of well-studied RNA-binding proteins. The RNA-binding sites of TFs have sequence and functional features analogous to the arginine-rich motif of the HIV transcriptional activator Tat8,9. RNA-binding contributes to TF function by promoting the dynamic association of TFs with chromatin. We conclude that the canonical definition of transcription factors is incomplete, and that the ability of many TFs to bind DNA, RNA and protein is fundamental to gene regulation.

2023-07-02 | PXD035484 | Pride

Expression data from LoVo and GP5d CRC cell lines

Project description:TF binding clusters in promoter correlate well with gene expression. We used ChIP-seq to map binding sites of the majority of highly expressed TFs in the cell. The size of clusters of TFs in the promoters of genes were found to correlate well with gene expression. CRC cell lines were grown on plastic This submission reprsents transcriptome component of study.

2013-08-16 | E-GEOD-48448 | biostudies-arrayexpress

Base-resolution methylation patterns accurately predict transcription factor bindings in vivo

Project description:Detecting in vivo transcription factor (TF) binding is important for understanding gene regulatory circuitries. ChIP-seq is a powerful technique to empirically define TF binding in vivo. However, the multitude of distinct TFs makes genome-wide profiling for them all labor-intensive and costly. Algorithms for in silico prediction of TF binding have been developed, based mostly on histone modification or DNase I hypersensitivity data in conjunction with DNA motif and other genomic features. However, technical limitations of these methods prevent them from being applied broadly, especially in clinical settings. We conducted a comprehensive survey involving multiple cell lines, TFs, and methylation types and found that there are intimate relationships between TF binding and methylation level changes around the binding sites. Exploiting the connection between DNA methylation and TF binding, we proposed a novel supervised learning approach to predict TF-DNA interaction using data from base-resolution whole-genome methylation sequencing experiments. We devised beta-binomial models to characterize methylation data around TF binding sites and the background. Along with other static genomic features, we adopted a random forest framework to predict TF-DNA interaction. After conducting comprehensive tests, we saw that the proposed method accurately predicts TF binding and performs favorably versus competing methods. Examine Oct4 genome-wide binding in mouse embryonic stem cells (E14)

2015-03-02 | E-GEOD-65093 | biostudies-arrayexpress

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