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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 1]

ABSTRACT: Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 1]

PROVIDER: PRJNA880347 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR21554273_1.fastq.gz	Fastqsanger.gz
	SRR21554273_2.fastq.gz	Fastqsanger.gz
	SRR21554274_1.fastq.gz	Fastqsanger.gz
	SRR21554274_2.fastq.gz	Fastqsanger.gz
	SRR21554275_1.fastq.gz	Fastqsanger.gz

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 2]

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 4]

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 3]

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 3]

Project description:3D chromatin structure is thought to play a critical role in regulating gene transcription during cellular transitions. While our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising 4 biological replicates and 6 billion reads per time point. Statistical analysis revealed 1,503 differential loops. Gained loops were enriched for AP-1 occupancy and correlated with increased expression of genes at their anchors. Lost loops were characterized by increases in expression of genes within the loop boundaries. Linear modeling revealed that changes in histone H3K27 acetylation, chromatin accessibility, and JUN binding in between the loop anchors were often just as predictive of changes in loop strength as changes to CTCF and/or cohesin occupancy at loop anchors. Finally, we built linear models and found that incorporating the dynamics of enhancer acetylation and loop strength increased accuracy of gene expression predictions. Together, our well-powered study has added to our understanding of the mechanisms that regulate looping, and the relationship of looping with gene expression.

2022-11-01 | GSE213908 | GEO

Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 4]

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features [dataset 2]

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A chromosomal loop anchor mediates bacterial genome organization

Project description:A chromosomal loop anchor mediates bacterial genome organization

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Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features.

Project description:Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.

| S-EPMC10547260 | biostudies-literature

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