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Homo sapiens

ABSTRACT: The functional enhancer repertoire of human embryonic stem cells [isolated plasmid DNA-seq]

PROVIDER: PRJNA389115 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR5642850_1.fastq.gz	Fastqsanger.gz
	SRR5642850_2.fastq.gz	Fastqsanger.gz
	SRR5642851_1.fastq.gz	Fastqsanger.gz
	SRR5642851_2.fastq.gz	Fastqsanger.gz
	SRR5642852_1.fastq.gz	Fastqsanger.gz

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Project description:We provide a novel functional genomics atlas of non-coding regulatory elements derived from human neural stem cells (NSCs), using the massively parallel reporter assay ChIP-STARR-seq. ChIP-STARR-seq was performed in NSCs using chromatin immunoprecipitation for H3K27ac, H3K4me1, YY1 and SOX2, and the generated STARR-seq plasmid reporter libraries were profiled for their enhancer activity in H9 derived NSCs and human embryonic stem cells. Subsequently a multi-omics data integration was performed, including the development of a convolutional neural network called BRAIN-MAGNET that allows to predict the effect of single nucleotide variants in non-coding regulatory elements on the enhancer activity. The various data sets generated in this study include ChIP-seq experiments in NSCs, DNA sequencing of the generated plasmid libraries, RNA-seq of transfected cells from the ChIP-STARR-seq experiments, generated ATAC-seq data sets used for data integration and the contribution scores from BRAIN-MAGNET for each nucleotide assessed in this ChIP-STARR-seq study.

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Dynamic-network-guided CRISPRi screen identifies CTCF loop-constrained 1 nonlinear enhancer-gene regulatory activity in cell state transitions

Project description:Enhancers play key roles in gene regulation. However, comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Through gene regulatory network modeling, we identified that dynamic cell state transitions, a critical missing component in prevalent enhancer discovery strategies, can be utilized to improve the cells’ sensitivity to enhancer perturbation. Guided by the modeling results, we performed a mid-transition CRISPRi-based enhancer screen utilizing human embryonic stem cell definitive endoderm differentiation as a dynamic transition system. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core lineage-specifying transcription factors (TFs), including many enhancers with weak to moderate effects. Integrating the screening results with enhancer activity measurements (ATAC-seq, H3K27ac ChIP-seq) and three-dimensional enhancer-promoter interaction information (CTCF looping, Hi-C), we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Together, our dynamic network-guided enhancer screen and the CIA enhancer prediction model provide generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.

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