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Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics [ATACseq]

ABSTRACT: Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics [ATACseq]

PROVIDER: PRJNA593991 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10601361.fastq.gz	Fastqsanger.gz
	SRR10601362.fastq.gz	Fastqsanger.gz
	SRR10601363.fastq.gz	Fastqsanger.gz
	SRR10601364.fastq.gz	Fastqsanger.gz
	SRR10601365.fastq.gz	Fastqsanger.gz

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Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics [Omni-ATACseq]

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Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics [ATACseq]

Project description:Enhancers act as docking stations in the genome to which transcription factors bind, tightly regulating gene expression. Although single-cell technologies allow measuring chromatin accessibility or gene expression in each individual cell, exploiting both layers towards bona fide gene regulatory networks and enhancers is still a challenge. Here, we independently generate comprehensive single-cell transcriptome and epigenome atlases of the Drosophila eye-antennal disc and propose the spatial integration of single-cell RNA-seq and single-cell ATAC-seq data using a virtual latent space that mimics the spatial organization of the 2D tissue. To validate spatially predicted enhancers, we use a large collection of enhancer-reporter lines and identify ~85% of enhancers for which chromatin accessibility and enhancer activity patterns agree; while the remaining ~15% are ubiquitously accessible regions bound by the pioneer transcription factor Grainyhead, for which accessibility and activity do not correlate. Next, we infer linear and non-linear enhancer-to-target gene relationships in the virtual space, and find that genes are mostly regulated by multiple -and in some cases, redundant - enhancers. In addition, using cell-type specific enhancers learned from the scATAC-seq data, we deconvolute the cell-type specific effects of chromatin accessibility QTLs from a panel of 50 bulk ATAC-seq profiles from Drosophila inbred lines. Finally, we identify Prospero as a key transcription factor driving neuronal photoreceptor differentiation through the binding of a GGG recognition motif. In summary, we provide a comprehensive spatial characterization of gene regulation in a 2D tissue, which can be explored via SCope (http://scope.aertslab.org/#/Bravo_et_al_EyeAntennalDisc) and the UCSC Genome browser (http://genome.ucsc.edu/s/cbravo/Bravo_et_al_EyeAntennalDisc).

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