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Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis [Hi-C]

ABSTRACT: Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis [Hi-C]

PROVIDER: PRJNA899840 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR22245600_1.fastq.gz	Fastqsanger.gz
	SRR22245600_2.fastq.gz	Fastqsanger.gz
	SRR22245601_1.fastq.gz	Fastqsanger.gz
	SRR22245601_2.fastq.gz	Fastqsanger.gz
	SRR22245602_1.fastq.gz	Fastqsanger.gz

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Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis [Hi-C]

Project description:Mammalian sex is determined by a network of antagonistic genes that are well characterized. However, its non-coding regulation is still largely unknown. Here we explore the 3D chromatin landscape of sex determination in vivo. We integrate Hi-C with ChIP-seq experiments using METALoci, a novel genome spatial auto-correlation analysis approach that identifies 3D regulatory hubs across the genome. We uncover a prominent rewiring of chromatin interactions during sex determination. By combining predictive approaches and validations in transgenic mice we identify a novel Fgf9 regulatory hub, which deletion results in male-to-female sex reversal.

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Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis

Project description:Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis

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Project description:Sex-determining 3D regulatory hubs revealed by genome spatial auto-correlation analysis [RNA-seq]

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Project description:This SuperSeries is composed of the SubSeries listed below.

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ecDNA hubs drive cooperative intermolecular oncogene expression [Hi-C]

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Project description:We have analyzed publicly available K562 Hi-C data, which enables genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 46 transcription factors and 8 histone modifications. We classified 12 different sets (clusters) of interacting loci that can be distinguished by their chromatin modifications and which can be categorized into three types of chromatin hubs. The different clusters of loci display very different relationships with transcription factor binding sites. As expected, many of the transcription factors show binding patterns specific to clusters composed of interacting loci that encompass promoters or enhancers. However, cluster 6, which is distinguished by marks of open chromatin but not by marks of active enhancers or promoters, was not bound by most transcription factors but was highly enriched for 3 transcription factors (GATA1, GATA2, and c-Jun) and 3 chromatin modifiers (BRG1, INI1, and SIRT6). To validate the identification of the clusters and to dissect the impact of chromatin organization on gene regulation, we performed RNA-seq analyses before and after knockdown of GATA1 or GATA2. We found that knockdown of the GATA factors greatly alters the expression of genes within cluster 6. Our work, in combination with previous studies linking regulation by GATA factors with c-Jun and BRG1, provide genome-wide evidence that Hi-C data identifies sets of biologically relevant interacting loci. RNA-seq of control, siGATA1 and siGATA2 K562 cells

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