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Genome-wide profiling of transcription factor-DNA binding interactions in Candida albicans: a comprehensive CUT&RUN method and data analysis workflow

ABSTRACT: Genome-wide profiling of transcription factor-DNA binding interactions in Candida albicans: a comprehensive CUT&RUN method and data analysis workflow

PROVIDER: PRJNA798025 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17644427_1.fastq.gz	Fastqsanger.gz
	SRR17644427_2.fastq.gz	Fastqsanger.gz
	SRR17644428_1.fastq.gz	Fastqsanger.gz
	SRR17644428_2.fastq.gz	Fastqsanger.gz
	SRR17644429_1.fastq.gz	Fastqsanger.gz

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Genome-wide profiling of transcription factor-DNA binding interactions in Candida albicans: a comprehensive CUT&RUN method and data analysis workflow

Project description:Regulatory transcription factors control many important biological processes including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&RUN is amenable to a higher throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs compared to ChIP-seq. Here, we describe a comprehensive CUT&RUN protocol and accompanying data analysis workflow that is tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans. This detailed protocol describes all necessary experimental procedures, from epitope tagging of transcription factor coding genes, to library preparation for sequencing; additionally, it includes our customized computational workflow for CUT&RUN data analysis.

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A tissue dissociation method optimized for ATAC-seq and CUT&RUN in Drosophila pupal tissues [CUT&RUN]

Project description:Chromatin accessibility, histone modifications and transcription factor binding are highly dynamic during Drosophila metamorphosis and drive global changes in gene expression as larval tissues differentiate into adult structures. Unfortunately, the presence of pupa cuticle on many Drosophila tissues during metamorphosis prevents enzyme access to cells and has limited the use of enzymatic in situ methods for assessing chromatin accessibility and histone modifications. Here, we present a dissociation method for cuticle-bound pupal tissues that is optimized for use with ATAC-Seq and CUT&RUN to interrogate chromatin accessibility and histone modifications. We show this method provides comparable chromatin accessibility data to the non-enzymatic approach FAIRE-seq, with only a fraction of the amount of input tissue required. This approach is also compatible with CUT&RUN, which allows genome-wide mapping of histone modifications with less than 1/10th of the tissue input required for more conventional approaches such as Chromatin Immunoprecipitation Sequencing (ChIP-seq). Our protocol makes it possible to use newer, more sensitive enzymatic in situ approaches to interrogate gene regulatory networks during Drosophila metamorphosis.

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Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow.

Project description:Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage under targets and release using nuclease (CUT&RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&RUN is amenable to a higher-throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs than ChIP-seq. Here, a comprehensive CUT&RUN protocol and accompanying data analysis workflow tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans are described. This detailed protocol includes all necessary experimental procedures, from epitope tagging of transcription factor-coding genes to library preparation for sequencing; additionally, it includes a customized computational workflow for CUT&RUN data analysis.

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Low-input chromatin profiling in Arabidopsis endosperm using CUT&RUN

Project description:Endosperm is an essential seed tissue with a unique epigenetic landscape. During endosperm development, differential epigenetic regulation of the maternal and paternal genomes plays important roles in regulating gene expression, especially at imprinted genes. Profiling the endosperm epigenetic landscape on a genome-wide scale is challenging due to its small size, mode of development, and close association with maternal tissue. Here, we applied a low input chromatin profiling method, CUT&RUN (cleavage under targets and release using nuclease), to profile parental-specific chromatin modifications using low numbers of Arabidopsis endosperm nuclei. We demonstrate that CUT&RUN generates genome-wide H3K27me3 landscapes with high sensitivity, specificity and reproducibility using around 20,000 endosperm nuclei purified by flow cytometry and fluorescence-activated cell sorting. H3K27me3 peaks identified by CUT&RUN and previous ChIP (chromatin immunoprecipitation) approaches were largely overlapping, with some distinctions in heterochromatin. The versatility and simplicity of CUT&RUN makes it a viable alternative to ChIP, which requires greater amounts of starting material, and will enable the study of tissue or even cell-type specific epigenomes in Arabidopsis and other plant species.

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