SNP-ChIP: a versatile and tag-free method to quantify changes in protein binding across the genome
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ABSTRACT:
PROVIDER: PRJNA473777 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7234500.fastq.gz | Fastqsanger.gz | |||
| SRR7234510.fastq.gz | Fastqsanger.gz | |||
| SRR7234520.fastq.gz | Fastqsanger.gz | |||
| SRR7234530.fastq.gz | Fastqsanger.gz | |||
| SRR7234540.fastq.gz | Fastqsanger.gz |
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Project description:SNP-ChIP is a novel method leveraging small-scale intra-species genetic polymorphisms, mainly SNPs, to allow quantitative spike-in normalization of ChIP-seq results. SNP-ChIP uses a different strain of the same organism as the spike-in material and can be applied to any organism for which genome assemblies are available for two different strains or individuals with sufficient genetic diversity. This ensures antibody cross-reactivity and thus extends the applicability of the method beyond the small number of highly conserved proteins. It also ensures complete physiological coherence between the test and the spike-in cells. In this work we develop and validate the method using test cases from budding yeast meiosis. We use strains with ~0.7% genomic sequence divergence as test strain background and the spike-in strain, respectively. Sequencing reads are mapped to a hybrid genome, with naturally occurring sequence polymorphisms allowing assignment of most reads to one of the two genomes. By targeting the yeast chromosomal protein Red1, we show that SNP-ChIP reliably identifies previously reported changes in overall protein levels, irrespective of changes in binding distribution. We also show that SNP-ChIP is robust to wide changes in sequencing depth, as well as the amount of spike-in material. SNP-ChIP allowed discovery of novel regulators of global Red1 protein accumulation and is also shown to allow quantitative analysis of the DNA-damage associated histone modification gamma-H2AX. SNP-ChIP is a robust and versatile spike-in normalization method that can be used with any target against which a ChIP-grade antibody is available and for any organisms with sufficient intra-species diversity, including most model organisms as well as human cells. Grant ID: FY16-208 Grant title: Meiotic segregation of small chromosomes Funding source: March of Dimes Grantee name: Andreas Hochwagen, New York University, New York, NY, United States
2018-11-21 | GSE115092 | GEO
Project description:BackgroundChromatin-immunoprecipitation followed by sequencing (ChIP-seq) is the method of choice for mapping genome-wide binding of chromatin-associated factors. However, broadly applicable methods for between-sample comparisons are lacking.ResultsHere, we introduce SNP-ChIP, a method that leverages small-scale intra-species polymorphisms, mainly SNPs, for quantitative spike-in normalization of ChIP-seq results. Sourcing spike-in material from the same species ensures antibody cross-reactivity and physiological coherence, thereby eliminating two central limitations of traditional spike-in approaches. We show that SNP-ChIP is robust to changes in sequencing depth and spike-in proportions, and reliably identifies changes in overall protein levels, irrespective of changes in binding distribution. Application of SNP-ChIP to test cases from budding yeast meiosis allowed discovery of novel regulators of the chromosomal protein Red1 and quantitative analysis of the DNA-damage associated histone modification γ-H2AX.ConclusionSNP-ChIP is fully compatible with the intra-species diversity of humans and most model organisms and thus offers a general method for normalizing ChIP-seq results.
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Project description:Next-generation sequencing has been widely used for the genome-wide profiling of histone modifications, transcription factor binding and gene expression through chromatin immunoprecipitated DNA sequencing (ChIP-seq) and cDNA sequencing (RNA-seq). Here, we describe a versatile library construction method that can be applied to both ChIP-seq and RNA-seq on the widely used Illumina platforms. Standard methods for ChIP-seq library construction require nanograms of starting DNA, substantially limiting its application to rare cell types or limited clinical samples. By minimizing the DNA purification steps that cause major sample loss, our method achieved a high sensitivity in ChIP-seq library preparation. Using this method, we achieved the following: (1) generated high-quality epigenomic and transcription factor-binding maps using ChIP-seq for murine adipocytes; (2) successfully prepared a ChIP-seq library from as little as 25 pg of starting DNA; (3) achieved paired-end sequencing of the ChIP-seq libraries; (4) systematically profiled gene expression dynamics during murine adipogenesis using RNA-seq; and (5) preserved the strand specificity of the transcripts in RNA-seq. Given its sensitivity and versatility in both double-stranded and single-stranded DNA library construction, this method has wide applications in genomic, epigenomic, transcriptomic and interactomic studies. Pre-adipocytes and mature adipocytes were collected. Their chromatin and RNA were subjected to ChIP and mRNA extraction. Sequencing libraries from ChIP DNA or mRNA were generated following either standard protocols or TELP method. The quality and features of TELP libraries were proved and demonstrated in comparison with standard libraries or other published data.
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Project description:We developed scNanoSeq-CUT&Tag, a streamlined method by adapting a modified CUT&Tag protocol to Oxford Nanopore sequencing platform for efficient chromatin modification profiling at single-cell resolution. We firstly tested the performance of scNanoSeq-CUT&Tag on six human cell lines: K562, 293T, GM12878, HG002, H9, HFF1 and adult mouse blood cells, it showed that scNanoSeq-CUT&Tag can accurately distinguish different cell types in vitro and in vivo. Moreover, scNanoSeq-CUT&Tag enables to effectively map the allele-specific epigenomic modifications in the human genome andallows to analyze co-occupancy of histone modifications. Taking advantage of long-read sequencing,scNanoSeq-CUT&Tag can sensitively detect epigenomic state of repetitive elements. In addition, by applying scNanoSeq-CUT&Tag to testicular cells of adult mouse B6D2F1, we demonstrated that scNanoSeq-CUT&Tag maps dynamic epigenetic state changes during mouse spermatogenesis. Finally, we exploited the epigenetic changes of human leukemia cell line K562 during DNA demethylation, it showed that NanoSeq-CUT&Tag can capture H3K27ac signals changes along DNA demethylation. Overall, we prove that scNanoSeq-CUT&Tag is a valuable tool for efficiently probing chromatin state changes within individual cells.
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