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Ultra-parallel ChIP-seq by barcoding of intact nuclei

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111000
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Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. Processing of samples still remains largely individual and labor-intensive, hindering the assay throughput and comparability across samples. Here we present a novel method for ultra-parallelized high-throughput ChIP-seq for the systematic mapping of histone modifications and transcription factors. The method, called RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ), barcodes chromatin within intact nuclei extracted from different tissutal sources. Barcoded nuclei are pooled and processed within the same ChIP, for maximal comparability and drastical workload reduction. The choice of user-friendly, straightforward, enzymatic steps for chromatin fragmentation and barcoding makes RELACS particularly suitable for implementation in any clinical laboratory settings, for scarce samples, and large-scale studies. RELACS ChIP-seq has been firstly validated using HepG2 cells and compared with traditional sonication-based protocol. For this purpose, ChIP against six histone modifications and two transcription factors has been performed. 20 parallel technical replicates were investigated for RELACS within the same ChIP. A sensitivity test for RELACS has been also performed. For this, seven technical replicates containing 10,000, 1,000 and 100 cells each have been barcoded and merged to be processed in three separated ChIPs (containing 7x10,000, 7x1,000, 7x100 cells respectively). ChIP sensitivity has been investigated for H3K4me3, H3K27me3 and CTCF. To demonstrate ChIP parallelization we applicated RELACS for barcoding 8 separate organs extracted from two mice and processed within the same ChIP. For mouse experiments H3K27ac, H3K36me3, H3K27me3 ChIPs (and input controls) have been performed. https://github.com/dpryan79/Misc/blob/master/InternalBarcodes/demultiplex_relacs.py
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2019-03-27
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