CUT&Tag recovers up to half of ENCODE ChIP-seq peaks
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ABSTRACT:
PROVIDER: PRJNA820826 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18507100_1.fastq.gz | Fastqsanger.gz | |||
| SRR18507100_2.fastq.gz | Fastqsanger.gz | |||
| SRR18507101_1.fastq.gz | Fastqsanger.gz | |||
| SRR18507101_2.fastq.gz | Fastqsanger.gz | |||
| SRR18507102_1.fastq.gz | Fastqsanger.gz |
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Project description:We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Across a total of 30 new and 6 published CUT&Tag datasets we found that no experiment recovers more than 50% of known ENCODE peaks, regardless of the histone mark. We tested peak callers MACS2 and SEACR, identifying optimal peak calling parameters. Balancing both precision and recall of known ENCODE peaks, SEACR without retention of duplicates showed the best performance. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.
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Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Kevin White mailto:kpwhite@uchicago.edu (Principal Investigator), Subhradip Karmakar mailto:subhradip@uchicago.edu (Project Lead), Nick Bild mailto:nbild@bsd.uchicago.edu (Data Analyst), Alina Choudhury mailto:achoudhury@uchicago.edu (Laboratory Technician), Marc Domanus mailto:mdomanus@anl.gov (Sequencing Technician at Argonne National Lab)). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This ENCODE track maps human transcription factor binding sites, genome-wide using second generation massively parallel sequencing. This mapping uses expressed transcription factors as GFP tagged fusion proteins after BAC (Bacterial artificial chromosomes) recombineering. The U. of Chicago and Max Planck Institute (Dresden) pipeline generates recombineered (recombination-mediated genetic engineering) BACs for the production of cell lines or animals that express fusion proteins from epitope tagged transgenes. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. (http://hgwdev/ENCODE/protocols/cell) Recombineering strategy: To facilitate high-throughput production of the transgenic constructs, the program BACFinder (Crowe, Rana et al. 2002) automatically selects the most suitable BAC clone for any given human gene and generates the sets of PCR primers required for tagging and verification (Poser, Sarov et al. 2008). Recombineering is used for tagging cassettes at either the N or C terminus of the protein. The N-terminal cassette has a dual eukaryotic-prokaryotic promoter (PGK-gb2) driving a neomycin-kanamycin resistance gene within an artificial intron inside the tag coding sequence. The selection cassette is flanked by two loxP sites and can be permanently removed by Cre recombinase-mediated excision. The C-terminal cassette contains the sequence encoding the tag followed by an internal ribosome entry site (IRES) in front of the neomycin resistance gene. In addition, a short bacterial promoter (Gb3) drives the expression of the neomycin-kanamycin resistance gene in E. coli. The tagging cassettes, containing 50 nucleotides of PCR-introduced homology arms are inserted into the BAC by recombineering, either behind the start codon (for the N-terminal tag) or in front of the stop codon (for the C-terminal tag) of the gene. E. coli cells that have successfully recombined the cassette are selected for kanamycin resistance in liquid culture. Each saturated culture from a specific recombineering reaction derived 10-200 independent recombination events. Checking two independent clones for each PCR through the tag insertion point, 97% (85/88) yielded a PCR product of the expected size. Most of the clones that failed to grow were missing the targeted genomic region. An estimated 10% of the BACs used are chimeric, rearranged or wrongly mapped. Thus, initial results indicate that the necessary recombineering steps can be carried out with high fidelity. The White lab produced all epitope tagged transcription and chromatin factor BACs, as well as the genome wide ChIP data and analysis. An application of this approach to the analysis of closely related paralogs (RARa and RARg) yielded transcription factors, chromatin factors, cell lines, ChIP chip data and ChIP-seq data (Hua, Kittler et al. Cell 2009). Such paralogous transcription factors often can not otherwise be distinguished by antibodies. Sample Preparation: ChIP DNA from samples are sheared to ~800bp using a nebulizer. The ends of the DNA are polished, and two unique adapters are ligated to the fragments. Ligated fragments of 150-200bp are isolated by gel extraction and amplified using limited cycles of PCR. Sequencing System: Illumina GAIIx and HySeq next-generation sequencing produced all ChIP-seq data. Processing and Analysis Software: Raw sequencing reads are aligned using Bowtie version 0.12.5 (Langmead et al. 2009). The "-m 1" parameter is applied to suppress alignments mapping more than once in the genome. Reads are aligned to the UCSC hg19 assembly. Wiggle format signal files are generated with SPP 2.7.1 for R 2.7.1. Macs 1.3.7 is used to call peaks. The Macs parameters used vary by experiment. The White lab used goat anti-GFP antibody to perform ChIP in untagged K562 cells as a background control. The test IP was performed in the same way as the background control. Results are expressed as values of the test normalized to the background
2011-08-12 | E-GEOD-31363 | biostudies-arrayexpress