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CUT&Tag recovers up to half of ENCODE ChIP-seq peaks

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE199611 | GEO | 2022/03/31

REPOSITORIES: GEO

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Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Scott Tenenbaum mailto:STenenbaum@uamail.albany.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). The RNA binding protein (RBP) associated mRNA sequencing track (RIP-Seq) is produced as part of the Encyclopedia of DNA Elements (ENCODE) Project (http://hgwdev.cse.ucsc.edu/ENCODE/index.html). This track displays transcriptional fragments associated with RBP in cell lines (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType) K562 and GM12878, using Ribonomic profiling via Illumina SBS. In eukaryotic organisms gene regulatory networks require an additional level of coordination that links transcriptional and post-transcriptional processes. Messenger RNAs have traditionally been viewed as passive molecules in the pathway from transcription to translation. However, it is now clear that RNA-binding proteins play a major role in regulating multiple mRNAs in order to facilitate gene expression patterns. These tracks show the associated mRNAs that co-precipitate with the targeted RNA-binding proteins using RIP-Seq profiling. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf RBP-mRNA complexes were purified from cells grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). RNA samples were amplified and converted to cDNA with the Nugen (http://www.nugeninc.com/) Ovation© RNA-Seq System and prepped for sequencing with the Illumina (http://www.illumina.com/) mRNA-Seq protocol. Approximately 30 million single end sequencing reads were obtained for each K562 and GM12878. RIP samples were analyzed for signal that was at or above the 60th percentile and statistically enriched compared to the negative control. Sequences were analyzed using TopHat (http://tophat.cbcb.umd.edu/) (Trapnell et al., 2009) with Bowtie (http://bowtie-bio.sourceforge.net/index.shtml) (Langmead et al., 2009). Peaks were called from the top 40% of TopHat normalized reads, with a max gap, min run of (24:48). Unions of overlapping peak regions from total RNA replicates (RIP-Input) are presented with p-value from a one tailed t-test for average signal from replicates versus 0 (no cut-off was used for totals). Replicate overlap for positive RIP treatment peaks (ELAVL1 and PABPC1) are presented with a p-value from one tailed t-test versus signal for same the region in negative control replicates (T7-tag). RIP peaks were from sequences longer than 120 bp and p-value < .05. For both totals (RIP-input) and RIPs, the peak scores are scaled relative p-values between treatment and control.

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CUT&Tag recovers up to half of ENCODE ChIP-seq peaks

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