Autor: |
Anna Nordin, Gianluca Zambanini, Pierfrancesco Pagella, Claudio Cantù |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Genome Biology, Vol 24, Iss 1, Pp 1-18 (2023) |
Druh dokumentu: |
article |
ISSN: |
1474-760X |
DOI: |
10.1186/s13059-023-03027-3 |
Popis: |
Abstract Background Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is an increasingly popular technique to map genome-wide binding profiles of histone modifications, transcription factors, and co-factors. The ENCODE project and others have compiled blacklists for ChIP-seq which have been widely adopted: these lists contain regions of high and unstructured signal, regardless of cell type or protein target, indicating that these are false positives. While CUT&RUN obtains similar results to ChIP-seq, its biochemistry and subsequent data analyses are different. We found that this results in a CUT&RUN-specific set of undesired high-signal regions. Results We compile suspect lists based on CUT&RUN data for the human and mouse genomes, identifying regions consistently called as peaks in negative controls. Using published CUT&RUN data from our and other labs, we show that the CUT&RUN suspect regions can persist even when peak calling is performed with SEACR or MACS2 against a negative control and after ENCODE blacklist removal. Moreover, we experimentally validate the CUT&RUN suspect lists by performing reiterative negative control experiments in which no specific protein is targeted, showing that they capture more than 80% of the peaks identified. Conclusions We propose that removing these problematic regions can substantially improve peak calling in CUT&RUN experiments, resulting in more reliable datasets. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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