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The CUT&RUN suspect list of problematic regions of the genome

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 wi...

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Detalles Bibliográficos
Autores principales: Nordin, Anna, Zambanini, Gianluca, Pagella, Pierfrancesco, Cantù, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416431/
https://www.ncbi.nlm.nih.gov/pubmed/37563719
http://dx.doi.org/10.1186/s13059-023-03027-3
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03027-3.