The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping

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dc.contributor(LCC) Lab. Ciclo Celularpt_BR
dc.contributorPrograma de Pós-Doutoradopt_BR
dc.contributor.authorMello, Fabio N. dept_BR
dc.contributor.authorTahira, Ana Carolinapt_BR
dc.contributor.authorBerzoti, Maria Gabriela Coelhopt_BR
dc.contributor.authorVerjovski-Almeida, Sergiopt_BR
dc.date.accessioned2024-02-20T18:17:58Z-
dc.date.available2024-02-20T18:17:58Z-
dc.date.issued2024pt_BR
dc.identifier.urihttps://repositorio.butantan.gov.br/handle/butantan/5253-
dc.description.abstractCleavage Under Targets and Release Using Nuclease (CUT&RUN) is a recent development for epigenome mapping, but its unique methodology can hamper proper quantitative analyses. As traditional normalization approaches have been shown to be inaccurate, we sought to determine endogenous normalization factors based on the human genome regions of constant nonspecific signal. This constancy was determined by applying Shannon’s information entropy, and the set of normalizer regions, which we named the ‘Greenlist’, was extensively validated using publicly available datasets. We demonstrate here that the greenlist normalization outperforms the current top standards, and remains consistent across different experimental setups, cell lines and antibodies; the approach can even be applied to different species or to CUT&Tag. Requiring no additional experimental steps and no added cost, this approach can be universally applied to CUT&RUN experiments to greatly minimize the interference of technical variation over the biological epigenome changes of interest.pt_BR
dc.description.sponsorship(FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulopt_BR
dc.format.extent1-15pt_BR
dc.language.isoEnglishpt_BR
dc.relation.ispartofBriefings in Bioinformaticspt_BR
dc.rightsOpen accesspt_BR
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/pt_BR
dc.titleThe CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mappingpt_BR
dc.typeArticlept_BR
dc.rights.licenseCC BY-NCpt_BR
dc.identifier.doi10.1093/bib/bbad538pt_BR
dc.identifier.citationvolume25pt_BR
dc.identifier.citationissue2pt_BR
dc.subject.keywordCUT&RUNpt_BR
dc.subject.keywordCUT&Tagpt_BR
dc.subject.keywordnormalizationpt_BR
dc.subject.keywordepigenomicspt_BR
dc.relation.ispartofabbreviatedBrief Bioinformpt_BR
dc.identifier.citationabntv. 25, n. 2, p. 1-15, 2024.pt_BR
dc.identifier.citationvancouver2024; 25(2):1-15pt_BR
dc.contributor.butantanTahira, Ana Carolina|:Pesquisador|:(LCC) Lab. Ciclo Celularpt_BR
dc.contributor.butantanBerzoti, Maria Gabriela Coelho|Pós-Doc|:Programa de Pós-Doutoradopt_BR
dc.contributor.butantanVerjovski-Almeida, Sergio|:Pesquisador|:(LCC) Lab. Ciclo Celular:Autor de correspondênciapt_BR
dc.sponsorship.butantan(FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦18/23693- 5pt_BR
dc.sponsorship.butantan(FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦22/11192-7pt_BR
dc.sponsorship.butantan(FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦20/02976-9pt_BR
dc.identifier.bvsccBR78.1pt_BR
dc.identifier.bvsdbIBProdpt_BR
dc.description.dbindexedYespt_BR
item.fulltextCom Texto completo-
item.languageiso639-1English-
item.grantfulltextopen-
item.openairetypeArticle-
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