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MEDEA: analysis of transcription factor binding motifs in accessible chromatin.
Mariani, Luca; Weinand, Kathryn; Gisselbrecht, Stephen S; Bulyk, Martha L.
Afiliação
  • Mariani L; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
  • Weinand K; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
  • Gisselbrecht SS; Bioinformatics and Integrative Genomics PhD Program, Harvard University, Cambridge, Massachusetts 02138, USA.
  • Bulyk ML; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Genome Res ; 30(5): 736-748, 2020 05.
Article em En | MEDLINE | ID: mdl-32424069
ABSTRACT
Deciphering the interplay between chromatin accessibility and transcription factor (TF) binding is fundamental to understanding transcriptional regulation, control of cellular states, and the establishment of new phenotypes. Recent genome-wide chromatin accessibility profiling studies have provided catalogs of putative open regions, where TFs can recognize their motifs and regulate gene expression programs. Here, we present motif enrichment in differential elements of accessibility (MEDEA), a computational tool that analyzes high-throughput chromatin accessibility genomic data to identify cell-type-specific accessible regions and lineage-specific motifs associated with TF binding therein. To benchmark MEDEA, we used a panel of reference cell lines profiled by ENCODE and curated by the ENCODE Project Consortium for the ENCODE-DREAM Challenge. By comparing results with RNA-seq data, ChIP-seq peaks, and DNase-seq footprints, we show that MEDEA improves the detection of motifs associated with known lineage specifiers. We then applied MEDEA to 610 ENCODE DNase-seq data sets, where it revealed significant motifs even when absolute enrichment was low and where it identified novel regulators, such as NRF1 in kidney development. Finally, we show that MEDEA performs well on both bulk and single-cell ATAC-seq data. MEDEA is publicly available as part of our Glossary-GENRE suite for motif enrichment analysis.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Cromatina / Análise de Sequência de DNA / Elementos Reguladores de Transcrição Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Cromatina / Análise de Sequência de DNA / Elementos Reguladores de Transcrição Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article