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Towards a map of cis-regulatory sequences in the human genome.
Niu, Meng; Tabari, Ehsan; Ni, Pengyu; Su, Zhengchang.
Afiliação
  • Niu M; Department of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
  • Tabari E; Department of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
  • Ni P; Department of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
  • Su Z; Department of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
Nucleic Acids Res ; 46(11): 5395-5409, 2018 06 20.
Article em En | MEDLINE | ID: mdl-29733395
ABSTRACT
Accumulating evidence indicates that transcription factor (TF) binding sites, or cis-regulatory elements (CREs), and their clusters termed cis-regulatory modules (CRMs) play a more important role than do gene-coding sequences in specifying complex traits in humans, including the susceptibility to common complex diseases. To fully characterize their roles in deriving the complex traits/diseases, it is necessary to annotate all CREs and CRMs encoded in the human genome. However, the current annotations of CREs and CRMs in the human genome are still very limited and mostly coarse-grained, as they often lack the detailed information of CREs in CRMs. Here, we integrated 620 TF ChIP-seq datasets produced by the ENCODE project for 168 TFs in 79 different cell/tissue types and predicted an unprecedentedly completely map of CREs in CRMs in the human genome at single nucleotide resolution. The map includes 305 912 CRMs containing a total of 1 178 913 CREs belonging to 736 unique TF binding motifs. The predicted CREs and CRMs tend to be subject to either purifying selection or positive selection, thus are likely to be functional. Based on the results, we also examined the status of available ChIP-seq datasets for predicting the entire regulatory genome of humans.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequência de Bases / Genoma Humano / Sequências Reguladoras de Ácido Nucleico / Elementos Reguladores de Transcrição Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequência de Bases / Genoma Humano / Sequências Reguladoras de Ácido Nucleico / Elementos Reguladores de Transcrição Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article