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Inferring changes in histone modification during cell differentiation by ancestral state estimation based on phylogenetic trees of cell types: Human hematopoiesis as a model case.
Koyanagi, Kanako O.
Afiliação
  • Koyanagi KO; Faculty of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo 060-0814, Japan. Electronic address: kkoyanag@ist.hokudai.ac.jp.
Gene ; 721S: 100021, 2019.
Article em En | MEDLINE | ID: mdl-34530996
ABSTRACT
Revealing the landscape of epigenetic changes in cells during differentiation is important for understanding the development of organisms. In this study, to infer such epigenetic changes during human hematopoiesis, ancestral state estimation based on a phylogenetic tree was applied to map the epigenomic changes in six kinds of histone modifications onto the hierarchical cell differentiation process of hematopoiesis using epigenomes of eight types of differentiated hematopoietic cells. The histone modification changes inferred during hematopoiesis showed that changes that occurred on the branches separating different cell types reflected the characteristics of hematopoiesis in terms of genomic position and gene function. These results suggested that ancestral state estimation based on phylogenetic analysis of histone modifications in differentiated hematopoietic cells could reconstruct an appropriate landscape of histone modification changes during hematopoiesis. Since integration of the inferred changes of different histone modifications could reveal genes with specific histone marks such as active histone marks and bivalent histone marks on each internal branch of cell-type trees, this approach could provide valuable information for understanding the cell differentiation steps of each cell lineage.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Gene Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Gene Ano de publicação: 2019 Tipo de documento: Article