Dataset Information

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

ABSTRACT: Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

SUBMITTER: FANTOM Consortium

PROVIDER: S-EPMC6711855 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Suzuki Harukazu H Forrest Alistair R R AR van Nimwegen Erik E Daub Carsten O CO Balwierz Piotr J PJ Irvine Katharine M KM Lassmann Timo T Ravasi Timothy T Hasegawa Yuki Y de Hoon Michiel J L MJ Katayama Shintaro S Schroder Kate K Carninci Piero P Tomaru Yasuhiro Y Kanamori-Katayama Mutsumi M Kubosaki Atsutaka A Akalin Altuna A Ando Yoshinari Y Arner Erik E Asada Maki M Asahara Hiroshi H Bailey Timothy T Bajic Vladimir B VB Bauer Denis D Beckhouse Anthony G AG Bertin Nicolas N Björkegren Johan J Brombacher Frank F Bulger Erika E Chalk Alistair M AM Chiba Joe J Cloonan Nicole N Dawe Adam A Dostie Josee J Engström Pär G PG Essack Magbubah M Faulkner Geoffrey J GJ Fink J Lynn JL Fredman David D Fujimori Ko K Furuno Masaaki M Gojobori Takashi T Gough Julian J Grimmond Sean M SM Gustafsson Mika M Hashimoto Megumi M Hashimoto Takehiro T Hatakeyama Mariko M Heinzel Susanne S Hide Winston W Hofmann Oliver O Hörnquist Michael M Huminiecki Lukasz L Ikeo Kazuho K Imamoto Naoko N Inoue Satoshi S Inoue Yusuke Y Ishihara Ryoko R Iwayanagi Takao T Jacobsen Anders A Kaur Mandeep M Kawaji Hideya H Kerr Markus C MC Kimura Ryuichiro R Kimura Syuhei S Kimura Yasumasa Y Kitano Hiroaki H Koga Hisashi H Kojima Toshio T Kondo Shinji S Konno Takeshi T Krogh Anders A Kruger Adele A Kumar Ajit A Lenhard Boris B Lennartsson Andreas A Lindow Morten M Lizio Marina M Macpherson Cameron C Maeda Norihiro N Maher Christopher A CA Maqungo Monique M Mar Jessica J Matigian Nicholas A NA Matsuda Hideo H Mattick John S JS Meier Stuart S Miyamoto Sei S Miyamoto-Sato Etsuko E Nakabayashi Kazuhiko K Nakachi Yutaka Y Nakano Mika M Nygaard Sanne S Okayama Toshitsugu T Okazaki Yasushi Y Okuda-Yabukami Haruka H Orlando Valerio V Otomo Jun J Pachkov Mikhail M Petrovsky Nikolai N Plessy Charles C Quackenbush John J Radovanovic Aleksandar A Rehli Michael M Saito Rintaro R Sandelin Albin A Schmeier Sebastian S Schönbach Christian C Schwartz Ariel S AS Semple Colin A CA Sera Miho M Severin Jessica J Shirahige Katsuhiko K Simons Cas C St Laurent George G Suzuki Masanori M Suzuki Takahiro T Sweet Matthew J MJ Taft Ryan J RJ Takeda Shizu S Takenaka Yoichi Y Tan Kai K Taylor Martin S MS Teasdale Rohan D RD Tegnér Jesper J Teichmann Sarah S Valen Eivind E Wahlestedt Claes C Waki Kazunori K Waterhouse Andrew A Wells Christine A CA Winther Ole O Wu Linda L Yamaguchi Kazumi K Yanagawa Hiroshi H Yasuda Jun J Zavolan Mihaela M Hume David A DA Arakawa Takahiro T Fukuda Shiro S Imamura Kengo K Kai Chikatoshi C Kaiho Ai A Kawashima Tsugumi T Kawazu Chika C Kitazume Yayoi Y Kojima Miki M Miura Hisashi H Murakami Kayoko K Murata Mitsuyoshi M Ninomiya Noriko N Nishiyori Hiromi H Noma Shohei S Ogawa Chihiro C Sano Takuma T Simon Christophe C Tagami Michihira M Takahashi Yukari Y Kawai Jun J Hayashizaki Yoshihide Y

Nature genetics 20090419 5

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the ...[more]

PMID: 19377474

Dataset Information

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Publications

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Similar Datasets

The Transcriptional Network That Controls Growth Arrest and Macrophage Differentiation in the Human Myeloid Leukemia Cell Line THP-1.
| S-EPMC7347797 | biostudies-literature

Batf promotes growth arrest and terminal differentiation of mouse myeloid leukemia cells.
| S-EPMC3060294 | biostudies-literature

Nucleosome repositioning during differentiation of a human myeloid leukemia cell line.
| S-EPMC5403151 | biostudies-literature

C/EBPγ deregulation results in differentiation arrest in acute myeloid leukemia.
| S-EPMC3533560 | biostudies-literature

Polycomb Factor PHF19 Controls Cell Growth and Differentiation Toward Erythroid Pathway in Chronic Myeloid Leukemia Cells.
| S-EPMC8116664 | biostudies-literature

An iPSC line derived from a human acute myeloid leukemia cell line (HL-60-iPSC) retains leukemic abnormalities and displays myeloid differentiation defects.
| S-EPMC8031422 | biostudies-literature

Transforming growth-interacting factor (TGIF) regulates proliferation and differentiation of human myeloid leukemia cells.
| S-EPMC5527533 | biostudies-literature

A network of transcriptional and signaling events is activated by FGF to induce chondrocyte growth arrest and differentiation.
| S-EPMC2172997 | biostudies-literature

ZFX controls propagation and prevents differentiation of acute T-lymphoblastic and myeloid leukemia.
| S-EPMC3936793 | biostudies-literature

First-line treatment strategies for newly diagnosed chronic myeloid leukemia: a network meta-analysis.
| S-EPMC6163008 | biostudies-other