最新《Cell》DNA转录因子作用谱（图）

　　

生物通报道，加州大学、日本横滨PIKEN Omics 科学中心、南非、挪威、澳大利亚等多国的科学家合作绘制了小鼠与人类的转录因子相互作用谱，相关成果文章An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man公布在最新一期的Cell上。

 

基因转录有正调控和负调控之分。如细菌基因的负调控机制是当一种阻遏蛋白(repressor protein)结合在受调控的基因上时，基因不表达；而从靶基因上去除阻遏蛋白后，RNA聚合酶识别受调控基因的启动子，使基因得以表达，这是正调控。这种阻遏蛋白是反式作用因子。

 

转录因子(transcription factor)是起正调控作用的反式作用因子。转录因子是转录起始过程中RNA聚合酶所需的辅助因子。真核生物基因在无转录因子时处于不表达状态，RNA聚合酶自身无法启动基因转录，只有当转录因子(蛋白质)结合在其识别的DNA序列上后，基因才开始表达。

 

据介绍，各种转录因子间的相互作用对组织特异性的基因表达具有重要的调控作用。为了绘制一个转录因子作用谱，科学家们分析了在人与小鼠体内起主要作用的DNA结合转录因子（DNA-binding transcription factors，TFs）。

 

在完成的图谱中，有762种人类的转录因子和877种小鼠的转录因子，它们可相互作用。分析研究发现，大部分的转录因子可在各种组织中表达并且相互发生作用，有近50%的转录因子功能保守（人与鼠的转录因子功能类似）。

 

 

研究发现，转录因子相互作用对细胞命运的决定具有重要的意义，在研究中，他们发现SMAD3/FLI1复合物的表达对免疫系统的建设具有重要作用。

 

科学家们通过一系列的分析，获得了大量的转录因子作用谱（人与鼠），这些作用谱将给基因组调节、组织分化以及哺乳动物进化的研究带来重要的影响。

（生物通 小茜）

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生物通推荐原文检索

An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

Timothy Ravasi1, 4, 5, 22, Harukazu Suzuki1, 2, 3, 6, 22, Carlo Vittorio Cannistraci1, 4, 5, 7, 8, 9, 22, Shintaro Katayama1, 2, 6, 22, Vladimir B. Bajic1, 5, 10, 22, Kai Tan1, 4, 23, Altuna Akalin1, 11, Sebastian Schmeier1, 10, Mutsumi Kanamori-Katayama1, 2, 6, Nicolas Bertin1, 2, 6, Piero Carninci1, 2, 6, Carsten O. Daub1, 2, 6, Alistair R.R. Forrest1, 2, 6, 12, Julian Gough1, 13, Sean Grimmond1, 14, Jung-Hoon Han1, 15, Takehiro Hashimoto1, 2, 6, Winston Hide1, 10, 16, Oliver Hofmann1, 10, Hideya Kawaji1, 2, 6, Atsutaka Kubosaki1, 2, 6, Timo Lassmann1, 2, 6, Erik van Nimwegen1, 17, Chihiro Ogawa1, 2, 6, Rohan D. Teasdale1, 14, Jesper Tegnér1, 18, 19, Boris Lenhard1, 11, Sarah A. Teichmann1, 15, Takahiro Arakawa1, 2, 6, Noriko Ninomiya1, 2, 6, Kayoko Murakami1, 2, 6, Michihira Tagami1, 2, 6, Shiro Fukuda1, 2, 6, Kengo Imamura1, 2, 6, Chikatoshi Kai1, 2, 6, Ryoko Ishihara1, 2, 6, Yayoi Kitazume1, 2, 6, Jun Kawai1, 2, 6, David A. Hume1, 20, Trey Ideker1, 4, 21, ,   and Yoshihide Hayashizaki1, 2, 3, 6, , 

 

1 The FANTOM Consortium, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

2 RIKEN Omics Science Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

3 General Organizers, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

4 Departments of Medicine and Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA

5 Red Sea Integrative Systems Biology Laboratory, Division of Chemical & Life Sciences and Engineering, Computational Bioscience Research Center, King Abdullah University for Science and Technology, Jeddah, Kingdom of Saudi Arabia

6 RIKEN Omics Science Center, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho Tsurumi-ku Yokohama, Kanagawa, 230-0045 Japan

7 Department of Mechanics, Politecnico di Torino, I-10129 Turin, Italy

8 Proteome Biochemistry, San Raffaele Scientific Institute, 20132 Milan, Italy

9 CMP Group Microsoft Research, Politecnico di Torino, I-10129 Turin, Italy

10 South African National Bioinformatics Institute, University of the Western Cape, Private Bag X17, Bellville, 7535 South Africa

11 Bergen Center for Computational Science, Høyteknologisenteret Thormøhlensgate 55, N-5008 Bergen, Norway

12 The Eskitis Institute for Cell and Molecular Therapies, Griffith University, QLD 4111, Australia

13 Department of Computer Science, University of Bristol, Merchant Venturers Building, Woodland Road, Bristol, BS8 1UB, UK

14 Australian Research Council Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia

15 MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK

16 Biostatistics Department, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA

17 Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Klingelbergstrasse 50/70, CH-4056 Basel, 4056, Switzerland

18 Compu

【Abstract】

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.