• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

《小鼠和人类组合转录调控图谱》

An atlas of combinatorial transcriptional regulation in mouse and man.

机构信息

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

出版信息

Cell. 2010 Mar 5;140(5):744-52. doi: 10.1016/j.cell.2010.01.044.

DOI:10.1016/j.cell.2010.01.044
PMID:20211142
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2836267/
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.

摘要

转录因子之间的组合相互作用对于指导组织特异性基因表达至关重要。为了构建这些组合的全局图谱,我们筛选了大多数人类和小鼠 DNA 结合转录因子(TF)之间的物理相互作用。完整的网络包含 762 个人类和 877 个小鼠相互作用。对网络的分析表明,高度连接的 TF 在组织中广泛表达,并且大约一半的测量相互作用在小鼠和人类之间是保守的。这些数据强调了 TF 组合对于确定细胞命运的重要性,并且导致了在免疫发育过程中表达的 SMAD3/FLI1 复合物的鉴定。人类和小鼠中大型 TF 组合网络的可用性将为研究基因调控、组织分化和哺乳动物进化提供许多机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/317787c3f199/nihms177825f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/48a5d69dd924/nihms177825f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/b2d7edc21570/nihms177825f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/eb50125996c7/nihms177825f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/317787c3f199/nihms177825f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/48a5d69dd924/nihms177825f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/b2d7edc21570/nihms177825f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/eb50125996c7/nihms177825f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25c0/2836267/317787c3f199/nihms177825f4.jpg

相似文献

1
An atlas of combinatorial transcriptional regulation in mouse and man.《小鼠和人类组合转录调控图谱》
Cell. 2010 Mar 5;140(5):744-52. doi: 10.1016/j.cell.2010.01.044.
2
Computational identification of tissue-specific transcription factor cooperation in ten cattle tissues.计算鉴定十种牛组织中组织特异性转录因子的合作。
PLoS One. 2019 May 16;14(5):e0216475. doi: 10.1371/journal.pone.0216475. eCollection 2019.
3
Tissue-specific atlas of trans-models for gene regulation elucidates complex regulation patterns.组织特异性跨模型图谱揭示了基因调控的复杂调控模式。
BMC Genomics. 2024 Apr 17;25(1):377. doi: 10.1186/s12864-024-10317-y.
4
Transcriptional regulatory networks underlying gene expression changes in Huntington's disease.亨廷顿病中基因表达变化的转录调控网络。
Mol Syst Biol. 2018 Mar 26;14(3):e7435. doi: 10.15252/msb.20167435.
5
Decoding transcriptional regulation via a human gene expression predictor.通过人类基因表达预测器解码转录调控。
J Genet Genomics. 2023 May;50(5):305-317. doi: 10.1016/j.jgg.2023.01.006. Epub 2023 Jan 21.
6
Circuitry and dynamics of human transcription factor regulatory networks.人类转录因子调控网络的电路和动力学。
Cell. 2012 Sep 14;150(6):1274-86. doi: 10.1016/j.cell.2012.04.040. Epub 2012 Sep 5.
7
Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors.转录调控网络的可控性分析揭示了转录因子之间的循环控制模式。
Integr Biol (Camb). 2015 May;7(5):560-8. doi: 10.1039/c4ib00247d. Epub 2015 Apr 9.
8
Inter- and intra-combinatorial regulation by transcription factors and microRNAs.转录因子和微小RNA的组合间及组合内调控
BMC Genomics. 2007 Oct 30;8:396. doi: 10.1186/1471-2164-8-396.
9
Taiji: System-level identification of key transcription factors reveals transcriptional waves in mouse embryonic development.太极:系统水平鉴定关键转录因子揭示了小鼠胚胎发育中的转录波。
Sci Adv. 2019 Mar 27;5(3):eaav3262. doi: 10.1126/sciadv.aav3262. eCollection 2019 Mar.
10
Canonical and single-cell Hi-C reveal distinct chromatin interaction sub-networks of mammalian transcription factors.规范和单细胞 Hi-C 揭示了哺乳动物转录因子独特的染色质相互作用子网络。
Genome Biol. 2018 Oct 25;19(1):174. doi: 10.1186/s13059-018-1558-2.

引用本文的文献

1
Multi-omics analysis highlights the link of aging-related cognitive decline with systemic inflammation and alterations of tissue-maintenance.多组学分析突出了衰老相关认知衰退与全身炎症及组织维持改变之间的联系。
bioRxiv. 2025 Jul 14:2025.07.13.662751. doi: 10.1101/2025.07.13.662751.
2
Identification of a Novel Gene ARNT2 for Osteogenic Differentiation of Mesenchymal Stem Cells.间充质干细胞成骨分化相关新基因ARNT2的鉴定
Calcif Tissue Int. 2025 Jul 18;116(1):100. doi: 10.1007/s00223-025-01407-4.
3
The evolutionary foundations of transcriptional regulation in animals.

本文引用的文献

1
Stem cells, pluripotency and nuclear reprogramming.干细胞、多能性与细胞核重编程。
J Thromb Haemost. 2009 Jul;7 Suppl 1:21-3. doi: 10.1111/j.1538-7836.2009.03418.x.
2
The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.控制人类髓系白血病细胞系生长停滞和分化的转录网络。
Nat Genet. 2009 May;41(5):553-62. doi: 10.1038/ng.375. Epub 2009 Apr 19.
3
Design of protein-interaction specificity gives selective bZIP-binding peptides.蛋白质相互作用特异性的设计产生选择性bZIP结合肽。
动物转录调控的进化基础。
Nat Rev Genet. 2025 Jul 9. doi: 10.1038/s41576-025-00864-9.
4
The cellular substrate of evolutionary novelty.进化新奇性的细胞基础。
Curr Biol. 2025 Jun 23;35(12):R626-R637. doi: 10.1016/j.cub.2025.04.014.
5
Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.转录因子亚型之间分子相互作用和调控特性的广泛差异。
Mol Cell. 2025 Apr 3;85(7):1445-1466.e13. doi: 10.1016/j.molcel.2025.03.004. Epub 2025 Mar 26.
6
Single-Cell Proteomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes.耐药前列腺癌细胞的单细胞蛋白质组学表征揭示与形态变化相关的分子特征。
Mol Cell Proteomics. 2025 Apr;24(4):100949. doi: 10.1016/j.mcpro.2025.100949. Epub 2025 Mar 14.
7
Multi-omic analysis of the ciliogenic transcription factor reveals a role in promoting activity-dependent responses via enhancing CREB binding in human neurons.纤毛生成转录因子的多组学分析揭示了其通过增强人类神经元中CREB结合来促进活动依赖性反应的作用。
bioRxiv. 2025 Mar 1:2025.02.27.640588. doi: 10.1101/2025.02.27.640588.
8
Region- and Cell-type-Resolved Multiomic Atlas of the Heart.心脏的区域和细胞类型解析多组学图谱
Mol Cell Proteomics. 2025 May;24(5):100922. doi: 10.1016/j.mcpro.2025.100922. Epub 2025 Feb 5.
9
Identification of co-localised transcription factors based on paired motifs analysis.基于配对基序分析鉴定共定位转录因子。
IET Syst Biol. 2024 Dec;18(6):238-249. doi: 10.1049/syb2.12104. Epub 2024 Nov 26.
10
Cell-state-dependent regulation of PPARγ signaling by the transcription factor ZBTB9 in adipocytes.脂肪细胞中转录因子ZBTB9对PPARγ信号通路的细胞状态依赖性调控。
J Biol Chem. 2024 Dec;300(12):107985. doi: 10.1016/j.jbc.2024.107985. Epub 2024 Nov 13.
Nature. 2009 Apr 16;458(7240):859-64. doi: 10.1038/nature07885.
4
A census of human transcription factors: function, expression and evolution.人类转录因子普查:功能、表达与进化
Nat Rev Genet. 2009 Apr;10(4):252-63. doi: 10.1038/nrg2538.
5
Dynamic modularity in protein interaction networks predicts breast cancer outcome.蛋白质相互作用网络中的动态模块化可预测乳腺癌预后。
Nat Biotechnol. 2009 Feb;27(2):199-204. doi: 10.1038/nbt.1522. Epub 2009 Feb 1.
6
Conservation and rewiring of functional modules revealed by an epistasis map in fission yeast.通过裂殖酵母上位性图谱揭示功能模块的保守性与重连
Science. 2008 Oct 17;322(5900):405-10. doi: 10.1126/science.1162609. Epub 2008 Sep 25.
7
EWS-FLI1 suppresses NOTCH-activated p53 in Ewing's sarcoma.EWS-FLI1在尤因肉瘤中抑制NOTCH激活的p53。
Cancer Res. 2008 Sep 1;68(17):7100-9. doi: 10.1158/0008-5472.CAN-07-6145.
8
Regulatory networks define phenotypic classes of human stem cell lines.调控网络定义了人类干细胞系的表型类别。
Nature. 2008 Sep 18;455(7211):401-5. doi: 10.1038/nature07213. Epub 2008 Aug 24.
9
High-quality binary protein interaction map of the yeast interactome network.酵母相互作用组网络的高质量二元蛋白质相互作用图谱。
Science. 2008 Oct 3;322(5898):104-10. doi: 10.1126/science.1158684. Epub 2008 Aug 21.
10
Nuclear architecture and gene regulation.核结构与基因调控。
Biochim Biophys Acta. 2008 Nov;1783(11):2174-84. doi: 10.1016/j.bbamcr.2008.07.018. Epub 2008 Jul 31.