Mapping transcription factor occupancy using minimal numbers of cells in vitro and in vivo.
Mapping transcription factor occupancy using minimal numbers of cells in vitro and in vivo.
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DOI:
10.1101/gr.227124.117
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发表时间:
2018-04
期刊:
影响因子:
7
通讯作者:
Kaji K
中科院分区:
文献类型:
--
作者:
Tosti L;Ashmore J;Tan BSN;Carbone B;Mistri TK;Wilson V;Tomlinson SR;Kaji K
The identification of transcription factor (TF) binding sites in the genome is critical to understanding gene regulatory networks (GRNs). While ChIP-seq is commonly used to identify TF targets, it requires specific ChIP-grade antibodies and high cell numbers, often limiting its applicability. DNA adenine methyltransferase identification (DamID), developed and widely used in Drosophila, is a distinct technology to investigate protein–DNA interactions. Unlike ChIP-seq, it does not require antibodies, precipitation steps, or chemical protein–DNA crosslinking, but to date it has been seldom used in mammalian cells due to technical limitations. Here we describe an optimized DamID method coupled with next-generation sequencing (DamID-seq) in mouse cells and demonstrate the identification of the binding sites of two TFs, POU5F1 (also known as OCT4) and SOX2, in as few as 1000 embryonic stem cells (ESCs) and neural stem cells (NSCs), respectively. Furthermore, we have applied this technique in vivo for the first time in mammals. POU5F1 DamID-seq in the gastrulating mouse embryo at 7.5 d post coitum (dpc) successfully identified multiple POU5F1 binding sites proximal to genes involved in embryo development, neural tube formation, and mesoderm-cardiac tissue development, consistent with the pivotal role of this TF in post-implantation embryo. This technology paves the way to unprecedented investigation of TF–DNA interactions and GRNs in specific cell types of limited availability in mammals, including in vivo samples.
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影响因子:
48
作者:
Huber W;Carey VJ;Gentleman R;Anders S;Carlson M;Carvalho BS;Bravo HC;Davis S;Gatto L;Girke T;Gottardo R;Hahne F;Hansen KD;Irizarry RA;Lawrence M;Love MI;MacDonald J;Obenchain V;Oleś AK;Pagès H;Reyes A;Shannon P;Smyth GK;Tenenbaum D;Waldron L;Morgan M
通讯作者:
Morgan M
影响因子:
9.8
作者:
Church DM;Goodstadt L;Hillier LW;Zody MC;Goldstein S;She X;Bult CJ;Agarwala R;Cherry JL;DiCuccio M;Hlavina W;Kapustin Y;Meric P;Maglott D;Birtle Z;Marques AC;Graves T;Zhou S;Teague B;Potamousis K;Churas C;Place M;Herschleb J;Runnheim R;Forrest D;Amos-Landgraf J;Schwartz DC;Cheng Z;Lindblad-Toh K;Eichler EE;Ponting CP;Mouse Genome Sequencing Consortium
通讯作者:
Mouse Genome Sequencing Consortium
影响因子:
64.5
作者:
Kind J;Pagie L;de Vries SS;Nahidiazar L;Dey SS;Bienko M;Zhan Y;Lajoie B;de Graaf CA;Amendola M;Fudenberg G;Imakaev M;Mirny LA;Jalink K;Dekker J;van Oudenaarden A;van Steensel B
通讯作者:
van Steensel B
影响因子:
48
作者:
Gibson, Daniel G.;Young, Lei;Smith, Hamilton O.
通讯作者:
Smith, Hamilton O.
影响因子:
64.8
作者:
Guelen, Lars;Pagie, Ludo;van Steensel, Bas
通讯作者:
van Steensel, Bas