iSLIM: a comprehensive approach to mapping and characterizing gene regulatory networks

Mapping gene regulatory networks is a significant challenge in systems biology, yet only a few methods are currently capable of systems-level identification of transcription factors (TFs) that bind a specific regulatory element. We developed a microfluidic method for integrated systems-level interaction mapping of TF–DNA interactions, generating and interrogating an array of 423 full-length Drosophila TFs. With integrated systems-level interaction mapping, it is now possible to rapidly and quantitatively map gene regulatory networks of higher eukaryotes.

[1]  Daniel E. Newburger,et al.  Diversity and Complexity in DNA Recognition by Transcription Factors , 2009, Science.

[2]  M. Frasch,et al.  Regulation of the twist target gene tinman by modular cis-regulatory elements during early mesoderm development. , 1997, Development.

[3]  Bryan Lajoie,et al.  Enhanced yeast one-hybrid (eY1H) assays for high-throughput gene-centered regulatory network mapping , 2011, Nature Methods.

[4]  Marcel Geertz,et al.  MITOMI: a microfluidic platform for in vitro characterization of transcription factor-DNA interaction. , 2012, Methods in molecular biology.

[5]  Marcel Geertz,et al.  Experimental strategies for studying transcription factor-DNA binding specificities. , 2010, Briefings in functional genomics.

[6]  Yue Zhao,et al.  Inferring Binding Energies from Selected Binding Sites , 2009, PLoS Comput. Biol..

[7]  S. Blackshaw,et al.  Profiling the Human Protein-DNA Interactome Reveals ERK2 as a Transcriptional Repressor of Interferon Signaling , 2009, Cell.

[8]  Juan M. Vaquerizas,et al.  Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities. , 2010, Genome research.

[9]  M. Vidal,et al.  Reverse two-hybrid and one-hybrid systems to detect dissociation of protein-protein and DNA-protein interactions. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[10]  S. Maerkl,et al.  A high-throughput microfluidic method for generating and characterizing transcription factor mutant libraries. , 2012, Methods in molecular biology.

[11]  Stephen R Quake,et al.  Experimental determination of the evolvability of a transcription factor , 2009, Proceedings of the National Academy of Sciences.

[12]  S. Quake,et al.  A Systems Approach to Measuring the Binding Energy Landscapes of Transcription Factors , 2007, Science.

[13]  Marcel Geertz,et al.  Massively parallel measurements of molecular interaction kinetics on a microfluidic platform , 2012, Proceedings of the National Academy of Sciences.

[14]  Yanhui Hu,et al.  Next generation high density self assembling functional protein arrays , 2008, Nature Methods.

[15]  Bart Deplancke,et al.  Automated protein-DNA interaction screening of Drosophila regulatory elements , 2011, Nature Methods.

[16]  Frank Jülicher,et al.  Topology and Dynamics of the Zebrafish Segmentation Clock Core Circuit , 2012, PLoS biology.

[17]  B. Deplancke.  Experimental advances in the characterization of metazoan gene regulatory networks. , 2008, Briefings in functional genomics & proteomics.

[18]  M. Eisen,et al.  Probing the Informational and Regulatory Plasticity of a Transcription Factor DNA–Binding Domain , 2012, PLoS genetics.

[19]  E. O’Shea,et al.  Integrated approaches reveal determinants of genome-wide binding and function of the transcription factor Pho4. , 2011, Molecular cell.

[20]  P. Park.  ChIP–seq: advantages and challenges of a maturing technology , 2009, Nature Reviews Genetics.

[21]  E. Furlong,et al.  Challenges for modeling global gene regulatory networks during development: insights from Drosophila. , 2010, Developmental biology.

[22]  S. Quake,et al.  Highly parallel measurements of interaction kinetic constants with a microfabricated optomechanical device. , 2009, Applied physics letters.

[23]  Stephen R Quake,et al.  An in vitro microfluidic approach to generating protein-interaction networks , 2009, Nature Methods.

[24]  S. Luo,et al.  Direct measurement of DNA affinity landscapes on a high-throughput sequencing instrument , 2011, Nature Biotechnology.

[25]  Kirby D. Johnson,et al.  Drosophila Mad binds to DNA and directly mediates activation of vestigial by Decapentaplegic , 1997, Nature.

[26]  S. Quake,et al.  De Novo Identification and Biophysical Characterization of Transcription Factor Binding Sites with Microfluidic Affinity Analysis , 2010, Nature Biotechnology.

[27]  Alexandre V. Morozov,et al.  Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE , 2006, ISMB.

[28]  Anthony A. Philippakis,et al.  Design of Compact, Universal DNA Microarrays for Protein Binding Microarray Experiments , 2007, RECOMB.