A Modeling Framework for Generation of Positional and Temporal Simulations of Transcriptional Regulation

We present a modeling framework aimed at capturing both the positional and temporal behavior of transcriptional regulatory proteins in eukaryotic cells. There is growing evidence that transcriptional regulation is the complex behavior that emerges not solely from the individual components, but rather from their collective behavior, including competition and cooperation. Our framework describes individual regulatory components using generic action oriented descriptions of their biochemical interactions with a DNA sequence. All the possible actions are based on the current state of factors bound to the DNA. We developed a rule builder to automatically generate the complete set of biochemical interaction rules for any given DNA sequence. Off-the-shelf stochastic simulation engines can model the behavior of a system of rules and the resulting changes in the configuration of bound factors can be visualized. We compared our model to experimental data at well-studied loci in yeast, confirming that our model captures both the positional and temporal behavior of transcriptional regulation.

[1]  Ernest Fraenkel,et al.  High-resolution computational models of genome binding events , 2006, Nature Biotechnology.

[2]  William S. Hlavacek,et al.  Simulation of large-scale rule-based models , 2009, Bioinform..

[3]  X. Darzacq,et al.  In vivo dynamics of RNA polymerase II transcription , 2007, Nature Structural &Molecular Biology.

[4]  J. Widom,et al.  New DNA sequence rules for high affinity binding to histone octamer and sequence-directed nucleosome positioning. , 1998, Journal of molecular biology.

[5]  Rui Zhu,et al.  Stochastic kinetics description of a simple transcription model , 2006, Bulletin of mathematical biology.

[6]  Paul J. Choi,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[7]  J. Lieb,et al.  Genomewide protein-DNA binding dynamics suggest a clutch for transcription factor function , 2012, Nature.

[8]  Alexander van Oudenaarden,et al.  Stochastic Gene Expression: from Single Molecules to the Proteome This Review Comes from a Themed Issue on Chromosomes and Expression Mechanisms Edited Measuring Noise Mrna Fluctuations , 2022 .

[9]  D. Gillespie.  A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[10]  Klaus Aktories,et al.  Noise Can Induce Bimodality in Positive Transcriptional Feedback Loops Without Bistability , 2010 .

[11]  J. Berg,et al.  Molecular dynamics simulations of biomolecules , 2002, Nature Structural Biology.

[12]  David Botstein,et al.  Promoter-specific binding of Rap1 revealed by genome-wide maps of protein–DNA association , 2001, Nature Genetics.

[13]  Claudine Chaouiya,et al.  Petri net modelling of biological networks , 2007, Briefings Bioinform..

[14]  Xia Sheng,et al.  Bayesian design of synthetic biological systems , 2011, Proceedings of the National Academy of Sciences.

[15]  A. Rufiange,et al.  Transcription Regulation by the Noncoding RNA SRG1 Requires Spt2-Dependent Chromatin Deposition in the Wake of RNA Polymerase II , 2011, Molecular and Cellular Biology.

[16]  Haseong Kim,et al.  Stochastic gene expression modeling with hill function for switch-like gene responses , 2010, BIBM.

[17]  Arthur D Lander,et al.  The edges of understanding , 2010, BMC Biology.

[18]  Hartmann J. Genrich,et al.  Executable Petri net models for the analysis of metabolic pathways , 2001, International Journal on Software Tools for Technology Transfer.

[19]  Nir Friedman,et al.  Dynamics of Replication-Independent Histone Turnover in Budding Yeast , 2007, Science.

[20]  Kevin Struhl,et al.  Evidence for Eviction and Rapid Deposition of Histones upon Transcriptional Elongation by RNA Polymerase II , 2004, Molecular and Cellular Biology.

[21]  Justin A. Pruneski,et al.  Intergenic transcription causes repression by directing nucleosome assembly. , 2011, Genes & development.

[22]  Vicent Pelechano,et al.  A Complete Set of Nascent Transcription Rates for Yeast Genes , 2010, PloS one.

[23]  Ting Wang,et al.  An improved map of conserved regulatory sites for Saccharomyces cerevisiae , 2006, BMC Bioinformatics.

[24]  Attila Csikász-Nagy,et al.  Stochastic Petri Net extension of a yeast cell cycle model. , 2008, Journal of theoretical biology.

[25]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[26]  C. Bustamante,et al.  Rapid spontaneous accessibility of nucleosomal DNA , 2005, Nature Structural &Molecular Biology.

[27]  Tsz-Leung To,et al.  Noise Can Induce Bimodality in Positive Transcriptional Feedback Loops Without Bistability , 2010, Science.

[28]  V. Studitsky,et al.  Mechanism of transcription through a nucleosome by RNA polymerase II. , 2013, Biochimica et biophysica acta.

[29]  Ernest Fraenkel,et al.  Practical Strategies for Discovering Regulatory DNA Sequence Motifs , 2006, PLoS Comput. Biol..

[30]  J. Davies,et al.  Molecular Biology of the Cell , 1983, Bristol Medico-Chirurgical Journal.

[31]  F. Cross,et al.  Multiple sequence-specific factors generate the nucleosome-depleted region on CLN2 promoter. , 2011, Molecular cell.

[32]  N. Proudfoot,et al.  Transcriptional collision between convergent genes in budding yeast , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[33]  J. Kondev,et al.  Stochastic models of transcription: from single molecules to single cells. , 2013, Methods.

[34]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[35]  Karolin Luger,et al.  Nucleosome structure(s) and stability: variations on a theme. , 2011, Annual review of biophysics.

[36]  K. Struhl,et al.  Determinants of nucleosome positioning , 2013, Nature Structural &Molecular Biology.

[37]  Guy Karlebach,et al.  Modelling and analysis of gene regulatory networks , 2008, Nature Reviews Molecular Cell Biology.

[38]  L. Regan,et al.  Kinetics and thermodynamics of phenotype: unwinding and rewinding the nucleosome. , 2012, Journal of molecular biology.

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

[40]  Robert H Singer,et al.  Single-Cell Gene Expression Profiling , 2002, Science.

[41]  Hamid Bolouri,et al.  Dizzy: Stochastic Simulation of Large-scale Genetic Regulatory Networks , 2005, J. Bioinform. Comput. Biol..

[42]  Bin Wu,et al.  Real-Time Observation of Transcription Initiation and Elongation on an Endogenous Yeast Gene , 2011, Science.

[43]  Kim Sneppen,et al.  A mathematical model for transcriptional interference by RNA polymerase traffic in Escherichia coli. , 2005, Journal of molecular biology.

[44]  S. Berger,et al.  Histone modifications in transcriptional regulation. , 2002, Current opinion in genetics & development.

[45]  G. Fink,et al.  Antisense Transcription Controls Cell Fate in Saccharomyces cerevisiae , 2006, Cell.

[46]  Michael Hecker,et al.  Gene regulatory network inference: Data integration in dynamic models - A review , 2009, Biosyst..

[47]  N. Proudfoot,et al.  Transcriptional interference and gene orientation in yeast: noncoding RNA connections. , 2010, Cold Spring Harbor symposia on quantitative biology.

[48]  Robin D. Dowell,et al.  Toggle involving cis-interfering noncoding RNAs controls variegated gene expression in yeast , 2009, Proceedings of the National Academy of Sciences.

[49]  P. Farnham.  Insights from genomic profiling of transcription factors , 2009, Nature Reviews Genetics.

[50]  Rob Phillips,et al.  Effect of Promoter Architecture on the Cell-to-Cell Variability in Gene Expression , 2010, PLoS Comput. Biol..

[51]  Olli Yli-Harja,et al.  Stochastic sequence-level model of coupled transcription and translation in prokaryotes , 2011, BMC Bioinformatics.

[52]  K. Shearwin,et al.  Transcriptional interference by RNA polymerase pausing and dislodgement of transcription factors , 2011, Transcription.

[53]  A. Hartemink,et al.  An ensemble model of competitive multi-factor binding of the genome. , 2009, Genome research.

[54]  Bryan J Venters,et al.  A comprehensive genomic binding map of gene and chromatin regulatory proteins in Saccharomyces. , 2011, Molecular cell.

[55]  Chrystopher L. Nehaniv,et al.  Stochastic model of template-directed elongation processes in biology , 2010, Biosyst..

[56]  A. Ribeiro.  Stochastic and delayed stochastic models of gene expression and regulation. , 2010, Mathematical biosciences.

[57]  Ronald W. Davis,et al.  A high-resolution atlas of nucleosome occupancy in yeast , 2007, Nature Genetics.

[58]  Lior Pachter,et al.  Binding Site Turnover Produces Pervasive Quantitative Changes in Transcription Factor Binding between Closely Related Drosophila Species , 2010, PLoS biology.

[59]  Irene K. Moore,et al.  The DNA-encoded nucleosome organization of a eukaryotic genome , 2009, Nature.

[60]  James R Faeder,et al.  Efficient modeling, simulation and coarse-graining of biological complexity with NFsim , 2011, Nature Methods.

[61]  Eran Segal,et al.  From DNA sequence to transcriptional behaviour: a quantitative approach , 2009, Nature Reviews Genetics.

[62]  B. Pugh,et al.  Genome-wide structure and organization of eukaryotic pre-initiation complexes , 2011, Nature.

[63]  J. Langowski,et al.  Nucleosome accessibility governed by the dimer/tetramer interface , 2010, Nucleic acids research.

[64]  Luay Nakhleh,et al.  The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks , 2008, PLoS Comput. Biol..

[65]  Daniel E. Newburger,et al.  High-resolution DNA-binding specificity analysis of yeast transcription factors. , 2009, Genome research.

[66]  A. Coulon,et al.  Eukaryotic transcriptional dynamics: from single molecules to cell populations , 2013, Nature Reviews Genetics.

[67]  P. V. von Hippel,et al.  Diffusion-driven mechanisms of protein translocation on nucleic acids. 1. Models and theory. , 1981, Biochemistry.

[68]  Andre S Ribeiro,et al.  Studying genetic regulatory networks at the molecular level: delayed reaction stochastic models. , 2007, Journal of theoretical biology.

[69]  Vasily M Studitsky,et al.  Nature of the nucleosomal barrier to RNA polymerase II. , 2005, Molecular cell.

[70]  Yaniv Lubling,et al.  Compensation for differences in gene copy number among yeast ribosomal proteins is encoded within their promoters. , 2011, Genome research.

[71]  R. Tjian,et al.  Orchestrated response: a symphony of transcription factors for gene control. , 2000, Genes & development.

[72]  P. V. von Hippel,et al.  Development of a "modular" scheme to describe the kinetics of transcript elongation by RNA polymerase. , 2011, Biophysical journal.

[73]  A. McKane,et al.  Stochastic formulation of ecological models and their applications. , 2012, Trends in ecology & evolution.

[74]  Sui Huang.  Non-genetic heterogeneity of cells in development: more than just noise , 2009, Development.

[75]  Jürgen Pahle,et al.  Biochemical simulations: stochastic, approximate stochastic and hybrid approaches , 2008, Briefings Bioinform..

[76]  D. Bernardo,et al.  A Yeast Synthetic Network for In Vivo Assessment of Reverse-Engineering and Modeling Approaches , 2009, Cell.

[77]  T. D. Schneider,et al.  Sequence logos: a new way to display consensus sequences. , 1990, Nucleic acids research.

[78]  Masaru Tomita,et al.  A multi-algorithm, multi-timescale method for cell simulation , 2004, Bioinform..

[79]  Anirvan M. Sengupta,et al.  Specificity and robustness in transcription control networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[80]  Antti Häkkinen,et al.  Delayed Stochastic Model of Transcription at the Single Nucleotide Level , 2009, J. Comput. Biol..

[81]  Răzvan V Chereji,et al.  Major Determinants of Nucleosome Positioning. , 2018, Biophysical journal.

[82]  Irene K. Moore,et al.  A genomic code for nucleosome positioning , 2006, Nature.

[83]  Caroline C. Friedel,et al.  FERN – a Java framework for stochastic simulation and evaluation of reaction networks , 2008, BMC Bioinformatics.

[84]  M. Ptashne,et al.  Independent recruitment in vivo by Gal4 of two complexes required for transcription. , 2003, Molecular cell.

[85]  Robert Landick,et al.  Diversity in the Rates of Transcript Elongation by Single RNA Polymerase Molecules* , 2004, Journal of Biological Chemistry.

[86]  C C Adams,et al.  Nucleosome displacement in transcription. , 2006, Cell.

[87]  F J Bruggeman,et al.  Origins of stochastic intracellular processes and consequences for cell-to-cell variability and cellular survival strategies. , 2011, Methods in enzymology.

[88]  H R Drew,et al.  DNA bending and its relation to nucleosome positioning. , 1985, Journal of molecular biology.

[89]  Leonid A. Mirny,et al.  Nucleosome-mediated cooperativity between transcription factors , 2009 .

[90]  Anirvan M. Sengupta,et al.  Regulated Antisense Transcription Controls Expression of Cell-Type-Specific Genes in Yeast , 2011, Molecular and Cellular Biology.

[91]  Alexandre V. Morozov,et al.  Using DNA mechanics to predict in vitro nucleosome positions and formation energies , 2009, Nucleic acids research.

[92]  Ahmet Ay,et al.  Mathematical modeling of gene expression: a guide for the perplexed biologist , 2011, Critical reviews in biochemistry and molecular biology.

[93]  Claudine Chaouiya,et al.  A Modular, Qualitative Modeling of Regulatory Networks Using Petri Nets , 2016, Modeling in Systems Biology, The Petri Net Approach.

[94]  Eran Segal,et al.  Modeling interactions between adjacent nucleosomes improves genome-wide predictions of nucleosome occupancy , 2009, Bioinform..

[95]  A. Jansen,et al.  Distal chromatin structure influences local nucleosome positions and gene expression , 2012, Nucleic acids research.

[96]  S. Hahn,et al.  Transcriptional Regulation in Saccharomyces cerevisiae: Transcription Factor Regulation and Function, Mechanisms of Initiation, and Roles of Activators and Coactivators , 2011, Genetics.

[97]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[98]  E. Segal,et al.  In pursuit of design principles of regulatory sequences , 2014, Nature Reviews Genetics.

[99]  Carlos Bustamante,et al.  Single molecule transcription elongation. , 2009, Methods.

[100]  Susana Vinga,et al.  A Survey on Methods for Modeling and Analyzing Integrated Biological Networks , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.