Integrative analysis of time course microarray data and DNA sequence data via log-linear models for identifying dynamic transcriptional regulatory networks

Since eukaryotic transcription is regulated by sets of Transcription Factors (TFs) having various transcriptional time delays, identification of temporal combinations of activated TFs is important to reconstruct Transcriptional Regulatory Networks (TRNs). Our methods combine time course microarray data, information on physical binding between the TFs and their targets and the regulatory sequences of genes using a log-linear model to reconstruct dynamic functional TRNs of the yeast cell cycle and human apoptosis. In conclusion, our results suggest that the proposed dynamic motif search method is more effective in reconstructing TRNs than the static motif search method.

[1]  Hans van Dam,et al.  Distinct roles of Jun : Fos and Jun : ATF dimers in oncogenesis , 2001, Oncogene.

[2]  G. Church,et al.  Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation , 1998, Nature Biotechnology.

[3]  Curt Wittenberg,et al.  Cell cycle-dependent transcription in yeast: promoters, transcription factors, and transcriptomes , 2005, Oncogene.

[4]  Patrik D'haeseleer,et al.  Linear Modeling of mRNA Expression Levels During CNS Development and Injury , 1998, Pacific Symposium on Biocomputing.

[5]  Emmitt R. Jolly,et al.  Inference of combinatorial regulation in yeast transcriptional networks: a case study of sporulation. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Michael Gribskov,et al.  Score Distributions for Simultaneous Matching to Multiple Motifs , 1997, J. Comput. Biol..

[7]  Trey Ideker,et al.  Integrated Assessment and Prediction of Transcription Factor Binding , 2006, PLoS Comput. Biol..

[8]  D. Pe’er,et al.  Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data , 2003, Nature Genetics.

[9]  Satoru Miyano,et al.  Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model , 1998, Pacific Symposium on Biocomputing.

[10]  H. Bussemaker,et al.  Regulatory element detection using correlation with expression , 2001, Nature Genetics.

[11]  Satoru Miyano,et al.  Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data , 2003, CMSB.

[12]  Carsten Peterson,et al.  Random Boolean network models and the yeast transcriptional network , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  G. Church,et al.  Expression dynamics of a cellular metabolic network , 2005, Molecular systems biology.

[14]  P. Bork,et al.  Dynamic Complex Formation During the Yeast Cell Cycle , 2005, Science.

[15]  Wyeth W. Wasserman,et al.  MSCAN: identification of functional clusters of transcription factor binding sites , 2004, Nucleic Acids Res..

[16]  Eric C. Rouchka,et al.  Gibbs Recursive Sampler: finding transcription factor binding sites , 2003, Nucleic Acids Res..

[17]  Feng Gao,et al.  Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data , 2004, BMC Bioinformatics.

[18]  Lucy Shapiro,et al.  A Bacterial Cell-Cycle Regulatory Network Operating in Time and Space , 2003, Science.

[19]  J. Blanchard,et al.  c-fos proto-oncogene regulation and function. , 1994, Critical reviews in oncology/hematology.

[20]  J. Strauss,et al.  Regulation of transcription of the steroidogenic acute regulatory protein (StAR) gene: temporal and spatial changes in transcription factor binding and histone modification , 2004, Molecular and Cellular Endocrinology.

[21]  G. Church,et al.  Systematic determination of genetic network architecture , 1999, Nature Genetics.

[22]  C. Ball,et al.  Saccharomyces Genome Database. , 2002, Methods in enzymology.

[23]  Nicola J. Rinaldi,et al.  Serial Regulation of Transcriptional Regulators in the Yeast Cell Cycle , 2001, Cell.

[24]  A. Sandelin,et al.  Applied bioinformatics for the identification of regulatory elements , 2004, Nature Reviews Genetics.

[25]  J. Bähler.  Cell-cycle control of gene expression in budding and fission yeast. , 2005, Annual review of genetics.

[26]  Ting Chen,et al.  Modeling Gene Expression with Differential Equations , 1998, Pacific Symposium on Biocomputing.

[27]  S. Knudsen,et al.  A new non-linear normalization method for reducing variability in DNA microarray experiments , 2002, Genome Biology.

[28]  Nicola J. Rinaldi,et al.  Computational discovery of gene modules and regulatory networks , 2003, Nature Biotechnology.

[29]  Nicola J. Rinaldi,et al.  Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.

[30]  Michal Linial,et al.  Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..

[31]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[32]  Andrew D. Miller,et al.  Identification and characterisation of human apoptosis inducing proteins using cell-based transfection microarrays and expression analysis , 2006, BMC Genomics.

[33]  Aurélien Mazurie,et al.  Gene networks inference using dynamic Bayesian networks , 2003, ECCB.

[34]  Bartek Wilczynski,et al.  Applying dynamic Bayesian networks to perturbed gene expression data , 2006, BMC Bioinformatics.

[35]  Douglas L. Brutlag,et al.  BioProspector: Discovering Conserved DNA Motifs in Upstream Regulatory Regions of Co-Expressed Genes , 2000, Pacific Symposium on Biocomputing.

[36]  Brad T. Sherman,et al.  DAVID: Database for Annotation, Visualization, and Integrated Discovery , 2003, Genome Biology.

[37]  Michael A. Beer,et al.  Predicting Gene Expression from Sequence , 2004, Cell.

[38]  G. Church,et al.  Identifying regulatory networks by combinatorial analysis of promoter elements , 2001, Nature Genetics.

[39]  M. Gerstein,et al.  Genomic analysis of regulatory network dynamics reveals large topological changes , 2004, Nature.

[40]  A. Agresti.  An introduction to categorical data analysis , 1997 .

[41]  Wei Wang,et al.  Dissecting the transcription networks of a cell using computational genomics. , 2003, Current opinion in genetics & development.

[42]  Kevin Murphy,et al.  Modelling Gene Expression Data using Dynamic Bayesian Networks , 2006 .

[43]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[44]  S. Squazzo,et al.  A computational genomics approach to identify cis-regulatory modules from chromatin immunoprecipitation microarray data--a case study using E2F1. , 2006, Genome research.