Learning transcriptional regulation on a genome scale: A theoretical analysis based on gene expression data

Briefings in Bioinformatics

Volumn 13, Issue 2, 2012, Pages 150-161

  Wu, Ming ^a   Chan, Christina ^a  

^a Michigan State University   (United States)

Author keywords

Gene expression; Network reconstruction; Transcription factors; Transcriptional regulation

Indexed keywords

TRANSCRIPTOME;

ARTICLE; FUNGAL GENOME; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC TRANSCRIPTION; GENETICS; METHODOLOGY; MICROARRAY ANALYSIS; SACCHAROMYCES CEREVISIAE;

GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENOME, FUNGAL; MICROARRAY ANALYSIS; SACCHAROMYCES CEREVISIAE; TRANSCRIPTION, GENETIC; TRANSCRIPTOME;

EID: 84858266638     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbr029     Document Type: Article

References (48)

1. Kim HD, Shay T, O'Shea EK, et al. Transcriptional regulatory circuits: predicting numbers from alphabets. Science 2009;325:429-32.
2. Chua G, Robinson MD, Morris Q, et al. Transcriptional networks: reverse-engineering gene regulation on a global scale. Curr Opin Microbiol 2004;7:638-46.
3. Hecker M, Lambeck S, Toepfer S, et al. Gene regulatory network inference: data integration in dynamic models-a review. BioSystems 2009;96:86-103.
4. Lee W, Tzou W. Computational methods for discovering gene networks from expression data. BriefBioinform 2009;10: 408-23.
5. Gardner TS, Faith JJ. Reverse-engineering transcription control networks. Phys Life Rev 2010;2:65-88.
6. Das D, Pellegrini M, Gray JW. A primer on regression methods for decoding cis-regulatory logic. PLoS Comput Biol 2009;5:e1000269.
7. Margolin AA, Califano A. Theory and limitations of genetic network inference from microarray data. Ann NYAcad Sci 2007;1115:51-72.
8. de Bivort B, Huang S, Bar-Yam Y. Dynamics of cellular level function and regulation derived from murine expression array data. PNASUSA 2004;101:17687-92.
9. Ihmels J, Friedlander G, Bergmann S, et al. Revealing modular organization in the yeast transcriptional network. Nat Genet 2002;31:370-7.
10. Marbach D, Prill RJ, Schaffter T, et al. Revealing strengths and weaknesses of methods for gene network inference. PNAS 2010;107:6286-91.
11. Lin K, Husmeier D. Modelling transcriptional regulation with a mixture of factor analyzers and variational Bayesian expectation maximization. EURASIP J Bioinform Syst Biol 2009;601068.
12. Segal E, Shapira M, Regev A, et al. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat Genet 2003;34: 166-76.
13. Segal E, Raveh-Sadka T, Schroeder M, et al. Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature 2008;451:535-540.
14. Sabatti C, James GM. Bayesian sparse hidden components analysis for transcription regulation networks. Bioinformatics 2006;22:739-46.
15. Ernst J, Vainas O, Harbison CT, et al. Reconstructing dynamic regulatory maps. Mol Syst Biol 2007;3:74.
16. Beer MA, Tavazoie S. Predicting gene expression from sequence. Cell 2004;117:185-98.
17. Gasch AP, Spellman PT, Kao CM, et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell 2000;11:4241-57.
18. Spellman PT, Sherlock G, Zhang MQ, et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 1998;9:3273-97.
19. Monteiro PT, Mendes ND, Teixeira MC, et al. YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Res 2008;36:D132-6.
20. Teixeira MC, Monteiro P, Jain P, et al. The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Res 2006; 34:D446-51.
21. Shi Y, Simon I, Mitchell T, et al. A combined expression-interaction model for inferring the temporal activity of transcription factors. Proceedings of the 12th Annual International Conference on Research in Computational Molecular Biology, Singapore, 2008. pp. 82-97, Springer.
22. Herrgård MJ, Covert MW, Palsson BØ. Reconciling gene expression data with known genome-scale regulatory network structures. Genome Res 2003;13:2423-34.
23. Venters BJ, Pugh BF. How eukaryotic genes are transcribed. Crit Rev Biochem Mol Biol 2009;44:117-41.
24. Davidson EH. Genomic regulatory systems: in development and evolution. 1st edn. San Diego: Academic Press, 2001.
25. Nuzhdin SV, Rychkova A, Hahn MW. The strength of transcription-factor binding modulates co-variation in transcriptional networks. TrendsGenet 2010;26:51-3.
26. Wunderlich Z, Mirny LA. Different gene regulation strategies revealed by analysis of binding motifs. Trends Genet 2009;25:434-40.
27. Li X, MacArthur S, Bourgon R, et al. Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm. PLoS Biol 2008;6:e27.
28. Ucar D, Beyer A, Parthasarathy S, etal. Predicting functionality of protein-DNA interactions by integrating diverse evidence. Bioinformatics 2009;25:i137-44.
29. White RJ, Sharrocks AD. Coordinated control of the gene expression machinery. TrendsGenet 2010;26:214-20.
30. Amorim MJ, Cotobal C, Duncan C, et al. Global coordination of transcriptional control and mRNA decay during cellular differentiation. Mol Syst Biol 2010;6:380.
31. Hartemink A, Gifford D, Jaakkola T, et al. Combining location and expression data for principled discovery of genetic regulatory network models. 2002;449:437.
32. Werhli AV, Husmeier D. Reconstructing gene regulatory networks with Bayesian networks by combining expression data with multiple sources of prior knowledge. Stat Appl Genet Mol Biol 2007;6:15.
33. Huang SC, Fraenkel E. Integrating proteomic, transcriptional, and interactome data reveals hidden components of signaling and regulatory networks. Sci Signal 2009;2:ra40.
34. Wang Y, Liu CL, Storey JD, et al. Precision and functional specificity in mRNA decay. PNASUSA 2002;99:5860-5.
35. Harbison CT, Gordon DB, Lee TI, et al. Transcriptional regulatory code of a eukaryotic genome. Nature 2004;431: 99-104.
36. Hansen L, Marino-Ramirez L, Landsman D. Many sequence-specific chromatin modifying protein-binding motifs show strong positional preferences for potential regulatory regions in the Saccharomyces cerevisiae genome. Nucleic Acids Res 2010;38:1772-9.
37. Goh WS, Orlov Y, Li J, et al. Blurring of high-resolution data shows that the effect of intrinsic nucleosome occupancy on transcription factor binding is mostly regional, not local. PLoS Comput Biol 2010;6:e1000649.
38. Hansen M, Everett L, Singh L, et al. Mimosa: Mixture model of co-expression to detect modulators of regulatory interaction. Algorithms Mol Biol 2010;5:4.
39. Pan Y, Tsai C, Ma B, et al. Mechanisms of transcription factor selectivity. Trends Genet 2010;26:75-83.
40. Browning DF, Busby SJ. The regulation of bacterial transcription initiation. Nat Rev Microbiol 2004;2:57-65.
41. Bintu L, Buchler NE, Garcia HG, et al. Transcriptional regulation by the numbers: models. Curr Opin Genet Dev 2005;15:116-24.
42. Bintu L, Buchler NE, Garcia HG, et al. Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev 2005;15:125-35.
43. Gitter A, Siegfried Z, Klutstein M, et al. Backup in gene regulatory networks explains differences between binding and knockout results. Mol Syst Biol 2009;5:276.
44. Hu Z, Killion PJ, Iyer VR. Genetic reconstruction of a functional transcriptional regulatory network. Nat Genet 2007;39:683-7.
45. Sprinzak E, Cokus SJ, Yeates TO, et al. Detecting coordinated regulation of multi-protein complexes using logic analysis of gene expression. BMC Syst Biol 2009;3:115.
46. Ni L, Bruce C, Hart C, et al. Dynamic and complex transcription factor binding during an inducible response in yeast. GenesDev 2009;23:1351-63.
47. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005;120:15-20.
48. Wang R, Jin G, Zhang X, et al. Modeling post-transcriptional regulation activity of small non-coding RNAs in Escherichia coli. BMC Bioinformatics 2009;10:S6.