Abstract
Reliable identification and assignment of cis-regulatory elements in promoter regions is a challenging problem in biology. The sophistication of transcriptional regulation in higher eukaryotes, particularly in metazoans, could be an important factor contributing to their organismal complexity. Here we present an integrated approach where networks of co-expressed genes are combined with gene ontology–derived functional networks to discover clusters of genes that share both similar expression patterns and functions. Regulatory elements are identified in the promoter regions of these gene clusters using a Gibbs sampling algorithm implemented in the A-GLAM software package. Using this approach, we analyze the cell-cycle co-expression network of the yeast Saccharomyces cerevisiae, showing that this approach correctly identifies cis-regulatory elements present in clusters of co-expressed genes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, Danford TW, Hannett NM, Tagne JB, Reynolds DB, Yoo J et al. Transcriptional regulatory code of a eukaryotic genome. Nature 2004, 431(7004):99–104.
Bieda M, Xu X, Singer MA, Green R, Farnham PJ. Unbiased location analysis of E2F1-binding sites suggests a widespread role for E2F1 in the human genome. Genome Res 2006, 16(5):595–605.
Cawley S, Bekiranov S, Ng HH, Kapranov P, Sekinger EA, Kampa D, Piccolboni A, Sementchenko V, Cheng J, Williams AJ et al. Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 2004, 116(4):499–509.
Guccione E, Martinato F, Finocchiaro G, Luzi L, Tizzoni L, Dall' Olio V, Zardo G, Nervi C, Bernard L, Amati B. Myc-binding-site recognition in the human genome is determined by chromatin context. Nat Cell Biol 2006, 8(7):764–770.
Tompa M, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV, Frith MC, Fu Y, Kent WJ et al. Assessing computational tools for the discovery of transcription factor binding sites. Nat Biotechnol 2005, 23(1):137–144.
Ohler U, Niemann H. Identification and analysis of eukaryotic promoters: recent computational approaches. Trends Genet 2001, 17(2):56–60.
Marino-Ramirez L, Spouge JL, Kanga GC, Landsman D. Statistical analysis of over-represented words in human promoter sequences. Nucleic Acids Res 2004, 32(3):949–958.
Tharakaraman K, Marino-Ramirez L, Sheetlin S, Landsman D, Spouge JL. Alignments anchored on genomic landmarks can aid in the identification of regulatory elements. Bioinformatics 2005, 21(Suppl 1):i440–448.
Cho RJ, Campbell MJ, Winzeler EA, Steinmetz L, Conway A, Wodicka L, Wolfsberg TG, Gabrielian AE, Landsman D, Lockhart DJ et al. A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell 1998, 2(1):65–73.
Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell 1998, 9(12):3273–3297.
Lord PW, Stevens RD, Brass A, Goble CA. Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation. Bioinformatics 2003, 19(10):1275–1283.
Azuaje F, Wang H, Bodenreider O. Ontology-driven similarity approaches to supporting gene functional assessment. In: Proceedings of the ISMB’2005 SIG Meeting on Bio-Ontologies. Detroit, MI, 2005:9–10.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13(11):2498–2504.
Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 2003, 4:2.
Tsaparas P, Marino-Ramirez L, Bodenreider O, Koonin EV, Jordan IK. Global similarity and local divergence in human and mouse gene co-expression networks. BMC Evol Biol 2006, 6:70.
Babu MM. An introduction to microarray data analysis. In: Computational Genomics: Theory and Application, Edited by Grant RP. Cambridge, UK: Horizon Bioscience, 2004:225–249.
Jordan IK, Marino-Ramirez L, Koonin EV. Evolutionary significance of gene expression divergence. Gene 2005, 345(1):119–126.
Jordan IK, Marino-Ramirez L, Wolf YI, Koonin EV. Conservation and coevolution in the scale-free human gene coexpression network. Mol Biol Evol 2004, 21(11):2058–2070.
Lawrence CE, Altschul SF, Boguski MS, Liu JS, Neuwald AF, Wootton JC. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 1993, 262(5131):208–214.
Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25(17):3389–3402.
Staden R. Methods for calculating the probabilities of finding patterns in sequences. Comput Appl Biosci 1989, 5(2):89–96.
Tharakaraman K, Marino-Ramirez L, Sheetlin S, Landsman D, Spouge JL. Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements. BMC Bioinformatics 2006, 7:408.
Orwant J, Hietaniemi J, Macdonald J. Mastering Algorithms with Perl. Sebastopol, CA: O'Reilly, 1999.
Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 2005, 21(16):3448–3449.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statist Soc Ser B 1995, 57(1):289–300.
Marino-Ramirez L, Jordan IK, Landsman D. Multiple independent evolutionary solutions to core histone gene regulation. Genome biology 2006, 7(12):R122.
Eriksson PR, Mendiratta G, McLaughlin NB, Wolfsberg TG, Marino-Ramirez L, Pompa TA, Jainerin M, Landsman D, Shen CH, Clark DJ. Global regulation by the yeast Spt10 protein is mediated through chromatin structure and the histone upstream activating sequence elements. Mol Cell Biol 2005, 25(20):9127–9137.
Schneider TD, Stephens RM. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res 1990, 18(20):6097–6100.
Crooks GE, Hon G, Chandonia JM, Brenner SE. WebLogo: a sequence logo generator. Genome Res 2004, 14(6):1188–1190.
Acknowledgments
The authors would like to thank King Jordan for important suggestions and helpful discussions and Alex Brick for his assistance in obtaining intergenic regions during his internship at NCBI. This research was supported by the Intramural Research Program of the NIH, NLM, NCBI.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Humana Press, a part of Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Mariño-Ramírez, L., Tharakaraman, K., Bodenreider, O., Spouge, J., Landsman, D. (2009). Identification of cis-Regulatory Elements in Gene Co-expression Networks Using A-GLAM. In: Ireton, R., Montgomery, K., Bumgarner, R., Samudrala, R., McDermott, J. (eds) Computational Systems Biology. Methods in Molecular Biology, vol 541. Humana Press. https://doi.org/10.1007/978-1-59745-243-4_1
Download citation
DOI: https://doi.org/10.1007/978-1-59745-243-4_1
Published:
Publisher Name: Humana Press
Print ISBN: 978-1-58829-905-5
Online ISBN: 978-1-59745-243-4
eBook Packages: Springer Protocols