Bioinformatics Advance Access originally published online on May 14, 2004
Bioinformatics 2004 20(16):2738-2750; doi:10.1093/bioinformatics/bth320
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Bioinformatics vol. 20 issue 16 © Oxford University Press 2004; all rights reserved.
Prediction of similarly acting cis-regulatory modules by subsequence profiling and comparative genomics in Drosophila melanogaster and D.pseudoobscura
1 The Lipper Center for Computational Genetics and Department of Genetics, 77 Avenue Louis Pasteur and 2 Department of Biological Chemistry and Molecular Pharmacology, 250 Longwood Avenue, Harvard Medical School, Boston, Massachusetts, 02115, USA and 3 Department of Biochemistry and Center of Excellence in Bioinformatics, SUNY at Buffalo, Buffalo, New York, 14214, USA
Received on December 23, 2003; revised on April 7, 2004; accepted on April 27, 2004
Advance Access Publication May 4, 2004
Motivation: To date, computational searches for cis-regulatory modules (CRMs) have relied on two methods. The first, phylogenetic footprinting, has been used to find CRMs in non-coding sequence, but does not directly link DNA sequence with spatio-temporal patterns of expression. The second, based on searches for combinations of transcription factor (TF) binding motifs, has been employed in genome-wide discovery of similarly acting enhancers, but requires prior knowledge of the set of TFs acting at the CRM and the TFs' binding motifs.
Results: We propose a method for CRM discovery that combines aspects of both approaches in an effort to overcome their individual limitations. By treating phylogenetically footprinted non-coding regions (PFRs) as proxies for CRMs, we endeavor to find PFRs near co-regulated genes that are comprised of similar short, conserved sequences. Using Markov chains as a convenient formulation to assess similarity, we develop a sampling algorithm to search a large group of PFRs for the most similar subset. When starting with a set of genes involved in Drosophila early blastoderm development and using phylogenetic comparisons of Drosophila melanogaster and D.pseudoobscura genomes, we show here that our algorithm successfully detects known CRMs. Further, we use our similarity metric, based on Markov chain discrimination, in a genome-wide search, and uncover additional known and many candidate early blastoderm CRMs.
Availability: Software is available via http://arep.med.harvard.edu/enhancers
Supplementary information: Can be accessed at http://arep.med.harvard.edu/enhancers
Contact: see http://arep.med.harvard.edu/email.html
* To whom correspondence should be addressed.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  P. Van Loo and P. Marynen Computational methods for the detection of cis-regulatory modules Brief Bioinform, September 1, 2009; 10(5): 509 - 524. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Narlikar and I. Ovcharenko Identifying regulatory elements in eukaryotic genomes Brief Funct Genomic Proteomic, July 1, 2009; 8(4): 215 - 230. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 V. Gotea and I. Ovcharenko DiRE: identifying distant regulatory elements of co-expressed genes Nucleic Acids Res., July 1, 2008; 36(suppl_2): W133 - W139. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W. S.W. Wong and R. Nielsen Finding cis-regulatory modules in Drosophila using phylogenetic hidden Markov models Bioinformatics, August 15, 2007; 23(16): 2031 - 2037. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Sosinsky, B. Honig, R. S. Mann, and A. Califano Discovering transcriptional regulatory regions in Drosophila by a nonalignment method for phylogenetic footprinting PNAS, April 10, 2007; 104(15): 6305 - 6310. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Pierstorff, C. M. Bergman, and T. Wiehe Identifying cis-regulatory modules by combining comparative and compositional analysis of DNA Bioinformatics, December 1, 2006; 22(23): 2858 - 2864. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
I. J. Donaldson and B. Gottgens TFBScluster web server for the identification of mammalian composite regulatory elements. Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W524 - W528. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. M. Gallo, L. Li, Z. Hu, and M. S. Halfon REDfly: a Regulatory Element Database for Drosophila Bioinformatics, February 1, 2006; 22(3): 381 - 383. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Ashburner and C. M. Bergman Drosophila melanogaster: A case study of a model genomic sequence and its consequences Genome Res., December 1, 2005; 15(12): 1661 - 1667. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. F. Odenwald, W. Rasband, A. Kuzin, and T. Brody EVOPRINTER, a multigenomic comparative tool for rapid identification of functionally important DNA PNAS, October 11, 2005; 102(41): 14700 - 14705. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Aerts, P. Van Loo, G. Thijs, H. Mayer, R. de Martin, Y. Moreau, and B. De Moor TOUCAN 2: the all-inclusive open source workbench for regulatory sequence analysis Nucleic Acids Res., July 1, 2005; 33(suppl_2): W393 - W396. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
I. J. Donaldson, M. Chapman, and B. Gottgens TFBScluster: a resource for the characterization of transcriptional regulatory networks Bioinformatics, July 1, 2005; 21(13): 3058 - 3059. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. M. Bergman, J. W. Carlson, and S. E. Celniker Drosophila DNase I footprint database: a systematic genome annotation of transcription factor binding sites in the fruitfly, Drosophila melanogaster Bioinformatics, April 15, 2005; 21(8): 1747 - 1749. [Abstract] [Full Text] [PDF]
|
|