Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Novel Method to Quantify The Distribution of Transcription Start Site
Budrul Ahsan, Shinichi Morishita
Pages - 105 - 112     |    Revised - 15-09-2012     |    Published - 24-10-2012
Volume - 6   Issue - 5    |    Publication Date - October 2012  Table of Contents
transcription start sites, gene regulation, 5'end mRNA, CAGE, gene expression profiling
Gene regulation is a significant problem in functional genomics. To understand gene regulation process, several tag-based sequencing methods such as Cap Analysis of Gene Expression (CAGE), 5’ end Serial Analysis of Gene Expression (5’ end SAGE) are developed. These novel methods pave the way to study gene regulation and expression profiling through Transcription Start Sites (TSSs). Several studies collected 5’end mRNA tag data from various species and showed that most of the promoters do not show a preference to a distinct TSS for a gene. Most of the promoters have several TSSs that are locally distributed in particular genomic regions. Analysis of these TSSs distributions may decipher the gene regulatory process. For that purpose, a numerical representation of TSS distribution is crucial for quantitative analysis of 5’end mRNA data. To characterize the TSSs distribution of a promoter as a single measurement score, we developed a novel scoring method that describes the distribution in a more meaningful way. Efficiency of this method to distinguish TSSs distribution is evaluated on both synthetic and real dataset. Finally, this numerical representation enables us to analyze 5’end mRNA data to understand gene regulation process more precisely.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
1 . Alberts, B., Molecular biology of the cell. 5th ed. 2008, New York: Garland Science.
2 . Hashimoto, S., et al., 5'-end SAGE for the analysis of transcriptional start sites. Nat Biotechnol,2004. 22(9): p. 1146-9.
3 . Carninci, P., et al., Genome-wide analysis of mammalian promoter architecture and evolution. Nat Genet, 2006. 38(6): p. 626-35.
4 . Ni, T., et al., A paired-end sequencing strategy to map the complex landscape of transcription initiation. Nat Methods. (7): p. 521-7.
5 . Fullwood, M.J., et al., Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Res, 2009. 19(4): p. 521-32.
6 . Hashimoto, S., et al., High-resolution analysis of the 5'-end transcriptome using a next generation DNA sequencer. PLoS ONE, 2009. (1): p. e4108.
7 . Valen, E., et al., Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE. Genome Res, 2009. 19(2): p. 255-65.
8 . Hoskins, R.A., et al., Genome-wide analysis of promoter architecture in Drosophila melanogaster.Genome Res. 21(2): p. 182-92.
9 . Gini, C., Measurement of Inequality and Incomes The Economic Journal, 1921(31): p. 3.
10 . Anand, S., Inequality and poverty in Malaysia : measurement and decomposition. A World Bank research publication. 1983, New York: Published for the World Bank [by] Oxford University Press. x,371 p.
11 . Kendall, M.G. and A. Stuart, The advanced theory of statistics. [3 vol. ed. 1963, New York,: Hafner Pub. Co.
12 . Ahsan, B., et al., MachiBase: a Drosophila melanogaster 5'-end mRNA transcription database.Nucleic Acids Res, 2009. 37(Database issue): p. D49-53.
13 . Drysdale, R.A. and M.A. Crosby, FlyBase: genes and gene models. Nucleic Acids Res, 2005.33(Database issue): p. D390-5.
Mr. Budrul Ahsan
The University of Tokyo - Japan
Miss Shinichi Morishita
The University of Tokyo Kashiwa - Japan