Literature DB >> 12595247

Comparative promoter analysis and its application in analysis of PTH-regulated gene expression.

Ping Qiu1, Ling Qin, Richard P Sorrentino, Jonathan R Greene, Luquan Wang, Nicola C Partridge.   

Abstract

Taking advantage of the "working draft" of the human genome and the MIT shotgun assembly of the mouse genome, we performed a comparative promoter analysis of human RefSeq mRNA (sequences from GenBank's RefSeq database). By combining this analysis with a transcription factor (TF) binding site analysis using a TRANSFAC position weight matrix (PWM) search, 86% of non-specific TF sites were removed. Using a set of genes that are regulated by parathyroid hormone (PTH), a statistical analysis was performed on the conserved TF binding sites among a set of eight human and mouse genes. From among the eight genes tested, we obtained a set of 31 TFs, suggesting possible roles for associated genes in PTH-mediated pathways. All three known PTH-responsive TFs (AP1, RUNX2, CREB) were correctly predicted by this analysis as well as two other potential TFs (VDR and CEBP Delta). Additionally, a model was made to describe the TF site characteristic module of PTH-regulated genes. This model was then used to search all human RefSeq gene promoters with established human-mouse ortholog relationships to identify other PTH-regulated genes. This comparative approach combined with statistical analysis proved to be sufficiently specific to decipher critical TFs involved in PTH-regulated pathways.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12595247     DOI: 10.1016/s0022-2836(03)00053-6

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  7 in total

1.  A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles.

Authors:  Li-Wei Chang; Rakesh Nagarajan; Jeffrey A Magee; Jeffrey Milbrandt; Gary D Stormo
Journal:  Genome Res       Date:  2006-01-31       Impact factor: 9.043

Review 2.  Computational methods to dissect cis-regulatory transcriptional networks.

Authors:  Vibha Rani
Journal:  J Biosci       Date:  2007-12       Impact factor: 1.826

3.  Computational identification and functional validation of regulatory motifs in cartilage-expressed genes.

Authors:  Sherri R Davies; Li-Wei Chang; Debabrata Patra; Xiaoyun Xing; Karen Posey; Jacqueline Hecht; Gary D Stormo; Linda J Sandell
Journal:  Genome Res       Date:  2007-09-04       Impact factor: 9.043

4.  Comparative promoter analysis allows de novo identification of specialized cell junction-associated proteins.

Authors:  Clemens D Cohen; Andreas Klingenhoff; Anissa Boucherot; Almut Nitsche; Anna Henger; Bodo Brunner; Holger Schmid; Monika Merkle; Moin A Saleem; Klaus-Peter Koller; Thomas Werner; Hermann-Josef Gröne; Peter J Nelson; Matthias Kretzler
Journal:  Proc Natl Acad Sci U S A       Date:  2006-03-31       Impact factor: 11.205

5.  BiologicalNetworks 2.0--an integrative view of genome biology data.

Authors:  Sergey Kozhenkov; Yulia Dubinina; Mayya Sedova; Amarnath Gupta; Julia Ponomarenko; Michael Baitaluk
Journal:  BMC Bioinformatics       Date:  2010-12-29       Impact factor: 3.169

6.  A genome-wide cis-regulatory element discovery method based on promoter sequences and gene co-expression networks.

Authors:  Zhen Gao; Ruizhe Zhao; Jianhua Ruan
Journal:  BMC Genomics       Date:  2013-01-21       Impact factor: 3.969

7.  The entire organization of transcription units on the Bacillus subtilis genome.

Authors:  Hirokazu Kobayashi; Joe Akitomi; Nobuyuki Fujii; Kazuo Kobayashi; Md Altaf-Ul-Amin; Ken Kurokawa; Naotake Ogasawara; Shigehiko Kanaya
Journal:  BMC Genomics       Date:  2007-06-28       Impact factor: 3.969

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.