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. 2006 Jan 1;34(Database issue):D111-4.
doi: 10.1093/nar/gkj052.

ARED 3.0: the large and diverse AU-rich transcriptome

Tala Bakheet  1 , Bryan R G Williams, Khalid S A Khabar
Affiliations

ARED 3.0: the large and diverse AU-rich transcriptome

Tala Bakheet et al. Nucleic Acids Res. .

Abstract

A comprehensive search that utilized a large set of mRNA data from human genome databases and additionally, expressed sequence tag (EST) database characterized this latest update of AU-rich elements (AREs) containing mRNA database (ARED). A large number of ARE-mRNA, as much as 4000, were recovered and include many of ARE alternative forms. This number represents as much as 5-8% of the human genes depending on the entire number of genes. The new ARED does not contain only larger and diverse number of ARE-mRNAs but additional functionality and enhanced search capabilities are given in the database website http://rc.kfshrc.edu.sa/ared/. These include class and cluster of AREs, source mRNAs, EST evidence, buildup information, retrieval of lists of genes, and integration with current and new NCBI data, such as Entrez ID and Unigene. Gene Ontology analysis shows there are significant differences in functional diversity of ARED when compared with the overall genome. Many of ARE-genes mediate regulatory processes, reactions to outside stimuli, RNA metabolism, and developmental processes particularly those of early and transient responses. The wide interest in mRNA turnover and importance of AREs in health and disease signify the compilation of ARE-genes.

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Figures

Figure 1
Figure 1
ARED 3.0 buildup. A schematic chart showing the stages of the ARED 3.0 buildup. Methods and computer programs used are described in Methods. n denotes number of sequences.
Figure 2
Figure 2
Gene Ontology (GO) of ARE-genes. Annotation of ARE-genes according to GO was performed using FatiGO program () and compared with GO of overall genome using GOStat (). **, *** and **** denote P-values of P < 0.01, P < 0.001 and P < 0.0001, respectively, according to GOStat algorithm.
See this image and copyright information in PMC

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