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Evolutionary Bioinformatics

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Computational Identification of Anthocyanin-Specific Transcription Factors using a Rice Microarray and Maximum Boundary Range Algorithm

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Publication Date: 20 Oct 2010

Type: Original Research

Journal: Evolutionary Bioinformatics

Citation: Evolutionary Bioinformatics 2010:6 133-141

doi: 10.4137/EBO.S6077

Abstract

This study identifies 2,617 candidate genes related to anthocyanin biosynthesis in rice using microarray analysis and a newly developed maximum boundary range algorithm. Three seed developmental stages were examined in white cultivar and two black Dissociation insertion mutants. The resultant 235 transcription factor genes found to be associated with anthocyanin were classified into nine groups. It is compared the 235 genes by transcription factor analysis and 593 genes from among clusters of COGs related to anthocyanin functions. Total 32 genes were found to be expressed commonly. Among these, 9 unknown and hypothetical genes were revealed to be expressed at each developmental stage and were verified by RT-PCR. These genes most likely play regulatory roles in either anthocyanin production or metabolism during flavonoid biosynthesis. While these genes require further validation, our results underline the potential usefulness of the newly developed algorithm.


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What Your Colleagues Say About Evolutionary Bioinformatics
My co-authors and I had a very positive experience with the review and publication process in Evolutionary Bioinformatics.  The reviewers were rapid and on point, and publication was also rapid after we made the necessary revisions.
Professor Steven Salzberg (Director, Center for Computational Biology, Johns Hopkins University School of Medicine, Baltimore, MD, USA)
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