RiceDB: A Web-Based Integrated Database for Annotating Rice Microarray

Abstract

Abstract: RiceDB, a web-based integrated database to annotate rice microarray in various biological contexts was developed. It is composed of eight modules. RiceMap module archives the process of Affymetrix probe sets mapping to different databases about rice, and aims to the genes represented by a microarray set by retrieving annotation information via the identifier or accession number of every database; RiceGO module indicates the association between a microarray set and gene ontology (GO) categories; RiceKO module is used to annotate a microarray set based on the KEGG biochemical pathways; RiceDO module indicates the information of domain associated with a microarray set; RiceUP module is used to obtain promoter sequences for all genes represented by a microarray set; RiceMR module lists potential microRNA which regulated the genes represented by a microarray set; RiceCD and RiceGF are used to annotate the genes represented by a microarray set in the context of chromosome distribution and rice paralogous family distribution. The results of automatic annotation are mostly consistent with manual annotation. Biological interpretation of the microarray data is quickened by the help of RiceDB.

Key words: Affymetrix, microarray annotation, Oryza sativa, molecular database

HE Fei, SHI Qing-yun, CHEN Ming, WU Ping. RiceDB: A Web-Based Integrated Database for Annotating Rice Microarray[J]. RICE SCIENCE, 2007, 14(4): 256-264 .

References

1 Sasaki T, Burr B. International rice genome sequencing project: The effort to completely sequence the rice genome. Curr Opin Plant Biol, 2000, 3: 138−141.
2 International Rice Genome Sequencing Project. The map- based sequence of the rice genome. Nature, 2005, 436: 793− 800.
3 Yu J, Hu S, Wang J, Wong G K S, Li S G, Liu B, Deng Y J, Dai L, Zhou Y, Zhang X Q, Cao M L, Liu J, Sun J D, Tang J B, Chen Y J, Huang X B, Lin W, Ye C, Tong W, Cong L J, Geng J N, Han Y J, Li L, Li W, Hu G Q, Huang X G, Li W J, Li J, Liu Z W, Li L, Liu J P, Qi Q H, Liu J S, Li L, Li T, Wang X G, Lu H, Wu T T, Zhu M, Ni P X, Han H, Dong W, Ren X Y, Feng X L, Cui P, Li X R, Wang H, Xu X, Zhai W X, Xu Z, Zhang J S, He S J, Zhang J G, Xu J C, Zhang K L, Zheng X W, Dong J H, Zeng W Y, Tao T, Ye J, Tan J, Ren X D, Chen X W, He J, Liu D F, Tian W, Tian C G, Xia H A, Bao Q Y, Li G, Gao H, Cao T, Wang J, Zhao W M, Li P, Chen W, Wang X D, Zhang Y, Hu J F, Wang J, Liu S, Yang J, Zhang G Y, Xiong Y Q, Li Z J, Mao L, Zhou C S, Zhu Z, Chen R S, Hao B L, Zheng W M, Chen S Y, Guo W, Li G J, Liu S Q, Tao M, Wang J, Zhu L H, Yuan L P, Yang H M. A draft sequence of the rice genome (Oryza sativa L. ssp. indica). Science, 2002, 296: 79−92.
4 Kikuchi S, Satoh K, Nagata T, Kawagashira N, Doi K, Kishimoto N, Yazaki J, Ishikawa M, Yamada H, Ooka H, Hotta I, Kojima K, Namiki T, Ohneda E, Yahagi W, Suzuki K, Li C J, Ohtsuki K, Shishiki T, Otomo Y, Murakami K, Iida Y, Sugano S, Fujimura T, Suzuki Y, Tsunoda Y, Kurosaki T, Kodama T, Masuda H, Kobayashi M, Xie Q H, Lu M, Narikawa R, Sugiyama A, Mizuno K, Yokomizo S, Niikura J, Ikeda R, Ishibiki J, Kawamata M, Yoshimura A, Miura J, Kusumegi T, Oka M, Ryu R, Ueda M, Matsubara K, Kawai J, Carninci P, Adachi J, Aizawa K, Arakawa T, Fukuda S, Hara A, Hashidume W, Hayatsu N, Imotani K, Ishii Y, Itoh M, Kagawa I, Kondo S, Konno H, Miyazaki A, Osato N, Ota Y, Saito R, Sasaki D, Sato K, Shibata K, Shinagawa A, Shiraki T, Yoshino M, Hayashizaki Y. Collection, mapping, and annotation of over 28,000 cDNA clones from japonica rice. Science, 2003, 301: 376−379.
5 Hennig L, Gruissem W, Grossniklaus U, Köhler C. Transcriptional programs of early stages of plant reproduction. Plant Physiol, 2004, 132: 640−652.
6 Clarke J D，Zhu T. Microarray analysis of the transcriptome as a stepping stone towards understanding biological systems: Pratical considerations and perspectives. Plant J, 2006, 45: 630−650.
7 Liu G, Loraine A E, Shigeta R, Cline M, Cheng J, Valmeekam V, Sun S, Kulp D, Siani-Rose M A. NetAffx: Affymetrix probesets and annotations. Nucl Acids Res, 2003, 31: 82−86.
8 Shen L, Gong J, Caldo R A, Nettleton D, Cook D, Wise R P, Dickerson J A. BarleyBase: An expression profiling database for plant genomics. Nucl Acids Res, 2005, 33: D614−D618.
9 Al-Shahrour F, Diaz-Uriarte R, Dopazo J. FatiGO: A web tool for finding significant associations of gene ontology terms with groups of genes. Bioinformatics, 2004, 20: 578−580.
10 Wrobel G, Chalmel F, Primig M. Gocluster integrates statistical analysis and functional interpretation of microarray expression data. Bioinformatics, 2005, 21: 3575−3577.
11 Cheng J, Sun S, Tracy A, Hubbell E, Morris J, Valmeekam V, Kimbrough A, Cline M S, Liu G Y, Shigeta R, Kulp D, Siani-Rose M A. NetAffx gene ontology mining tool: A visual approach for microarray data analysis. Bioinformatics, 2004, 20: 1462−1463.
12 Dennis G Jr, Sherman B T, Hosack D A, Yang J, Gao W, Lane H C, Lempicki R A. DAVID: Database for annotation, visualization and integrated discovery. Genome Biol, 2003, 4: 3.
13 Zeeberg B R, Feng W M, Wang G, Wang M D, Fojo A T, Sunshine M, Narasimhan S, Kane D W, Reinhold W C, Lababidi S, Bussey K J, Riss J, Barrett J C, Weinstein J M. GoMiner: Resource for biological interpretation of genomic and proteomic data. Genome Biol, 2003, 4: 28.
14 Grosu P, Townsend J P, Hartl D L, Cavalieri D. Pathway processor: A tool for integrating whole-genome expression results into metabolic networks. Genome Res, 2002, 12: 1121−1126.
15 Pan D Y, Sun N, Cheung K H, Guan Z, Ma L G, Holford M, Deng X W, Zhao H. PathMAPA: A tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis. BMC Bioinformatics, 2003, 4: 56.
16 Chung H J, Kim M, Park C H, Kim J H. ArrayXPath: Mapping and visualization microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics. Nucl Acids Res, 2004, 32: W460−W464.
17 Mao X Z, Cai T, Olyarchuk J G, Wei L P. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics, 2005, 21: 3787−3793.
18 Higo K, Ugawa Y, Iwamoto M, Korenaga T. Plant cis-acting regulatory DNA elements (PLACE) database. Nucl Acids Res, 1999, 27: 297−300.
19 Bateman A, Birney E, Cerruti L, Durbin R, Etwiller L, Eddy S R, Griffiths-Jones S, Howe K L, Marshall M, Sonnhammer E L L. The Pfam protein families database. Nucl Acids Res, 2004, 32: D138−D141.
20 Zhang Y J. miRU: An automated plant miRNA target prediction server. Nucl Acids Res, 2005, 33: W701−W704.
21 Walia H, Wilson C, Cindamine P, Liu X, Ismail A M, Zeng L H, Wanamaker S I, Mandal J, Xu J, Cui X P, Close T J. Comparative transcriptional profiling of two contrasting rice genotypes under salinity stress during the vegetative growth stage. Plant Physiol, 2005, 139: 822−835.
22 Spellman P T, Rubin G M. Evidence for large domains of similarly expressed genes in the Drosophila. Genome J Biol, 2002, 1: 5.

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