Rice Expression Database (RED): An integrated RNA-Seq-derived gene expression database for rice

Lin Xia; Dong Zou; Jian Sang; Xingjian Xu; Hongyan Yin; Mengwei Li; Shuangyang Wu; Songnian Hu; Lili Hao; Zhang Zhang

doi:10.1016/j.jgg.2017.05.003

Volume 44 Issue 5

May 2017

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Article Navigation > Journal of Genetics and Genomics > 2017 > 44(5): 235-241

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Rice Expression Database (RED): An integrated RNA-Seq-derived gene expression database for rice

doi: 10.1016/j.jgg.2017.05.003

Lin Xia^{a, b, c, #},
Dong Zou^{a, b, #},
Jian Sang^{a, b, c},
Xingjian Xu^{a, b, c},
Hongyan Yin^{a, b, c},
Mengwei Li^{a, b, c},
Shuangyang Wu^{a, c},
Songnian Hu^{a, c, d},
Lili Hao^{a, b},
Zhang Zhang^{a, b, c, d}

a
CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
b
BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
c
University of Chinese Academy of Sciences, Beijing 100049, China
d
Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai 200438, China

More Information

Corresponding author: E-mail address: haolili@big.ac.cn (Lili Hao); E-mail address: zhangzhang@big.ac.cn (Zhang Zhang)
Received Date: 2017-01-03
Revised Date: 2017-04-24
Accepted Date: 2017-05-02

Available Online: 2017-05-04

Publish Date: 2017-05-20

Abstract

Abstract

Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community. Here, we present RED (Rice Expression Database; http://expression.ic4r.org), an integrated database of rice gene expression profiles derived entirely from RNA-Seq data. RED features a comprehensive collection of 284 high-quality RNA-Seq experiments, integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments. Based on massive expression profiles, RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene(s) of interest. Besides, it provides user-friendly web interfaces for querying, browsing and visualizing expression profiles of concerned genes. Together, as a core resource in BIG Data Center, RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice.
- Rice expression database,
- Expression profiles,
- Housekeeping gene,
- Tissue-specific gene,
- Co-expression network

These authors contributed equally to this work.

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References(21)

References

[1]	BIG Data Center Members The BIG Data Center: from deposition to integration to translation Nucleic Acids Res., 45 (2017),pp. D18-D24
[2]	Bolger, A.M., Lohse, M., Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data Bioinformatics, 30 (2014),pp. 2114-2120
[3]	Cao, P., Jung, K.H., Choi, D. et al. The rice oligonucleotide array database: an atlas of rice gene expression Rice, 5 (2012),p. 17
[4]	Hamada, K., Hongo, K., Suwabe, K. et al. OryzaExpress: an integrated database of gene expression networks and omics annotations in rice Plant Cell Physiol., 52 (2011),pp. 220-229
[5]	IC4R Project Consortium Information Commons for rice (IC4R) Nucleic Acids Res., 44 (2016),pp. D1172-D1180
[6]	International Rice Genome Sequencing Project The map-based sequence of the rice genome Nature, 436 (2005),pp. 793-800
[7]	Kato, H., Minamikawa, T. Identification and characterization of a rice cysteine endopeptidase that digests glutelin Eur. J. Biochem., 239 (1996),pp. 310-316
[8]	Kawahara, Y., de la Bastide, M., Hamilton, J.P. et al. Rice, 6 (2013),p. 4
[9]	Kawahara, Y., Oono, Y., Wakimoto, H. et al. TENOR: database for comprehensive mRNA-Seq experiments in rice Plant Cell Physiol., 57 (2016),p. e7
[10]	Kim, D., Langmead, B., Salzberg, S.L. HISAT: a fast spliced aligner with low memory requirements Nat. Methods, 12 (2015),pp. 357-360
[11]	Ouyang, S., Zhu, W., Hamilton, J. et al. The TIGR rice genome annotation resource: improvements and new features Nucleic Acids Res., 35 (2007),pp. D883-D887
[12]	Pertea, M., Pertea, G.M., Antonescu, C.M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads Nat. Biotechnol., 33 (2015),pp. 290-295
[13]	Petryszak, R., Keays, M., Tang, Y.A. et al. Expression Atlas update – an integrated database of gene and protein expression in humans, animals and plants Nucleic Acids Res., 44 (2016),pp. D746-D752
[14]	Sakai, H., Lee, S.S., Tanaka, T. et al. Rice Annotation Project Database (RAP-DB): an integrative and interactive database for rice genomics Plant Cell Physiol., 54 (2013),p. e6
[15]	Sato, Y., Antonio, B.A., Namiki, N. et al. Nucleic Acids Res., 39 (2011),pp. D1141-D1148
[16]	Skinner, M.E., Uzilov, A.V., Stein, L.D. et al. JBrowse: a next-generation genome browser Genome Res., 19 (2009),pp. 1630-1638
[17]	Stuart, J.M., Segal, E., Koller, D. et al. A gene-coexpression network for global discovery of conserved genetic modules Science, 302 (2003),pp. 249-255
[18]	Yanai, I., Benjamin, H., Shmoish, M. et al. Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification Bioinformatics, 21 (2005),pp. 650-659
[19]	Yu, J., Hu, S., Wang, J. et al. Science, 296 (2002),pp. 79-92
[20]	Zhu, J., He, F., Hu, S. et al. On the nature of human housekeeping genes Trends Genet., 24 (2008),pp. 481-484
[21]	Zou, D., Sun, S., Li, R. et al. MethBank: a database integrating next-generation sequencing single-base-resolution DNA methylation programming data Nucleic Acids Res., 43 (2015),pp. D54-D58