Plant omics data center: An integrated web repository for interspecies gene expression networks with NLP-based curation

Hajime Ohyanagi; Tomoyuki Takano; Shin Terashima; Masaaki Kobayashi; Maasa Kanno; Kyoko Morimoto; Hiromi Kanegae; Yohei Sasaki; Misa Saito; Satomi Asano; Soichi Ozaki; Toru Kudo; Koji Yokoyama; Koichiro Aya; Keita Suwabe; Go Suzuki; Koh Aoki; Yasutaka Kubo; Masao Watanabe; Makoto Matsuoka; Kentaro Yano

doi:10.1093/pcp/pcu188

Plant omics data center: An integrated web repository for interspecies gene expression networks with NLP-based curation

Hajime Ohyanagi, Tomoyuki Takano, Shin Terashima, Masaaki Kobayashi, Maasa Kanno, Kyoko Morimoto, Hiromi Kanegae, Yohei Sasaki, Misa Saito, Satomi Asano, Soichi Ozaki, Toru Kudo, Koji Yokoyama, Koichiro Aya, Keita Suwabe, Go Suzuki, Koh Aoki, Yasutaka Kubo, Masao Watanabe, Makoto MatsuokaKentaro Yano^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

47 Scopus citations

Abstract

Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.

Original language	English (US)
Pages (from-to)	e9
Journal	Plant and Cell Physiology
Volume	56
Issue number	1
DOIs	https://doi.org/10.1093/pcp/pcu188
State	Published - Jan 1 2015
Externally published	Yes

Bibliographical note

Funding Information:
This work is supported by the Japan Society for the Promotion of Science (JSPS) [Grants-in-Aid for Scientific Research on Innovative Areas (No. 26113716 to K.Y., No. 23113006 to G.S., No. 23113005 to M.M., No. 23113001 to G.S. and M.M.), Scientific Research (A) (No. 23248005 to K.A., No. 25252001 to M.W.), Scientific Research (B) (No. 25292005 to K.S., No. 24380023 to Y.K.) and Scientific Research (C) (No. 25450515 to G.S.); the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) [Supported Program for the Strategic Research Foundation at Private Universities (2014– 2018)]; Meiji University [Research Funding for Computational Software Supporting Program].

Publisher Copyright:
© 2014 The Author.

Keywords

Correspondence analysis
Database
Gene expression network
Manual curation
Natural language processing (NLP)
Omics

ASJC Scopus subject areas

Physiology
Plant Science
Cell Biology

Access to Document

10.1093/pcp/pcu188

Cite this

Ohyanagi, H., Takano, T., Terashima, S., Kobayashi, M., Kanno, M., Morimoto, K., Kanegae, H., Sasaki, Y., Saito, M., Asano, S., Ozaki, S., Kudo, T., Yokoyama, K., Aya, K., Suwabe, K., Suzuki, G., Aoki, K., Kubo, Y., Watanabe, M., ... Yano, K. (2015). Plant omics data center: An integrated web repository for interspecies gene expression networks with NLP-based curation. Plant and Cell Physiology, 56(1), e9. https://doi.org/10.1093/pcp/pcu188

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abstract = "Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.",

keywords = "Correspondence analysis, Database, Gene expression network, Manual curation, Natural language processing (NLP), Omics",

author = "Hajime Ohyanagi and Tomoyuki Takano and Shin Terashima and Masaaki Kobayashi and Maasa Kanno and Kyoko Morimoto and Hiromi Kanegae and Yohei Sasaki and Misa Saito and Satomi Asano and Soichi Ozaki and Toru Kudo and Koji Yokoyama and Koichiro Aya and Keita Suwabe and Go Suzuki and Koh Aoki and Yasutaka Kubo and Masao Watanabe and Makoto Matsuoka and Kentaro Yano",

note = "Funding Information: This work is supported by the Japan Society for the Promotion of Science (JSPS) [Grants-in-Aid for Scientific Research on Innovative Areas (No. 26113716 to K.Y., No. 23113006 to G.S., No. 23113005 to M.M., No. 23113001 to G.S. and M.M.), Scientific Research (A) (No. 23248005 to K.A., No. 25252001 to M.W.), Scientific Research (B) (No. 25292005 to K.S., No. 24380023 to Y.K.) and Scientific Research (C) (No. 25450515 to G.S.); the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) [Supported Program for the Strategic Research Foundation at Private Universities (2014– 2018)]; Meiji University [Research Funding for Computational Software Supporting Program]. Publisher Copyright: {\textcopyright} 2014 The Author.",

year = "2015",

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doi = "10.1093/pcp/pcu188",

language = "English (US)",

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Ohyanagi, H, Takano, T, Terashima, S, Kobayashi, M, Kanno, M, Morimoto, K, Kanegae, H, Sasaki, Y, Saito, M, Asano, S, Ozaki, S, Kudo, T, Yokoyama, K, Aya, K, Suwabe, K, Suzuki, G, Aoki, K, Kubo, Y, Watanabe, M, Matsuoka, M & Yano, K 2015, 'Plant omics data center: An integrated web repository for interspecies gene expression networks with NLP-based curation', Plant and Cell Physiology, vol. 56, no. 1, pp. e9. https://doi.org/10.1093/pcp/pcu188

TY - JOUR

T1 - Plant omics data center

T2 - An integrated web repository for interspecies gene expression networks with NLP-based curation

AU - Ohyanagi, Hajime

AU - Takano, Tomoyuki

AU - Terashima, Shin

AU - Kobayashi, Masaaki

AU - Kanno, Maasa

AU - Morimoto, Kyoko

AU - Kanegae, Hiromi

AU - Sasaki, Yohei

AU - Saito, Misa

AU - Asano, Satomi

AU - Ozaki, Soichi

AU - Kudo, Toru

AU - Yokoyama, Koji

AU - Aya, Koichiro

AU - Suwabe, Keita

AU - Suzuki, Go

AU - Aoki, Koh

AU - Kubo, Yasutaka

AU - Watanabe, Masao

AU - Matsuoka, Makoto

AU - Yano, Kentaro

N1 - Funding Information: This work is supported by the Japan Society for the Promotion of Science (JSPS) [Grants-in-Aid for Scientific Research on Innovative Areas (No. 26113716 to K.Y., No. 23113006 to G.S., No. 23113005 to M.M., No. 23113001 to G.S. and M.M.), Scientific Research (A) (No. 23248005 to K.A., No. 25252001 to M.W.), Scientific Research (B) (No. 25292005 to K.S., No. 24380023 to Y.K.) and Scientific Research (C) (No. 25450515 to G.S.); the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) [Supported Program for the Strategic Research Foundation at Private Universities (2014– 2018)]; Meiji University [Research Funding for Computational Software Supporting Program]. Publisher Copyright: © 2014 The Author.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.

AB - Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.

KW - Correspondence analysis

KW - Database

KW - Gene expression network

KW - Manual curation

KW - Natural language processing (NLP)

KW - Omics

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DO - 10.1093/pcp/pcu188

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VL - 56

SP - e9

JO - Plant and Cell Physiology

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ER -

Plant omics data center: An integrated web repository for interspecies gene expression networks with NLP-based curation

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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