in silico prediction of gene function associated with agronomically useful traits in crops using differential network analysis
Project/Area Number |
26850024
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Horticultural science
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Research Institution | Institute of Physical and Chemical Research |
Principal Investigator |
Fukushima Atsushi 国立研究開発法人理化学研究所, 環境資源科学研究センター, 研究員 (80415281)
|
Project Period (FY) |
2014-04-01 – 2017-03-31
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Project Status |
Completed (Fiscal Year 2016)
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Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2014: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
|
Keywords | バイオインフォマティクス / ネットワーク解析 / 共発現解析 / 遺伝子発現調節ネットワーク / 遺伝子共発現 / ディファレンシャル共発現 / ネットワーク推定 / トマト / 統合データベース |
Outline of Final Research Achievements |
This study aims to develop computational prediction methods of gene function associated with agronomically useful traits in crops using differential network analysis. To this end we analyzed comparative transcriptome dataset from leaf development samples using three Solanum species exhibiting different leaf development characteristics. Our differential network approach has detected coexpression alterations for genes making up the most significantly divergent cluster, and has identified thousands of potential key gene pairs under interspecific differential regulation. We are now developing and integrating a set of R pakcages for the analysis.
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Report
(4 results)
Research Products
(13 results)
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[Journal Article] Comparative Characterization of the Leaf Tissue of Physalis alkekengi and Physalis peruviana Using RNA-seq and Metabolite Profiling2016
Author(s)
Atsushi Fukushima, Michimi Nakamura, Hideyuki Suzuki, Mami Yamazaki, Eva Knoch, Tetsuya Mori, Naoyuki Umemoto, Masaki Morita, Go Hirai, Mikiko Sodeoka, and Kazuki Saito
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Journal Title
Frontiers in Plant Science
Volume: 7
Pages: 1883-1883
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] Lack of cytosolic glutamine synthetase1;2 in vascular tissues of axillary buds caused severe reduction in their outgrowth and disorder of metabolic balance in rice seedlings2015
Author(s)
Ohashi, M., Ishiyama, K., Kusano, M., Fukushima, A., Kojima, S., Hanada, A., Kanno, K., Hayakawa, T., Seto, Y., Kyozuka, J., Yamaguchi, S., Yamaya, T.
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Journal Title
Plant J.
Volume: 81
Issue: 2
Pages: 347-356
DOI
Related Report
Peer Reviewed / Acknowledgement Compliant
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[Journal Article] Assessing metabolomic and chemical diversity of a soybean lineage representing 35 years of breeding2015
Author(s)
Miyako Kusano, Ivan Baxter, Atsushi Fukushima, Akira Oikawa, Yozo Okazaki, Ryo Nakabayashi, Denise J. Bouvrette, Frederic Achard, Andrew R. Jakubowski, Joan M. Ballam, Jonathan R. Phillips, Angela H. Culler, Kazuki Saito, George G. Harrigan
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Journal Title
Metabolomics
Volume: 11
Issue: 2
Pages: 261-270
DOI
Related Report
Peer Reviewed
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[Journal Article] Metabolomic Characterization of Knockout Mutants in Arabidopsis: Development of a Metabolite Profiling Database for Knockout Mutants in Arabidopsis2014
Author(s)
Atsushi Fukushima, Miyako Kusano, Ramon Francisco Mejia, Mami Iwasa, Makoto Kobayashi, Naomi Hayashi, Akiko Watanabe-Takahashi, Tomoko Narisawa, Takayuki Tohge, Manhoi Hur, Eve Syrkin Wurtele, Basil J. Nikolau, Kazuki Saito
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Journal Title
Plant Physiology
Volume: 165
Issue: 3
Pages: 948-961
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Integrated analysis of transcriptome and metabolome of Arabidopsis albino or pale green mutants with disrupted nuclear-encoded chloroplast proteins.2014
Author(s)
M. Satou, H. Enoki, A. Oikawa, D. Ohta, K. Saito, T. Hachiya, H. Sakakibara, M. Kusano, A. Fukushima, K. Saito, M. Kobayashi, N. Nagata, F. Myouga, K. Shinozaki, R. Motohashi
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Journal Title
Plant Molecular Biology
Volume: 85
Issue: 4-5
Pages: 411-428
DOI
Related Report
Peer Reviewed / Open Access / Acknowledgement Compliant
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