in silico prediction of gene function associated with agronomically useful traits in crops using differential network analysis

2016 Fiscal Year Final Research Report

• Project/Area Number: 26850024
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Horticultural science
• 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
• 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

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.

Free Research Field

植物システム生物学