Literature DB >> 20931377

Methods for rice phenomics studies.

Chyr-Guan Chern1, Ming-Jen Fan, Sheng-Chung Huang, Su-May Yu, Fu-Jin Wei, Cheng-Chieh Wu, Arunee Trisiriroj, Ming-Hsing Lai, Shu Chen, Yue-Ie C Hsing.   

Abstract

With the completion of the rice genome sequencing project, the next major challenge is the large-scale determination of gene function. A systematic phenotypic profiling of mutant collections will provide major insights into gene functions important for crop growth or production. Thus, detailed phenomics analysis is the key to functional genomics. Currently, the two major types of rice mutant collections are insertional mutants and chemical or irradiation-induced mutants. Here we describe how to manipulate a rice mutant population, including conducting phenomics studies and the subsequent propagation and seed storage. We list the phenotypes screened and also describe how to collect data systematically for a database of the qualitative and quantitative phenotypic traits. Thus, data on mutant lines, phenotypes, and segregation rate for all kinds of mutant populations, as well as integration sites for insertional mutant populations, would be searchable, and the collection would be a good resource for rice functional genomics study.

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Year:  2011        PMID: 20931377     DOI: 10.1007/978-1-60761-682-5_10

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping.

Authors:  Luis Diaz-Garcia; Giovanny Covarrubias-Pazaran; Brandon Schlautman; Juan Zalapa
Journal:  PLoS One       Date:  2016-08-16       Impact factor: 3.240

2.  Large-scale phenomics analysis of a T-DNA tagged mutant population.

Authors:  Hshin-Ping Wu; Fu-Jin Wei; Cheng-Chieh Wu; Shuen-Fang Lo; Liang-Jwu Chen; Ming-Jen Fan; Shu Chen; Ien-Chie Wen; Su-May Yu; Tuan-Hua David Ho; Ming-Hsin Lai; Yue-Ie C Hsing
Journal:  Gigascience       Date:  2017-08-01       Impact factor: 6.524

  2 in total

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