Rice transgenic resources with gain-of-function phenotypes
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- Tsuchida-Mayama Tomoko
- Division of Genome and Biodiversity Research, National Institute of Agrobiological Sciences
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- Nakamura Hidemitsu
- Division of Genome and Biodiversity Research, National Institute of Agrobiological Sciences Present address: Department of Applied Biological Chemistry, The University of Tokyo
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- Hakata Makoto
- Division of Genome and Biodiversity Research, National Institute of Agrobiological Sciences Present address: Hokuriku Research Center, National Agricultural Research Center
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- Ichikawa Hiroaki
- Division of Genome and Biodiversity Research, National Institute of Agrobiological Sciences Division of Plant Sciences, National Institute of Agrobiological Sciences
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Abstract
After the completion of its genomic sequencing, rice (Oryza sativa L.) has become firmly established as the premiere model plant among monocot crops. Various genetic resources have been developed for rice to accelerate the identification and characterization of rice genes with as-yet unknown functions. These resources include collections that carry natural variations and progeny derived from chemical and irradiation mutagenesis. Collections of rice strains with natural or artificial DNA insertions that create loss-of-function mutations have been of great importance for gene discovery and tagging. However, it is often difficult to observe mutant phenotypes for functionally duplicated genes and genes essential for plant growth and development. To overcome this disadvantage, gain-of-function strategies have been developed, including activation tagging and full-length cDNA overexpressing gene (FOX)-hunting systems. In this review, we summarize the current status and discuss the advantages and disadvantages of the gain-of-function approaches, and then, perspectives on accelerating discovery of rice genes.<br>
Journal
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- Breeding Science
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Breeding Science 60 (5), 493-501, 2010
Japanese Society of Breeding
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Keywords
Details 詳細情報について
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- CRID
- 1390282679699711616
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- NII Article ID
- 130004146262
- 10027120789
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- NII Book ID
- AA11317194
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- ISSN
- 13473735
- 13447610
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- NDL BIB ID
- 10924667
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed