Abstract
The cultivated rice (Oryza sativa L.) has two subspecies, indica and japonica. The japonica rice germplasm has a narrower genetic diversity compared to the indica subspecies. Rice breeders aim to develop new varieties with a higher yield potential, with enhanced resistances to biotic and abiotic stresses, and improved adaptation to environmental changes. In order to face some of these challenges, japonica rice germplasm will have to be diversified and new breeding strategies developed. Indica rice improvement could also profit from more "genepool mingling" for which japonica rice could play an important role. Interesting traits such as low-temperature tolerance, and wider climate adaptation could be introgressed into the indica subspecies. In the past decade, huge developments in rice genomics have expanded our available knowledge on this crop and it is now time to use these technologies for improving and accelerating rice breeding research. With the full sequence of the rice genome, breeders may take advantage of new genes. Also new genes may be discovered from the genepool of wild relatives, or landraces of the genus Oryza, and incorporated into elite japonica cultivars in a kind of "gene revolution" program. Expectedly, new technologies that are currently being optimized, aiming for novel gene discovery or for tracking the regions under selection, will be suggested as new breeding approaches. This paper revisits breeding strategies successfully employed in indica rice, and discusses their application in japonica rice improvement (e.g. ideotype breeding, wide hybridization and hybrid performance).
Original language | English (US) |
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Pages (from-to) | 159-168 |
Number of pages | 10 |
Journal | Molecular Breeding |
Volume | 22 |
Issue number | 2 |
DOIs | |
State | Published - Sep 2008 |
Externally published | Yes |
Keywords
- Breeding
- Genomics
- Indica
- Japonica
- Marker-Assisted Selection
- Rice
ASJC Scopus subject areas
- Genetics
- Molecular Biology
- Agronomy and Crop Science
- Biotechnology
- Plant Science