Back to Search
Start Over
Mining and effect evaluation and prediction of natural allele combinations of rice grain-size regulating genes.
- Source :
-
Euphytica . Dec2023, Vol. 219 Issue 12, p1-14. 14p. - Publication Year :
- 2023
-
Abstract
- Rice grain size directly affects grain yield and is an important quantitative trait target. Many genes regulating grain size have been mapped and cloned in recent years. These genes not only play a single role on grain size regulation but have mutual interactive effect on grain size. Mining key allele combinations of grain-size regulating genes will favorite the pyramiding of favorable alleles in rice varieties with desired grain size and shape that meet people's preferences. Here, we studied the effect of seven major grain-size regulating genes (GS3, GS5, GW8/OsSPL16, BG2, GS6, GS2 and TGW3) and their allele combinations on grain size-related traits (grain length, grain width, grain length width ratio, thousand grain weight), and established multiple regression equations to predict rice grain size. We found that alleles of seven genes displayed significant differences in rice grain size. Among the seven genes, GS3 gene played the most important effect in regulating grain size, pyramiding GS3 alleles with other alleles such as GS6-II/III allele could significantly enhance grain size or grain weight. Specific allele combination of GS3-A, GS2-ZH11, GS5-Zhenshan97, GS6-II/III, BG2-9311 and GW8-HJX74 can produce rice varieties with slender grains; allele combination of GS3-A, GS6-I, BG2-Nipponbare and TGW3-CW23 produce grains with higher grain weight. The regression equation model developed in this study provided a useful tool to predict rice grain size. These results would help in breeding rice varieties with ideal traits and high yield by pyramiding favorable alleles. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ALLELES
*GRAIN size
*GENES
*RICE
*RICE breeding
*MOLECULAR cloning
Subjects
Details
- Language :
- English
- ISSN :
- 00142336
- Volume :
- 219
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Euphytica
- Publication Type :
- Academic Journal
- Accession number :
- 174323769
- Full Text :
- https://doi.org/10.1007/s10681-023-03254-6