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Identification of QTLs for rice grain size and weight by high-throughput SNP markers in the IR64 x Sadri population.
- Source :
- Frontiers in Genetics; 8/19/2022, Vol. 13, p1-10, 10p
- Publication Year :
- 2022
-
Abstract
- Grain appearance is one of the most important attributes of rice. It is determined by grain size, shape, and weight, which in turn influences the rice yield and market value. In this study, QTLs for grain length, grain width, grain length/width ratio, and grain weight were mapped using the high-throughput indica/indica SNP platforms. The population of the mega indica variety IR64 and the highquality aromatic variety Sadri from Iran was phenotyped. Based on this phenotypic data, plants of 94 F<subscript>2:3</subscript> families including both parents were selected. A linkage map analysis of 210 SNP markers identified 14 QTLs controlling the grain length, grain width, length/width ratio, and 1,000 grain weight. Among these 14, one important region containing the QTLs for all the four studies' traits was mapped on chromosome 8. It was derived from Sadri for the decreased length/width ratio and increased grain weight. This study demonstrated the speed and efficiency in using multiplex SNP genotyping for QTL analysis. Moreover, this study identified four novel QTLs (qGL8, qTGW8, qLWR8, and qGW8) sharing the same position on chromosome 8 which were linked with grain quality characteristics between one indica and one aromatic variety. It will enable more precise marker-assisted selection for grain weight, shape, and size. Further in-depth studies are required to dissect this region of interest and identify the related gene(s). [ABSTRACT FROM AUTHOR]
- Subjects :
- GRAIN size
SINGLE nucleotide polymorphisms
RICE
GENE mapping
MARKET value
GRAIN
Subjects
Details
- Language :
- English
- ISSN :
- 16648021
- Volume :
- 13
- Database :
- Complementary Index
- Journal :
- Frontiers in Genetics
- Publication Type :
- Academic Journal
- Accession number :
- 158974167
- Full Text :
- https://doi.org/10.3389/fgene.2022.955347