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Updated: May 13, 2025
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Identifying Mutations by High Resolution Melting in a TILLING Population of Rice
Published on: September 2, 2019
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Correlation of rice yield based on RILs population QTL analysis
Junrong Liu1, Xinyi Lou1, Lin Zhang1
1Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China.
BMC Genomic Data
|April 14, 2025
Summary
This study identified 19 quantitative trait loci (QTLs) for rice yield traits using molecular markers. Seed setting rate (SSR) and panicle length (PL) significantly impacted yield per plant (YPP) in the F7 population.
Area of Science:
- Agricultural Science
- Genetics
- Plant Breeding
Background:
- Rice production is crucial for global food security and crop quality breeding.
- Understanding genetic factors influencing yield is essential for developing improved rice varieties.
Purpose of the Study:
- To identify quantitative trait loci (QTLs) associated with yield-related traits in rice.
- To analyze the relationships between agronomic traits and overall rice yield.
Main Methods:
- Hybridization and selfing of indica and japonica rice varieties to create recombinant inbred lines (RILs).
- Analysis of F3 and F7 populations for six yield traits and tillering angle.
- QTL mapping using SSR molecular markers and regression/path analysis.
Main Results:
- Identified 19 QTLs controlling panicle length, grain number per panicle, effective panicle number, seed setting rate, and grain density.
- Developed an optimal regression equation for yield per plant (YPP).
- Seed setting rate (SSR) and panicle length (PL) were identified as the most impactful traits on YPP.
Conclusions:
- QTL mapping is effective for dissecting the genetic basis of rice yield traits.
- SSR and PL are key determinants of rice yield, providing targets for breeding programs.
- Further research can leverage these findings for marker-assisted selection in rice improvement.
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