Characterisation of a novel quantitative trait locus, GN4-1, for grain number and yield in rice (Oryza sativa L.)

Zhou, Yong; Tao, Yajun; Yuan, Yuan; Zhang, Yanzhou; Ron, Zhang; Yi, Chuandeng; Gong, Zhiyun; Yang, Zefeng

doi:10.1007/s00122-017-3025-y

Cited by 24 publications

(17 citation statements)

References 41 publications

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“…Path analysis is a statistical tool that has been used to organize and present causal relationships between prediction variables and response variables through a path chart based on experimental results (Samonte et al, 1998, Esmail, 2001). Yield and its component traits are complex traits associated with the number of traits of the component that are interrelated (Ikeda et al, 2013, Zhou et al, 2018. Often this is dependent on its relationship to the grain yield, which makes the relationship ineffective.…”

Section: Introductionmentioning

confidence: 99%

Definition of selection criterion using correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes

2020

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Background and objective: Investigation on genetic variability and correlation study between yield and its components of genotypes on rice may increase the opportunity to exploit its potential which will help meet the demand of high grain yield and nutrition supply. The current study aimed to determine correlation and path coefficients between twenty-two Egyptian and exotic rice genotypes to establish selection criteria which might help to develop genotypes for high yielding. Materials and methods: Twenty-two Egyptian and exotic rice genotypes were evaluated through seven agronomic traits. Agronomic data were collected during the two successive rice growing seasons, 2017 and 2018. The matrix of phenotypic correlations was estimated and analyzed into direct and indirect effects through path coefficient analysis. Results: Results showed that grain yield per plant had a high positive and significant correlation (p ≤ 0.01) with panicle number per plant, full grain number per panicle, and 1000 grain weight, 0.791**, 0.670**, and0.766**, respectively. As expected, there was a negative correlation (p ≤ 0.05) between days to heading and panicle number per plant (r =-0.496*) and with1000 grain weight (r =-0.433*). Path coefficient analysis showed that despite high positive and significant correlation (p ≤ 0.01) between grain yield per plant and many variables, a small number of these correlations was verified to have a relationship of cause and effect. Variables with positive and significant correlation and with a high direct effect on grain yield per plant were 1000 grain weight (0.5107 direct effects) followed by panicle number per plant (0.4003), and full grain number per panicle (0.3028). Conclusion: The three traits (1000 grain weight, panicle number per plant, and full grain number per panicle) are the most important variables for use in grain yield per plant assessment programs as selection indices because they have positive and significant correlations and direct and/or indirect effect on the correlation value of the increased rice grain yield production. Hence, for increasing grain yield, the direct selection of genotypes based on positively correlated traits will be more fruitful while planning any rice breeding program to achieve higher grain yield in rice.

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Section: Introductionmentioning

confidence: 99%

Definition of selection criterion using correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes

2020

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“…Most of them were detected in different mapping populations such as F 2 , doubled haploid lines, and recombinant inbred lines (RILs) [5][6][7][8][9][10]. Several dozens of QTLs for NGP and NSP have been fine-mapped [11][12][13][14][15][16][17]. So far, eight QTLs have been cloned.…”

Section: Introductionmentioning

confidence: 99%

Identification and Validation of Quantitative Trait Loci for Grain Number in Rice (Oryza sativa L.)

et al. 2020

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Grains number is one of the most important agronomic traits in the determination of rice productivity. To explore the underlying genetic basis of grain number in rice, quantitative trait locus (QTL) analysis was performed using three recombinant inbred line populations derived from indica rice crosses of Teqing/IRBB lines, Zhenshan 97/Milyang 46, and Xieqingzao/Milyang 46, respectively. A total of 58 QTLs distributed on all 12 rice chromosomes were identified, including 22 for number of grains per panicle (NGP), 17 for number of spikelets per panicle, and 19 for spikelet fertility. The individual QTL counted for 1.5 to 22.1% of phenotypic variation. Among them, 15 QTLs shared by two or three populations and eight QTLs showed large effects with R2 larger than 10%. Furthermore, three QTLs with minor effects for NGP, qNGP5.5, qNGP9.1, and qNGP12.1, were detected and validated by eliminating the segregation of major-effect QTL using four residual heterozygote-derived populations. These results not only enrich our understanding of the mechanism of grain number, but also provide a foundation for cloning and selecting candidate for marker-assisted selection breeding in rice.

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“…However, this QTL was fine mapped to a large 190-kb region consisting of 20 genes. Near-isogenic lines (NILs) carrying GN4-1 also showed increased CK accumulation in young panicles and decreased transcript abundance of as many as eight CKX enzyme family members, including OsCKX2 (Zhou et al, 2018).…”

Section: Cytokininsmentioning

confidence: 99%

Phytohormone-Mediated Molecular Mechanisms Involving Multiple Genes and QTL Govern Grain Number in Rice

et al. 2020

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Increasing the grain number is the most direct route toward enhancing the grain yield in cereals. In rice, grain number can be amplified through increasing the shoot branching (tillering), panicle branching, panicle length, and seed set percentage. Phytohormones have been conclusively shown to control the above characteristics by regulating molecular factors and their cross-interactions. The dynamic equilibrium of cytokinin levels in both shoot and inflorescence meristems, maintained by the regulation of its biosynthesis, activation, and degradation, determines the tillering and panicle branching, respectively. Auxins and gibberellins are known broadly to repress the axillary meristems, while jasmonic acid is implicated in the determination of reproductive meristem formation. The balance of auxin, gibberellin, and cytokinin determines meristematic activities in the inflorescence. Strigolactones have been shown to repress the shoot branching but seem to regulate panicle branching positively. Ethylene, brassinosteroids, and gibberellins regulate spikelet abortion and grain filling. Further studies on the optimization of endogenous hormonal levels can help in the expansion of the grain yield potential of rice. This review focuses on the molecular machinery, involving several genes and quantitative trait loci (QTL), operational in the plant that governs hormonal control and, in turn, gets governed by the hormones to regulate grain number and yield in rice.

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Characterisation of a novel quantitative trait locus, GN4-1, for grain number and yield in rice (Oryza sativa L.)

Cited by 24 publications

References 41 publications

Definition of selection criterion using correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes

Definition of selection criterion using correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes

Identification and Validation of Quantitative Trait Loci for Grain Number in Rice (Oryza sativa L.)

Phytohormone-Mediated Molecular Mechanisms Involving Multiple Genes and QTL Govern Grain Number in Rice

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