Detection of QTL for panicle architecture in $$\hbox {F}_{2}$$ population of rice

Bhat, Rohini; Singh, Anil Kumar; Salgotra, Romesh Kumar; Sharma, Manmohan; Mushtaq, Muntazir; Bagati, Sreshti; Hangloo, Sharmishta; Singh, Amrinder

doi:10.1007/s12041-019-1088-z

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Identification of the genes associated with QTLs controlling a trait was challenging owing to the low resolution of early QTL maps with low-density markers. Since the first linkage map constructed using RFLP markers in rice ( McCouch et al., 1988 ), several linkage maps have been produced using SSR ( Golestan Hashemi et al., 2015 ; Bazrkar-Khatibani et al., 2019 ; Bhat et al., 2019 ; Jia et al., 2019 ) and SNP ( Rahman et al., 2017 ; Jewel et al., 2019 ) markers in rice. However, these maps could not overcome the issues of either low-density linkage maps with unreasonable marker coverage or high-density linkage maps requiring considerably more time, manpower, and financial resources.…”

Section: Discussionmentioning

confidence: 99%

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Jin

Yang

et al. 2023

Front. Plant Sci.

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Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F2 population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits—the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness—of the F2 population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%–61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.

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Section: Discussionmentioning

confidence: 99%

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Jin

Yang

et al. 2023

Front. Plant Sci.

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“…Rice is one of the most important cereal crops about caloric intake and human nutrition ( Yuan, 2014 ; Bhat et al, 2019 ). To meet the food requirements of the global population, an increase of agricultural production by more than 50% will be required by the year 2050 ( Mumtaz et al, 2020 ), particularly in rice production in the developing countries in Asia and Africa.…”

Section: Introductionmentioning

confidence: 99%

Detection of QTLs for panicle-related traits using an indica × japonica recombinant inbred line population in rice

Guan

Cheng

Yin

et al. 2021

PeerJ

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Background The panicle is the most important organ in rice, and all the panicle-related traits are correlated with rice grain yield. Understanding the underlying genetic mechanisms controlling panicle development is very important for improving rice production. Methods Nine panicle-related traits including heading date, panicle length, number of primary branches, number of secondary branches, number of grains per panicle, number of panicles per plant, number of filled grains per plant, seed-setting rate, and grain yield per plant were investigated. To map the quantitative trait loci (QTLs) for the nine panicle-related traits, a PCR-based genetic map with 208 markers (including 121 simple sequence repeats and 87 InDels) and a high-density linkage map with 18,194 single nucleotide polymorphism (SNP) markers were both used. Results Using a recombinant inbred line population derived from an indica variety Huanghuazhan and a japonica line Jizi 1560, a total of 110 and 112 QTLs were detected for panicle-related traits by PCR-based genetic map and by high-density linkage map, respectively. Most of the QTLs were clustered on chromosomes 1, 2, 3, 6, and 7 while no QTLs were detected on chromosome 10. Almost all the QTLs with LOD values of more than 5.0 were repeatedly detected, indicating the accuracy of the two methods and the stability of the QTL effects. No genes for panicle-related traits have been previously reported in most of these regions. QTLs found in JD1006–JD1007 and RM1148–RM5556 with high LOD and additive values deserved further research. The results of this study are beneficial for marker-assisted breeding and provide research foundation for further fine-mapping and cloning of these QTLs for panicle-related traits.

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Identification of QTLs for Yield and Associated Traits in F2 Population of Rice

Bhat¹,

Singh²,

Mushtaq³

et al. 2022

Phyton

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Detection of QTL for panicle architecture in $$\hbox {F}_{2}$$ population of rice

Cited by 4 publications

References 25 publications

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Detection of QTLs for panicle-related traits using an indica × japonica recombinant inbred line population in rice

Identification of QTLs for Yield and Associated Traits in F2 Population of Rice

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