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"Kyung-Hwan Kim"

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"Kyung-Hwan Kim"

Research Article

Kompetitive Allele-Specific PCR Marker Development and Quantitative Trait Locus Mapping for Bakanae Disease Resistance in Korean Japonica Rice Varieties
Kyeong-Seong Cheon, Young-Min Jeong, Youn-Young Lee, Jun Oh, Do-Yu Kang, Hyoja Oh, Song Lim Kim, Nyunhee Kim, Eungyeong Lee, Jeongho Baek, Inchan Choi, Kyung-Hwan Kim, Yong Jae Won, In Sun Yoon, Young-il Cho, Jung-Heon Han, Hyeonso Ji
Plant Breed. Biotech. 2019;7(3):208-219.   Published online September 1, 2019
DOI: https://doi.org/10.9787/PBB.2019.7.3.208

High-throughput molecular markers with high genotyping accuracy will be helpful for genetic analysis, mapping of interesting genes, and rice breeding program. To develop high-throughput and cost-effective molecular markers for Korean japonica rice varieties, which are closely-related genetically, we designed kompetitive allele-specific polymerase chain reaction (KASP) assays from the sequence data of 13 Korean japonica rice varieties. Of the 504 new KASP assays, 371 (73.6%) showed polymorphisms among the tested varieties. In addition to the 400 previously developed KASP markers, this resulted in 771 KASP markers being applicable for Korean japonica rice varieties. These KASP markers were used to map the quantitative trait loci (QTLs) for rice bakanae disease (BD) resistance. From the results of QTL mapping and determination of the mortality rate of BD in two F2:F3 populations, a major QTL, qFfR1-1, and a novel QTL, qFfR6, were revealed on chromosome 1 in the Junam/Nampyeong F2:F3 population and on chromosome 6 in the Saenuri/Nampyeong F2:F3 population, respectively. Further, the insertion/deletion markers in the qFfR1-1 region were developed to select BD-resistant japonica rice varieties. The 771 developed KASP markers will accelerate the molecular breeding in Korean japonica rice varieties, and the detected QTLs will be helpful in identifying candidate genes for BD resistance.

Citations

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  • Genome-Wide Association Study to identify Bakanae disease resistance-related QTLs carrying novel candidate genes in rice (Oryza sativa L.)
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    npj Science of Plants.2025;[Epub]     CrossRef
  • Genome-wide association mapping of bakanae disease resistance in rice
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  • Quantitative Trait Locus Analysis for Quality-Related Traits Using the Recombinant Inbred Lines Derived from a Cross between “Boramchan” and “Pecos” Japonica Rice
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  • Map-Based Cloning and Characterization of a Major QTL Gene, FfR1, Which Confers Resistance to Rice Bakanae Disease
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    International Journal of Molecular Sciences.2024; 25(11): 6214.     CrossRef
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    Korean Journal of Breeding Science.2024; 56(1): 31.     CrossRef
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    Agronomy.2024; 14(7): 1507.     CrossRef
  • Identification of qBK2.1, a novel QTL controlling rice resistance against Fusarium fujikuroi
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    Botanical Studies.2023;[Epub]     CrossRef
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  • Current insights on rice (Oryza sativa L.) bakanae disease and exploration of its management strategies
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    Frontiers in Plant Science.2023;[Epub]     CrossRef
  • Molecular Breeding of Zheyou810, an Indica–Japonica Hybrid Rice Variety with Superior Quality and High Yield
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    Agriculture.2023; 13(9): 1807.     CrossRef
  • The Multiple Disease-resistant, Mid-late Maturing Rice Cultivar ‘Chamdongjin’, Carrying the Bacterial Blight Resistance Gene Xa21, with the Genetic Background of ‘Sindongjin’
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    Euphytica.2023;[Epub]     CrossRef
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  • Breeding of High Cooking and Eating Quality in Rice by Marker-Assisted Backcrossing (MABc) Using KASP Markers
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  • Recent Advances in Rice Varietal Development for Durable Resistance to Biotic and Abiotic Stresses through Marker-Assisted Gene Pyramiding
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  • Genomic Variation in Korean japonica Rice Varieties
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  • Evaluation of the Rsistant to Bakanae Disease in Korean Rice Landraces (Oryza sativa L.)
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    Plant Breeding and Biotechnology.2021; 9(4): 355.     CrossRef
  • QTL mapping for pre-harvest sprouting resistance in japonica rice varieties utilizing genome re-sequencing
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    Molecular Genetics and Genomics.2020; 295(5): 1129.     CrossRef
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Review Article
Phenotyping of Plants for Drought and Salt Tolerance Using Infra-Red Thermography
Taek-ryoun Kwon, Kyung-hwan Kim, Hae-Jin Yoon, Seung-kon Lee, Beom-ki Kim, Zamin Shaheed Siddiqui
Plant Breed. Biotech. 2015;3(4):299-307.   Published online November 30, 2015
DOI: https://doi.org/10.9787/PBB.2015.3.4.299

Drought and salinity are the major environmental constrains in global agricultural production. Plant breeding for the drought and salt tolerance needs a proper assessment procedure to overcome stress constrain. Fundamental understanding on the physiological nature of the plant tolerance provides valuable information for the genetically modified crop’s development. Drought or salt stress induces several common physiological responses in plants such as water relation and photosynthetic capacitiy. It is because both stresses lead cellular dehydration in the plants, particularly, during the early phase of stress imposition. Drought and salinity decrease CO2 availability for photosynthesis via stomatal limitation as well as elevate leaf temperature due to partially closed stomata. In this scenario, stomatal regulation and plant water status are important aspects in abiotic stress environment. These physiological responses have a function to stabilize the temperature inside plant/leaf. Therefore phenotyping through an infra-red thermography (heat sensitive sensor), could be a useful tool in the selection of a tolerant genotypes. Infra-red thermography is a part of the electromagnetic spectrum which emits a certain amount of radiation as a function of their temperatures. In general, the plants which have less water, would have higher temperature and display more infra-red radiations. In abiotic stresses such as drought and salinity, plant water status is affected and varied from the sensitive to tolerant level. Infra-red images of plants are often linked with some of the physiological attributes to the tolerance. This review covers the limits, advantages, linkages, comparison and other prospectives of using thermal imagaes in modern phenotyping techniques.

Citations

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  • Artificial Intelligence (AI) in Detection of Abiotic Stress in Plants: A Review
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    S. Anand, R. L. Visakh, R. Nalishma, R. P. Sah, R. Beena
    Journal of Plant Biochemistry and Biotechnology.2025; 34(1): 119.     CrossRef
  • Functional phenotyping: Understanding the dynamic response of plants to drought stress
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    Current Plant Biology.2024; 38: 100331.     CrossRef
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    Ecological Indicators.2023; 154: 110781.     CrossRef
  • Improving Drought Tolerance in Mungbean (Vigna radiata L. Wilczek): Morpho-Physiological, Biochemical and Molecular Perspectives
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    Letters in Applied Microbiology.2021; 72(6): 714.     CrossRef
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  • Thermal Imaging for Plant Stress Detection and Phenotyping
    Mónica Pineda, Matilde Barón, María-Luisa Pérez-Bueno
    Remote Sensing.2020; 13(1): 68.     CrossRef
  • 17 View
  • 0 Download
  • 9 Crossref