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      QTL-seq Identifies Genomic Regions Associated with Resistance to Dirty Panicle Disease in Rice

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      Agronomy
      MDPI AG

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          Abstract

          Dirty panicle disease is one of the most important diseases that can cause yield losses in rice production. Despite the severity of the disease, the molecular basis of resistance to the pathogen is poorly understood. Using QTL-seq with an F2 population, we identified three genomic regions on chromosomes 1, 9, and 10, namely qDP1, qDP9, and qDP10. These regions are significantly associated with resistance to dirty panicle disease caused by two fungal pathogens, Bioplaris oryzae and Cirvularia lunata. qDP1 was significantly associated only with resistance to B. oryzae, whereas qDP9 and qDP10 were significantly associated with both B. oryzae and C. lunata. We also developed KASP markers for each QTL detected and validated them in the F2 population. The markers were able to explain phenotypic variation in a range of 5.87–15.20%. Twelve potential candidate genes with annotated functions as resistance-related genes were proposed. These candidate genes include those encoding RLK, MATE, WAK, NBS-LRR, subtilisin-like protease, and ankyrin repeat proteins. The results of this study provide insights into the genetic mechanism of dirty panicles in rice and will be useful for future breeding programs for dirty panicle resistance. This is the first report of QTLs associated with resistance to dirty panicle disease in rice.

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          QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations.

          The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker-assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time-consuming and labor-intensive. Here we report the rapid identification of plant QTLs by whole-genome resequencing of DNAs from two populations each composed of 20-50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL-seq as applied to plant species. We applied QTL-seq to rice recombinant inbred lines and F2 populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL-seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps. © 2013 The Authors The Plant Journal © 2013 Blackwell Publishing Ltd.
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            Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

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              Genome sequencing reveals agronomically important loci in rice using MutMap.

              The majority of agronomic traits are controlled by multiple genes that cause minor phenotypic effects, making the identification of these genes difficult. Here we introduce MutMap, a method based on whole-genome resequencing of pooled DNA from a segregating population of plants that show a useful phenotype. In MutMap, a mutant is crossed directly to the original wild-type line and then selfed, allowing unequivocal segregation in second filial generation (F(2)) progeny of subtle phenotypic differences. This approach is particularly amenable to crop species because it minimizes the number of genetic crosses (n = 1 or 0) and mutant F(2) progeny that are required. We applied MutMap to seven mutants of a Japanese elite rice cultivar and identified the unique genomic positions most probable to harbor mutations causing pale green leaves and semidwarfism, an agronomically relevant trait. These results show that MutMap can accelerate the genetic improvement of rice and other crop plants.
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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                ABSGGL
                Agronomy
                Agronomy
                MDPI AG
                2073-4395
                July 2023
                July 19 2023
                : 13
                : 7
                : 1905
                Article
                10.3390/agronomy13071905
                a9c5a0ea-0b55-4409-aa1b-955260769a4e
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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