ArticleScientific reports2018
Haplotype-based allele mining in the Japan-MAGIC rice population.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 34 citations in OpenAlex.
- Dissecting Agronomically favorable genotypes in temperate japonica rice via haplotype analysis of a Japan-MAGIC population.The Plant journal : for cell and molecular biology · 2026Article
- GWAS and Candidate Gene Prediction of Elemental Accumulation Traits in Rice Using a Multiparental Population.Rice (New York, N.Y.) · 2026Article
- Analysis of Genetic Variation of Rice Straw Characteristics and Its Influence on Biomass.Plant direct · 2026Article
- Review
- Genetic background influences mineral accumulation in rice straw and grains under different soil pH conditions.Scientific reports · 2024Article
- Phenology analysis for trait prediction using UAVs in a MAGIC rice population with different transplanting protocols.Frontiers in artificial intelligence · 2024Article
- Haplotype mining panel for genetic dissection and breeding in Eucalyptus.The Plant journal : for cell and molecular biology · 2023Article
- Haplogenome assembly reveals structural variation in Eucalyptus interspecific hybrids.GigaScience · 2022Article
- Review
- Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review.Life (Basel, Switzerland) · 2022Review
- Identification of QTLs Associated With Agronomic Traits in TobaccoFrontiers in plant science · 2022Article
- Crafting for a better MAGIC: systematic design and test for Multiparental Advanced Generation Inter-Cross population.G3 (Bethesda, Md.) · 2021Article
- Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture.Journal of experimental botany · 2021Article
- Remote-Sensing-Combined Haplotype Analysis Using Multi-Parental Advanced Generation Inter-Cross Lines Reveals Phenology QTLs for Canopy Height in Rice.Frontiers in plant science · 2021Article
- Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Frontiers in plant science · 2021Article
- Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding.Heredity · 2020Review
- Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions.BMC genomics · 2020Article
- Review
- Evaluation of major rice cultivars for resistance to bacterial seedling rot caused byBreeding science · 2020Article
- Genetic Analysis of Agronomic Traits and Grain Iron and Zinc Concentrations in a Doubled Haploid Population of Rice (Oryza sativa L.).Scientific reports · 2020Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations.
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