ArticleBreeding science2021
Detection of a major QTL related to smut disease resistance inherited from a Japanese wild sugarcane using GRAS-Di technology.
Article in Breeding science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Deciphering the mosaic genome of sugarcane cultivars through polyploid admixture inference with AdmixPoly.Genome biology · 2026Article
- Machine learning for genomic and pedigree prediction in sugarcane.The plant genome · 2024Article
- Fungal Diversity and Gibberellin Hormones Associated with Long Whips of Smut-Infected Sugarcanes.International journal of molecular sciences · 2024Article
- A Data-Driven Approach to Sugarcane Breeding Programs with Agronomic Characteristics and Amino Acid Constituent Profiling.Metabolites · 2024Article
- Quantitative trait locus (QTL) analysis and fine-mapping forBreeding science · 2023Article
- Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review.Life (Basel, Switzerland) · 2022Review
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smut disease of sugarcane causes considerable yield losses and the use of resistant varieties is the best control practice. Our group identified a Japanese wild sugarcane with highly smut disease resistance named 'Iriomote8'. In this study, we conducted QTL analysis for smut disease resistance using a mapping population derived from a resistant variety 'Yaenoushie', in which resistance is inherited from 'Iriomote8'. We identified 4813 non-redundant markers using GRAS-Di technology and developed a linkage map of mapping parents. We evaluated smut disease resistance of the mapping population by the inoculation test. Consequently, a large number of clones did not show the disease symptoms and the distribution of smut disease incidence tended to be "L shaped". Composite interval mapping detected an identical QTL for indices of smut disease incidence with a markedly high LOD score (26.6~45.6) at the end of linkage group 8 of 'Yaenoushie'. This QTL explained approximately 50% of the cases of smut disease incidence. In the mapping population, there were no correlations between the indices of smut disease incidence and other agronomic traits. In conclusion, this QTL could be used for marker-assisted selection to significantly improve smut disease resistance without negative effects on other agronomic traits.
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