Unveiling key genetic loci and candidate genes for brown spot disease resistance in rice based on QTL analysis

Rice brown spot, a widespread disease caused by the fungus Bipolaris oryzae (teleomorph: Cochliobolus miyabeanus), significantly diminishes both grain yield and quality. Developing resistant rice cultivars remains the most sustainable and effective strategy for managing this disease. In this study, we conducted quantitative trait locus (QTL) analysis to identify genetic loci and candidate genes associated with brown spot resistance. A mapping population was generated from a cross between the resistant variety ‘Cheongcheong’ and the susceptible variety ‘Nagdong’. Disease evaluations were performed following inoculation with a mixture of six Cochliobolus miyabeanus isolates collected in 2023 to represent current field diversity, and disease severity was assessed seven days post-inoculation using a 0–9 scale. The QTL analysis revealed a new major locus on chromosome 3 linked to brown spot resistance, between markers RM15749 and RM15689. Within this genomic interval, 32 candidate genes were identified using qRT-PCR-based expression profiling. Among them, a gene designated OsRBSq3 (Os03g0687400), encoding a ribosome-inactivating protein family member that plays a role in defense mechanisms against necrotrophic pathogens, exhibited notable differential expression between Cheongcheong and Nagdong. These results provide new insights into the genetic architecture underlying brown spot resistance in rice and highlight OsRBSq3 as a potential target for marker-assisted selection and functional studies.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-01-29
DOI
https://doi.org/10.1038/s41598-025-33890-y
Primary Topic
Fungal and yeast genetics research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unveiling key genetic loci and candidate genes for brown spot disease resistance in rice based on QTL analysis

Xiao-Xuan Du, S. Y. Choi, K. M. Kim, Nam-Kuk Kim et al.
Scientific Reports
Fungal and yeast genetics research
article

Unveiling key genetic loci and candidate genes for brown spot disease resistance in rice based on QTL analysis

Xiao-Xuan Du, S. Y. Choi, K. M. Kim, Nam-Kuk Kim, Hyunjung Chung, Shinhwa Kim, Dan-Dan Zhao, Sangmin Kim, Jang-Ho Lee, Muhammad Farooq
article en

Abstract

Rice brown spot, a widespread disease caused by the fungus Bipolaris oryzae (teleomorph: Cochliobolus miyabeanus), significantly diminishes both grain yield and quality. Developing resistant rice cultivars remains the most sustainable and effective strategy for managing this disease. In this study, we conducted quantitative trait locus (QTL) analysis to identify genetic loci and candidate genes associated with brown spot resistance. A mapping population was generated from a cross between the resistant variety ‘Cheongcheong’ and the susceptible variety ‘Nagdong’. Disease evaluations were performed following inoculation with a mixture of six Cochliobolus miyabeanus isolates collected in 2023 to represent current field diversity, and disease severity was assessed seven days post-inoculation using a 0–9 scale. The QTL analysis revealed a new major locus on chromosome 3 linked to brown spot resistance, between markers RM15749 and RM15689. Within this genomic interval, 32 candidate genes were identified using qRT-PCR-based expression profiling. Among them, a gene designated OsRBSq3 (Os03g0687400), encoding a ribosome-inactivating protein family member that plays a role in defense mechanisms against necrotrophic pathogens, exhibited notable differential expression between Cheongcheong and Nagdong. These results provide new insights into the genetic architecture underlying brown spot resistance in rice and highlight OsRBSq3 as a potential target for marker-assisted selection and functional studies.

Scientific ReportsVol. 16(1)
Rural Development Administration (KR), Kyungpook National University (KR), Jiangsu Vocational College of Medicine (CN)
Rural Development Administration
Openalex Percentile: Top 74%
Fungal and yeast genetics research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.