ArticleJournal of biosciences2024
Defining genomic landscape for identification of potential candidate resistance genes associated with major rice diseases through MetaQTL analysis.
Article in Journal of biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- QTL mapping and identification of linked markers for anthracnose fruit rot resistance inFrontiers in plant science · 2026Article
- An Integrated Meta-QTL and Transcriptome Analysis Provides Candidate Genes Associated with Drought Tolerance in Rice Seedlings.Plants (Basel, Switzerland) · 2025Article
- Genetic dissection of crown rust resistance in oat and the identification of key adult plant resistance genes.The plant genome · 2025Article
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Authors and funding
9 authors.
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Abstract
Rice production is severely affected by various diseases such as bacterial leaf blight (BLB), brown spot (BS), false smut (FS), foot rot (FR), rice blast (RB), and sheath blight (SB). In recent years, several quantitative trait loci (QTLs) studies involving different populations have been carried out, resulting in the identification of hundreds of resistance QTLs for each disease. These QTLs can be integrated and analyzed using meta-QTL (MQTL) analysis for better understanding of the genetic architecture underlying multiple disease resistance (MDR). This study involved an MQTL analysis on 661 QTLs (378, 161, 21, 41, 44, and 16 QTLs for SB, RB, BLB, BS, FS, and FR, respectively) retrieved from 50 individual studies published from 1995 to 2021. Of these, 503 QTLs were projected finally onto the consensus map saturated with 6,275 markers, resulting in 73 MQTLs, including 27 MDR-MQTLs conferring resistance to three or more diseases. Forty-seven MQTLs were validated using marker-trait associations identified in published genome-wide association studies. A total of 3,310 genes, including both R and defense genes, were also identified within some selected high-confidence MQTL regions that were investigated further for the syntenic relationship with barley, wheat, and maize genomes. Thirty-nine high-confidence candidate genes were selected based on their expression patterns and recommended for future studies involving functional validation, genetic engineering, and gene editing. Nineteen MQTLs were co-localized with 39 known R genes for BLB and RB diseases. These results could pave the way to utilize candidate genes in a marker-assisted breeding program for MDR in rice.
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