ArticleHeliyon2025
Meta-QTL analysis for mining of candidate genes and constitutive gene network development for viral disease resistance in maize (
Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Developing resistance to Fusarium wilt in chickpea: From identifying meta-QTLs to molecular breeding.The plant genome · 2025Pooled it
- Meta-Quantitative Trait Loci Analysis and Candidate Gene Mining for Drought Tolerance-Associated Traits in Maize (International journal of molecular sciences · 2024Pooled it
- Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding.International journal of molecular sciences · 2023Pooled it
- Integrative transcriptomics and defense-related gene family analysis reveals key genes for maize resistance to fall armyworm.BMC plant biology · 2026Article
- Meta-QTL analysis for mining key genes associated with seed oil content in maize.BMC plant biology · 2025Article
- Identification of Stable Meta-QTLs and Candidate Genes Underlying Fiber Quality and Agronomic Traits in Cotton.Plants (Basel, Switzerland) · 2025Article
- Identification of Quality-Related Genomic Regions and Candidate Genes in Silage Maize by Combining GWAS and Meta-Analysis.Plants (Basel, Switzerland) · 2025Article
- Dissecting the genetic architecture of polygenic nutritional traits in maize through meta-QTL analysis.Food chemistry. Molecular sciences · 2025Article
- Genetic dissection of crown rust resistance in oat and the identification of key adult plant resistance genes.The plant genome · 2025Article
- Exploring of Antidepressant Components and Mechanisms of Zhizichi Decoction: Integration of Serum Pharmacochemistry, Network Pharmacology and Anti-inflammatory Analysis Verification.Analytical science advances · 2025Article
- Article
- Advances in Research on Southern Corn Rust, a Devasting Fungal Disease.International journal of molecular sciences · 2024Review
- GWAS and Meta-QTL Analysis of Kernel Quality-Related Traits in Maize.Plants (Basel, Switzerland) · 2024Article
- Teosinte-Derived Advanced Backcross Population Harbors Genomic Regions for Grain Yield Attributing Traits in Maize.International journal of molecular sciences · 2024Article
- Integrated meta-QTL and in silico transcriptome assessment pinpoint major genomic regions responsible for spike length in wheat (Triticum aestivum L.).The plant genome · 2024Article
- Refinement of rice blast disease resistance QTLs and gene networks through meta-QTL analysis.Scientific reports · 2024Article
- GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize.Plants (Basel, Switzerland) · 2023Article
- Review
- Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Frontiers in genetics · 2023Article
- Meta-QTL Analysis for Yield Components in Common Bean (Plants (Basel, Switzerland) · 2022Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Viral diseases severely impact maize yields, with occurrences of maize viruses reported worldwide. Deployment of genetic resistance in a plant breeding program is a sustainable solution to minimize yield loss to viral diseases. The meta-QTL (MQTL) has demonstrated to be a promising approach to pinpoint the most robust QTL(s)/candidate gene(s) in the form of an overlapping or common genomic region identified through leveraging on different research studies that independently report genomic regions significantly associated with the target traits. Here, we employed an MQTL approach by targeting 39 independent research investigations aimed at genetic dissection of the resistance in maize against 14 viral diseases. We could project 27 % (53) of the total 196 QTLs onto the maize genome. Our analysis found a robust set of 14 MQTLs on chromosomes 1, 3 and 10 that explain significant proportion of the variations for resistance against 11 viral diseases. Marker trait associations (MTAs) identified from genome-wide association studies (GWAS) provide evidence in support of the two MQTLs (MQTL3_2 and MQTL10_2) playing crucial roles in viral disease resistance (VDR) in maize. A total of 1,715 candidate genes underlie the identified MQTL regions, of which, we further examined the constitutively-expressed genes for their involvement in various metabolic pathways. The involvement of the identified genes in the antiviral resistance mechanism renders them a valuable genomic resource for allele mining and elucidating plant-virus interactions for maize research and breeding.
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