ArticlePlants (Basel, Switzerland)2021
Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (
Article in Plants (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 7 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
31 citing papers in PubMed, 7 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- Transcriptomic Landscape and Regulatory Pathways of Drought Response in Rice (International journal of molecular sciences · 2026Pooled it
- Dissection of QTLs underlying the genetic basis of drought resistance in wheat: a meta-analysis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Pooled it
- Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice.BMC genomics · 2024Pooled it
- Meta-QTL s and haplotypes for efficient zinc biofortification of rice.The plant genome · 2023Pooled it
- Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment.BMC genomics · 2023Pooled it
- Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding.Scientific reports · 2022Pooled it
- Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Pooled it
- Genomic dissection of iron toxicity tolerance in rice identifies key loci, candidate genes, and associated haplotypes.Scientific reports · 2026Article
- Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage.BMC plant biology · 2026Article
- Article
- Stress-tolerance genes in rice: bridging gene discovery, functional validation, and breeding applications.Frontiers in plant science · 2026Review
- Root system architecture and drought adaptation: emerging tools and genetic insights.Frontiers in plant science · 2026Review
- Genomic and Transcriptomic Insights into Stage-Specific Drought Resilience in Diverse Myanmar Rice Germplasm.Rice (New York, N.Y.) · 2025Article
- An Integrated Meta-QTL and Transcriptome Analysis Provides Candidate Genes Associated with Drought Tolerance in Rice Seedlings.Plants (Basel, Switzerland) · 2025Article
- Genome-Wide Association Study Reveals Candidate Genes Regulating Plant Height and First-Branch Height inInternational journal of molecular sciences · 2025Article
- Drought's physiological footprint: implications for crop improvement in rice.Molecular biology reports · 2025Review
- 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
- Autophagy in plants.Autophagy reports · 2024Review
- Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses.Genes · 2023Review
- Plant Tolerance to Drought Stress with Emphasis on Wheat.Plants (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.