SynthesisPlanta2020
Whole-genome mining of abiotic stress gene loci in rice.
Synthesis in Planta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice.BMC genomics · 2024Pooled it
- Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis.G3 (Bethesda, Md.) · 2023Pooled it
- Advances in Functional Genomics for Exploring Abiotic Stress Tolerance Mechanisms in Cereals.Plants (Basel, Switzerland) · 2025Review
- Genome-wide identification of CRF gene family members in four rice subspecies and expression analysis of OsCRF members in response to cold stress at seedling stage.Scientific reports · 2024Article
- Comparative transcriptomics and co-expression networks reveal cultivar-specific molecular signatures associated with reproductive-stage cold stress in rice.Plant cell reports · 2023Article
- Candidate Genes and Pathways in Rice Co-Responding to Drought and Salt Identified by gcHap Network.International journal of molecular sciences · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
MAIN
conclusionWe projected meta-QTL (MQTL) for drought, salinity, cold state, and high metal ion tolerance in rice using a meta-analysis based on high-density consensus maps. In addition, a genome-wide association analysis was used to validate the results of the meta-analysis, and four new chromosome intervals for mining abiotic stress candidate genes were obtained. Drought, severe cold, high salinity, and high metallic ion concentrations severely restrict rice production. Consequently, the breeding of abiotic stress-tolerant variety is being paid increasingly more attention. This study aimed to identify meta-quantitative trait loci (MQTL) for abiotic stress tolerance in rice, as well as the molecular markers and potential candidate genes of the MQTL regions. We summarized 2785 rice QTL and conducted a meta-analysis of 159 studies. We found 82 drought tolerance (DT), 70 cold tolerance (CT), 70 salt tolerance (ST), and 51 heavy metal ion tolerance (IT) meta-QTL, as well as 20 DT, 11 CT, 22 ST, and 5 IT candidate genes in the MQTL interval. Thirty-one multiple-tolerance related MQTL regions, which were highly enriched, were also detected, and 13 candidate genes related to multiple-tolerance were obtained. In addition, the correlation between DT, CT, and ST was significant in the rice genome. Four candidate genes and four MM-QTL regions were detected simultaneously by GWAS and meta-analysis. The four candidate genes showed distinct genetic differentiation and substantial genetic distance between indica and japonica rice, and the four MM-QTL are potential intervals for mining abiotic stress-related candidate genes. The candidate genes identified in this study will not only be useful for marker-assisted selection and pyramiding but will also accelerate the fine mapping and cloning of the candidate genes associated with abiotic stress-tolerance mechanisms 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 OpenQuestion graph.