Rice (Oryza sativa L.) is known for its inherent tolerance to highly acidic soils, yet the underlying genetic and physiological mechanisms, particularly for iron (Fe) toxicity tolerance, remain insufficiently characterised. Although several quantitative trait loci (QTLs) and candidate genes (CGs) associated with Fe-toxicity tolerance have been identified, their fine mapping is unresolved. In this study, we performed a meta-QTL (M-QTL) analysis by integrating data from 11 QTL mapping studies and nine genome-wide association studies (GWAS), resulting in 63 M-QTLs with a minimum cluster size of two. The largest cluster comprised 10 QTLs, with an average cluster size of 4.01. Phenotypic variance explained (R2) ranged from 7% to 31% (mean 11.77%), and the average confidence interval (CI) was reduced from 4.68 to 2.12. Gene retrieval within these M-QTL regions identified 4,070 non-redundant genes. Comparison with 5 Fe-toxicity-related transcriptomic datasets revealed 897 differentially expressed genes, of which 284 were common to at least two datasets and designated as CGs. Characterisation of these CGs identified key regulatory elements, transcription factors, and transporters implicated in Fe tolerance. Notable CGs included OsNRAMP6, OsCDAP1, OsFRO2, OsFRDL2, OsPT2, OsPDR9, OsHSP70, OsACS2, OsZIP8, OsWRKY46, OsTIP2;2, OsGSTU17, OsINH2, and OsPEZ1. Association analysis identified 13 novel marker–trait associations (MTAs), and haplotype analysis revealed nine haplotypes (H001–H009). M-QTL1.6 and M-QTL7.3 were characterised by large QTL clusters and multiple candidate genes, while M-QTL10.1 contained an Fe-tolerance–associated haplotype within OsFRDL2. Key MTAs (MTA8, MTA16, MTA19, MTA24) formed central nodes in protein–protein interaction networks. This study identifies stable M-QTLs and favourable haplotypes associated with Fe toxicity tolerance in rice, offering clear genomic targets that regulate plant growth under excess iron stress.
Jaiswal et al. (Mon,) studied this question.