Frontiers in Genetics · 2021 · 49 citations · 62 references
Life SciencesCrop SciencesGeneticsCrop ImprovementPlant GeneticsPlant GenomicsCereal GeneticsCrop GenomicsGene MappingQuantitative Trait LociQuantitative Trait Loci MappingQuantitative Trait Locus MappingGrain Yield MappingMarker-assisted PyramidingNitrogen Efficiency TraitsNitrogen Utilization EfficiencyQtl Meta-analysisQuantitative Trait Loci (Qtl) MappingYield-related Trait AnalysisYield-related Trait Assessment
The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.
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