Population genetic structure and association mapping for iron toxicity tolerance in rice

Abstract

Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.

Below-ground plant-soil interactions affecting adaptations of rice to iron toxicity

“…From these and other studies it can be concluded that ample genetic variation for tolerance to Fe toxicity exists within theO. sativa gene pool (Matthus et al 2015;Pawar et al 2021), and that wild relatives may serve as sources of novel traits enhancing adaptation to Fe toxicity (Bierschenk et al 2020;Wairich et al, 2021).…”

“…6 implications for rice breeding 6 .1 Tolerance within the Oryza gene pool Numerous studies have screened sets of varieties or larger germplasm collections in attempts to identify donors for Fe toxicity, typically employing one of two main screening strategies. They may have been conducted in the field in Fe toxic hotspots, evaluating grain yield in addition to biomass and leaf symptoms (Melandri et al, 2021;Pawar et al 2021;Sikirou et al 2018), or they were designed as rapid screens in nutrient solution to which excess Fe had been added at high concentrations for short periods of time (Dufey et al 2015;Matthus et al 2015). From these and other studies it can be concluded that ample genetic variation for tolerance to Fe toxicity exists within theO.…”

“…Where such environmental variation reduces the reliability of phenotyping, marker assisted selection rather than conventional phenotypic selection should be the breeding method of choice. Markers associated with aspects of Fe toxicity tolerance exist, identified through genome-wide associations studies (GWAS) (Matthus et al 2015;Pawar et al 2021;Melandri et al, 2021) or through bi-parental QTL mapping populations (Dufey et al 2015;Rasheed et al, 2020 and references therein). To our knowledge none of these studies identified loci with large enough effects to be utilized in applied breeding.…”

“…Hence yield losses are only weakly correlated with above-ground symptoms, though these are widely used for screening (Sikirou et al 2015). Most work on tolerance mechanisms has been done in hydroponics, far removed from field reality, and there has been limited progress with the genetics of tolerance and gene mapping (Dufey et al, 2015;Matthus et al, 2015;Melandri et al, 2021;Pawar et al, 2021;Sikirou et al, 2018). There is a need for an integrated approach to understand the mechanisms and genetics of Fe toxicity tolerance, taking account of the complex below-ground plant-soil interactions.…”

Uncovering Genomic Regions Regulating the Superoxide Dismutase, Flavonoids, Anthocyanins, Carotenoids, γ-Oryzanol and Antioxidant Activity in Rice Through Association Mapping

“…The genetic diversity and structure of the population will be helpful for detecting marker-trait association which could be useful for trait enhancement in molecular breeding programs. In order to avoid spurious association of marker-phenotype in a population, population structure (Q) with relative kinship (K) analyses is essential to check the correctness of the panel population composition for linkage disequilibrium (LD) mapping analyses 50,51,52 . Thus, association estimate based on both the models of Generalized linear model (GLM) and Mixed linear model (MLM) is considered appropriate for mapping complex traits that have shown to perform better than other model analyses.…”