Genetic mapping of ionomic quantitative trait loci in rice grain and straw reveals OsMOT1;1 as the putative causal gene for a molybdenum QTL qMo8

Genetic background influences mineral accumulation in rice straw and grains under different soil pH conditions

Mineral element accumulation in plants is influenced by soil conditions and varietal factors. We investigated the dynamic accumulation of 12 elements in straw at the flowering stage and in grains at the mature stage in eight rice varieties with different genetic backgrounds (Japonica, Indica, and admixture) and flowering times (early, middle, and late) grown in soil with various pH levels. In straw, Cd, As, Mn, Zn, Ca, Mg, and Cu accumulation was influenced by both soil pH and varietal factors, whereas P, Mo, and K accumulation was influenced by pH, and Fe and Ni accumulation was affected by varietal factors. In grains, Cd, As, Mn, Cu, Ni, Mo, Ca, and Mg accumulation was influenced by both pH and varietal factors, whereas Zn, Fe, and P accumulation was affected by varietal factors, and K accumulation was not altered. Only As, Mn, Ca and Mg showed similar trends in the straw and grains, whereas the pH responses of Zn, P, K, and Ni differed between them. pH and flowering time had synergistic effects on Cd, Zn, and Mn in straw and on Cd, Ni, Mo, and Mn in grains. Soil pH is a major factor influencing mineral uptake in rice straw and grains, and genetic factors, flowering stage factors, and their interaction with soil pH contribute in a combined manner.

Genetic Mapping for QTL Associated with Seed Nickel and Molybdenum Accumulation in the Soybean 'Forrest' by 'Williams 82' RIL Population

Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (RIL) population was derived from a cross between 'Forrest' and 'Williams 82' (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71-3.44, and with phenotypic variance ranging from 4.48-6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.

Explicating genetic architecture governing nutritional quality in pigmented rice

Rice is one of the most important staple plant foods that provide a major source of calories and nutrients for tackling the global hunger index especially in developing countries. In terms of nutritional profile, pigmented rice grains are favoured for their nutritional and health benefits. The pigmented rice varieties are rich sources of flavonoids, anthocyanin and proanthocyanidin that can be readily incorporated into diets to help address various lifestyle diseases. However, the cultivation of pigmented rice is limited due to low productivity and unfavourable cooking qualities. With the advances in genome sequencing, molecular breeding, gene expression analysis and multi-omics approaches, various attempts have been made to explore the genetic architecture of rice grain pigmentation. In this review, we have compiled the current state of knowledge of the genetic architecture and nutritional value of pigmentation in rice based upon the available experimental evidence. Future research areas that can help to deepen our understanding and help in harnessing the economic and health benefits of pigmented rice are also explored.

Identification of subspecies-divergent genetic loci responsible for mineral accumulation in rice grains

Rice (Oryza sativa L.) is a major staple food that provides not only dietary calories but also trace elements for the global inhabitants. The insufficiency of mineral nutrients and the potential accumulation of excessive toxic elements in grains pose risks to human health. The substantial natural variations in mineral accumulation in rice grains presents potentials for genetic improvements of rice via biofortifications of essential mineral nutrients and eliminations of toxic elements in grains. However, the genetic mechanisms underlying the natural variations in mineral accumulation have not been fully explored to date owing to unstable phenotypic variations, which are attributed to poor genetic performance and strong environmental effects. In this study, we first compared the genetic performance of different normalization approaches in determining the grain-Cd, grain-Mn, and grain-Zn variations in rice in different genetic populations. Then through quantitative trait loci (QTLs) identification in two rice inter-ectype populations, three QTLs, including qCd7, qMn3, and qZn7, were identified and the QTLs were found to exhibit allelic differentiation in the different ecotypes. Our results were expected to broaden our understanding for mineral accumulation in rice and propose the potential functional alleles that can be explored for further genetic improvement of rice.

Molybdenum: More than an essential element

Molybdenum (Mo) is an essential element for almost all living organisms. After being taken up into the cells as molybdate, it is incorporated into the molybdenum cofactor, which functions as the active site of several molybdenum-requiring enzymes and thus plays crucial roles in multiple biological processes. The uptake and transport of molybdate is mainly mediated by two types of molybdate transporters. The homeostasis of Mo in plant cells is tightly controlled, and such homeostasis likely plays vital roles in plant adaptation to local environments. Recent evidence suggests that Mo is more than an essential element required for plant growth and development; it is also involved in local adaptation to coastal salinity. In this review, we summarize recent research progress on molybdate uptake and transport, molybdenum homeostasis network in plants, and discuss the potential roles of the molybdate transporter in plant adaptation to their local environment.

The Vacuolar Molybdate Transporter OsMOT1;2 Controls Molybdenum Remobilization in Rice

Molybdenum (Mo) is an essential micronutrient for almost all living organisms. The Mo uptake process in plants has been well investigated. However, the mechanisms controlling Mo translocation and remobilization among different plant tissues are largely unknown, especially the allocation of Mo to rice grains that are the major dietary source of Mo for humans. In this study, we characterized the functions of a molybdate transporter, OsMOT1;2, in the interorgan allocation of Mo in rice. Heterologous expression in yeast established the molybdate transport activity of OsMOT1;2. OsMOT1;2 was highly expressed in the blades of the flag leaf and the second leaf during the grain filling stage. Subcellular localization revealed that OsMOT1;2 localizes to the tonoplast. Knockout of OsMOT1;2 led to more Mo accumulation in roots and less Mo translocation to shoots at the seedling stage and to grains at the maturity stage. The remobilization of Mo from older leaves to young leaves under molybdate-depleted condition was also decreased in the osmot1;2 knockout mutant. In contrast, overexpression of OsMOT1;2 enhanced the translocation of Mo from roots to shoots at the seedling stage. The remobilization of Mo from upper leaves to grains was also enhanced in the overexpression lines during grain filling. Our results suggest that OsMOT1;2 may function as a vacuolar molybdate exporter facilitating the efflux of Mo from the vacuole into the cytoplasm, and thus, it plays an important role in the root-to-shoot translocation of Mo and the remobilization of Mo from leaves to grains.

Genome-Wide Association Study Reveals Genomic Regions Associated With Molybdenum Accumulation in Wheat Grains

Molybdenum (Mo) is an essential micronutrient for almost all organisms. Wheat, a major staple crop worldwide, is one of the main dietary sources of Mo. However, the genetic basis for the variation of Mo content in wheat grains remains largely unknown. Here, a genome-wide association study (GWAS) was performed on the Mo concentration in the grains of 207 wheat accessions to dissect the genetic basis of Mo accumulation in wheat grains. As a result, 77 SNPs were found to be significantly associated with Mo concentration in wheat grains, among which 52 were detected in at least two sets of data and distributed on chromosome 2A, 7B, and 7D. Moreover, 48 out of the 52 common SNPs were distributed in the 726,761,412-728,132,521 bp genomic region of chromosome 2A. Three putative candidate genes, including molybdate transporter 1;2 (TraesCS2A02G496200), molybdate transporter 1;1 (TraesCS2A02G496700), and molybdopterin biosynthesis protein CNX1 (TraesCS2A02G497200), were identified in this region. These findings provide new insights into the genetic basis for Mo accumulation in wheat grains and important information for further functional characterization and breeding to improve wheat grain quality.

Advances in "Omics" Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants

Food safety has emerged as a high-urgency matter for sustainable agricultural production. Toxic metal contamination of soil and water significantly affects agricultural productivity, which is further aggravated by extreme anthropogenic activities and modern agricultural practices, leaving food safety and human health at risk. In addition to reducing crop production, increased metals/metalloids toxicity also disturbs plants' demand and supply equilibrium. Counterbalancing toxic metals/metalloids toxicity demands a better understanding of the complex mechanisms at physiological, biochemical, molecular, cellular, and plant level that may result in increased crop productivity. Consequently, plants have established different internal defense mechanisms to cope with the adverse effects of toxic metals/metalloids. Nevertheless, these internal defense mechanisms are not adequate to overwhelm the metals/metalloids toxicity. Plants produce several secondary messengers to trigger cell signaling, activating the numerous transcriptional responses correlated with plant defense. Therefore, the recent advances in omics approaches such as genomics, transcriptomics, proteomics, metabolomics, ionomics, miRNAomics, and phenomics have enabled the characterization of molecular regulators associated with toxic metal tolerance, which can be deployed for developing toxic metal tolerant plants. This review highlights various response strategies adopted by plants to tolerate toxic metals/metalloids toxicity, including physiological, biochemical, and molecular responses. A seven-(omics)-based design is summarized with scientific clues to reveal the stress-responsive genes, proteins, metabolites, miRNAs, trace elements, stress-inducible phenotypes, and metabolic pathways that could potentially help plants to cope up with metals/metalloids toxicity in the face of fluctuating environmental conditions. Finally, some bottlenecks and future directions have also been highlighted, which could enable sustainable agricultural production.

Genomic analysis of ionome-related QTLs in Arabidopsis thaliana

Ionome contributes to maintain cell integrity and acts as cofactors for catalyzing regulatory pathways. Identifying ionome contributing genomic regions provides a practical framework to dissect the genetic architecture of ionomic traits for use in biofortification. Meta-QTL (MQTL) analysis is a robust method to discover stable genomic regions for traits regardless of the genetic background. This study used information of 483 QTLs for ionomic traits identified from 12 populations for MQTL analysis in Arabidopsis thaliana. The selected QTLs were projected onto the newly constructed genetic consensus map and 33 MQTLs distributed on A. thaliana chromosomes were identified. The average confidence interval (CI) of the drafted MQTLs was 1.30 cM, reduced eight folds from a mean CI of 10.88 cM for the original QTLs. Four MQTLs were considered as stable MQTLs over different genetic backgrounds and environments. In parallel to the gene density over the A. thaliana genome, the genomic distribution of MQTLs over the genetic and physical maps indicated the highest density at non- and sub-telomeric chromosomal regions, respectively. Several candidate genes identified in the MQTLs intervals were associated with ion transportation, tolerance, and homeostasis. The genomic context of the identified MQTLs suggested nine chromosomal regions for Zn, Mn, and Fe control. The QTLs for potassium (K) and phosphorus (P) were the most frequently co-located with Zn (78.3%), Mn (76.2%), and Fe (88.2% and 70.6%) QTLs. The current MQTL analysis demonstrates that meta-QTL analysis is cheaper than, and as informative as genome-wide association study (GWAS) in refining the known QTLs.

A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica

This study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.

Identification and Validation of QTLs for Macronutrient Contents in Brown and Milled Rice Using Two Backcross Populations between Oryza sativa and O. rufipogon

Mineral malnutrition as a prevalent public health issue can be alleviated by increasing the intake of dietary minerals from major staple crops, such as rice. Identification of the gene responsible for mineral contents in rice would help breed cultivars enriched with minerals through marker-assisted selection. Two segregating populations of backcross inbred lines (BIL) were employed to map quantitative trait loci (QTLs) for macronutrient contents in brown and milled rice, BC₁F₅, and BC₂F_4:5 derived from an interspecific cross of Xieqingzao B (Oryza sativa) and Dongxiang wild rice (O. rufipogon). Phenotyping the populations was conducted in multiple locations and years, and up to 169 DNA markers were used for the genotyping. A total of 17 QTLs for P, K, Na, Ca, and Mg contents in brown and milled rice distributed on eight regions were identified in the BC₁F₅ population, which is explained to range from 5.98% to 56.80% of phenotypic variances. Two regions controlling qCa1.1 and qCa4.1 were validated, and seven new QTLs for Ca and Mg contents were identified in the BC₂F_4:5 population. 18 of 24 QTLs were clustered across seven chromosomal regions, indicating that different mineral accumulation might be involved in common regulatory pathways. Of 24 QTLs identified in two populations, 16 having favorable alleles were derived from O. rufipogon and 10 were novel. These results will not only help understand the molecular mechanism of macronutrient accumulation in rice but also provide candidate QTLs for further gene cloning and grain nutrient improvement through QTL pyramiding.

Genome-wide association mapping identifies HvNIP2;2/HvLsi6 accounting for efficient boron transport in barley

Boron (B) is an essential mineral element for plant growth, and the seed B pool of crops can be crucial when seedlings need to establish on low-B soils. To date, it is poorly understood how B accumulation in grain crops is genetically controlled. Here, we assessed the genotypic variation of the B concentration in grains of a spring barley (Hordeum vulgare L.) association panel that represents broad genetic diversity. We found a large genetic variation of the grain B concentration and detected in total 23 quantitative trait loci (QTLs) using genome-wide association mapping. HvNIP2;2/HvLsi6, encoding a potential B-transporting membrane protein, mapped closely to a major-effect QTL accounting for the largest proportion of grain B variation. Based on transport studies using heterologous expression systems and gene expression analysis, we demonstrate that HvNIP2;2/HvLsi6 represents a functional B channel and that expression variation in its transcript level associates with root and shoot B concentrations as well as with root dry mass formation under B-deficient conditions.

Genetic Control Diversity Drives Differences Between Cadmium Distribution and Tolerance in Rice

Rice, a staple crop for nearly half the planet's population, tends to absorb and accumulate excessive cadmium (Cd) when grown in Cd-contaminated fields. Low levels of Cd can degrade the quality of rice grains, while high levels can inhibit the growth of rice plants. There is genotypic diversity in Cd distribution and Cd tolerance in different rice varieties, but their underlying genetic mechanisms are far from elucidated, which hinders genetic improvements. In this study, a joint study of phenotypic investigation with quantitative trait loci (QTLs) analyses of genetic patterns of Cd distribution and Cd tolerance was performed using a biparent population derived from japonica and indica rice varieties. We identified multiple QTLs for each trait and revealed that additive effects from various loci drive the inheritance of Cd distribution, while epistatic effects between various loci contribute to differences in Cd tolerance. One pleiotropic locus, qCddis8, was found to affect the Cd distribution from both roots to shoots and from leaf sheaths to leaf blades. The results expand our understanding of the diversity of genetic control over Cd distribution and Cd tolerance in rice. The findings provide information on potential QTLs for genetic improvement of Cd distribution in rice varieties.

Grain Inorganic Arsenic Content in Rice Managed Through Targeted Introgressions and Irrigation Management

Arsenic (As) accumulation in rice grain is a significant public health concern. Inorganic As (iAs) is of particular concern because it has increased toxicity as compared to organic As. Irrigation management practices, such as alternate wetting and drying (AWD), as well as genotypic differences between cultivars, have been shown to influence As accumulation in rice grain. A 2 year field study using a Lemont × TeQing backcross introgression line (TIL) mapping population examined the impact of genotype and AWD severity on iAs grain concentrations. The "Safe"-AWD [35-40% soil volumetric water content (VWC)] treatment did not reduce grain iAs levels, whereas the more severe AWD30 (25-30% VWC) consistently reduced iAs concentrations across all genotypes. The TILs displayed a range of iAs concentrations by genotype, from less than 10 to up to 46 μg kg-1 under AWD30 and from 28 to 104 μg kg-1 under Safe-AWD. TIL grain iAs concentrations for flood treatments across both years ranged from 26 to 127 μg kg-1. Additionally, seven quantitative trait loci (QTLs) were identified in the mapping population associated with grain iAs. A subset of eight TILs and their parents were grown to confirm field-identified grain iAs QTLs in a controlled greenhouse environment. Greenhouse results confirmed the genotypic grain iAs patterns observed in the field; however, iAs concentrations were higher under greenhouse conditions as compared to the field. In the greenhouse, the number of days under AWD was negatively correlated with grain iAs concentrations. Thus, longer drying periods to meet the same soil VWC resulted in lower grain iAs levels. Both the number and combinations of iAs-affecting QTLs significantly impacted grain iAs concentrations. Therefore, identifying more grain iAs-affecting QTLs could be important to inform future breeding efforts for low iAs rice varieties. Our study suggests that coupling AWD practices targeting a soil VWC of less than or equal to 30% coupled with the use of cultivars developed to possess multiple QTLs that negatively regulate grain iAs concentrations will be helpful in mitigating exposure of iAs from rice consumption.

Univariate and Multivariate QTL Analyses Reveal Covariance Among Mineral Elements in the Rice Ionome

Rice provides more than one fifth of daily calories for half of the world’s human population, and is a major dietary source of both essential mineral nutrients and toxic elements. Rice grains are generally poor in some essential nutrients but may contain unsafe levels of some toxic elements under certain conditions. Identification of quantitative trait loci (QTLs) controlling the concentrations of mineral nutrients and toxic trace metals (the ionome) in rice will facilitate development of nutritionally improved rice varieties. However, QTL analyses have traditionally considered each element separately without considering their interrelatedness. In this study, we performed principal component analysis (PCA) and multivariate QTL analyses to identify the genetic loci controlling the covariance among mineral elements in the rice ionome. We resequenced the whole genomes of a rice recombinant inbred line (RIL) population, and performed univariate and multivariate QTL analyses for the concentrations of 16 elements in grains, shoots and roots of the RIL population grown in different conditions. We identified a total of 167 unique elemental QTLs based on analyses of individual elemental concentrations as separate traits, 53 QTLs controlling covariance among elemental concentrations within a single environment/tissue (PC-QTLs), and 152 QTLs which determined covariation among elements across environments/tissues (aPC-QTLs). The candidate genes underlying the QTL clusters with elemental QTLs, PC-QTLs and aPC-QTLs co-localized were identified, including OsHMA4 and OsNRAMP5. The identification of both elemental QTLs and PC QTLs will facilitate the cloning of underlying causal genes and the dissection of the complex regulation of the ionome in rice.