Meta-analysis of grain iron and zinc associated QTLs identified hotspot chromosomal regions and positional candidate genes for breeding biofortified rice

Meta-QTL mapping for wheat thousand kernel weight

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait.

Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations

Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval mapping (ICIM), and 16 QTLs for two traits (YLD and Zn) by association mapping. The phenotypic variance (PV) varied from 4.5% (qPN 4.1 ) to 31.7% (qPH 1.1 ). qDF 1.1 , qDF 7.2 , qDF 8.1 , qPH 1.1 , qPH 7.1 , qPL 1.2 , qPL 9.1, qZn 5.1 , qZn 5.2 , qZn 6.1 and qZn 7.1 were identified in both dry and wet seasons; qZn 5.1 , qZn 5.2 , qZn 5.3, qZn 6.2, qZn 7.1 and qYLD 1.2 were detected by both ICIM and association mapping. qZn 7.1 had the highest PV (17.8%) and additive effect (2.5 ppm). Epistasis and QTL co-locations were also observed for different traits. The multi-trait genomic prediction values were 0.24 and 0.16 for YLD and Zn respectively. qZn 6.2 was co-located with a gene (OsHMA2) involved in Zn transport. These results are useful for Zn biofortificatiton of rice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13562-024-00886-0.

Meta-QTL s and haplotypes for efficient zinc biofortification of rice

Biofortification of rice with improved grain zinc (Zn) content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.

Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents

Rice is a highly consumed staple cereal cultivated predominantly in Asian countries, which share 90% of global rice production. Rice is a primary calorie provider for more than 3.5 billion people across the world. Preference and consumption of polished rice have increased manifold, which resulted in the loss of inherent nutrition. The prevalence of micronutrient deficiencies (Zn and Fe) are major human health challenges in the 21^st century. Biofortification of staples is a sustainable approach to alleviating malnutrition. Globally, significant progress has been made in rice for enhancing grain Zn, Fe, and protein. To date, 37 biofortified Fe, Zn, Protein and Provitamin A rich rice varieties are available for commercial cultivation (16 from India and 21 from the rest of the world; Fe > 10 mg/kg, Zn > 24 mg/kg, protein > 10% in polished rice as India target while Zn > 28 mg/kg in polished rice as international target). However, understanding the micronutrient genetics, mechanisms of uptake, translocation, and bioavailability are the prime areas that need to be strengthened. The successful development of these lines through integrated-genomic technologies can accelerate deployment and scaling in future breeding programs to address the key challenges of malnutrition and hidden hunger.

Genome-wide analysis of sulfur-encoding biosynthetic genes in rice (Oryza sativa L.) with Arabidopsis as the sulfur-dependent model plant

Sulfur is an essential element required for plant growth and development, physiological processes and stress responses. Sulfur-encoding biosynthetic genes are involved in the primary sulfur assimilation pathway, regulating various mechanisms at the gene, cellular and system levels, and in the biosynthesis of sulfur-containing compounds (SCCs). In this study, the SCC-encoding biosynthetic genes in rice were identified using a sulfur-dependent model plant, the Arabidopsis. A total of 139 AtSCC from Arabidopsis were used as reference sequences in search of putative rice SCCs. At similarity index > 30%, the similarity search against Arabidopsis SCC query sequences identified 665 putative OsSCC genes in rice. The gene synteny analysis showed a total of 477 syntenic gene pairs comprised of 89 AtSCC and 265 OsSCC biosynthetic genes in Arabidopsis and rice, respectively. Phylogenetic tree of the collated (AtSCCs and OsSCCs) SCC-encoding biosynthetic genes were divided into 11 different clades of various sizes comprised of branches of subclades. In clade 1, nearing equal representation of OsSCC and AtSCC biosynthetic genes imply the most ancestral lineage. A total of 25 candidate Arabidopsis SCC homologs were identified in rice. The gene ontology enrichment analysis showed that the rice-Arabidopsis SCC homologs were significantly enriched in the following terms at false discovery rate (FDR) < 0.05: (i) biological process; sulfur compound metabolic process and organic acid metabolic processes, (ii) molecular function; oxidoreductase activity, acting on paired donors with incorporation or reduction of molecular oxygen and (iii) KEGG pathway; metabolic pathways and biosynthesis of secondary metabolites. At less than five duplicated blocks of separation, no tandem duplications were observed among the SCC biosynthetic genes distributed in rice chromosomes. The comprehensive rice SCC gene description entailing syntenic events with Arabidopsis, motif distribution and chromosomal mapping of the present findings offer a foundation for rice SCC gene functional studies and advanced strategic rice breeding.

Current Status and Potential of Biofortification to Enhance Crop Nutritional Quality: An Overview

Around 2 billion people are suffering from chronic malnutrition or “hidden hunger”, which is the result of many diseases and disorders, including cognitive degeneration, stunting growth, and mortality. Thus, biofortification of staple food crops enriched with micronutrients is a more sustainable option for providing nutritional supplements and managing malnutrition in a society. Since 2001, when the concept of biofortification came to light, different research activities have been carried out, like the development of target populations, breeding or genetic engineering, and the release of biofortified cultivars, in addition to conducting nutritional efficacy trials and delivery plan development. Although, being a cost-effective intervention, it still faces many challenges, like easy accessibility of biofortified cultivars, stakeholders’ acceptance, and the availability of biofortified germplasm in the public domain, which varies from region to region. Hence, this review is focused on the recent potential, efforts made to crop biofortification, impacts analysis on human health, cost-effectiveness, and future perspectives to further strengthen biofortification programs. Through regular interventions of sustainable techniques and methodologies, biofortification holds huge potential to solve the malnutrition problem through regular interventions of nutrient-enriched staple food options for billions of people globally.

Meta-QTLs, ortho-MetaQTLs and candidate genes for grain Fe and Zn contents in wheat (Triticum aestivum L.)

Majority of cereals are deficient in essential micronutrients including grain iron (GFe) and grain zinc (GZn), which are therefore the subject of research involving biofortification. In the present study, 11 meta-QTLs (MQTLs) including nine novel MQTLs for GFe and GZn contents were identified in wheat. Eight of these 11 MQTLs controlled both GFe and GZn. The confidence intervals of the MQTLs were narrower (0.51-15.75 cM) relative to those of the corresponding QTLs (0.6 to 55.1 cM). Two ortho-MQTLs involving three cereals (wheat, rice and maize) were also identified. Results of MQTLs were also compared with the results of earlier genome wide association studies (GWAS). As many as 101 candidate genes (CGs) underlying MQTLs were also identified. Twelve of these CGs were prioritized; these CGs encoded proteins with important domains (zinc finger, RING/FYVE/PHD type, flavin adenine dinucleotide linked oxidase, etc.) that are involved in metal ion binding, heme binding, iron binding, etc. qRT-PCR analysis was conducted for four of these 12 prioritized CGs using genotypes which have differed for GFe and GZn. Significant differential expression in these genotypes was observed at 14 and 28 days after anthesis. The MQTLs/CGs identified in the present study may be utilized in marker-assisted selection (MAS) for improvement of GFe/GZn contents and also for understanding the molecular basis of GFe/GZn homeostasis in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01149-9.

Meta-analysis and validation of genomic loci governing seedling and reproductive stage salinity tolerance in rice

Identification of concurrent genomic regions contributing tolerance to salinity at the seedling and reproductive stages were done using 45 quantitative trait loci (QTL) mapping studies reporting 915 individual QTLs. The QTL-data were used to perform a meta-analysis to predict, validate and analyze the Meta-QTLs governing component traits contributing to salinity tolerance. We predicted a total of 65 and 49 Meta-QTLs distributed across the genome governing seedling and reproductive stage salinity tolerance, respectively. Salinity stress (EC ~10.0 dSm^-1 ) was evaluated in a set of 32 genotypes grown hydroponically, from these eight extreme (highly tolerant and highly susceptible) genotypes were selected for validation of significant Meta-QTLs. Another set of eight previously known and reported (highly tolerant and highly susceptible) genotypes were evaluated under saline micro plot conditions (EC ~8.0 dSm^-1 ) and used for validation of significant Meta-QTLs for reproductive stage salinity tolerance. The microsatellite marker "RM5635" linked to MSQTL4.2 (~295.43 kb) was able to clearly differentiate contrasting genotypes for seedling stage salinity tolerance, whereas at the reproductive stage, none of the markers were able to validate the predicted Meta-QTL for salinity tolerance. Earlier reported, gene expression studies were used for candidate gene analysis of validated MSQTL4.2, which indicated the down regulation of Os04g0423100, a gene encoding Mono-oxygenase-FAD binding domain containing protein. The traits associated with this Meta-QTL were root and shoot sodium and potassium concentration and leaf chlorophyll content. The identified and validated genomic region assumes a great significant role in seedling stage salinity tolerance in rice, and it can be used for marker-assisted backcross breeding programs.

Challenges and opportunities to regulate mineral transport in rice

Iron (Fe) is an essential mineral for plants, and its deficiency as well as toxicity severely affects plant growth and development. Although Fe is ubiquitous in mineral soils, its acquisition by plants is difficult to regulate particularly in acidic and alkaline soils. Under alkaline conditions, where lime is abundant, Fe and other mineral elements are sparingly soluble. In contrast, under low pH conditions, especially in paddy fields, Fe toxicity could occur. Fe uptake is complicated and could be integrated with copper (Cu), manganese (Mn), zinc (Zn), and cadmium (Cd) uptake. Plants have developed sophisticated mechanisms to regulate the Fe uptake from soil and its transport to root and above-ground parts. Here, we review recent developments in understanding metal transport and discuss strategies to effectively regulate metal transport in plants with a particular focus on rice.

Transcriptomics View over the Germination Landscape in Biofortified Rice

Hidden hunger, or micronutrient deficiency, is a worldwide problem. Several approaches are employed to alleviate its effects (e.g., promoting diet diversity, use of dietary supplements, chemical fortification of processed food), and among these, biofortification is considered as one of the most cost-effective and highly sustainable. Rice is one of the best targets for biofortification since it is a staple food for almost half of the world’s population as a high-energy source but with low nutritional value. Multiple biofortified rice lines have been produced during the past decades, while few studies also reported modifications in germination behavior (in terms of enhanced or decreased germination percentage or speed). It is important to underline that rapid, uniform germination, and seedling establishment are essential prerequisites for crop productivity. Combining the two traits, biofortified, highly-nutritious seeds with improved germination behavior can be envisaged as a highly-desired target for rice breeding. To this purpose, information gathered from transcriptomics studies can reveal useful insights to unveil the molecular players governing both traits. The present review aims to provide an overview of transcriptomics studies applied at the crossroad between biofortification and seed germination, pointing out potential candidates for trait pyramiding.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Omics Technologies to Enhance Plant Based Functional Foods: An Overview

Functional foods are natural products of plants that have health benefits beyond necessary nutrition. Functional foods are abundant in fruits, vegetables, spices, beverages and some are found in cereals, millets, pulses and oilseeds. Efforts to identify functional foods in our diet and their beneficial aspects are limited to few crops. Advances in sequencing and availability of different omics technologies have given opportunity to utilize these tools to enhance the functional components of the foods, thus ensuring the nutritional security. Integrated omics approaches including genomics, transcriptomics, proteomics, metabolomics coupled with artificial intelligence and machine learning approaches can be used to improve the crops. This review provides insights into omics studies that are carried out to find the active components and crop improvement by enhancing the functional compounds in different plants including cereals, millets, pulses, oilseeds, fruits, vegetables, spices, beverages and medicinal plants. There is a need to characterize functional foods that are being used in traditional medicines, as well as utilization of this knowledge to improve the staple foods in order to tackle malnutrition and hunger more effectively.

Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Triticum aestivum L.)

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

Genetic determinants of micronutrient traits in graminaceous crops to combat hidden hunger

KEY MESSAGE

Improving the nutritional content of graminaceous crops is imperative to ensure nutritional security, wherein omics approaches play pivotal roles in dissecting this complex trait and contributing to trait improvement. Micronutrients regulate the metabolic processes to ensure the normal functioning of the biological system in all living organisms. Micronutrient deficiency, thereby, can be detrimental that can result in serious health issues. Grains of graminaceous crops serve as an important source of micronutrients to the human population; however, the rise in hidden hunger and malnutrition indicates an insufficiency in meeting the nutritional requirements. Improving the elemental composition and nutritional value of the graminaceous crops using conventional and biotechnological approaches is imperative to address this issue. Identifying the genetic determinants underlying the micronutrient biosynthesis and accumulation is the first step toward achieving this goal. Genetic and genomic dissection of this complex trait has been accomplished in major cereals, and several genes, alleles, and QTLs underlying grain micronutrient content were identified and characterized. However, no comprehensive study has been reported on minor cereals such as small millets, which are rich in micronutrients and other bioactive compounds. A comparative narrative on the reports available in major and minor Graminaceae species will illustrate the knowledge gained from studying the micronutrient traits in major cereals and provides a roadmap for dissecting this trait in other minor species, including millets. In this context, this review explains the progress made in studying micronutrient traits in major cereals and millets using omics approaches. Moreover, it provides insights into deploying integrated omics approaches and strategies for genetic improvement in micronutrient traits in graminaceous crops.

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.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat

Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

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.

Identification of Promising RILs for High Grain Zinc Through Genotype × Environment Analysis and Stable Grain Zinc QTL Using SSRs and SNPs in Rice (Oryza sativa L.)

Polished rice is one of the commonly consumed staple foods across the world. However, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising recombinant inbred lines (RILs) for grain Zn and single plant yield, 190 RILs developed from PR116 and Ranbir Basmati were evaluated in two environments (E1 and E2). A subset of 44 contrasting RILs for grain Zn was screened in another two environments (E3 and E4). Phenotypic data was collected for 10 traits, viz., days to 50% flowering, plant height, panicle length, number of tillers, single plant yield (SPY), test weight, Fe and Zn in brown (IBR, ZBR), and polished rice (IPR, ZPR). Stepwise regression analysis of trait data in 190 RILs and a subset of 44 RILs revealed the interdependence of ZPR, ZBR, IPR, and IBR and the negative association of grain Zn with single plant yield. Based on the additive main effect and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) analyses of the subset of 44 RILs across four environments (E1-E4), six promising RILs were identified for ZPR with >28 ppm. Mapping of 190 RILs with 102 simple sequence repeats (SSRs) resulted in 13 QTLs for best linear unbiased estimates (BLUEs) of traits including advantage over check (AOC). Using genotype-based sequencing (GBS), the subset of 44 RILs was mapped with 1035 single-nucleotide polymorphisms (SNPs) and 21 QTLs were identified. More than 100 epistatic interactions were observed. A major QTL qZPR.1.1 (PV 37.84%) and another QTL qZPR.11.1 (PV 15.47%) were identified for grain Zn in polished rice. A common major QTL (qZBR.2.1 and qZPR.2.1) was also identified on chromosome 2 for grain Zn content across SSR and SNP maps. Two potential candidate genes related to transporters were identified based on network analyses in the genomic regions of QTL < 3 Mb. The RILs identified for grain Zn and SPY were nominated for national evaluation as under rice biofortification, and two QTLs identified based on BLUEs could be used in the rice biofortification breeding programs.

Grain Fe and Zn contents linked SSR markers based genetic diversity in rice

Rice is critical for sustainable food and nutritional security; however, nominal micronutrient quantities in grains aggravate malnutrition in rice-eating poor populations. In this study, we evaluated genetic diversity in grain iron (Fe) and zinc (Zn) contents using trait-linked simple sequence repeat (SSR) markers in the representative subset of a large collection of local and exotic rice germplasm. Results demonstrated that aromatic fine grain accessions contained relatively higher Fe and Zn contents in brown rice (BR) than coarse grain accessions and a strong positive correlation between both mineral elements. Genotyping with 24 trait-linked SSR markers identified 21 polymorphic markers, among which 17 demonstrated higher gene diversity and polymorphism information content (PIC) values, strongly indicating that markers used in current research were moderate to highly informative for evaluating the genetic diversity. Population structure, principal coordinate and phylogenetic analyses classified studied rice accessions into two fine grain specific and one fine and coarse grain admixture subpopulations. Single marker analysis recognized four ZnBR and single FeBR significant marker-trait associations (MTAs) contributing 15.41-39.72% in total observed phenotypic variance. Furthermore, high grain Fe and Zn contents linked marker alleles from significant MTAs were also identified. Collectively, these results indicate a wide genetic diversity exist in grain Fe and Zn contents of studied rice accessions and reveal perspective for marker-assisted biofortification breeding.

Reproductive tissues-specific meta-QTLs and candidate genes for development of heat-tolerant rice cultivars

By integrating genetics and genomics data, reproductive tissues-specific and heat stress responsive 35 meta-QTLs and 45 candidate genes were identified, which could be exploited through marker-assisted breeding for fast-track development of heat-tolerant rice cultivars. Rice holds the key to future food security. In rice-growing areas, temperature has already reached an optimum level for growth, hence, any further increase due to global climate change could significantly reduce rice yield. Several mapping studies have identified a plethora of reproductive tissue-specific and heat stress associated inconsistent quantitative trait loci (QTL), which could be exploited for improvement of heat tolerance. In this study, we performed a meta-analysis on previously reported QTLs and identified 35 most consistent meta-QTLs (MQTLs) across diverse genetic backgrounds and environments. Genetic and physical intervals of nearly 66% MQTLs were narrower than 5 cM and 2 Mb respectively, indicating hotspot genomic regions for heat tolerance. Comparative analyses of MQTLs underlying genes with microarray and RNA-seq based transcriptomic data sets revealed a core set of 45 heat-responsive genes, among which 24 were reproductive tissue-specific and have not been studied in detail before. Remarkably, all these genes corresponded to various stress associated functions, ranging from abiotic stress sensing to regulating plant stress responses, and included heat-shock genes (OsBiP2, OsMed37_1), transcription factors (OsNAS3, OsTEF1, OsWRKY10, OsWRKY21), transmembrane transporters (OsAAP7A, OsAMT2;1), sugar metabolizing (OsSUS4, α-Gal III) and abiotic stress (OsRCI2-7, SRWD1) genes. Functional data evidences from Arabidopsis heat-shock genes also suggest that OsBIP2 may be associated with thermotolerance of pollen tubes under heat stress conditions. Furthermore, promoters of identified genes were enriched with heat, dehydration, pollen and sugar responsive cis-acting regulatory elements, proposing a common regulatory mechanism might exist in rice for mitigating reproductive stage heat stress. These findings strongly support our results and provide new candidate genes for fast-track development of heat-tolerant rice cultivars.

Stable SNP Allele Associations With High Grain Zinc Content in Polished Rice (Oryza sativa L.) Identified Based on ddRAD Sequencing

Polished rice is widely consumed staple food across the globe, however, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising genotypes for grain Zn, a total of 40 genotypes consisting 20 rice landraces, and 20 released high yielding rice varieties were evaluated in three environments (wet seasons 2014, 2015 and 2016) for nine traits including days to 50% flowering (DFF), plant height (PH), panicle length (PL), total number of tillers (TNT), single plant yield (SPY), Fe and Zn in brown (IBR, ZBR) and polished rice (IPR, ZPR). Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) analyses identified genotypes G22 (Edavankudi Pokkali), G17 (Taraori Basmati), G27 (Chittimuthyalu) and G26 (Kalanamak) stable for ZPR and G8 (Savitri) stable for SPY across three environments. Significant negative correlation between yield and grain Zn was reaffirmed. Regression analysis indicated the contribution of traits toward ZPR and SPY and also desirable level of grain Zn in brown rice. A total of 39,137 polymorphic single nucleotide polymorphisms (SNPs) were obtained through double digest restriction site associated DNA (dd-RAD) sequencing of 40 genotypes. Association analyses with nine phenotypic traits revealed 188 stable SNPs with six traits across three environments. ZPR was associated with SNPs located in three putative candidate genes (LOC_Os03g47980, LOC_Os07g47950 and LOC_Os07g48050) on chromosomes 3 and 7. The genomic region of chromosome 7 co localized with reported genomic regions (rMQTL₇.₁) and OsNAS3 candidate gene. SPY was found to be associated with 12 stable SNPs located in 11 putative candidate genes on chromosome 1, 6, and 12. Characterization of rice landraces and varieties in terms of stability for their grain Zn and yield identified promising donors and recipients along with genomic regions in the present study to be deployed rice Zn biofortification breeding program.

Rice Biofortification With Zinc and Selenium: A Transcriptomic Approach to Understand Mineral Accumulation in Flag Leaves

Human malnutrition due to micronutrient deficiencies, particularly with regards to Zinc (Zn) and Selenium (Se), affects millions of people around the world, and the enrichment of staple foods through biofortification has been successfully used to fight hidden hunger. Rice (Oryza sativa L.) is one of the staple foods most consumed in countries with high levels of malnutrition. However, it is poor in micronutrients, which are often removed during grain processing. In this study, we have analyzed the transcriptome of rice flag leaves biofortified with Zn (900 g ha-1), Se (500 g ha-1), and Zn-Se. Flag leaves play an important role in plant photosynthesis and provide sources of metal remobilization for developing grains. A total of 3170 differentially expressed genes (DEGs) were identified. The expression patterns and gene ontology of DEGs varied among the three sets of biofortified plants and were limited to specific metabolic pathways related to micronutrient mobilization and to the specific functions of Zn (i.e., its enzymatic co-factor/coenzyme function in the biosynthesis of nitrogenous compounds, carboxylic acids, organic acids, and amino acids) and Se (vitamin biosynthesis and ion homeostasis). The success of this approach should be followed in future studies to understand how landraces and other cultivars respond to biofortification.