Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding.

BACKGROUND: High yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Bio-fortification is a cheaper and easier way to improve the content of these nutrients in rice grain. RESULTS: A population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg's expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namely qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected using association mapping. Four QTLs, namely qFe3.3, qFe7.3, qFe8.1 and qFe12.2 for grain Fe content were detected to be co-localized with qZn3.1, qZn7, qZn8.3 and qZn12.3 QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs, qTBGW, OsSPL14 and qPN. The QTLs qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9-1 for grain Fe-Zn content reported in earlier studies were validated in this study. CONCLUSION: Novel QTLs, qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be co-localized. The QTLs, qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3 and qZn12.3 will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.

A rice small GTPase, Rab6a, is involved in the regulation of grain yield and iron nutrition in response to CO2 enrichment.

Despite extensive studies on the effects of elevated atmospheric CO2 concentrations ([CO2]) on rice, the molecular mechanisms and signaling events underlying the adaptation of plants remain largely elusive. Here, we report that OsRab6a, which encodes a small GTPase, is involved in the regulation of rice growth, grain yield, and accumulation of iron (Fe) in response to elevated [CO2] (e[CO2]). We generated transgenic plants with OsRab6a-overexpression (-OE) together with OsRab6a-RNAi lines, and found no differences in growth and grain yield among them and wild-type (WT) plants under ambient [CO2] conditions. Under e[CO2] conditions, growth and grain yield of the WT and OsRab6a-OE plants were enhanced, with a greater effect being observed in the latter. In contrast, there were no effects of e[CO2] on growth and grain yield of the OsRab6a-RNAi plants. Photosynthetic rates in both the WT and OsRab6a-OE plants were stimulated by e[CO2], with the magnitude of the increase being higher in OsRab6a-OE plants. Fe concentrations in vegetative tissues and the grain of the WT and transgenic plants were reduced by e[CO2], and the magnitude of the decrease was lower in the OE plants than in the WT and RNAi plants. Genes associated with Fe acquisition in the OsRab6a-OE lines exhibited higher levels of expression than those in the WT and the RNAi lines under e[CO2]. Analysis of our data using Dunnett's multiple comparison test suggested that OsRab6a is an important molecular regulator that underlies the adaptation of rice to e[CO2] by controlling photosynthesis and Fe accumulation.

Genome-Wide Association Analysis Reveals Trait-Linked Markers for Grain Nutrient and Agronomic Traits in Diverse Set of Chickpea Germplasm.

Chickpea is an inexpensive source of protein, minerals, and vitamins to the poor people living in arid and semi-arid regions of Southern Asia and Sub-Saharan Africa. New chickpea cultivars with enhanced levels of protein, Fe and Zn content are a medium-term strategy for supplying essential nutrients for human health and reducing malnutrition. In the current study, a chickpea reference set of 280 accessions, including landraces, breeding lines, and advanced cultivars, was evaluated for grain protein, Fe, Zn content and agronomic traits over two seasons. Using a mid-density 5k SNP array, 4603 highly informative SNPs distributed across the chickpea genome were used for GWAS analysis. Population structure analysis revealed three subpopulations (K = 3). Linkage disequilibrium (LD) was extensive, and LD decay was relatively low. A total of 20 and 46 marker-trait associations (MTAs) were identified for grain nutrient and agronomic traits, respectively, using FarmCPU and BLINK models. Of which seven SNPs for grain protein, twelve for Fe, and one for Zn content were distributed on chromosomes 1, 4, 6, and 7. The marker S4_4477846 on chr4 was found to be co-associated with grain protein over seasons. The markers S1_11613376 and S1_2772537 co-associated with grain Fe content under NSII and pooled seasons and S7_9379786 marker under NSI and pooled seasons. The markers S4_31996956 co-associated with grain Fe and days to maturity. SNP annotation of associated markers were found to be related to gene functions of metal ion binding, transporters, protein kinases, transcription factors, and many more functions involved in plant metabolism along with Fe and protein homeostasis. The identified significant MTAs has potential use in marker-assisted selection for developing nutrient-rich chickpea cultivars after validation in the breeding populations.

Combining ability studies of grain Fe and Zn contents of pearl millet (Pennisetum glaucum L.) in West Africa.

Micronutrient malnutrition is a major challenge in Africa, where half a million children die each year because of lack of micronutrients in their food. Pearl millet is an important food and fodder crop for the people living in the Semi-Arid regions of West Africa. The present study was conducted to determine the stability, combining ability, and gene action conditions of the high level of Fe and Zn content in grain and selected agronomic traits. Hence, eight genotypes were selected based on the availability of grain Fe and Zn contents and crossed in a full diallel mating design. Progenies from an 8 × 8 diallel mating along with the parents were evaluated in an alpha lattice design with three replications in three locations for two years. The parental lines Jirani, LCIC 9702 and MORO, had positive significant general combining ability (GCA) effects for grain Fe concentration, while Jirani and MORO had positive significant GCA effects for grain Zn concentration. For the specific combining ability (SCA), among the 56 hybrids evaluated, only the hybrids LCIC 9702 × Jirani and MORO × ZANGO had positive significant SCA effects for grain Fe concentration across locations, and for grain Zn concentration, the hybrids Gamoji × MORO, LCIC 9702 × Jirani, and ICMV 167006 × Jirani had positive significant SCA effects. The reciprocal effects were significant for grain Zn concentration, grain yield, flowering time, plant height, test weight, and downy mildew incidence, suggesting that the choice of a female or male parent is critical in hybrid production. Grain Fe and Zn concentration, flowering time, plant height, panicle length, panicle girth, panicle compactness, and downy mildew incidence were found to be predominantly under additive gene action, while grain yield and test weight were predominantly under non-additive gene action. A highly positive correlation was found between grain Fe and Zn concentrations, which implies that improving grain Fe trait automatically improves the grain Zn content. The stability analysis revealed that the hybrid ICMV 167006 × Jirani was the most stable and high-yielding with a high level of grain Fe and Zn micronutrients.

Identification of High-Yielding Iron-Biofortified Open-Pollinated Varieties of Pearl Millet in West Africa.

Pearl millet is a predominant food and fodder crop in West Africa. This study was carried out to test the newly developed open-pollinated varieties (OPVs) for field performance and stability for grain yield, grain iron (Fe), and grain zinc (Zn) contents across 10 locations in West Africa (i.e., Niger, Nigeria, Mali, Burkina Faso, Senegal, and Ghana). The test material consisted of 30 OPVs, of which 8 are Fe/Zn biofortified. The experiment was conducted in a randomized complete block design in three replications. ANOVA revealed highly significant variability for grain yield and micronutrient traits. The presence of genotype × environment (G × E) indicated that the expressions of traits are significantly influenced by both genetic and G × E factors, for grain Fe and Zn contents. Days to 50% flowering and plant height showed less G × E, suggesting these traits are largely under genetic control. The genotypes CHAKTI (46 days), ICTP 8203 (46 days), ICMV 177002 (50 days), ICMV 177003 (48 days), and Moro (53 days) had exhibited early flowering across locations leading to early physiological maturity. CHAKTI (1.42 t/ha yield; 62.24 mg/kg of grain Fe, 47.29 mg/kg of grain Zn) and ICMP 177002 (1.19 t/ha yield, 62.62 mg/kg of grain Fe, 46.62 mg/kg of grain Zn) have performed well for grain yield and also for micronutrients, across locations, compared with the check. Additive Main Effect and Multiplicative Interaction (AMMI) ANOVA revealed the highly significant genotypic differences, the mean sum of squares of environment, and its interaction with the genotypes. Based on the AMMI stability value (ASV), the most stable genotype is SOSAT-C88 (ASV = 0.04) for grain yield and resistance to downy mildew; mean grain yield and stability rankings (YSI) revealed that the genotypes CHAKTI, SOSAT-C88, and ICMV IS 99001 were high yielding and expressed stability across regions. The strong correlation (r = 0.98∗∗) of grain Fe and Zn contents that merits Fe-based selection is highly rewarding. CHAKTI outperformed over other genotypes for grain yield (71% higher), especially with early maturing varieties in West Africa, such as GB 8735, LCIC 9702, and Jirani, and for grain Fe (16.11% higher) and Zn (7% higher) contents across locations, and made a candidate of high-iron variety to be promoted for combating the micronutrient malnutrition in West and Central Africa (WCA).

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

Biofortification of staple crops with essential micronutrients is the sustainable way to overcome the hidden hunger. A large number of quantitative trait loci (QTL) linked with grain micronutrient contents have been reported in different mapping studies. Identification of consistent QTLs across diverse genetic backgrounds is useful for candidate gene analysis and marker assisted selection of target traits. In this study, an up to date meta-analysis of grain iron and zinc associated QTLs was performed and 48 meta-QTLs (MQTLs) distributed across 12 rice chromosomes were identified. The 95% confidence intervals of identified genomic regions were significantly narrower than the average of their corresponding original QTLs. A total of 9308 genes/transcripts physically located within or near MQTL regions were retrieved and through prioritization of candidate genes (CGs) 663 non-redundant iron and zinc CGs were selected and studied in detailed. Several functionally characterized iron and zinc homoeostasis related genes e.g OsATM3, OsDMAS1, OsFRO2, OsNAS1-3, OsVIT2, OsYSL16, OsZIP3 and OsZIP7 were also included in our MQTL analysis. More than 64% genes were enriched with zinc and iron binding gene ontology terms and were involved in oxidation reduction process, carbohydrate metabolic process, regulation of transcription, trans-membrane transport, response to oxidative stress, cell redox homeostasis and proteolysis etc. In-silico transcriptomic analysis of rice identified 260 CGs which were regulated in response to iron and zinc stresses. We also identified at least 37 genes which were differentially expressed under both stress conditions and majority of these have not been studied in detailed before. Our results strongly indicate that majority of the MQTLs identified in this study are hotspots for grain iron and zinc concentration and are worth of intensive functional studies in near future.

QTL Mapping of Grain Zn and Fe Concentrations in Two Hexaploid Wheat RIL Populations with Ample Transgressive Segregation.

More than 50% of undernourished children live in Asia and more than 25% live in Africa. Coupled with an inadequate food supply, mineral deficiencies are widespread in these populations; particularly zinc (Zn) and iron (Fe) deficiencies that lead to retarded growth, adverse effects on both the immune system and an individual's cognitive abilities. Biofortification is one solution aimed at reducing the incidence of these deficiencies. To efficiently breed a biofortified wheat variety, it is important to generate knowledge of the genomic regions associated with grain Zn (GZn) and Fe (GFe) concentration. This allows for the introgression of favorable alleles into elite germplasm. In this study we evaluated two bi-parental populations of 188 recombinant inbred lines (RILs) displaying a significant range of transgressive segregation for GZn and GFe during three crop cycles in CIMMYT, Mexico. Parents of the RILs were derived from Triticum spelta L. and synthetic hexaploid wheat crosses. QTL analysis identified a number of significant QTL with a region denominated as QGZn.cimmyt-7B_1P2 on chromosome 7B explaining the largest (32.7%) proportion of phenotypic variance (PVE) for GZn and leading to an average additive effect of -1.3. The QTL with the largest average additive effect for GFe (-0.161) was found on chromosome 4A (QGFe.cimmyt-4A_P2), with 21.14% of the PVE. The region QGZn.cimmyt-7B_1P2 co-localized closest to the region QGZn.cimmyt-7B_1P1 in a consensus map built from the linkage maps of both populations. Pleiotropic or tightly linked QTL were also found on chromosome 3B, however of minor effects and PVE between 4.3 and 10.9%. Further efforts are required to utilize the QTL information in marker assisted backcrossing schemes for wheat biofortification. A strategy to follow is to intercross the transgressive individuals from both populations and then utilize them as sources in biofortification breeding pipelines.