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Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.
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Oryza , Oryza/genética , Melhoramento Vegetal , Locos de Características Quantitativas/genética , Mapeamento Cromossômico , Alelos , Grão Comestível/genéticaRESUMO
A 1D/2D genome-wide association study strategy was adopted to investigate the genetic systems underlying the reciprocal adaptation of rice (Oryza sativa) and its bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo) using the whole-genome sequencing and large-scale phenotyping data of 701 rice accessions and 23 diverse Xoo strains. Forty-seven Xoo virulence-related genes and 318 rice quantitative resistance genes (QR-genes) mainly located in 41 genomic regions, and genome-wide interactions between the detected virulence-related genes and QR genes were identified, including well-known resistance genes/virulence genes plus many previously uncharacterized ones. The relationship between rice and Xoo was characterized by strong differentiation among Xoo races corresponding to the subspecific differentiation of rice, by strong shifts toward increased resistance/virulence of rice/Xoo populations and by rich genetic diversity at the detected rice QR-genes and Xoo virulence genes, and by genome-wide interactions between many rice QR-genes and Xoo virulence genes in a multiple-to-multiple manner, presumably resulting either from direct protein-protein interactions or from genetic epistasis. The observed complex genetic interaction system between rice and Xoo likely exists in other crop-pathogen systems that would maintain high levels of diversity at their QR-loci/virulence-loci, resulting in dynamic coevolutionary consequences during their reciprocal adaptation.
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Interações Hospedeiro-Patógeno/genética , Oryza/genética , Oryza/microbiologia , Xanthomonas/genética , Adaptação Fisiológica/genética , Resistência à Doença/genética , Regulação Bacteriana da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Genoma Bacteriano , Genoma de Planta , Estudo de Associação Genômica Ampla , Desequilíbrio de Ligação , Filogenia , Melhoramento Vegetal , Doenças das Plantas/genética , Doenças das Plantas/microbiologia , Polimorfismo de Nucleotídeo Único , Virulência/genética , Sequenciamento Completo do Genoma , Xanthomonas/patogenicidadeRESUMO
KEY MESSAGE: Estimating genetic gains and formulating a future salinity elite breeding panel for rice pave the way for developing better high-yielding salinity tolerant lines with enhanced genetic gains. Genetic gain is a crucial parameter to check the breeding program's success and help optimize future breeding strategies for enhanced genetic gains. To estimate the genetic gains in IRRI's salinity breeding program and identify the best genotypes based on high breeding values for grain yield (kg/ha), we analyzed the historical data from the trials conducted in the IRRI, Philippines and Bangladesh. A two-stage mixed-model approach accounting for experimental design factors and a relationship matrix was fitted to obtain the breeding values for grain yield and estimate genetic trends. A positive genetic trend of 0.1% per annum with a yield advantage of 1.52 kg/ha was observed in IRRI, Philippines. In Bangladesh, we observed a genetic gain of 0.31% per annum with a yield advantage of 14.02 kg/ha. In the released varieties, we observed a genetic gain of 0.12% per annum with a 2.2 kg/ha/year yield advantage in the IRRI, Philippines. For the Bangladesh dataset, a genetic gain of 0.14% per annum with a yield advantage of 5.9 kg/ha/year was observed in the released varieties. Based on breeding values for grain yield, a core set of the top 145 genotypes with higher breeding values of > 2400 kg/ha in the IRRI, Philippines, and > 3500 kg/ha in Bangladesh with a reliability of > 0.4 were selected to develop the elite breeding panel. Conclusively, a recurrent selection breeding strategy integrated with novel technologies like genomic selection and speed breeding is highly required to achieve higher genetic gains in IRRI's salinity breeding programs.
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Oryza , Oryza/genética , Reprodutibilidade dos Testes , Salinidade , Melhoramento Vegetal , Bangladesh , Grão ComestívelRESUMO
Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.
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Produtos Agrícolas/classificação , Produtos Agrícolas/genética , Variação Genética , Genoma de Planta/genética , Oryza/classificação , Oryza/genética , Ásia , Evolução Molecular , Genes de Plantas/genética , Genética Populacional , Genômica , Haplótipos , Mutação INDEL/genética , Filogenia , Melhoramento Vegetal , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
KEY MESSAGE: Schemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain and less depletion of genetic variance One of the most common methods to improve hybrid performance is reciprocal recurrent selection (RRS). Genomic prediction (GP) can be used to increase genetic gain in RRS by reducing cycle length, but it is also possible to use GP to predict single-cross hybrid performance. The impact of the latter method on genetic gain has yet to be previously reported. Therefore, we compared via stochastic simulations various phenotypic and genomics-assisted RRS breeding schemes which used GP to predict hybrid performance rather than reducing cycle length, which allows minimal changes to traditional breeding schemes. We also compared three breeding sizes scenarios that varied the number of genotypes crossed within heterotic pools, the number of genotypes crossed between heterotic pools, the number of hybrids evaluated, and the number of genomic predicted hybrids. Our results demonstrated that schemes that used genomic prediction of hybrid performance outperformed the others for the average interpopulation hybrid population and the best hybrid performance. Furthermore, updating the testers increased hybrid genetic gain with phenotypic RRS. As expected, the largest breeding size tested had the highest rates of genetic improvement and the lowest decrease in additive genetic variance due to the drift. Therefore, this study demonstrates the usefulness of single-cross prediction, which may be easier to implement than rapid-cycling RRS and cyclical updating of testers. We also reiterate that larger population sizes tend to have higher genetic gain and less depletion of genetic variance.
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Hibridização Genética , Oryza , Humanos , Oryza/genética , Modelos Genéticos , Melhoramento Vegetal , Genômica/métodos , PaisRESUMO
Sheath blight (ShB) is one of the most serious diseases in rice, leading to severe yield losses globally. In our study, we evaluated a total of 63 rice genotypes for resistance against sheath blight disease by artificial inoculation over two seasons under field conditions and studied the weather parameters associated with disease incidence. Based on two years of testing, 23 genotypes were found moderately resistant, 38 were moderately susceptible, and 2 exhibited a susceptible reaction to sheath blight disease. Among the specific four genotypes (IC283139, IC283041, IC283038, and IC283023) of the moderately resistant group exhibited less disease reaction in comparison with check variety Tetep. Further, the correlation of percent disease index (PDI) with weather parameters revealed negative associations between PDI and maximum temperature, minimum temperature, low rainfall and the positive association with maximum relative humidity (RH) suggest that very low temperature or high precipitation might have a negative impact on pathogen establishment. In addition, the sheath blight-linked SSRs were assessed using distance and model-based approaches, results of both the models revealed that genotypes distinguished the resistant population from the susceptible one. From the output of two years of principal component analysis, two genotypes from each group of moderately resistant, moderately susceptible and susceptible were studied for their biochemical reaction against the sheath blight pathogen. The biochemical study revealed that the accumulation of defense and antioxidant enzymes, namely, polyphenol oxidase, peroxidase, total phenol, phenylalanine ammonia-lyase, catalase, and superoxide dismutase, were higher in moderately resistant genotypes, but was observed to be lower in moderately susceptible and susceptible genotypes. The statistical analysis revealed the enzyme activities (defense and antioxidant) exhibited a strong negative correlation with area under the disease progress curve (AUDPC) and influence of weather parameter RH. This demonstrates that the environment factor RH plays a major role in imparting the resistance mechanism by decreasing the enzymes activities and increasing PDI. This study found that the identified novel resistant genotype (IC283139) with purple stem base demonstrated improved resistance against sheath blight infection through a defense response and the use of antioxidant machinery.
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The underground reserve (root) has been an uncharted research territory with its untapped genetic variation yet to be exploited. Identifying ideal traits and breeding new rice varieties with efficient root system architecture (RSA) has great potential to increase resource-use efficiency and grain yield, especially under direct-seeded rice, by adapting to aerobic soil conditions. In this review, we tried to mine the available research information on the direct-seeded rice (DSR) root system to highlight the requirements of different root traits such as root architecture, length, number, density, thickness, diameter, and angle that play a pivotal role in determining the uptake of nutrients and moisture at different stages of plant growth. RSA also faces several stresses, due to excess or deficiency of moisture and nutrients, low or high temperature, or saline conditions. To counteract these hindrances, adaptation in response to stress becomes essential. Candidate genes such as early root growth enhancer PSTOL1, surface rooting QTL qSOR1, deep rooting gene DRO1, and numerous transporters for their respective nutrients and stress-responsive factors have been identified and validated under different circumstances. Identifying the desired QTLs and transporters underlying these traits and then designing an ideal root architecture can help in developing a suitable DSR cultivar and aid in further advancement in this direction.
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Adaptação Fisiológica/fisiologia , Oryza/fisiologia , Raízes de Plantas/anatomia & histologia , Raízes de Plantas/fisiologia , Sementes/fisiologia , Germinação/fisiologia , Oryza/genética , Oryza/crescimento & desenvolvimento , Locos de Características Quantitativas/genética , Sementes/genética , Sementes/crescimento & desenvolvimentoRESUMO
Hybrid breeding is the main strategy for improving productivity in many crops, especially in rice and maize. Genomic hybrid breeding is a technology that uses whole-genome markers to predict future hybrids. Predicted superior hybrids are then field evaluated and released as new hybrid cultivars after their superior performances are confirmed. This will increase the opportunity of selecting true superior hybrids with minimum costs. Here, we used genomic best linear unbiased prediction to perform hybrid performance prediction using an existing rice population of 1495 hybrids. Replicated 10-fold cross-validations showed that the prediction abilities on ten agronomic traits ranged from 0.35 to 0.92. Using the 1495 rice hybrids as a training sample, we predicted six agronomic traits of 100 hybrids derived from half diallel crosses involving 21 parents that are different from the parents of the hybrids in the training sample. The prediction abilities were relatively high, varying from 0.54 (yield) to 0.92 (grain length). We concluded that the current population of 1495 hybrids can be used to predict hybrids from seemingly unrelated parents. Eventually, we used this training population to predict all potential hybrids of cytoplasm male sterile lines from 3000 rice varieties from the 3K Rice Genome Project. Using a breeding index combining 10 traits, we identified the top and bottom 200 predicted hybrids. SNP genotypes of the training population and parameters estimated from this training population are available for general uses and further validation in genomic hybrid prediction of all potential hybrids generated from all varieties of rice.
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Hibridização Genética , Oryza/genética , Melhoramento Vegetal , Produtos Agrícolas/genética , Genoma de Planta , Genômica , Modelos Genéticos , Polimorfismo de Nucleotídeo ÚnicoRESUMO
KEY MESSAGE: The "Green Super Rice" (GSR) project aims to fundamentally transform crop production techniques and promote the development of green agriculture based on functional genomics and breeding of GSR varieties by whole-genome breeding platforms. Rice (Oryza sativa L.) is one of the leading food crops of the world, and the safe production of rice plays a central role in ensuring food security. However, the conflicts between rice production and environmental resources are becoming increasingly acute. For this reason, scientists in China have proposed the concept of Green Super Rice for promoting resource-saving and environment-friendly rice production, while still achieving a yield increase and quality improvement. GSR is becoming one of the major goals for agricultural research and crop improvement worldwide, which aims to mine and use vital genes associated with superior agronomic traits such as high yield, good quality, nutrient efficiency, and resistance against insects and stresses; establish genomic breeding platforms to breed and apply GSR; and set up resource-saving and environment-friendly cultivation management systems. GSR has been introduced into eight African and eight Asian countries and has contributed significantly to rice cultivation and food security in these countries. This article mainly describes the GSR concept and recent research progress, as well as the significant achievements in GSR breeding and its application.
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Genoma de Planta , Oryza/classificação , Oryza/genética , Melhoramento Vegetal/normas , Plantas Geneticamente Modificadas/genética , Locos de Características Quantitativas , África , Ásia , Oryza/crescimento & desenvolvimento , Fenótipo , Plantas Geneticamente Modificadas/crescimento & desenvolvimentoRESUMO
The article Genomic Breeding of Green Super Rice Varieties and Their Deployment in Asia and Africa.
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Improving the performance of rice (Oryza sativa) under drought stress has the potential to significantly affect rice productivity. Here, we report that the ERF family transcription factor OsLG3 positively regulates drought tolerance in rice. In our previous work, we found that OsLG3 has a positive effect on rice grain length without affecting grain quality. In this study, we found that OsLG3 was more strongly expressed in upland rice than in lowland rice under drought stress conditions. By performing candidate gene association analysis, we found that natural variation in the promoter of OsLG3 is associated with tolerance to osmotic stress in germinating rice seeds. Overexpression of OsLG3 significantly improved the tolerance of rice plants to simulated drought, whereas suppression of OsLG3 resulted in greater susceptibility. Phylogenetic analysis indicated that the tolerant allele of OsLG3 may improve drought tolerance in cultivated japonica rice. Introgression lines and complementation transgenic lines containing the elite allele of OsLG3IRAT109 showed increased drought tolerance, demonstrating that natural variation in OsLG3 contributes to drought tolerance in rice. Further investigation suggested that OsLG3 plays a positive role in drought stress tolerance in rice by inducing reactive oxygen species scavenging. Collectively, our findings reveal that natural variation in OsLG3 contributes to rice drought tolerance and that the elite allele of OsLG3 is a promising genetic resource for the development of drought-tolerant rice varieties.
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Adaptação Fisiológica/genética , Secas , Variação Genética , Oryza/genética , Proteínas de Plantas/genética , Espécies Reativas de Oxigênio/metabolismo , Alelos , Regulação da Expressão Gênica de Plantas , Genótipo , Oryza/metabolismo , Pressão Osmótica , Filogenia , Proteínas de Plantas/classificação , Proteínas de Plantas/metabolismo , Plantas Geneticamente Modificadas , Regiões Promotoras Genéticas/genética , Sementes/genética , Sementes/metabolismo , Estresse FisiológicoRESUMO
The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC1F5 introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (â»N), minus phosphorus (â»P), (â»NP), minus nitrogen phosphorus and potassium (â»NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under â»P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.
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Cruzamentos Genéticos , Genética Populacional , Fenômenos Fisiológicos da Nutrição , Oryza/genética , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Característica Quantitativa Herdável , Análise de Variância , Variação Biológica da População , Oryza/metabolismo , FenótipoRESUMO
In the coming decades, rice production needs to be carried out sustainably to keep the balance between profitability margins and essential resource input costs. Many fertilizers, such as N, depend primarily on fossil fuels, whereas P comes from rock phosphates. How long these reserves will last and sustain agriculture remains to be seen. Therefore, current agricultural food production under such conditions remains an enormous and colossal challenge. Researchers have been trying to identify nutrient use-efficient varieties over the past few decades with limited success. The concept of nutrient use efficiency is being revisited to understand the molecular genetic basis, while much of it is not entirely understood yet. However, significant achievements have recently been observed at the molecular level in nitrogen and phosphorus use efficiency. Breeding teams are trying to incorporate these valuable QTLs and genes into their rice breeding programs. In this review, we seek to identify the achievements and the progress made so far in the fields of genetics, molecular breeding and biotechnology, especially for nutrient use efficiency in rice.
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Grão Comestível/genética , Oryza/genética , Melhoramento Vegetal/métodos , Grão Comestível/crescimento & desenvolvimento , Grão Comestível/metabolismo , Grão Comestível/normas , Nitrogênio/metabolismo , Oryza/crescimento & desenvolvimento , Oryza/metabolismo , Fósforo/metabolismo , Locos de Características QuantitativasRESUMO
Drought is one of the major abiotic stresses that directly implicate plant growth and crop productivity. Although many genes in response to drought stress have been identified, genetic improvement to drought resistance especially in food crops is showing relatively slow progress worldwide. Here, we reported the isolation of abscisic acid, stress and ripening (ASR) genes from upland rice variety, IRAT109 (Oryza sativa L. ssp. japonica), and demonstrated that overexpression of OsASR5 enhanced osmotic tolerance in Escherichia coli and drought tolerance in Arabidopsis and rice by regulating leaf water status under drought stress conditions. Moreover, overexpression of OsASR5 in rice increased endogenous ABA level and showed hypersensitive to exogenous ABA treatment at both germination and postgermination stages. The production of H2 O2 , a second messenger for the induction of stomatal closure in response to ABA, was activated in overexpression plants under drought stress conditions, consequently, increased stomatal closure and decreased stomatal conductance. In contrast, the loss-of-function mutant, osasr5, showed sensitivity to drought stress with lower relative water content under drought stress conditions. Further studies demonstrated that OsASR5 functioned as chaperone-like protein and interacted with stress-related HSP40 and 2OG-Fe (II) oxygenase domain containing proteins in yeast and plants. Taken together, we suggest that OsASR5 plays multiple roles in response to drought stress by regulating ABA biosynthesis, promoting stomatal closure, as well as acting as chaperone-like protein that possibly prevents drought stress-related proteins from inactivation.
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Arabidopsis/metabolismo , Secas , Peróxido de Hidrogênio/metabolismo , Oryza/metabolismo , Proteínas de Plantas/genética , Estômatos de Plantas/metabolismo , Estresse Fisiológico/fisiologia , Ácido Abscísico/metabolismo , Ácido Abscísico/farmacologia , Arabidopsis/enzimologia , Arabidopsis/genética , Escherichia coli/genética , Genes de Plantas , Germinação , Proteínas de Choque Térmico HSP40/genética , Proteínas de Choque Térmico HSP40/metabolismo , Mutação , Oryza/enzimologia , Oryza/genética , Proteínas de Plantas/metabolismo , Plantas Geneticamente Modificadas , Estresse Fisiológico/genética , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Água/metabolismoRESUMO
BACKGROUND: Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is a devastating rice disease worldwide. Xa39 is a resistance (R) gene with a broad-spectrum hypersensitive response (BSHR) to Xoo. Nevertheless, the molecular mechanisms of resistance mediated by Xa39 remain unclear. In this study, the transcriptome profiling of a rice line carrying Xa39 and its parents at the early stage of Xoo infection were investigated. RESULTS: A rice introgression line H471 carrying Xa39 exhibited a typical local hypersensitive response phenotype, accompanied by programmed cell death after inoculation with the Xoo Philippines' race 9b. Transcriptome profiling of H471 and its parents at 1 and 2 days post-inoculation was performed using RNA sequencing. In total, 306 differentially expressed genes (DEGs) were identified in H471 compared with its recurrent parent Huang-Hua-Zhan after inoculation with Xoo. Among them, 121 (39.5%) genes, with functional enrichments that were related to defense response, protein amino acid phosphorylation, and apoptosis, were found to be constitutively expressed. The other 185 (60.5%) genes, with GO terms that belonged to defense response, were significantly responsive to Xoo infection in H471. Ten up-regulated and 12 down-regulated genes encoding intracellular immune receptors were identified in H471 compared with Huang-Hua-Zhan. LOC_Os11g37759, which was located in the fine-mapping region harboring Xa39, is a Xa39 candidate gene. The putative BSHR-related co-regulatory networks were constructed using 33 DEGs from four functional groups, including gibberellic acid receptors and brassinosteroid regulators, which were differentially co-expressed with LOC_Os11g37759 in infected H471. Our results indicated that there might be cross-talk between the Xa39-mediated signal transduction cascades and the GA/BR signaling pathway, and that the defense mechanism was related to diverse kinases, transcription factors, post-translational regulation, and R genes. CONCLUSIONS: The present study provides the comprehensive transcriptome profile of a rice introgression line carrying Xa39 and its parents, and identifies a set of DEGs involved in BSHR mediated by Xa39. These data provide novel insights into the regulatory networks of plant disease resistance mediated by R genes, and the identified DEGs will serve as candidates for Xa39 cloning and for further understanding the molecular mechanism of BSHR.
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Perfilação da Expressão Gênica , Oryza/microbiologia , Transcriptoma/genética , Xanthomonas/genética , Resistência à Doença/genética , Regulação da Expressão Gênica de Plantas , Redes Reguladoras de Genes , Análise de Sequência com Séries de Oligonucleotídeos , Oryza/genética , Doenças das Plantas/microbiologia , Proteínas de Plantas/biossíntese , Proteínas de Plantas/genética , Transdução de Sinais , Xanthomonas/patogenicidadeRESUMO
Crop improvement and production domains encounter large amounts of expanding data with multi-layer complexity that forces researchers to use machine-learning approaches to establish predictive and informative models to understand the sophisticated mechanisms underlying these processes. All machine-learning approaches aim to fit models to target data; nevertheless, it should be noted that a wide range of specialized methods might initially appear confusing. The principal objective of this study is to offer researchers an explicit introduction to some of the essential machine-learning approaches and their applications, comprising the most modern and utilized methods that have gained widespread adoption in crop improvement or similar domains. This article explicitly explains how different machine-learning methods could be applied for given agricultural data, highlights newly emerging techniques for machine-learning users, and lays out technical strategies for agri/crop research practitioners and researchers.
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Contamination of paddy soils with arsenic (As) can cause phytotoxicity in rice and increase the accumulation of arsenic in grains. The uptake and accumulation of As in rice depends on the different As species present in the soil. Plants detoxify As by conjugating and sequestering xenobiotic compounds into vacuoles using various enzymes. However, the severity of damage induced by arsenite (As(III)) and arsenate (As(V)), as well as the roles of glutathione S-transferase in detoxifying these As species in rice, are not fully understood. In this study, we developed plant materials overexpressing a glutathione S-transferase gene OsGSTU40 under the control of the maize UBIL promoter. Through systematic investigations of both wild-type Nipponbare (Oryza sativa L., ssp. japonica) and OsGSTU40 overexpression lines under chronic or acute stress of As, we aimed to understand the toxic effects of both As(III) and As(V) on rice plants at the vegetative growth stage. We hypothesized that (i) As(III) and As(V) have different toxic effects on rice plants and (ii) OsGSTU40 played positive roles in As toxicity tolerance. Our results showed that As(III) was more detrimental to plant growth than As(V) in terms of plant growth, biomass, and lipid peroxidation in both chronic and acute exposure. Furthermore, overexpression of OsGSTU40 led to better plant growth even though uptake of As(V), but not As(III), into shoots was enhanced in transgenic plants. In acute As(III) stress, transgenic plants exhibited a lower level of lipid peroxidation than wild-type plants. The element composition of plants was dominated by the different As stress treatments rather than by the genotype, while the As concentration was negatively correlated with phosphorus and silicon. Overall, our findings suggest that As(III) is more toxic to plants than As(V) and that glutathione S-transferase OsGSTU40 differentially affects plant reactions and tolerance to different species of arsenic.
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Arsênio , Arsenitos , Oryza , Arseniatos/toxicidade , Arseniatos/metabolismo , Arsênio/toxicidade , Arsenitos/toxicidade , Arsenitos/metabolismo , Glutationa Transferase/genética , Glutationa Transferase/metabolismo , Plantas Geneticamente Modificadas/genética , Expressão Gênica , Raízes de Plantas/metabolismoRESUMO
The productivity of rice is greatly affected by the infection of the plant pathogenic fungus Rhizoctonia solani, which causes a significant grain yield reduction globally. There exist a limited number of rice accessions that are available to develop sheath blight resistance (ShB). Our objective was to identify a good source of the ShB resistance, understand the heritability, and trait interactions, and identify the genomic regions for ShB resistance traits by genome-wide association studies (GWAS). In the present study, a set of 330 traditional landraces and improved rice varieties were evaluated for ShB resistance and created a core panel of 192 accessions used in the GWAS. This panel provides a more considerable amount of genetic variance and found a significant phenotypic variation among the panel of rice accessions for all the agro-morphological and disease-resistance traits over the seasons. The infection rate of ShB and disease reaction were calculated as percent disease index (PDI) and area under the disease progress curve (AUDPC). The correlation analysis showed a significant positive association between PDIs and AUPDC and a negative association between PDI and plant height, flag leaf length, and grain yield. The panel was genotyped with 133 SSR microsatellite markers, resulting in a genome coverage of 314.83 Mb, and the average distance between markers is 2.53 Mb. By employing GLM and MLM (Q + K) models, 30 marker-trait associations (MTAs) were identified with targeted traits over the seasons. Among these QTLs, eight were found to be novel and located on 2, 4, 8, 10, and 12 chromosomes, which explained the phenotypic variation ranging from 5% to 15%. With the GWAS approach, six candidate genes were identified. Os05t0566400, Os08t0155900, and Os09t0567300 were found to be associated with defense mechanisms against ShB. These findings provided insights into the novel donors of IC283139, IC 277248, Sivappuchithirai Kar, and Bowalia. The promising genomic regions on 10 of 12 chromosomes associated with ShB would be useful in developing rice varieties with durable disease resistance.
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Introduction: Drought and submergence are contrasting abiotic stresses that often occur in the same rice crop season and cause complete crop failure in many rain-fed lowland areas of Asia. Methods: To develop rice varieties with good tolerances to drought and submergence, 260 introgression lines (ILs) selected for drought tolerance (DT) from nine BC2 populations were screened for submergence tolerance (ST), resulting in 124 ILs with significantly improved ST. Results: Genetic characterization of the 260 ILs with DNA markers identified 59 DT quantitative trait loci (QTLs) and 68 ST QTLs with an average 55% of the identified QTLs associated with both DT and ST. Approximately 50% of the DT QTLs showed 'epigenetic' segregation with very high donor introgression and/or loss of heterozygosity (LOH). Detailed comparison of the ST QTLs identified in ILs selected only for ST with ST QTLs detected in the DT-ST selected ILs of the same populations revealed three groups of QTLs underlying the relationship between DT and ST in rice: a) QTLs with pleiotropic effects on both DT and ST; b) QTLs with opposite effects on DT and ST; and c) QTLs with independent effects on DT and ST. Combined evidence identified most likely candidate genes for eight major QTLs affecting both DT and ST. Moreover, group b QTLs were involved in the Sub1regulated pathway that were negatively associated with most group aQTLs. Discussion: These results were consistent with the current knowledge that DT and ST in rice are controlled by complex cross-talks between or among different phytohormone-mediated signaling pathways. Again, the results demonstrated that the strategy of selective introgression was powerful and efficient for simultaneous improvement and genetic dissection of multiple complex traits, including DT and ST.
RESUMO
Introduction: Sheath blight caused by Rhizoctonia solani is one of the major diseases of rice, causing widespread crop losses. The use of semi-dwarf rice varieties in the ongoing nutrient-intensive rice cultivation system has further accentuated the incidence of the disease. An ideal solution to this problem would be identifying a stable sheath blight-tolerant genotype. Material and methods: A multi-environment evaluation of 32 rice genotypes against sheath blight infection was conducted over six seasons across two locations (Agricultural Research Farm, Institute of Agricultural Sciences, Banaras Hindu University (28.18° N, 38.03° E, and 75.5 masl), for four years during the wet seasons (kharif) from 2015 to 2018 and two seasons at the National Rice Research Institute (20°27'09" N, 85°55'57" E, 26 masl), Cuttack, Odisha, during the dry season (rabi) of 2019 and the kharif of 2019, including susceptible and resistant check. Percent disease index data were collected over 4 weeks (on the 7th, 14th, 21st, and 28th day after infection), along with data on other morphological and physiological traits. Result and discussion: The resistant genotypes across seasons were the ones with a higher hemicellulose content (13.93-14.64) and lower nitrogen content (1.10- 1.31) compared with the susceptible check Tapaswini (G32) (hemicellulose 12.96, nitrogen 1.38), which might explain the resistant reaction. Three different stability models-additive main effect and multiplicative interaction (AMMI), genotype + genotype x environment (GGE) biplot, and multi-trait stability index (MTSI)-were then used to identify the stable resistant genotypes across six seasons. The results obtained with all three models had common genotypes highlighted as stable and having a low area under the disease progress curve (AUDPC) values. The ideal stable genotypes with low disease incidence were IC 283139 (G19), Tetep (G28), IC 260917 (G4), and IC 277274 (G10), with AUDPC values of 658.91, 607.46, 479.69, and 547.94, respectively. Weather parameters such as temperature, rainfall, sunshine hours, and relative humidity were also noted daily. Relative humidity was positively correlated with the percent disease index.