Rice Species Research Articles

Evolutionary Dynamics and Expression Divergence of the MADS-Box Gene Family During Recent Speciation of AA-Genome Oryza Species

To investigate the evolutionary trajectory during the recent speciation of AA-genome Oryza species, we conducted a comprehensive analysis of the MADS-box gene family across eight Oryza species. We identified 1093 MADS-box genes in total and systematically examined their evolutionary history, gene family expansion, and expression divergence. Our results revealed that extensive lineage-specific expansions occurred in AA-genome Oryza species, which were primarily generated by proximal and tandem duplications, with a particularly notable episode in Type-I genes. Despite the significant expansion, Type-I genes were generally expressed at low levels or not expressed across various organs. In contrast, the expansion of Type-II genes was primarily observed in the AG, AGL12, SOC1, GGM13, and MIKC* subfamilies, which exhibited high levels of expression in reproductive organs such as panicles and stigmas. Additionally, we found species-specific gene expression in the two out-crossing wild rice species, Oryza rufipogon and Oryza longistaminata. Notably, a unique MADS-box gene in O. longistaminata exhibited high expression levels in rhizomes and stems, which may be associated with the species’ distinctive rhizomatous growth habit.

The genomes of the most diverse AA genome rice species provide a resource for rice improvement and studies of rice evolution and domestication

Rice (Oryza sativa) is a staple food crop globally, with origins in wild progenitors within the AA genome group of Oryza species. Oryza rufipogon and Oryza meridionalis are native to tropical Asia and Northern Australia and offer unique genetic reservoirs. Here we explored the relationships of the genomes of these wild rice species with the domesticated rice genome. We utilized long read sequencing (PacBio HiFi) and chromatin mapping (Hi-C) to produce de novo chromosomal level genomes of Oryza meridionalis, the most divergent AA gnome species, and the unique Australian Oryza rufipogon like taxon that is a sister to the clade of domesticated and wild AA genome rice species of Asia and Africa. Comparative genomic analyses were conducted to identify structural variations and syntenic relationships between these wild taxa and the domesticated rice variety Nipponbare. The genome assemblies of the wild rice species achieved high completeness and contiguity, revealing the shared and unique genes in each species. Both wild species uniquely shared some genes with domesticated rice many of which were associated with disease resistance and stress tolerance. Structural differences included the large 6 Mb inversion on chromosome 6 specific to Japonica rice. Functional annotation highlighted conserved biological functions and novel genes unique to the wild taxa. These findings provide a deeper understanding of rice domestication and highlight the genetic contributions of wild species to enhancing the genetic diversity and ecological adaptability of modern rice varieties. Our study emphasizes the importance of conserving wild rice populations as genetic resources for breeding and adaptation in changing environments.

Genetic resource utilization in wild rice species: Genomes and gene bank

Genetic resource utilization in wild rice species: Genomes and gene bank

Application of Automated Machine Learning and Bagging Techniques to Classify Rice Varieties

We have witnessed increased research investigating digitalisation in the agricultural sector in recent years. In particular, machine learning and artificial intelligence find applications in agricultural product classification, quality control and species identification. The fast-processing times, high accuracy levels and cost-effectiveness offered by digital solutions for quality control and classification accelerate these studies. This study proposes a collaborative learning model utilising Automated Machine Learning and Bagging techniques for rice species detection and classification. The model uses a dataset from the UCI Irvine Machine Learning Repository, which contains characteristics specific to the Osmancık and Cammeo rice varieties grown in Turkey. The data set consists of 3810 data points, 2180 of which belong to Osmancık rice and 1630 to Cammeo rice. During the analysis, MLBox, an Automated Machine Learning library, was used to determine the optimal algorithm (Light Gradient Boosting Machine - LGBM) and its hyperparameters. Later, by applying the Bagging technique within the developed learning model, an accuracy rate of 93.54% was achieved in rice-type classification.

Endophytic Bacterial Communities in Wild Rice (Oryza eichingeri) and Their Effects on Cultivated Rice Growth

Endophytic bacteria play crucial roles in plant pathogen protection and growth. Oryza eichingeri is a unique wild rice species rich with genetic resources. Studies have explored beneficial endophytic bacteria and investigated the synergistic interaction between microbes and wild rice. However, the endophytic bacterial community of Oryza eichingeri and their plant growth-promoting (PGP) abilities characteristics remain largely unknown. Here, endophytic bacteria in the root, stem, and leaf tissues of Oryza eichingeri were characterized using metagenomic Illumina 16S rRNA gene sequencing. Additionally, culturable endophytic bacteria were isolated. The metagenomic analysis showed that, compared to those in other tissue compartments, the endophytic bacterial community in the roots had a more complex structure and enhanced functions, and each compartment had its own specific endophytic bacterial biomarkers. A total of 94 endophytic bacteria were isolated from Oryza eichingeri, among which 80 strains possessed PGP traits including increasing phosphate solubilization, siderophore production, IAA production, and nitrogen fixation. These strains displayed good PGP effects on cultivated rice seedlings, promoting the formation of strong root systems, stimulating biomass accumulation, and increasing root length and plant height. These findings provide insights into the composition of the bacterial endosphere of Oryza eichingeri and potential applications of the dominant PGP bacteria in rice cultivation.

Identification of novel sources of bacterial leaf blight resistance in wild species of rice

Identification of novel sources of bacterial leaf blight resistance in wild species of rice

GRAS-Di analysis on recombinant inbred lines derived from the cross between Asian cultivated and wild rice species suitable for agronomic evaluation in high-latitude areas

GRAS-Di analysis on recombinant inbred lines derived from the cross between Asian cultivated and wild rice species suitable for agronomic evaluation in high-latitude areas

Structural characterization and proteomic profiling of oviposition secretions across three rice planthopper species

Insect oviposition secretions play crucial roles during the reproductive process, yet systematic studies on their structural characterization and protein compositions remain limited. This study investigated the oviposition secretions of three major rice pests: the brown planthopper (Nilaparvata lugens, BPH), small brown planthopper (Laodelphax striatella, SBPH), and white-backed planthopper (Sogatella furcifera, WBPH). Ultrastructural observation revealed differences in the oviposition secretions of them. The eggs of BPH and SBPH were adhered to rice tissue by abundant secretions, while WBPH eggs were embedded deeper within the leaf sheath with less secretions. Proteomic analysis identified 111, 98, and 66 oviposition secretion proteins (OSPs) in BPH, SBPH, and WBPH, respectively. 4 common protein subgroups were shared among them, along with varying numbers of shared subgroups between species pairs. Notably, the majority of OSPs were exclusively found in one species, indicating the existence of both similar and specialized functions unique to each planthopper species. The functions of 4 uncharacterized OSPs (Nl.chr07.0363, Nl.chr12.078, Nl.chr11.716, Nl.scaffold.0714) that were uniquely identified in the BPH were studied by maternal RNAi. Downregulation of each of these 4 protein-coding genes led to a significant decrease in egg production and hatchability. Moreover, knockdown of Nl.chr12.078 or Nl.chr07.0363 also disrupt the secretory function of the lateral oviduct. In conclusion, this study provides insights into the structural characteristics and protein components of the oviposition secretions of BPH, SBPH, and WBPH, which could serve as potential targets for RNAi-based pest control and lay a foundation for future studies on insect-plant interactions mediated by oviposition secretions.

Deciphering Codon Usage Patterns in the Mitochondrial Genome of the Oryza Species

Rice (Oryza) is a genus in the Gramineae family, which has grown widely all over the world and is a staple food source for people’s survival. The genetic information of rice has garnered significant attention in recent years, prompting numerous researchers to conduct extensive investigations in this field. But rice mitochondrial codon usage patterns have received little attention. The present study systematically analyzed the codon usage patterns and sources of variance in the mitochondrial genome sequences of five rice species by the CodonW and R software programs. Our results revealed that the GC content of codons in rice mitochondrial genome genes was determined to be 43.60%. Notably, the individual codon positions exhibited distinct GC contents: 48.00% for position 1, 42.65% for position 2, and 40.16% for position 3. These findings suggest the preference of the rice mitochondrial genome for codons ending in A or U. A weak codon bias was observed, with the effective number of codons (ENC) varying between 40.02 and 61.00, with an average value of 54.34. Subsequently, we identified 25 identical high-frequency codons in five rice mitochondrial genomes, with 11 codons ending in A and 12 codons ending in U. The regression lines in the neutrality plot exhibited slopes of less than 0.5 in five rice species, indicating a predominant role of natural selection, while mutation pressure remained relatively insignificant. In the PR2-plot analysis, most of the genes were located in the right half of the plot, indicating that the third base of the synonymous codon was preferred to end in G than C. Additionally, the ENC plot and ENC ratio analysis unveiled that codon preferences in the rice mitochondrial genome were predominantly influenced by natural selection rather than mutational pressure. The analysis of correspondence revealed distinct variations in the codon usage pattern across five rice mitochondrial genomes. Based on the RSCU values of species, a cluster tree was inconsistent with the mitochondrial genetic data, indicating that RSCU data could not be used as a basis for classification at the species level in the Oryza genus. These results will help decide the specific types of natural selection pressures influencing codon usage and improve the expression of exogenous genes in rice mitochondrial genomes by optimizing their codons.

Genome evolution and diversity of wild and cultivated rice species

Wild species of crops serve as a valuable germplasm resource for breeding of modern cultivars. Rice (Oryza sativa L.) is a vital global staple food. However, research on genome evolution and diversity of wild rice species remains limited. Here, we present nearly complete genomes of 13 representative wild rice species. By integrating with four previously published genomes for pangenome analysis, a total of 101,723 gene families are identified across the genus, including 9834 (9.67%) core gene families. Additionally, 63,881 gene families absent in cultivated rice species but present in wild rice species are discovered. Extensive structural rearrangements, sub-genomes exchanges, widespread allelic variations, and regulatory sequence variations are observed in wild rice species. Interestingly, expanded but less diverse disease resistance genes in the genomes of cultivated rice, likely due to the loss of some resistance genes and the fixing and amplification of genes encoding resistance genes to specific diseases during domestication and artificial selection. This study not only reveals natural variations valuable for gene-level studies and breeding selection but also enhances our understanding on rice evolution and domestication.

Impact of tillage methods and cultivars on phenology & productivity of wheat-rice system under irrigated conditions

The research was conducted at the Agricultural Research farm of the Agronomy Department at Palampur, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya (CSK HPKV) and Rice and Wheat Research Center (RWRC) Malan, Himachal Pradesh to study the impact of tillage methods & crop species on phenology & production of wheat-rice crops under irrigated conditions. The study's basic premise was to identify wheat and rice cultivars that can perform well under specific tillage options. The trial was conducted from the winter 2019 to the rainy season of 2021, using a split-plot design. Four tillage methods- zero tillage, conventional tillage, natural farming and reduced tillage- were tested on three species of rice (HPR 2656 (Him Palam Dhan 1), HPR 2795 (Him Palam Dhan Lal 1) & HPR 1156 (Sukara Dhan Lal 1) and three species of wheat (HPW 368 (Him Palam Gehun 2), HS 562 (Central Dwarf wheat) & HPW 349). The results showed that in both crops, traditional farming (conventional tillage) methods were more efficient than other methods in terms of crop yield.Conversely, the lowest grain yields were observed with natural farming for both crops. Specifically, the adoption of zero tillage, natural agriculture, and reduced tillage results in wheat grain yield reductions of 10.9%, 4.6%, and 59.4%, respectively, compared to conventional tillage. Similarly, rice grain yields declined by 10.8%, 34.0%, and 16.1% with zero tillage, natural farming, and reduced tillage, respectively, compared to conventional tillage. Among the cultivars evaluated, HPW 368 for wheat and HPR 2795 for rice produced significantly higher grain yields at both locations over the two years. The findings of the present investigation would help the wheat and rice growers identify suitable cultivars that would be economically grown with varying tillage options and under natural farming conditions.

Physical and biochemical characteristics of cereal grains affect population growth parameters of Sitophilus oryzae (L.) (Coleoptera: Curculionidae)

The rice weevil, Sitophilus oryzae L. (Coleoptera: Curculionidae), is a significant pest of rice and other cereal grains. In this research, the effects of various grain species, including barley, maize, millet, rice, sorghum, and wheat, were assessed on biological properties and life history variables of S. oryzae under laboratory conditions. Data were analyzed based on the age-stage, two-sex life table method. Furthermore, various physicochemical properties of cereal grains, including protein content, starch content, humidity content, and seed hardness, were investigated to explore their correlation with the studied parameters of S. oryzae. The longest development time was observed on millet and sorghum hosts, while the shortest was on maize seed. The beetles reared on rice and millet species showed the maximum fecundity, whereas those reared on sorghum and millet grains showed the lowest. Maize grain had the highest intrinsic rate of increase (r), whereas millet and sorghum grains had the lowest. According to the correlation analysis, overall, seed protein content was negatively correlated with insect fecundity, R0 and r, but positively correlated with development time. Furthermore, starch content was positively correlated with insect fecundity, R0 and r, and negatively correlated with development time. The cluster results demonstrated that whereas sorghum and millet were comparatively resistant hosts for the growth of S. oryzae, maize and rice were relatively susceptible seeds. This information can be helpful in the development or improvement of integrated pest management (IPM) strategies against rice weevil. The findings of this research will also be helpful in introducing unsuitable hosts for the development of transgenic grains resistant to S. oryzae. The pest-resistant cereal grains identified in this study can potentially be utilized in combination with other pest control strategies for sustainable management of S. oryzae, which may help reduce the excessive use of chemical insecticides.

Reexploring Rice Germplasm: Enlightening a New Path Towards Abiotic Stress-resilient Crop

Oryza sativa, the commonly cultivated rice, is one of the most important crops for human consumption, but is also a crop whose production system is increasingly threatened by the current climate changes. Due to its intensive water requirement rice faces a lot of challenges due to abiotic stresses like drought, heat stress, salinity, flooding etc. Drought is the major abiotic stress to rice grain production under unpredictable and changing environmental conditions. Traits supporting drought resistance are limited in cultivars, while wild rice species like O. glaberrima, O. longistaminata, O. rufipogon and O. meridonalis represent an important reservoir of useful genes for this trait which can be exploited to develop varieties tolerant to drought. Similarly O. australiensis, O. coarctata and O. rufipogon serve as an important sources for salinity-tolerant genes. O. rufipogon, O. meridonalis, O. australiensis comprise a collection of accessions that are reservoirs for heat-tolerant genes. Although many efforts have resulted in breeding rice varieties that are relatively tolerant to their local environments; climate change and population growth are expected to soon require a new, rapid generation of stress-tolerant rice germplasm. Diversity studies suggest that the current diversity within rice varieties may not be sufficient for generation of highly resistant or tolerant varieties for the unfavorable growing conditions. All the efforts to design an ideotype to increase production and productivity has been attempted previously, rice self-sufficiency can be attained only if high production and productivity is coupled with a high degree of tolerance and resistance to biotic and abiotic stress factors. Since it has been found that wild rice relatives serve as a hub for many desirable genes conferring tolerance or resistance to specific stresses, the present article is focused on provide an overview of different wild ancestors of rice which can be exploited to identify suitable donors for gene of interest, their ecological and genomic diversity and the variation observed in wild Oryza species for different stress tolerance traits. Such identified traits can be incorporated in modern day breeding programmes through marker assisted breeding to develop cultivable varieties with desired tolerance to abiotic stresses or transfer such traits to modern day cultivars through backcross breeding.

Mechanism of betterment towards growth and induction of defense in rice (Oryza sativa L.) by biopriming with bacterial endophytes isolated from wild rice

Utilizing beneficial microorganisms associated with plants, particularly endophytes, is becoming more and more prevalent since it supports the physiological health and evolutionary adaption of the host. The range of enhanced endophytic bacteria found in wild rice makes it a promising resource for sustainable agriculture. Current study focused on benefits of bacterial endophytes isolated from tissues of wild rice plants' roots, stems, and leaves for managing the health and development of rice (Oryza sativa L.) plants. Bacterial endophytes were characterized using 16 S rRNA. Treatments with Priestia megaterium (NRRI EB 1) and Priestia aryabhattai (NRRI EB 2) outperformed the other isolates in rice growth enhancement activities significantly. The biocontrol efficacy of bacterial endophytes was tested against Xanthomonas oryzae pv. oryzae and Rhizoctonia solani and percentage of inhibition was higher in NRRI EB 1 by 79.32–80.83 % and in NRRI EB 2 by 79.69–80.45 %. Bio-priming the seeds with specific endophytic bacterial strains led to a decrease in average germination time, an increase in seedling vigor, and total chlorophyll content. Additionally, they generated greater amounts of soluble phosphate (40.91–83.70 μg/mL) and indole acetic acid (28.10–60.18 μg/mL), which are in the midst of encouraging more plant development. Higher expressions of defense enzymes in comparison to the control, including catalase (>220 % in root and shoot), peroxidase (>200 % in shoot and root), and superoxide dismutase (>150 % in shoot and root) illustrates the rice crop's resilience to withstand stress. The activity of the mentioned enzymes was further validated through the activation of corresponding defense genes such as DEFENSIN (>2-fold), PAL (>3-fold), PR-3 (>2-fold), POX (>2-fold) and LOX (>1-fold) in relation to the untreated plants. The possibility exists to extract advantageous endophytic bacteria from wild rice species, potentially rewilding the microbiome of cultivated rice cultivars and fostering their deployment.

Evolutionary Systems Biology Identifies Genetic Trade-offs In Rice Defense Against Above- and Belowground Attackers.

Like other plants, wild and domesticated rice species (Oryza nivara, O. rufipogon, and O. sativa) evolve in environments with various biotic and abiotic stresses that fluctuate in intensity through space and time. Microbial pathogens and invertebrate herbivores such as plant-parasitic nematodes and caterpillars show geographical and temporal variation in activity patterns and may respond differently to certain plant defensive mechanisms. As such, plant interactions with multiple community members may result in conflicting selection pressures on genetic polymorphisms. Here, through assays with different above- and belowground herbivores, the fall armyworm (Spodoptera frugiperda) and the southern root-knot nematode (Meloidogyne incognita), respectively, and comparison with rice responses to microbial pathogens, we identify potential genetic trade-offs at the KSL8 and MG1 loci on chromosome 11. KSL8 encodes the first committed step towards biosynthesis of either stemarane- or stemodane-type diterpenoids through the japonica (KSL8-jap) or indica (KSL8-ind) allele. Knocking out KSL8-jap and CPS4, encoding an enzyme that acts upstream in diterpenoid synthesis, in japonica rice cultivars increased resistance to S. frugiperda and decreased resistance to M. incognita. Furthermore, MG1 resides in a haplotype that provided resistance to M. incognita, while alternative haplotypes are involved in mediating resistance to the rice blast fungus Magnaporthe oryzae and other pests and pathogens. Finally, KSL8 and MG1 alleles are located within trans-species haplotypes and may be evolving under long-term balancing selection. Our data are consistent with a hypothesis that polymorphisms at KSL8 and MG1 may be maintained through complex and diffuse community interactions.

A proposed plant classification framework for smart agricultural applications using UAV images and artificial intelligence techniques

Utilizing Wireless Sensor Networks (WSNs), Internet of Things (IoTs) sensors, and Unmanned Aerial Vehicles (UAVs), in conjunction with optimization techniques and machine learning algorithms, can present a novel approach to Precision Agricultural (PA) crops. Agriculture has transitioned from traditional legacy systems to incorporate advanced smart technologies. Several complex farming problems are utilized to promote a variety of UAV sensing and Artificial Intelligence (AI) algorithms in PA applications of smart agriculture, especially in developing countries. This paper proposes the design of a conceptual UAV sensing system for crop management using a novel classification framework. UAV-based image datasets can be implemented and expanded to various types of crops. In addition, it can classify various types of rice species and detect weed farms as it consists of a multistage process for identifying and monitoring different crops. The proposed classification framework is evaluated using three different real UAV image datasets compared with Naive Bayes, Decision Tree (DT), Bagging, and Random Forest (RF) techniques. The classification performance metrics obtained are as follows: i) the WeedNet dataset with 100 % F1-score, 100 % recall, 100 % precision, and 100 % accuracy; ii) the Rice Seedling dataset with 99.5 % F1-score, 99.5 % recall, 99.5 % precision, and 99.5 % accuracy; and iii) the Rice Varieties dataset with 97.99 % F1-score, 97.99 % recall, 98.14 % precision, and 97.99 % accuracy. The success rates achieved by the proposed classification framework outperform those of other recent state-of-the-art techniques, demonstrating its efficacy in crop management applications.

Recognition of Rice Species Based on Gas Chromatography-Ion Mobility Spectrometry and Deep Learning

To address the challenge of relying on complex biochemical methods for identifying rice species, a prediction model that combines gas chromatography-ion mobility spectroscopy (GC-IMS) with a convolutional neural network (CNN) was developed. The model utilizes the GC-IMS fingerprint data of each rice variety sample, and an improved CNN structure is employed to increase the recognition accuracy. First, an improved generative adversarial network based on the diffusion model (DGAN) is used for data enhancement to expand the dataset size. Then, on the basis of a residual network called ResNet50, a transfer learning method is introduced to improve the training effect of the model under the condition of a small sample. In addition, a new attention mechanism called Triplet is introduced to further highlight useful features and improve the feature extraction performance of the model. Finally, to reduce the number of model parameters and improve the efficiency of the model, a method called knowledge distillation is used to compress the model. The results of our experiments revealed that the recognition accuracy for identifying the 10 rice varieties was close to 96%; hence, the proposed model significantly outperformed traditional models such as principal component analysis and support vector machine. Furthermore, compared to the traditional CNN, our model reduced the number of parameters and number of computations by 53% and 55%, respectively, without compromising classification accuracy. The study also suggests that the combination of GC-IMS and our proposed deep learning method had better discrimination abilities for rice varieties than traditional chromatography and other spectral analysis methods and that it effectively identified rice varieties.

Tetraploid interspecific hybrids between Asian and African rice species restore fertility depending on killer-protector loci for hybrid sterility.

Interspecific F1 hybrids between Asian (Oryza sativa) and African rice (Oryza glaberrima) exhibit severe sterility caused by the accumulation of hybrid sterility genes/loci at 15 or more loci. The mechanisms underlying the hybrid sterility genes are largely unknown; however, a few genes associated with the killer-protector system, which is the system most frequently associated with hybrid sterility genes, have been identified. We previously produced fertile plants as tetraploids derived from diploid interspecific F1 hybrids through anther culture; therefore, it was suggested that hybrid sterility could be overcome following tetraploidization. We investigated whether tetraploid interspecific plants produced by crossing are fertile and tested the involvement of hybrid sterility genes in the process. Fertile tetraploid interspecific F1 hybrid plants were obtained by crossing 2 tetraploids of O. sativa and O. glaberrima. To elucidate the relationships between pollen fertility and the hybrid sterility loci in the tetraploid F1 microspores, we performed genetic analyses of the tetraploid F2 hybrids and diploid plants obtained from the microspores of tetraploid interspecific hybrids by anther culture. The result suggested that the tetraploid interspecific hybrids overcame pollen and seed infertility based on the proportion of loci with the killer-protector system present in the tetraploids. The heterozygous hybrid sterility loci with the killer-protector system in the tetraploid segregate the homozygous killed allele (16.7-21.4%), with more than three-quarters of the gametes surviving. We theoretically and experimentally demonstrated that fertile rice progenies can be grown from tetraploid interspecific hybrids.

Wild rice: unlocking the future of rice breeding.

Germplasm resources serve as the foundations of advancements in breeding and are crucial for maintaining food security. Wild rice species of the genus Oryza include rich sources of genetic diversity and high adaptability, making them a substantial resource for rice breeding. The discovery of wild-type cytoplasmic male sterility resources enabled the achievement of the 'three lines' goal in hybrid rice, significantly increasing rice yields. The application of resistance alleles from wild rice enables rice production to withstand losses caused by stress. Reduced genetic diversity due to rice breeding poses a significant limitation to further advances and can be alleviated through a systematic use of wild genetic resources that integrate geographic, climatic and environmental data of the original habitat, along with extensive germplasm collection and identification using advanced methods. Leveraging technological advancements in plant genomics, the understanding of genetic mechanisms and the application of artificial intelligence and gene editing can further enhance the efficiency and accuracy of this process. These advancements facilitate rapid isolation and functional studies of genes, and precise genome manipulation. This review systematically summarizes the utilization of superior genes and germplasm resources derived from wild rice sources, while also exploring the collection, conservation, identification and utilization of further wild rice germplasm resources. A focus on genome sequencing and biotechnology developments is leading to new breeding and biotechnology opportunities. These new opportunities will not only promote the development of rice varieties that exhibit high yields, superior stress resistance and high quality but also expand the genetic diversity among rice cultivars.

Comparative Analysis of Peroxidase and Catalase Isoenzymes via Native-PAGE Electrophoresis and SDS-PAGE Profiling of Leaf Proteins in Rice Varieties under Infection Stress

Rice (Oryza sativa L.) is a staple food for over half of the world's population. However, rice productivity is significantly hindered by various diseases, including sheath blight caused by Rhizoctonia solani. This study aims to evaluate the resistance of different rice varieties and wild rice accessions to sheath blight and to analyze the biochemical responses, specifically peroxidase and catalase activities, under infection stress. The results revealed that Kalanamak and Pusa Basmati were highly susceptible, with high disease indices and visual ratings. Conversely, wild rice accessions such as O. rufipogon and O. australiensis exhibited lower disease indices, indicating moderate resistance. Peroxidase activity varied significantly among the rice leaves, ranging from 148.83 to 182.44 mg/g fresh weight/min. Dhanya 748 showed the highest peroxidase activity, followed by O. australiensis and O. rufipogon. Native-PAGE electrophoresis of peroxidase isoenzymes demonstrated high-intensity bands in O. rufipogon, BPT 5204, and Swarna Sub-1, while minimal or no bands were observed in other genotypes, indicating varying levels of peroxidase activity. Catalase activity also showed significant variation, ranging from 138.18 to 152.14 mg/g fresh weight/min. BPT-5204 exhibited the highest catalase activity, followed by O. australiensis and Pusa Basmati. Isoenzyme analysis via Native-PAGE revealed high-intensity catalase bands in O. australiensis, Dhanya 748, NDR 118, and Pusa Basmati, while no bands were observed in O. rufipogon, CSR 13, Arize 6444, and Swarna Sub-1. SDS-PAGE analysis of leaf proteins showed variability in banding patterns. Non-infected leaves of Swarna Sub-1, Arize 6444, Kalanamak, and Pusa Basmati had minimal bands, while O. australiensis and Dhanya 748 showed maximum bands. Infected leaves of CSR 13, NDR 118, Arize 6444, Kalanamak, Dhanya 748, and Pusa Basmati had minimal bands, whereas O. australiensis exhibited maximum bands. Overall, the study highlights the potential of wild rice species in enhancing disease resistance and provides insights into the biochemical responses of rice varieties under pathogen stress.