Implications of tolerance to iron toxicity on root system architecture changes in rice (Oryza sativa L.)

IntroductionToxicity due to excess soil iron (Fe) is a significant concern for rice cultivation in lowland areas with acidic soils. Toxic levels of Fe adversely affect plant growth by disrupting the absorption of essential macronutrients, and by causing cellular damage. To understand the responses to excess Fe, particularly on seedling root system, this study evaluated rice genotypes under varying Fe levels.MethodsSixteen diverse rice genotypes were hydroponically screened under induced Fe levels, ranging from normal to excess. Morphological and root system characteristics were observed. The onset of leaf bronzing was monitored to identify the toxic response to the excess Fe. Additionally, agronomic and root characteristics were measured to classify genotypes into tolerant and sensitive categories by computing a response stability index.ResultsOur results revealed that 460 ppm of Fe in the nutrient solution served as a critical threshold for screening genotypes during the seedling stage. Fe toxicity significantly affected root system traits, emphasizing the consequential impact on aerial biomass and nutrient deprivation. To classify genotypes into tolerant and sensitive categories, leaf bronzing score was used as a major indicator of Fe stress. However, the response stability index provided a robust basis for classification for the growth performance. Apart from the established tolerant varieties, we could identify a previously unrecognized tolerant variety, ILS 12–5 in this study. Some of the popular mega varieties, including BPT 5204 and Pusa 44, were found to be highly sensitive.DiscussionOur findings suggest that root system damage, particularly in root length, surface area, and root volume, is the key factor contributing to the sensitivity responses under Fe toxicity. Tolerant genotypes were found to retain more healthy roots than the sensitive ones. Fe exclusion, by reducing Fe2+ uptake, may be a major mechanism for tolerance among these genotypes. Further field evaluations are necessary to confirm the behavior of identified tolerant and sensitive lines under natural conditions. Insights from the study provide potential scope for enhancement of tolerance through breeding programs as well as throw light on the role root system in conferring tolerance

Genome-Wide Identification and Characterisation of Cytokinin-O-Glucosyltransferase (CGT) Genes of Rice Specific to Potential Pathogens

Cytokinin glucosyltransferases (CGTs) are key enzymes of plants for regulating the level and function of cytokinins. In a genomic identification of rice CGTs, 41 genes with the plant secondary product glycosyltransferases (PSPG) motif of 44-amino-acid consensus sequence characteristic of plant uridine diphosphate (UDP)-glycosyltransferases (UGTs) were identified. In-silico physicochemical characterisation revealed that, though the CGTs belong to the same subfamily, they display varying molecular weights, ranging from 19.6 kDa to 59.7 kDa. The proteins were primarily acidic (87.8%) and hydrophilic (58.6%) and were observed to be distributed in the plastids (16), plasma membrane (13), mitochondria (5), and cytosol (4). Phylogenetic analysis of the CGTs revealed that their evolutionary relatedness ranged from 70–100%, and they aligned themselves into two major clusters. In a comprehensive analysis of the available transcriptomics data of rice samples representing different growth stages only the CGT, Os04g25440.1 was significantly expressed at the vegetative stage, whereas 16 other genes were highly expressed only at the reproductive growth stage. On the contrary, six genes, LOC_Os07g30610.1, LOC_Os04g25440.1, LOC_Os07g30620.1, LOC_Os04g25490.1, LOC_Os04g37820.1, and LOC_Os04g25800.1, were significantly upregulated in rice plants inoculated with Rhizoctonia solani (RS), Xoo (Xanthomonas oryzae pv. oryzae) and Mor (Magnaporthe oryzae). In a qRT-PCR analysis of rice sheath tissue susceptible to Rhizoctonia solani, Mor, and Xoo pathogens, compared to the sterile distilled water control, at 24 h post-infection only two genes displayed significant upregulation in response to all the three pathogens: LOC_Os07g30620.1 and LOC_Os04g25820.1. On the other hand, the expression of genes LOC_Os07g30610.1, LOC_Os04g25440, LOC_Os04g25490, and LOC_Os04g25800 were observed to be pathogen-specific. These genes were identified as the candidate-responsive CGT genes and could serve as potential susceptibility genes for facilitating pathogen infection

Discovery of a Novel Induced Polymorphism in SD1 Gene Governing Semi-Dwarfism in Rice and Development of a Functional Marker for Marker-Assisted Selection

The semi-dwarfing allele, sd1-d, has been widely utilized in developing high-yielding rice cultivars across the world. Originally identified from the rice cultivar Dee-Geo-Woo-Gen (DGWG), sd1-d, derived from a spontaneous mutation, has a 383-bp deletion in the SD1 gene. To date, as many as seven alleles of the SD1 gene have been identified and used in rice improvement, either with a functional single-nucleotide polymorphism (SNP), with insertion–deletions (InDels), or both. Here, we report discovery of a novel SNP in the SD1 gene from the rice genotype, Pusa 1652. Genetic analysis revealed that the inheritance of the semi-dwarfism in Pusa 1652 is monogenic and recessive, but it did not carry the sd1-d allele. However, response to exogenous gibberellic acid (GA3) application and the subsequent bulked segregant and linkage analyses confirmed that the SD1 gene is involved in the plant height reduction in Pusa 1652. Sequencing of the SD1 gene from Pusa 1652 revealed a novel transition in exon 3 (T/A) causing a nonsense mutation at the 300th codon. The stop codon leads to premature termination, resulting in a truncated protein of OsGA20ox2 obstructing the GA3 biosynthesis pathway. This novel recessive allele, named sd1-bm, is derived from Bindli Mutant 34 (BM34), a γ-ray induced mutant of a short-grain aromatic landrace, Bindli. BM34 is the parent of an aromatic semi-dwarf cultivar, Pusa 1176, from which Pusa 1652 is derived. The semi-dwarfing allele, sd1-bm, was further validated by developing a derived cleaved amplified polymorphic sequence (dCAPS) marker, AKS-sd1. This allele provides an alternative to the most widely used sd1-d in rice improvement programs and the functional dCAPS marker will facilitate marker-assisted introgression of the semi-dwarf trait into tall genotypes

Genetic Analysis and Molecular Mapping of the Quantitative Trait Loci Governing Low Phytic Acid Content in a Novel LPA Rice Mutant, PLM11

Breeding rice varieties with a low phytic acid (LPA) content is an effective strategy to overcome micronutrient deficiency in a population which consume rice as a staple food. An LPA mutant, Pusa LPA Mutant 11 (PLM11), was identified from an ethyl methane sulfonate (EMS)-induced population of Nagina 22. The present study was carried out to map the loci governing the LPA trait in PLM11 using an F2:3 population derived from a cross between a high phytic acid rice variety, Pusa Basmati 6, with PLM11. The genotyping of the F2 population with 78 polymorphic SSR markers followed by the estimation of phytic acid content in the seeds harvested from 176 F2 plants helped in mapping a major QTL, qLPA8.1, explaining a 22.2% phenotypic variation on Chromosome 8. The QTL was delimited to a 1.96 cM region flanked by the markers RM25 and RM22832. Since there are no previous reports of a QTL/gene governing the LPA content in rice in this region, the QTL qLPA8.1 is a novel QTL. In silico analysis based on the annotated physical map of rice suggested the possible involvement of a locus, Os08g0274775, encoding for a protein similar to a phosphatidylinositol 3- and 4-kinase family member. This needs further validation and fine mapping. Since this QTL is currently specific to PLM11, the linked markers can be utilized for the development of rice varieties with reduced phytic acid (PA) content using PLM11 as the donor, thus enhancing the bioavailability of mineral micronutrients in humans

Marker-Assisted Introgression of Saltol QTL Enhances Seedling Stage Salt Tolerance in the Rice Variety “Pusa Basmati 1”

Marker-assisted selection is an unequivocal translational research tool for crop improvement in the genomics era. Pusa Basmati 1 (PB1) is an elite Indian Basmati rice cultivar sensitive to salinity. Here, we report enhanced seedling stage salt tolerance in improved PB1 genotypes developed through marker-assisted transfer of a major QTL, Saltol. A highly salt tolerant line, FL478, was used as the Saltol donor. Parental polymorphism survey using 456 microsatellite (SSR)/QTL-linked markers revealed 14.3% polymorphism between PB1 and FL478. Foreground selection was carried out using three Saltol-linked polymorphic SSR markers RM8094, RM493, and RM10793 and background selection by 62 genome-wide polymorphic SSR markers. In every backcross generation, foreground selection was restricted to the triple heterozygotes of foreground markers, which was followed by phenotypic and background selections. Twenty-four near isogenic lines (NILs), with recurrent parent genome recovery of 96.0–98.4%, were selected after two backcrosses followed by three selfing generations. NILs exhibited agronomic traits similar to those of PB1 and additional improvement in the seedling stage salt tolerance. They are being tested for per se performance under salt-affected locations for release as commercial varieties. These NILs appear promising for enhancing rice production in salinity-affected pockets of Basmati Geographical Indication (GI) areas of India

Molecular Breeding for Improving Productivity of Oryza sativa L. cv. Pusa 44 under Reproductive Stage Drought Stress through Introgression of a Major QTL, qDTY12.1

Increasing rice production is quintessential to the task of sustaining global food security, as a majority of the global population is dependent on rice as its staple dietary cereal. Among the various constraints affecting rice production, reproductive stage drought stress (RSDS) is a major challenge, due to its direct impact on grain yield. Several quantitative trait loci (QTLs) conferring RSDS tolerance have been identified in rice, and qDTY12.1 is one of the major QTLs reported. We report the successful introgression of qDTY12.1 into Pusa 44, a drought sensitive mega rice variety of the northwestern Indian plains. Marker-assisted backcross breeding (MABB) was adopted to transfer qDTY12.1 into Pusa 44 in three backcrosses followed by four generations of pedigree selection, leading to development of improved near isogenic lines (NILs). Having a recurrent parent genome (RPG) recovery ranging from 94.7–98.7%, the improved NILs performed 6.5 times better than Pusa 44 under RSDS, coupled with high yield under normal irrigated conditions. The MABB program has been modified so as to defer background selection until BC3F4 to accelerate generational advancements. Deploying phenotypic selection alone in the early backcross generations could help in the successful recovery of RPG. In addition, the grain quality could be recovered in the improved NILs, leading to superior selections. Owing to their improved adaptation to drought, the release of improved NILs for regions prone to intermittent drought can help enhance rice productivity and production

Introgression of qDTY1.1 Governing Reproductive Stage Drought Tolerance into an Elite Basmati Rice Variety “Pusa Basmati 1” through Marker Assisted Backcross Breeding

Drought stress at the reproductive stage in rice is one of the most important cause for yield reduction, affecting both productivity and quality. All Basmati rice varieties, including the popular cultivar “Pusa Basmati 1 (PB1)” is highly sensitive to reproductive stage drought stress (RSDS). We report for the first time, improvement of a Basmati cultivar for RSDS tolerance, with the introgression of a major quantitative trait locus (QTL), “qDTY1.1” into PB1. The QTL was sourced from an aus variety, Nagina 22 (N22). A microsatellite (simple sequence repeat (SSR)) marker “RM 431” located at telomeric end (38.89 mb) of chromosome 1, and located within a 1.04 mb QTL region was employed for foreground selection for qDTY1.1 in the marker assisted backcross breeding process. A set of 113 SSR markers polymorphic between N22 and PB1 were utilized for background selection to ensure higher recurrent parent genome recovery. After three backcrosses followed by five generations of selfing, eighteen near isogenic lines (NILs) were developed, through combinatory selection for agro-morphological, grain and cooking quality traits. The NILs were evaluated for three consecutive Kharif seasons, 2017, 2018 and 2019 under well-watered and drought stress conditions. RSDS tolerance and yield stability indicated that P1882-12-111-3, P1882-12-111-5, P1882-12-111-6, P1882-12-111-7, P1882-12-111-12, P1882-12-111-15 and P1882-12-111-17 were best in terms of overall agronomic and grain quality under RSDS. Additionally, NILs exhibited high yield potential under normal condition as well. The RSDS tolerant Basmati NILs with high resilience to water stress, is a valuable resource for sustaining Basmati rice production under water limiting production environments

Population Structure of a Worldwide Collection of Tropical Japonica Rice Indicates Limited Geographic Differentiation and Shows Promising Genetic Variability Associated with New Plant Type

Abating the approaching yield plateau in rice requires taking advantage of potential technologies that requires knowledge on genetic diversity. Hybrid breeding, particularly in indica rice, requires the recruitment of large genetic variability from outside because the available genetic diversity of the cultivated pool has already been utilized to a great extent. In this study, we examined an assembly of 200 tropical japonica lines collected worldwide for population genetic structure and variability in yield-associated traits. Tested along with 30 indica and six wild rice lines belonging to India, the tropical japonica lines indicated great phenotypic variability, particularly related to new plant type (NPT) phenology, and formed six clusters. Furthermore, a marker-based characterization using a universal diversity marker panel classified the genotype assembly into four clusters, of which three encompassed tropical japonica lines, while the last cluster included mostly indica lines. The population structure of the panel also revealed a similar pattern, with tropical japonica lines forming three subpopulations. Remarkable variation in the allelic distribution was observed between the subpopulations. Superimposing the geographical sources of the genotypes over the population structure did not reveal any pattern. The genotypes sourced closer to the center of origin of rice showed relatively little diversity compared with the ones obtained from other parts of the world, suggesting migration from a common region of origin. The tropical japonica lines can be a great source of parental diversification for hybrid development after confirming the presence of widely compatible genes

Imaging Sensor-Based High-Throughput Measurement of Biomass Using Machine Learning Models in Rice

Phenomics technologies have advanced rapidly in the recent past for precision phenotyping of diverse crop plants. High-throughput phenotyping using imaging sensors has been proven to fetch more informative data from a large population of genotypes than the traditional destructive phenotyping methodologies. It provides accurate, high-dimensional phenome-wide big data at an ultra-super spatial and temporal resolution. Biomass is an important plant phenotypic trait that can reflect the agronomic performance of crop plants in terms of growth and yield. Several image-derived features such as area, projected shoot area, projected shoot area with height constant, estimated bio-volume, etc., and machine learning models (single or multivariate analysis) are reported in the literature for use in the non-invasive prediction of biomass in diverse crop plants. However, no studies have reported the best suitable image-derived features for accurate biomass prediction, particularly for fully grown rice plants (70DAS). In this present study, we analyzed a subset of rice recombinant inbred lines (RILs) which were developed from a cross between rice varieties BVD109 × IR20 and grown in sufficient (control) and deficient soil nitrogen (N stress) conditions. Images of plants were acquired using three different sensors (RGB, IR, and NIR) just before destructive plant sampling for the quantitative estimation of fresh (FW) and dry weight (DW). A total of 67 image-derived traits were extracted and classified into four groups, viz., geometric-, color-, IR- and NIR-related traits. We identified a multimodal trait feature, the ratio of PSA and NIR grey intensity as estimated from RGB and NIR sensors, as a novel trait for predicting biomass in rice. Among the 16 machine learning models tested for predicting biomass, the Bayesian regularized neural network (BRNN) model showed the maximum predictive power (R2 = 0.96 and 0.95 for FW and DW of biomass, respectively) with the lowest prediction error (RMSE and bias value) in both control and N stress environments. Thus, biomass can be accurately predicted by measuring novel image-based parameters and neural network-based machine learning models in rice

Population Dynamics of Wide Compatibility System and Evaluation of Intersubspecific Hybrids by indica-japonica Hybridization in Rice

The exploitation of heterosis through intersubspecific hybridisation between indica and japonica has been a major breeding target in rice, but is marred by the cross incompatibility between the genomes. Wide compatibility (WC) is a triallelic system at the S5 locus on chromosome 6 that ensures the specificity of hybridisation within and between indica and japonica. The S5n allele that favours intercrossing is sparsely distributed in the rice gene pool and therefore warrants identification of diverse WC sources to develop superior intersubspecific hybrids. In this study, we have identified several novel WC sources through the marker-assisted screening of a large set of 950 rice genotypes. Seventeen percent of the genotypes carried S5n, which fell into two subpopulations. The WC genotypes showed wide phenotypic and genotypic variability, including both indica and japonica lines. Based on phenotypic performance, the WC varieties were grouped into three clusters. A subset of 41 WC varieties was used to develop 164 hybrids, of which WC/japonica hybrids showed relative superiority over WC/indica hybrids. The multilocation evaluation of hybrids indicated that hybrids derived from WC varieties, such as IRG137, IRG143, OYR128, and IRGC10658, were higher yielding across all the three different locations. Most of the hybrids showed the stability of performance across locations. The identified diverse set of wide compatible varieties (WCVs) can be used in the development of intersubspecific hybrids and also for parental line development in hybrid rice breeding