Analysis of Stress Resistance Using Next Generation Techniques

Evaluation of efficacy of non-coding RNA in abiotic stress management of field crops: Current status and future prospective

Abiotic stresses are responsible for the major losses in crop yield all over the world. Stresses generate harmful ROS which can impair cellular processes in plants. Therefore, plants have evolved antioxidant systems in defence against the stress-induced damages. The frequency of occurrence of abiotic stressors has increased several-fold due to the climate change experienced in recent times and projected for the future. This had particularly aggravated the risk of yield losses and threatened global food security. Non-coding RNAs are the part of eukaryotic genome that does not code for any proteins. However, they have been recently found to have a crucial role in the responses of plants to both abiotic and biotic stresses. There are different types of ncRNAs, for example, miRNAs and lncRNAs, which have the potential to regulate the expression of stress-related genes at the levels of transcription, post-transcription, and translation of proteins. The lncRNAs are also able to impart their epigenetic effects on the target genes through the alteration of the status of histone modification and organization of the chromatins. The current review attempts to deliver a comprehensive account of the role of ncRNAs in the regulation of plants' abiotic stress responses through ROS homeostasis. The potential applications ncRNAs in amelioration of abiotic stresses in field crops also have been evaluated.

Effect of selenium nanoparticles on biological and morphofunctional parameters of barley seeds (Hordéum vulgáre L.)

The purpose of this work was to study the effect of selenium nanoparticles (Se NPs) on the biological and morphofunctional parameters of barley seeds (Hordéum vulgáre L.) We used seeds of Hordéum vulgáre L. with reduced morphofunctional characteristics. For the experiment, Se NPs were synthesized and stabilized with didecyldimethylammonium chloride. It was found that Se NPs have a spherical shape and a diameter of about 50 nm. According to dynamic light scattering data, the average hydrodynamic radius of the particles was 28 ± 8 nm. It is observed that the nanoparticles have a positive ζ-potential (+ 27.3 mV). For the experiment, we treated Hordéum vulgáre L. seeds with Se NPs (1, 5, 10 and 20 mg/L). The experiment showed that treatment of Hordéum vulgáre L. seeds with Se NPs has the best effect on the length of roots and sprout at concentration of 5 mg/L and on the number and thickness of roots at 10 mg/L. Germinability and germination energy of Hordéum vulgáre L. seeds were higher in group treated with 5 mg/L Se NPs. Analysis of macrophotographs of samples, histological sections of roots and 3D visualization of seeds by microcomputing tomography confirmed the best effect at 5 mg/L Se NPs. Moreover, no local destructions were detected at concentrations > 5 mg/L, which is most likely due to the inhibition of regulatory and catalytic processes in the germinating seeds. the treatment of Hordéum vulgáre L. seeds with > 5 mg/L Se NPs caused significant stress, coupled with intensive formation of reactive oxygen species, leading to a reorientation of root system growth towards thickening. Based on the results obtained, it was concluded that Se NPs at concentrations > 5 mg/L had a toxic effect. The treatment of barley seeds with 5% Se NPs showed maximum efficiency in the experiment, which allows us to further consider Se NPs as a stimulator for the growth and development of crop seeds under stress and reduced morphofunctional characteristics.

Genome-Wide Association Study and Genomic Prediction for Bacterial Wilt Resistance in Common Bean (Phaseolus vulgaris) Core Collection

Common bean (Phaseolus vulgaris) is one of the major legume crops cultivated worldwide. Bacterial wilt (BW) of common bean (Curtobacterium flaccumfaciens pv. flaccumfaciens), being a seed-borne disease, has been a challenge in common bean producing regions. A genome-wide association study (GWAS) was conducted to identify SNP markers associated with BW resistance in the USDA common bean core collection. A total of 168 accessions were evaluated for resistance against three different isolates of BW. Our study identified a total of 14 single nucleotide polymorphism (SNP) markers associated with the resistance to BW isolates 528, 557, and 597 using mixed linear models (MLMs) in BLINK, FarmCPU, GAPIT, and TASSEL 5. These SNPs were located on chromosomes Phaseolus vulgaris [Pv]02, Pv04, Pv08, and Pv09 for isolate 528; Pv07, Pv10, and Pv11 for isolate 557; and Pv04, Pv08, and Pv10 for isolate 597. The genomic prediction accuracy was assessed by utilizing seven GP models with 1) all the 4,568 SNPs and 2) the 14 SNP markers. The overall prediction accuracy (PA) ranged from 0.30 to 0.56 for resistance against the three BW isolates. A total of 14 candidate genes were discovered for BW resistance located on chromosomes Pv02, Pv04, Pv07, Pv08, and Pv09. This study revealed vital information for developing genetic resistance against the BW pathogen in common bean. Accordingly, the identified SNP markers and candidate genes can be utilized in common bean molecular breeding programs to develop novel resistant cultivars.

Cross-species transcriptomic analyses reveals common and opposite responses in Arabidopsis, rice and barley following oxidative stress and hormone treatment

BACKGROUND

For translational genomics, a roadmap is needed to know the molecular similarities or differences between species, such as model species and crop species. This knowledge is invaluable for the selection of target genes and pathways to alter downstream in response to the same stimuli. Here, the transcriptomic responses to six treatments including hormones (abscisic acid - ABA and salicylic acid - SA); treatments that cause oxidative stress (3-amino-1,2,4-triazole - 3AT, methyl viologen - MV); inhibit respiration (antimycin A - AA) or induce genetic damage (ultraviolet radiation -UV) were analysed and compared between Arabidopsis (Arabidopsis thaliana), barley (Hordeum vulgare) and rice (Oryza sativa).

RESULTS

Common and opposite responses were identified between species, with the number of differentially expressed genes (DEGs) varying greatly between treatments and species. At least 70% of DEGs overlapped with at least one other treatment within a species, indicating overlapping response networks. Remarkably, 15 to 34% of orthologous DEGs showed opposite responses between species, indicating diversity in responses, despite orthology. Orthologous DEGs with common responses to multiple treatments across the three species were correlated with experimental data showing the functional importance of these genes in biotic/abiotic stress responses. The mitochondrial dysfunction response was revealed to be highly conserved in all three species in terms of responsive genes and regulation via the mitochondrial dysfunction element.

CONCLUSIONS

The orthologous DEGs that showed a common response between species indicate conserved transcriptomic responses of these pathways between species. However, many genes, including prominent salt-stress responsive genes, were oppositely responsive in multiple-stresses, highlighting fundamental differences in the responses and regulation of these genes between species. This work provides a resource for translation of knowledge or functions between species.

Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest

Biomass and yield are key variables for assessing the production and performance of agricultural systems. Modeling and predicting the biomass and yield of individual plants at the farm scale represents a major challenge in precision agriculture, particularly when salinity and other abiotic stresses may play a role. Here, we evaluate a diversity panel of the wild tomato species (Solanum pimpinellifolium) through both field and unmanned aerial vehicle (UAV)-based phenotyping of 600 control and 600 salt-treated plants. The study objective was to predict fresh shoot mass, tomato fruit numbers, and yield mass at harvest based on a range of variables derived from the UAV imagery. UAV-based red-green-blue (RGB) imageries collected 1, 2, 4, 6, 7, and 8 weeks before harvest were also used to determine if prediction accuracies varied between control and salt-treated plants. Multispectral UAV-based imagery was also collected 1 and 2 weeks prior to harvest to further explore predictive insights. In order to estimate the end of season biomass and yield, a random forest machine learning approach was implemented using UAV-imagery-derived predictors as input variables. Shape features derived from the UAV, such as plant area, border length, width, and length, were found to have the highest importance in the predictions, followed by vegetation indices and the entropy texture measure. The multispectral UAV imagery collected 2 weeks prior to harvest produced the highest explained variances for fresh shoot mass (87.95%), fruit numbers (63.88%), and yield mass per plant (66.51%). The RGB UAV imagery produced very similar results to those of the multispectral UAV dataset, with the explained variance reducing as a function of increasing time to harvest. The results showed that predicting the yield of salt-stressed plants produced higher accuracies when the models excluded control plants, whereas predicting the yield of control plants was not affected by the inclusion of salt-stressed plants within the models. This research demonstrates that it is possible to predict the average biomass and yield up to 8 weeks prior to harvest within 4.23% of field-based measurements and up to 4 weeks prior to harvest at the individual plant level. Results from this work may be useful in providing guidance for yield forecasting of healthy and salt-stressed tomato plants, which in turn may inform growing practices, logistical planning, and sales operations.

Unmanned Aerial Vehicle-Based Phenotyping Using Morphometric and Spectral Analysis Can Quantify Responses of Wild Tomato Plants to Salinity Stress

With salt stress presenting a major threat to global food production, attention has turned to the identification and breeding of crop cultivars with improved salt tolerance. For instance, some accessions of wild species with higher salt tolerance than commercial varieties are being investigated for their potential to expand food production into marginal areas or to use brackish waters for irrigation. However, assessment of individual plant responses to salt stress in field trials is time-consuming, limiting, for example, longitudinal assessment of large numbers of plants. Developments in Unmanned Aerial Vehicle (UAV) sensing technologies provide a means for extensive, repeated and consistent phenotyping and have significant advantages over standard approaches. In this study, 199 accessions of the wild tomato species, Solanum pimpinellifolium, were evaluated through a field assessment of 600 control and 600 salt-treated plants. UAV imagery was used to: (1) delineate tomato plants from a time-series of eight RGB and two multi-spectral datasets, using an automated object-based image analysis approach; (2) assess four traits, i.e., plant area, growth rates, condition and Plant Projective Cover (PPC) over the growing season; and (3) use the mapped traits to identify the best-performing accessions in terms of yield and salt tolerance. For the first five campaigns, >99% of all tomato plants were automatically detected. The omission rate increased to 2-5% for the last three campaigns because of the presence of dead and senescent plants. Salt-treated plants exhibited a significantly smaller plant area (average control and salt-treated plant areas of 0.55 and 0.29 m2, respectively), maximum growth rate (daily maximum growth rate of control and salt-treated plant of 0.034 and 0.013 m2, respectively) and PPC (5-16% difference) relative to control plants. Using mapped plant condition, area, growth rate and PPC, we show that it was possible to identify eight out of the top 10 highest yielding accessions and that only five accessions produced high yield under both treatments. Apart from showcasing multi-temporal UAV-based phenotyping capabilities for the assessment of plant performance, this research has implications for agronomic studies of plant salt tolerance and for optimizing agricultural production under saline conditions.

Biotic and Abiotic Stress Responses in Crop Plants

Agricultural productivity depends on increasingly extreme weather phenomena, and the use of germplasm that has to be continuously improved by plant breeders to become tolerant to various biotic and abiotic stresses. Molecular plant biologists try to understand the mechanisms associated with stress responses and provide knowledge that could be used in breeding programs. To provide a partial overview about our current understanding about molecular and physiological stress responses, and how this knowledge can be used in agriculture, we have edited a special issue on “Biotic and Abiotic Stress Responses in Crop Plants”. Contributions are from different fields including heat stress responses, stress responses during drought and salinity, as well as during flooding, and resistance and susceptibility to pathogenetic stresses and about the role of plant functional metabolites in biotic stress responses. Future research demand in particular areas of crop stress physiology is discussed, as well as the importance of translational research and investigations directly in elite crop plants and in the genetic resources available for breeding.