OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security

Do DEEPER ROOTING 1 Homologs Regulate the Lateral Root Slope Angle in Cucumber (Cucumis sativus)?

The architecture of the root system is fundamental to plant productivity. The rate of root growth, the density of lateral roots, and the spatial structure of lateral and adventitious roots determine the developmental plasticity of the root system in response to changes in environmental conditions. One of the genes involved in the regulation of the slope angle of lateral roots is DEEPER ROOTING 1 (DRO1). Its orthologs and paralogs have been identified in rice, Arabidopsis, and several other species. However, nothing is known about the formation of the slope angle of lateral roots in species with the initiation of lateral root primordia within the parental root meristem. To address this knowledge gap, we identified orthologs and paralogs of the DRO1 gene in cucumber (Cucumis sativus) using a phylogenetic analysis of IGT protein family members. Differences in the transcriptional response of CsDRO1, CsDRO1-LIKE1 (CsDRO1L1), and CsDRO1-LIKE2 (CsDRO1L2) to exogenous auxin were analyzed. The results showed that only CsDRO1L1 is auxin-responsive. An analysis of promoter-reporter fusions demonstrated that the CsDRO1, CsDRO1L1, and CsDRO1L2 genes were expressed in the meristem in cell files of the central cylinder, endodermis, and cortex; the three genes displayed different expression patterns in cucumber roots with only partial overlap. A knockout of individual CsDRO1, CsDRO1L1, and CsDRO1L2 genes was performed via CRISPR/Cas9 gene editing. Our study suggests that the knockout of individual genes does not affect the slope angle formation during lateral root primordia development in the cucumber parental root.

Microbial tapestry of the Shulgan-Tash cave (Southern Ural, Russia): influences of environmental factors on the taxonomic composition of the cave biofilms

BACKGROUND

Cave biotopes are characterized by stable low temperatures, high humidity, and scarcity of organic substrates. Despite the harsh oligotrophic conditions, they are often inhabited by rich microbial communities. Abundant fouling with a wide range of morphology and coloration of colonies covers the walls of the Shulgan-Tash cave in the Southern Urals. This cave is also famous for the unique Paleolithic painting discovered in the middle of the last century. We aimed to investigate the diversity, distribution, and potential impact of these biofilms on the cave's Paleolithic paintings, while exploring how environmental factors influence the microbial communities within the cave.

RESULTS

The cave's biofilm morphotypes were categorized into three types based on the ultrastructural similarities. Molecular taxonomic analysis identified two main clusters of microbial communities, with Actinobacteria dominating in most of them and a unique "CaveCurd" community with Gammaproteobacteria prevalent in the deepest cave sections. The species composition of these biofilms reflects changes in environmental conditions, such as substrate composition, temperature, humidity, ventilation, and CO2 content. Additionally, it was observed that cave biofilms contribute to biocorrosion on cave wall surfaces.

CONCLUSIONS

The Shulgan-Tash cave presents an intriguing example of a stable extreme ecosystem with diverse microbiota. However, the intense dissolution and deposition of carbonates caused by Actinobacteria pose a potential threat to the preservation of the cave's ancient rock paintings.

Lateral Root Initiation in Cucumber (Cucumis sativus): What Does the Expression Pattern of Rapid Alkalinization Factor 34 (RALF34) Tell Us?

In Arabidopsis, the small signaling peptide (peptide hormone) RALF34 is involved in the gene regulatory network of lateral root initiation. In this study, we aimed to understand the nature of the signals induced by RALF34 in the non-model plant cucumber (Cucumis sativus), where lateral root primordia are induced in the apical meristem of the parental root. The RALF family members of cucumber were identified using phylogenetic analysis. The sequence of events involved in the initiation and development of lateral root primordia in cucumber was examined in detail. To elucidate the role of the small signaling peptide CsRALF34 and its receptor CsTHESEUS1 in the initial stages of lateral root formation in the parental root meristem in cucumber, we studied the expression patterns of both genes, as well as the localization and transport of the CsRALF34 peptide. CsRALF34 is expressed in all plant organs. CsRALF34 seems to differ from AtRALF34 in that its expression is not regulated by auxin. The expression of AtRALF34, as well as CsRALF34, is regulated in part by ethylene. CsTHESEUS1 is expressed constitutively in cucumber root tissues. Our data suggest that CsRALF34 acts in a non-cell-autonomous manner and is not involved in lateral root initiation in cucumber.

Integrative Proteomics and Metabolomics Analysis Reveals the Role of Small Signaling Peptide Rapid Alkalinization Factor 34 (RALF34) in Cucumber Roots

The main role of RALF small signaling peptides was reported to be the alkalization control of the apoplast for improvement of nutrient absorption; however, the exact function of individual RALF peptides such as RALF34 remains unknown. The Arabidopsis RALF34 (AtRALF34) peptide was proposed to be part of the gene regulatory network of lateral root initiation. Cucumber is an excellent model for studying a special form of lateral root initiation taking place in the meristem of the parental root. We attempted to elucidate the role of the regulatory pathway in which RALF34 is a participant using cucumber transgenic hairy roots overexpressing CsRALF34 for comprehensive, integrated metabolomics and proteomics studies, focusing on the analysis of stress response markers. CsRALF34 overexpression resulted in the inhibition of root growth and regulation of cell proliferation, specifically in blocking the G2/M transition in cucumber roots. Based on these results, we propose that CsRALF34 is not part of the gene regulatory networks involved in the early steps of lateral root initiation. Instead, we suggest that CsRALF34 modulates ROS homeostasis and triggers the controlled production of hydroxyl radicals in root cells, possibly associated with intracellular signal transduction. Altogether, our results support the role of RALF peptides as ROS regulators.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

A Neural Network-Based Spectral Approach for the Assignment of Individual Trees to Genetically Differentiated Subpopulations

Studying population structure has made an essential contribution to understanding evolutionary processes and demographic history in forest ecology research. This inference process basically involves the identification of common genetic variants among individuals, then grouping the similar individuals into subpopulations. In this study, a spectral-based classification of genetically differentiated groups was carried out using a provenance–progeny trial of Eucalyptus cladocalyx. First, the genetic structure was inferred through a Bayesian analysis using single-nucleotide polymorphisms (SNPs). Then, different machine learning models were trained with foliar spectral information to assign individual trees to subpopulations. The results revealed that spectral-based classification using the multilayer perceptron method was very successful at classifying individuals into their respective subpopulations (with an average of 87% of correct individual assignments), whereas 85% and 81% of individuals were assigned to their respective classes correctly by convolutional neural network and partial least squares discriminant analysis, respectively. Notably, 93% of individual trees were assigned correctly to the class with the smallest size using the spectral data-based multi-layer perceptron classification method. In conclusion, spectral data, along with neural network models, are able to discriminate and assign individuals to a given subpopulation, which could facilitate the implementation and application of population structure studies on a large scale.

Multigenerational Exposure to Heat Stress Induces Phenotypic Resilience, and Genetic and Epigenetic Variations in Arabidopsis thaliana Offspring

Plants are sedentary organisms that constantly sense changes in their environment and react to various environmental cues. On a short-time scale, plants respond through alterations in their physiology, and on a long-time scale, plants alter their development and pass on the memory of stress to the progeny. The latter is controlled genetically and epigenetically and allows the progeny to be primed for future stress encounters, thus increasing the likelihood of survival. The current study intended to explore the effects of multigenerational heat stress in Arabidopsis thaliana. Twenty-five generations of Arabidopsis thaliana were propagated in the presence of heat stress. The multigenerational stressed lineage F25H exhibited a higher tolerance to heat stress and elevated frequency of homologous recombination, as compared to the parallel control progeny F25C. A comparison of genomic sequences revealed that the F25H lineage had a three-fold higher number of mutations [single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs)] as compared control lineages, suggesting that heat stress induced genetic variations in the heat-stressed progeny. The F25H stressed progeny showed a 7-fold higher number of non-synonymous mutations than the F25C line. Methylome analysis revealed that the F25H stressed progeny showed a lower global methylation level in the CHH context than the control progeny. The F25H and F25C lineages were different from the parental control lineage F2C by 66,491 and 80,464 differentially methylated positions (DMPs), respectively. F25H stressed progeny displayed higher frequency of methylation changes in the gene body and lower in the body of transposable elements (TEs). Gene Ontology analysis revealed that CG-DMRs were enriched in processes such as response to abiotic and biotic stimulus, cell organizations and biogenesis, and DNA or RNA metabolism. Hierarchical clustering of these epimutations separated the heat stressed and control parental progenies into distinct groups which revealed the non-random nature of epimutations. We observed an overall higher number of epigenetic variations than genetic variations in all comparison groups, indicating that epigenetic variations are more prevalent than genetic variations. The largest difference in epigenetic and genetic variations was observed between control plants comparison (F25C vs. F2C), which clearly indicated that the spontaneous nature of epigenetic variations and heat-inducible nature of genetic variations. Overall, our study showed that progenies derived from multigenerational heat stress displayed a notable adaption in context of phenotypic, genotypic and epigenotypic resilience.

MicroRNA Mediated Plant Responses to Nutrient Stress

To complete their life cycles, plants require several minerals that are found in soil. Plant growth and development can be affected by nutrient shortages or high nutrient availability. Several adaptations and evolutionary changes have enabled plants to cope with inappropriate growth conditions and low or high nutrient levels. MicroRNAs (miRNAs) have been recognized for transcript cleavage and translational reduction, and can be used for post-transcriptional regulation. Aside from regulating plant growth and development, miRNAs play a crucial role in regulating plant’s adaptations to adverse environmental conditions. Additionally, miRNAs are involved in plants’ sensory functions, nutrient uptake, long-distance root transport, and physiological functions related to nutrients. It may be possible to develop crops that can be cultivated in soils that are either deficient in nutrients or have extreme nutrient supplies by understanding how plant miRNAs are associated with nutrient stress. In this review, an overview is presented regarding recent advances in the understanding of plants’ responses to nitrogen, phosphorus, potassium, sulfur, copper, iron, boron, magnesium, manganese, zinc, and calcium deficiencies via miRNA regulation. We conclude with future research directions emphasizing the modification of crops for improving future food security.

Alterations in the Transcriptome of Rye Plants following the Microdochium nivale Infection: Identification of Resistance/Susceptibility-Related Reactions Based on RNA-Seq Analysis

Microdochium nivale is a progressive and devastating phytopathogen that causes different types of cereal crop and grass diseases that are poorly characterized at the molecular level. Although rye (Secale cereale L.) is one of the most resistant crops to most of the phytopathogens, it is severely damaged by M. nivale. The recent high-quality chromosome-scale assembly of rye genome has improved whole-genome studies of this crop. In the present work, the first transcriptome study of the M. nivale-infected crop plant (rye) with the detailed functional gene classification was carried out, along with the physiological verification of the RNA-Seq data. The results revealed plant reactions that contributed to their resistance or susceptibility to M. nivale. Phytohormone abscisic acid was shown to promote plant tolerance to M. nivale. Flavonoids were proposed to contribute to plant resistance to this pathogen. The upregulation of plant lipase encoding genes and the induction of lipase activity in M. nivale-infected plants revealed in our study were presumed to play an important role in plant susceptibility to the studied phytopathogen. Our work disclosed important aspects of plant-M. nivale interactions, outlined the directions for future studies on poorly characterized plant diseases caused by this phytopathogen, and provided new opportunities to improve cereals breeding and food security strategies.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.