A Comparative Transcriptomic Meta-Analysis Revealed Conserved Key Genes and Regulatory Networks Involved in Drought Tolerance in Cereal Crops

CRF transcription factors in the trade-off between abiotic stress response and plant developmental processes

Climate change-induced environmental stress significantly affects crop yield and quality. In response to environmental stressors, plants use defence mechanisms and growth suppression, creating a resource trade-off between the stress response and development. Although stress-responsive genes have been widely engineered to enhance crop stress tolerance, there is still limited understanding of the interplay between stress signalling and plant growth, a research topic that can provide promising targets for crop genetic improvement. This review focuses on Cytokinin Response Factors (CRFs) transcription factor's role in the balance between abiotic stress adaptation and sustained growth. CRFs, known for their involvement in cytokinin signalling and abiotic stress responses, emerge as potential targets for delaying senescence and mitigating yield penalties under abiotic stress conditions. Understanding the molecular mechanisms regulated by CRFs paves the way for decoupling stress responses from growth inhibition, thus allowing the development of crops that can adapt to abiotic stress without compromising development. This review highlights the importance of unravelling CRF-mediated pathways to address the growing need for resilient crops in the face of evolving climatic conditions.

Nitrogen mitigates the negative effects of combined heat and drought stress on winter wheat by improving physiological characteristics

Extreme drought stress is often accompanied by heat stress after anthesis in winter wheat. Whether nitrogen (N) can mitigate the damage caused by combined stress on wheat plants by regulating root physiological characteristics is still unclear. Thus, this study aimed to study the effects of combined heat and drought stress on photosynthesis, leaf water relations, root antioxidant system, osmoregulatory, and yield in wheat to reveal the physiological mechanism of N regulating the adverse impacts of combined stress on wheat. Heat and drought stress markedly reduced photosynthesis, leaf water content, root vitality, and bleeding sap. The combination of heat and drought strengthens these changes. Within a certain stress range, the increase in soluble sugar and proline contents and the activities of superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase under combined stress effectively alleviated the oxidative damage. Compared with those under high N application (N3), wheat plants under low N application (N1) maintained higher yield and yield components under combined stress; the number of grains per spike, 1000-grain weight, and yield increased by 13.65%, 9.07%, and 15.33%, respectively, under N1 compared with those under N3 treatment, which may be attributed to the greater maintenance of photosynthesis, leaf water status, root vitality, and antioxidant and osmoregulation capacities. In summary, reduced N application mitigated the damage caused by combined heat and drought stress in wheat by improving root physiological characteristics and enhanced adaptability to combined stress, which is an appropriate strategy to compensate for yield losses.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

A Novel Role of Medicago truncatula KNAT3/4/5-like Class 2 KNOX Transcription Factors in Drought Stress Tolerance

Class 2 KNOX homeobox transcription factors (KNOX2) play a role in promoting cell differentiation in several plant developmental processes. In Arabidopsis, they antagonize the meristematic KNOX1 function during leaf development through the modulation of phytohormones. In Medicago truncatula, three KNOX2 genes belonging to the KNAT3/4/5-like subclass (Mt KNAT3/4/5-like or MtKNOX3-like) redundantly works upstream of a cytokinin-signaling module to control the symbiotic root nodule formation. Their possible role in the response to abiotic stress is as-of-yet unknown. We produced transgenic M. truncatula lines, in which the expression of four MtKNOX3-like genes was knocked down by RNA interference. When tested for response to water withdrawal in the soil, RNAi lines displayed a lower tolerance to drought conditions compared to the control lines, measured as increased leaf water loss, accelerated leaf wilting time, and faster chlorophyll loss. Reanalysis of a transcriptomic M. truncatula drought stress experiment via cluster analysis and gene co-expression networks pointed to a possible role of MtKNOX3-like transcription factors in repressing a proline dehydrogenase gene (MtPDH), specifically at 4 days after water withdrawal. Proline measurement and gene expression analysis of transgenic RNAi plants compared to the controls confirmed the role of KNOX3-like genes in inhibiting proline degradation through the regulation of the MtPDH gene.

Transcriptomic analysis reveals the gene regulatory networks involved in leaf and root response to osmotic stress in tomato

Introduction

Tomato (Solanum lycopersicum L.) is a major horticultural crop that is cultivated worldwide and is characteristic of the Mediterranean agricultural system. It represents a key component of the diet of billion people and an important source of vitamins and carotenoids. Tomato cultivation in open field often experiences drought episodes, leading to severe yield losses, since most modern cultivars are sensitive to water deficit. Water stress leads to changes in the expression of stress-responsive genes in different plant tissues, and transcriptomics can support the identification of genes and pathways regulating this response.

Methods

Here, we performed a transcriptomic analysis of two tomato genotypes, M82 and Tondo, in response to a PEG-mediated osmotic treatment. The analysis was conducted separately on leaves and roots to characterize the specific response of these two organs.

Results

A total of 6,267 differentially expressed transcripts related to stress response was detected. The construction of gene co-expression networks defined the molecular pathways of the common and specific responses of leaf and root. The common response was characterized by ABA-dependent and ABA-independent signaling pathways, and by the interconnection between ABA and JA signaling. The root-specific response concerned genes involved in cell wall metabolism and remodeling, whereas the leaf-specific response was principally related to leaf senescence and ethylene signaling. The transcription factors representing the hubs of these regulatory networks were identified. Some of them have not yet been characterized and can represent novel candidates for tolerance.

Discussion

This work shed new light on the regulatory networks occurring in tomato leaf and root under osmotic stress and set the base for an in-depth characterization of novel stress-related genes that may represent potential candidates for improving tolerance to abiotic stress in tomato.

A Survey of the Transcriptomic Resources in Durum Wheat: Stress Responses, Data Integration and Exploitation

Durum wheat (Triticum turgidum subsp. durum (Desf.) Husn.) is an allotetraploid cereal crop of worldwide importance, given its use for making pasta, couscous, and bulgur. Under climate change scenarios, abiotic (e.g., high and low temperatures, salinity, drought) and biotic (mainly exemplified by fungal pathogens) stresses represent a significant limit for durum cultivation because they can severely affect yield and grain quality. The advent of next-generation sequencing technologies has brought a huge development in transcriptomic resources with many relevant datasets now available for durum wheat, at various anatomical levels, also focusing on phenological phases and environmental conditions. In this review, we cover all the transcriptomic resources generated on durum wheat to date and focus on the corresponding scientific insights gained into abiotic and biotic stress responses. We describe relevant databases, tools and approaches, including connections with other "omics" that could assist data integration for candidate gene discovery for bio-agronomical traits. The biological knowledge summarized here will ultimately help in accelerating durum wheat breeding.

Genome-Wide Identification of Potential mRNAs in Drought Response in Wheat (Triticum aestivum L.)

Plant cell metabolism inevitably forms an important drought-responsive mechanism, which halts crop productivity. Globally, more than 30% of the total harvested area was affected by dehydration. RNA-seq technology has enabled biologists to identify stress-responsive genes in relatively quick times. However, one shortcoming of this technology is the inconsistent data generation compared to other parts of the world. So, we have tried, here, to generate a consensus by analyzing meta-transcriptomic data available in the public microarray database GEO NCBI. In this way, the aim was set, here, to identify stress genes commonly identified as differentially expressed (p < 0.05) then followed by downstream analyses. The search term “Drought in wheat” resulted in 233 microarray experiments from the GEO NCBI database. After discarding empty datasets containing no expression data, the large-scale meta-transcriptome analytics and one sample proportional test were carried out (Bonferroni adjusted p < 0.05) to reveal a set of 11 drought-responsive genes on a global scale. The annotation of these genes revealed that the transcription factor activity of RNA polymerase II and sequence-specific DNA-binding mechanism had a significant role during the drought response in wheat. Similarly, the primary root differentiation zone annotations, controlled by TraesCS5A02G456300 and TraesCS7B02G243600 genes, were found as top-enriched terms (p < 0.05 and Q < 0.05). The resultant standard drought genes, glycosyltransferase; Arabidopsis thaliana KNOTTED-like; bHLH family protein; Probable helicase MAGATAMA 3; SBP family protein; Cytochrome c oxidase subunit 2; Trihelix family protein; Mic1 domain-containing protein; ERF family protein; HD-ZIP I protein; and ERF family protein, are important in terms of their worldwide proved link with stress. From a future perspective, this study could be important in a breeding program contributing to increased crop yield. Moreover, the wheat varieties could be identified as drought-resistant/sensitive based on the nature of gene expression levels.

Gene Co-Expression Network Tools and Databases for Crop Improvement

Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.

Meta-Analysis as a Tool to Identify Candidate Genes Involved in the Fagus sylvatica L. Abiotic Stress Response

In this study, we aimed to evaluate whether candidate genes for abiotic stresses in Fagus sylvatica L. are also candidate genes for herbaceous plants, with the purpose of better defining the abiotic stress response model of F. sylvatica. Therefore, a meta-analysis was performed on published papers related to abiotic stress. Firstly, we carried out a systematic review regarding the activity of 24 candidate genes selected for F. sylvatica under abiotic stress reported in 503 articles. After choosing the inclusion criteria, 73 articles out of 503, regarding 12 candidate genes, were included in this analysis. We performed an exploratory meta-analysis based on the random-effect model and the combined effect-size approach (Cohen’s d). The results obtained through Forest and Funnel plots indicate that the candidate genes for F. sylvatica are considered to be candidate genes in other herbaceous species. These results allowed us to set up models of plants’ response to abiotic stresses implementing the stress models in forest species. The results of this study will serve to bridge knowledge gaps regarding the pathways of response to abiotic stresses in trees based on the meta-analysis. The study approach used could be extended to observe larger gene databases and different species.