Stress-resistant Cultivars Research Articles

AScirRNA: A novel computational approach to discover abiotic stress-responsive circular RNAs in plant genome

In the realm of plant biology, understanding the intricate regulatory mechanisms governing stress responses stands as a pivotal pursuit. Circular RNAs (circRNAs), emerging as critical players in gene regulation, have garnered attention in recent days for their potential roles in abiotic stress adaptation. A comprehensive grasp of circRNAs' functions in stress response offers avenues for breeders to manipulating plants to develop abiotic stress resistant crop cultivars to thrive in challenging climates. This study pioneers a machine learning-based model for predicting abiotic stress-responsive circRNAs. The K-tuple nucleotide composition (KNC) and Pseudo KNC (PKNC) features were utilized to numerically represent circRNAs. Three different feature selection strategies were employed to select relevant and non-redundant features. Eight shallow and four deep learning algorithms were evaluated to build the final predictive model. Following five-fold cross-validation process, XGBoost learning algorithm demonstrated superior performance with LightGBM-chosen 260 KNC features (Accuracy: 74.55 %, auROC: 81.23 %, auPRC: 76.52 %) and 160 PKNC features (Accuracy: 74.32 %, auROC: 81.04 %, auPRC: 76.43 %), over other combinations of learning algorithms and feature selection techniques. Further, the robustness of the developed models were evaluated using an independent test dataset, where the overall accuracy, auROC and auPRC were found to be 73.13 %, 72.34 % and 72.68 % for KNC feature set and 73.52 %, 79.53 % and 73.09 % for PKNC feature set, respectively. This computational approach was also integrated into an online prediction tool, AScirRNA (https://iasri-sg.icar.gov.in/ascirna/) for easy prediction by the users. Both the proposed model and the developed tool are poised to augment ongoing efforts in identifying stress-responsive circRNAs in plants.

Effect of Subsoiling on the Nutritional Quality of Grains of Maize Hybrids of Different Eras.

To achieve high maize (Zea mays L.) yields and quality grain, it is necessary to develop stress-resistant cultivars and related cultivation practices, aiming to maximize efficiency. Thus, our objectives were (i) to investigate the impact of tillage practices and maize hybrids (which have improved over time) on yield and its components, and (ii) to characterize the response pattern of maize hybrid grain nutrient quality components to subsoiling. To achieve this, we conducted field trials with five maize hybrids from different eras under two tillage practices: rotary tillage and subsoiling. We compared grain yield, nutritional quality, and other indicators across different tillage conditions from the 1970s to the 2010s. The main results of this study are as follows: under rotary tillage conditions, the 2010s hybrid (DH618) significantly increased yields (9.37-55.89%) compared to hybrids from the 1970s-2000s. After subsoiling, the physiologically mature grains of all hybrids exhibited minimal changes in crude protein and fat content, while there was a significant reduction in the total soluble sugar content of the grains. After subsoiling, there was a substantial 8.14 to 12.79 percent increase in total starch accumulation in the grain for all hybrids during the period of 47-75 days post-anthesis. Furthermore, during the period of 47-75 days after anthesis, the consumption of grain crude protein significantly contributed to the accumulation of total starch in the grains. Ultimately, subsoiling significantly increased the yield of each hybrid and enhanced the total grain starch content at physiological maturity of all hybrids, with the 2010s hybrid (DH618) performing exceptionally well.

Integrating Omics Approaches for Climate-Resilient Crops: A Comprehensive Review

Climate change is a looming threat to global agriculture, impacting temperature, rainfall patterns, pest dynamics, and soil quality. These challenges transcend numerous crops vital for global food security. Drought, soil acidity, and nutrient fluctuations induced by climate change impede crop productivity, necessitating the development of breeding strategies to produce climate-resilient varieties. This review delves into the integration of omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, to bolster breeding programs across diverse crops. By harnessing high-throughput technologies, researchers gain insights into the genetic and molecular mechanisms underlying traits such as stress resistance, yield, and disease tolerance. The cultivation of elite cultivars with enhanced stress tolerance is paramount for sustainable agriculture in the face of climate change. Various breeding approaches, encompassing functional genomics and mutagenomics, are explored alongside the application of genome editing tools like CRISPR/Cas9 and TALEN for targeted trait enhancement. Through the integration of multi-omics data, novel genetic targets are unearthed, facilitating the development of crop varieties resilient to climate-induced stressors beyond maize. This review underscores the significance of multi-omics in crop breeding and highlights strides made toward climate-resilient crop production. Understanding crop responses to abiotic stresses induced by climate change is imperative for the development of resilient varieties. The integration of modern genetics into classical breeding methods aims to cultivate stress-resistant cultivars, mitigating food security risks. Multi-omics approaches play pivotal roles in unraveling crop performance and stress tolerance mechanisms under diverse environmental conditions. Moving forward, the integration of multi-omics approaches will pinpoint candidate genes and pathways, enabling precision breeding to enhance crop performance amidst changing climates. These endeavors will propel the advancement of climate-resilient crops, safeguarding global food security in the face of climate change's challenges.

Image-based classification of wheat spikes by glume pubescence using convolutional neural networks.

Pubescence is an important phenotypic trait observed in both vegetative and generative plant organs. Pubescent plants demonstrate increased resistance to various environmental stresses such as drought, low temperatures, and pests. It serves as a significant morphological marker and aids in selecting stress-resistant cultivars, particularly in wheat. In wheat, pubescence is visible on leaves, leaf sheath, glumes and nodes. Regarding glumes, the presence of pubescence plays a pivotal role in its classification. It supplements other spike characteristics, aiding in distinguishing between different varieties within the wheat species. The determination of pubescence typically involves visual analysis by an expert. However, methods without the use of binocular loupe tend to be subjective, while employing additional equipment is labor-intensive. This paper proposes an integrated approach to determine glume pubescence presence in spike images captured under laboratory conditions using a digital camera and convolutional neural networks. Initially, image segmentation is conducted to extract the contour of the spike body, followed by cropping of the spike images to an equal size. These images are then classified based on glume pubescence (pubescent/glabrous) using various convolutional neural network architectures (Resnet-18, EfficientNet-B0, and EfficientNet-B1). The networks were trained and tested on a dataset comprising 9,719 spike images. For segmentation, the U-Net model with EfficientNet-B1 encoder was chosen, achieving the segmentation accuracy IoU = 0.947 for the spike body and 0.777 for awns. The classification model for glume pubescence with the highest performance utilized the EfficientNet-B1 architecture. On the test sample, the model exhibited prediction accuracy parameters of F1 = 0.85 and AUC = 0.96, while on the holdout sample it showed F1 = 0.84 and AUC = 0.89. Additionally, the study investigated the relationship between image scale, artificial distortions, and model prediction performance, revealing that higher magnification and smaller distortions yielded a more accurate prediction of glume pubescence.

Genomic assisted breeding and holistic management of abiotic and biotic stress in silkworm host cultivation: A review

Silk is a high-value, low-volume product, produced by an important insect commonly known as the silkworm. Sericulture serves as a source of livelihood for farmers besides being an important source of economy for many countries including India. Sustainable production of premium silk depends on continuous production of quality foliage as feed for silkworms obtained from host plants. The production of silk is significantly hampered when host plants are subjected to biotic and abiotic stresses. The foliage harvest could be enhanced when these constraints are efficiently managed by the development of stress-resistant host cultivars. Improved stress-resistant cultivars have been developed using conventional breeding strategies and used in commercial cultivation. However, the highly heterozygous genetic nature of the hosts makes it difficult to understand the inheritance and expression of these quantitative traits. Adoption of appropriate conventional breeding strategies along with genomics tools such as genome-wide association studies, transcriptomics, proteomics, metabolomics and advanced OMICS approaches could prove handy in the development of improved and stress-resistant cultivars. Deeper understanding of the mechanism of tolerance to various stress is required in breeding for improved cultivars. The number of stress-tolerant cultivars is scanty and therefore, holistic management of these stresses through an inter-disciplinary approach could be the most suitable strategy. Adoption of appropriate cultural practices and control measures is necessary for sustainable production under stress regimes. This comprehensive review holds great importance in improving silkworm host cultivation and to researchers in the field of sericulture.

Major challenges in widespread adaptation of aerobic rice system and potential opportunities for future sustainability

Climate change and diminishing resources are the major challenges in sustainable rice production. The aerobic rice system can be a transformational approach to replace conventional rice in the face of climate change and scarcity of resources due to its high input-use efficiency. However, it could not be adapted widely yet due to several challenges like higher weed infestation and low nitrogen (N) use efficiencies. This transformed system can only be adapted at a wider scale through investigation of associated constraints and risks and provision of potential adjustive measures. Aerobic rice crop failure can be reduced if the availability of suitable and stress-resistant cultivars with early improved vigour, and short-duration characteristics are ensured for maintaining the reproductive capability under resource stressed environment. This transformed rice system exhibits limited response to applied N because of increased losses due to higher volatilization and rapid coupled nitrification-denitrification processes under alternate wetting and drying systems. Shifting from the flooded to aerobic rice system bringing changes in crop water demand, organic matter (OM) turnover, N dynamics, weed flora, and greenhouse gases (GHGs) emissions. Along with N-losses, continuous monocropping, higher weed infestation, weedy rice emergence, nitrous oxide (N2O) emissions, nutrient disorders, higher prevalence of pathogens and diseases, increased panicle sterility, and an increase in soilborne pathogens lodging are other major constraints negatively impacting the widespread adaptation of aerobic rice. This article reviews the climate change status, its associated impacts on the sustainability of traditional rice systems, and the rationale for transforming from traditional to aerobic rice systems. Furthermore, it describes the major challenges associated with the aerobic rice system, thereby presenting management strategies ensuring its wider adaptation for sustainable rice production in the face of projected climate change and scarcity of resources.

Genome-wide identification of Alfin Like (AL) transcription factors and their regulatory role in abiotic stress responses in Poplar (Populus trichocarpa)

Poplar is a valuable natural resource that is extensively utilized to manufacture many types of paper and wood products. It has considerable economic and ecological importance. However, forest dieback caused by environmental stressors has been increasing in recent years. Abiotic stress is managed by the Alfin-like (AL) gene in plants. The highly conserved DUF3594 domain and PHD-finger motif, which belong to the family Alfin-like transcription factors (AL-TFs), are essential for the metabolic and physiological reactions of plants to abiotic stress. Although the environmental stress sensitivity of AL-TFs has not yet been elucidated, these TFs play a vital role in regulating plant growth. We performed a database search and discovered 9 AL TFs. Using the AL-protein sequences from a variety of plant species, gene structures as well as conserved amino acid sequences, cis-elements of promoter regions, and events in the evolution of genes were examined. A phylogenetic tree was constructed and divided into six distinct groups. The expression of PtAL genes was specific to certain organs, and their gene mapping reveled that these genes are situated on seven out of the nineteen chromosomes present in Populus trichocarpa. Moreover, the majority of PtAL genes were strongly expressed in response to abiotic conditions such as low temperature (4 °C), high temperature (39 °C), salt (100 mM NaCl solution), and drought (Water holding). Two PtAL genes (PtAL4 and PtAL6) were sensitive to all abiotic stressors evaluated. The highly expressed PtAL genes (PtAL5 and PtAL7) discovered in this study could be employed in the Populus breeding program to generate stress-resistant cultivars. Our research shows that PtAL genes are very important for plant growth and development and for their ability to cope with environmental stress. This discovery offers valuable insights for improving plant stress tolerance.

Genetic diversity of wild barley (<i>Hordeum spontaneum</i> K. Koch) in the context of resistance to toxic aluminum ions

Background. The problem of resistance to aluminum toxicity of soils is very relevant for the cultivated type of barley. The area of acidic soils in Russia is about forty percent of the total area of arable land, so the toxicity of aluminum is one of the main factors that reduce the yield of barley. The study of wild relatives of the main crops, including barley, is of considerable interest for the development of stress-resistant cultivars. Wild barley Hordeum spontaneum K. Koch has biological characteristics similar to the cultivated H. vulgare L., grows in various ecogeographic zones, and is well adapted to local soil and climate conditions. All this makes it possible to use it as a new donor of source material for breeding high-yielding cultivars adapted to certain environmental conditions. The objective of this work was to search for H. spontaneum genotypes highly resistant to ionic (Al3+) toxicity.Materials and methods. One hundred accessions of H. spontaneum from the collection of the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) were examined. The resistance of barley accessions to toxic aluminum ions was studied at the early stages of plant development by the root test method (185 mcМ Al3+, pH 4.0) with the calculation of root and sprout length indices.Results and conclusions. The studied fragment of the wild barley collection demonstrated broad genetic diversity in terms of resistance to phytotoxic aluminum ions. Laboratory assessment allowed us to identify barley genotypes differing in the reaction of their roots and sprouts at the early phases of ontogenesis. The identified genotypes with a high level of resistance to ion stress can be used as a valuable source of genetic material to improve existing cultivars and develop new ones by introgression of foreign resistance genes.

Multi-omics assisted breeding for biotic stress resistance in soybean.

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

The response to crop health and productivity of field pea (Pisum sativum L.) at different growing conditions

ABSTRACT With increasing the area of legumes one of the most possible risks for productivity limitation is diseases. The research on the response to diseases and productivity of field peas was carried out during 2018–2020. The six cultivars and breeding lines were grown at two different infection levels: at natural field infection and under disease control using seed treatment and foliar fungicides. The main disease in field peas during the research year was Ascochyta blight at different intensites depending on year, cultivar/breeding line and disease control efficacy. Dominating pathogenic fungus D. pisi on harvested grains prevailed. Pea grain yield was significantly affected by cultivar/breeding line, experiments year and growing conditions. The highest yield difference between growing conditions (natural field infection and under disease control) was recorded in 2020 when Ascochyta blight and Grey mould gave the most severe attack. This finding illustrates the importance to eliminate one of the most important limiting factors for productivity – severe diseases. Future research on the forecast system of Ascochyta blight and other field pea diseases infection risk is needed. The response of cultivar/breeding line to weather conditions was established in this research as well. Tested breeding lines showed higher drought stress tolerance compared with commercial cultivars. More focus on environment stress-resistant cultivars is needed.

Genomics Enabled Breeding Strategies for Major Biotic Stresses in Pea (Pisum sativum L.).

Pea (Pisum sativum L.) is one of the most important and productive cool season pulse crops grown throughout the world. Biotic stresses are the crucial constraints in harnessing the potential productivity of pea and warrant dedicated research and developmental efforts to utilize omics resources and advanced breeding techniques to assist rapid and timely development of high-yielding multiple stress-tolerant–resistant varieties. Recently, the pea researcher’s community has made notable achievements in conventional and molecular breeding to accelerate its genetic gain. Several quantitative trait loci (QTLs) or markers associated with genes controlling resistance for fusarium wilt, fusarium root rot, powdery mildew, ascochyta blight, rust, common root rot, broomrape, pea enation, and pea seed borne mosaic virus are available for the marker-assisted breeding. The advanced genomic tools such as the availability of comprehensive genetic maps and linked reliable DNA markers hold great promise toward the introgression of resistance genes from different sources to speed up the genetic gain in pea. This review provides a brief account of the achievements made in the recent past regarding genetic and genomic resources’ development, inheritance of genes controlling various biotic stress responses and genes controlling pathogenesis in disease causing organisms, genes/QTLs mapping, and transcriptomic and proteomic advances. Moreover, the emerging new breeding approaches such as transgenics, genome editing, genomic selection, epigenetic breeding, and speed breeding hold great promise to transform pea breeding. Overall, the judicious amalgamation of conventional and modern omics-enabled breeding strategies will augment the genetic gain and could hasten the development of biotic stress-resistant cultivars to sustain pea production under changing climate. The present review encompasses at one platform the research accomplishment made so far in pea improvement with respect to major biotic stresses and the way forward to enhance pea productivity through advanced genomic tools and technologies.

Identification of Potential Cytokinin Responsive Key Genes in Rice Treated With Trans-Zeatin Through Systems Biology Approach.

Rice is an important staple food grain consumed by most of the population around the world. With climate and environmental changes, rice has undergone a tremendous stress state which has impacted crop production and productivity. Plant growth hormones are essential component that controls the overall outcome of the growth and development of the plant. Cytokinin is a hormone that plays an important role in plant immunity and defense systems. Trans-zeatin is an active form of cytokinin that can affect plant growth which is mediated by a multi-step two-component phosphorelay system that has different roles in various developmental stages. Systems biology is an approach for pathway analysis to trans-zeatin treated rice that could provide a deep understanding of different molecules associated with them. In this study, we have used a weighted gene co-expression network analysis method to identify the functional modules and hub genes involved in the cytokinin pathway. We have identified nine functional modules comprising of different hub genes which contribute to the cytokinin signaling route. The biological significance of these identified hub genes has been tested by applying well-proven statistical techniques to establish the association with the experimentally validated QTLs and annotated by the DAVID server. The establishment of key genes in different pathways has been confirmed. These results will be useful to design new stress-resistant cultivars which can provide sustainable yield in stress-specific conditions.

Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured B. napus Breeding Population.

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, Brassica napus, an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse B. napus breeding population, SKBnNAM, introduced here for the first time. The experiment comprised 50 spring-type B. napus lines, grown and phenotyped in six replicates under two treatment conditions (control and drought) over 38 days in a LemnaTec Scanalyzer 3D facility. Growth traits including plant height, width, projected leaf area, and estimated biovolume were extracted and derived through processing of RGB and NIR images. Anthesis was automatically and accurately scored (97% accuracy) and the number of flowers per plant and day was approximated alongside relevant canopy traits (width, angle). Further, supervised machine learning was used to predict the total number of raceme branches from flower attributes with 91% accuracy (linear regression and Huber regression algorithms) and to identify mild drought stress, a complex trait which typically has to be empirically scored (0.85 area under the receiver operating characteristic curve, random forest classifier algorithm). The study demonstrates the potential of HTP, image processing and computer vision for effective characterization of agronomic trait diversity in B. napus, although limitations of the platform did create significant variation that limited the utility of the data. However, the results underscore the value of machine learning for phenotyping studies, particularly for complex traits such as drought stress resistance.

Genome-wide analysis of potassium transport genes in Gossypium raimondii suggest a role of GrHAK/KUP/KT8, GrAKT2.1 and GrAKT1.1 in response to abiotic stress

Potassium (K+) is an important macro-nutrient for plants, which comprises almost 10% of plant's dry mass. It plays a crucial role in the growth of plants as well as other important processes related to metabolism and stress tolerance. Plants have a complex and well-organized potassium distribution system (channels and transporters). Cotton is the most important economic crop, which is the primary source of natural fiber. Soil deficiency in K+ can negatively affect yield and fiber quality of cotton. However, potassium transport system in cotton is poorly studied. Current study identified 43 Potassium Transport System (PTS) genes in Gossypium raimondii genome. Based on conserved domains, transmembrane domains, and motif structures, these genes were classified as K+ transporters (2 HKTs, 7 KEAs, and 16 KUP/HAK/KTs) and K+ channels (11 Shakers and 7 TPKs/KCO). The phylogenetic comparison of GrPTS genes from Arabidopsis thaliana, Glycine max, Oryza sativa, Medicago truncatula and Cicer arietinum revealed variations in PTS gene conservation. Evolutionary analysis predicted that most GrPTS genes were segmentally duplicated. Gene structure analysis showed that the intron/exon organization of these genes was conserved in specific-family. Chromosomal localization demonstrated a random distribution of PTS genes across all the thirteen chromosomes except chromosome six. Many stress responsive cis-regulatory elements were predicted in promoter regions of GrPTS genes. The RNA-seq data analysis followed by qRT-PCR validation demonstrated that PTS genes potentially work in groups against environmental factors. Moreover, a transporter gene (GrHAK/KUP/KT8) and two channel genes (GrAKT2.1 and GrAKT1.1) are important candidate genes for plant stress response. These results provide useful information for further functional characterization of PTS genes with the breeding aim of stress-resistant cultivars.

Comparative analysis of wild and cultivated Lathyrus L. species to assess their content of sugars, polyols, free fatty acids, and phytosterols.

Under the condition of climate change, the need for crops resistant to abiotic and biotic stresses is increasing. Lathyrus spp. are characterized by a high nutritional value of their green biomass. The grass pea is one of the most resistant to drought, waterlogging, cold, salinity, diseases and pests among cultivated legumes, and it is grown at minimal cost. The creation of new Lathyrus L. sorts with an improved nutrient composition of nutrients will allow to obtain high-quality feed in areas with extremely unstable weather conditions. In this connection, we studied the patterns of variability in the parameters of the carbohydrate complex (sugars, their lactone and methyl forms), polyols (including phenol-containing alcohols), phytosterols, free fatty acids (FFA) and acylglycerols in the green mass of 32 samples of Lathyrus sativus L., L. tuberosus L., L. sylvestris L., L. vernus (L.) Bernh., L. latifolius L., L. linifolius (Reichard) Bassler. from the VIR collection, reproduced in the Leningrad region in contrasting conditions 2012, 2013.The content of identified compounds varied depending on the genotype, species, and weather conditions. High temperatures and high level of precipitation in 2013 contributed to the accumulation of monosaccharides, in more colder and drier conditions in 2012 – oligosaccharides, most of polyols and FFA. The cultivated species (L. sativus) was distinguished by its high sugar content, and the wild species as follows: L. latifolius by FFA; L. linifolius by ononitol, myo-inositol, and glycerol 3-phosphate; L. vernus by MAG and methylpentofuranoside. The species cultivated in culture (L. sativus) was distinguished by a high sugar content, wild species: L. latifolius – by FFA, L. linifolius – ononitol, myo-inositol and glycerol-3-phosphate, L. vernus – MAG and methylpentofuranoside. According to our results, the studied samples are promising for the selection of Lathyrus varieties with high nutrition quality and stress-resistant.

BRIDGE - A Visual Analytics Web Tool for Barley Genebank Genomics.

Genebanks harbor a large treasure trove of untapped plant genetic diversity. A growing world population and a changing climate require an increase in the production and development of stress resistant plant cultivars while decreasing the acreage. These requirements for improved plant cultivars can be supported by the broader exploitation of plant genetic resources (PGR) as inputs for genomics-assisted breeding. To support this process we have developed BRIDGE, a data warehouse and exploratory data analysis tool for genebank genomics of barley (Hordeum vulgare L.). Using efficient technologies for data storage, data transfer and web development, we facilitate access to digital genebank resources of barley by prioritizing the interactive and visual analysis of integrated genotypic and phenotypic data. The underlying data resulted from a barley genebank genomics study cataloging sequence and morphological data of 22,626 barley accessions, mainly from the German Federal ex situ genebank. BRIDGE consists of interactively coupled modules to visualize integrated, curated and quality checked data, such as variation data, results of dimensionality reduction and genome wide association studies (GWAS), phenotyping results, passport data as well as the geographic distribution of germplasm samples. The core component is a manager for custom collections of germplasm. A search module to find and select germplasm by passport and phenotypic attributes is included as well as modules to export genotypic data in gzip-compressed variant call format (VCF) files and phenotypic data in MIAPPE-compliant ISA-Tab files. BRIDGE is accessible at the following URL: https://bridge.ipk-gatersleben.de.

The Use of Proline in Screening for Tolerance to Drought and Salinity in Common Bean (Phaseolus vulgaris L.) Genotypes

The selection of stress-resistant cultivars, to be used in breeding programmes aimed at enhancing the drought and salt tolerance of our major crops, is an urgent need for agriculture in a climate change scenario. In the present study, the responses to water deficit and salt stress treatments, regarding growth inhibition and leaf proline (Pro) contents, were analysed in 47 Phaseolus vulgaris genotypes of different origins. A two-way analysis of variance (ANOVA), Pearson moment correlations and principal component analyses (PCAs) were performed on all measured traits, to assess the general responses to stress of the investigated genotypes. For most analysed growth variables and Pro, the effects of cultivar, treatment and their interactions were highly significant (p < 0.001); the root morphological traits, stem diameter and the number of leaves were mostly due to uncontrolled variation, whereas the variation of fresh weight and water content of stems and leaves was clearly induced by stress. Under our experimental conditions, the average effects of salt stress on plant growth were relatively weaker than those of water deficit. In both cases, however, growth inhibition was mostly reflected in the stress-induced reduction of fresh weight and water contents of stems and leaves. Pro, on the other hand, was the only variable showing a negative correlation with all growth parameters, but particularly with those of stems and leaves mentioned above, as indicated by the Pearson correlation coefficients and the loading plots of the PCAs. Therefore, in common beans, higher stress-induced accumulation of Pro is unequivocally associated with a stronger inhibition of growth; that is, with a higher sensitivity to stress of the corresponding cultivar. We propose the use of Pro as a suitable biochemical marker for simple, rapid, large-scale screenings of bean genotypes, to exclude the most sensitive, those accumulating higher Pro concentrations in response to water or salt stress treatments.

Genome-wide identification of CNGC genes in Chinese jujube (Ziziphus jujuba Mill.) and ZjCNGC2 mediated signalling cascades in response to cold stress

BackgroundsCyclic nucleotide gated channels (CNGCs) play multifaceted roles in plant physiological processes, especially with respect to signalling processes, plant development, and responses to environmental stresses. However, little information is known about the CNGC family in the large cosmopolitan family Rhamnaceae, which has strong tolerance to biotic and abiotic stresses.ResultsIn the current study, a total of 15 ZjCNGCs which located on 7 chromosomes were firstly identified in Chinese jujube (Ziziphus jujuba Mill.), the most important species of Rhamnaceae in terms of economic and ecological values. Phylogenetic analysis showed that these ZjCNGCs could be classified into four groups, ZjCNGC12 belonged to group IVA, and ZjCNGC13, 14, 15 belonged to group IVB. In addition, the paralogous and orthologous homology duplication of ZjCNGC15 occurred during the evolutionary process. The characteristics of ZjCNGCs regarding to exon-intron numbers and post-translational modifications showed diversified structures and functions. Motif composition and protein sequence analysis revealed that the phosphate-binding cassette and hinge regions were conserved among ZjCNGCs. Prediction of the cis-acting regulatory elements and expression profiles by real-time quantitative PCR analysis showed that some of the ZjCNGCs responded to environmental changes, especially ZjCNGC2, which was significantly downregulated in response to cold stress, and ZjCNGC4 was highly induced in response to cold, salt and alkaline stresses. ZjCNGC13 and 14 were highly induced in the phytoplasma-resistant cultivar and downregulated in the susceptible cultivar. Furthermore, ZjCNGC2 could be regulated by cAMP treatment, microtubule changes and interact with ZjMAPKK4, which suggested that cAMP and microtubule might play important roles in ZjCNGC2 mediated ZjMAPKK4 signalling transduction involved in cold stress.ConclusionsThe identification and classification analysis of ZjCNGCs were firstly reported, and some key individual ZjCNGCs might play essential roles in the response to biotic and abiotic stresses, especially ZjCNGC2 mediated ZjMAPKK4 signalling transduction involved in cold stress. This systematic analysis could provide important information for further functional characterization of ZjCNGCs with the aim of breeding stress-resistant cultivars.

Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat.

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_11), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.

GENETIC APPROACHES FOR ENGINEERING BIOTIC STRESS RESISTANCE IN POTATO (Solanum tuberosum L.)

Potato is one of the most important food crops in terms of annual production and food security worldwide. The crop is affected by several types of biotic stresses, e.g. insects, viruses, fungus, nematodes and weeds, which are the prominent limiting factors for its production. The conventional breeding methods in potato have been associated with limitations; none of the present day commercial cultivar has built-in resistance against biotic stresses. There is strong need for the development of new resistant potato varieties to cope against biotic stresses using non-classical approaches in combination with classical methods. The scientific literature suggests the contribution of modern biotechnological techniques for the development of transgenic potato lines resistant against insects and diseases. The present comprehensive review describes different genetic engineering approaches for the development of transgenic potatoes resistant to insects, weeds, nematodes, fungus and viruses by fellow researchers worldwide. It also gives an insight into modern technologies, e.g. RNAi and CRISPR-Cas9, which have emerged recently and can be implemented in the development of biotic stress resistant potato cultivars.