Subtractive hybridization-mediated analysis of genes and in silico prediction of associated microRNAs under waterlogged conditions in sugarcane (Saccharum spp.)

Uncovering waterlogging-responsive genes in cucumber through machine learning and differential gene correlation analysis

As climate change intensifies, the frequency and severity of waterlogging are expected to increase, necessitating a deeper understanding of the cucumber response to this stress. In this study, three public RNA-seq datasets (PRJNA799460, PRJNA844418, and PRJNA678740) comprising 36 samples were analyzed. Various feature selection algorithms including Uncertainty, Relief, SVM (Support Vector Machine), Correlation, and logistic least absolute shrinkage, and selection operator (LASSO) were performed to identify the most significant genes related to the waterlogging stress response. These feature selection techniques, which have different characteristics, were used to reduce the complexity of the data and thereby identify the most significant genes related to the waterlogging stress response. Uncertainty, Relief, SVM, Correlation, and LASSO identified 4, 4, 10, 21, and 13 genes, respectively. Differential gene correlation analysis (DGCA) focusing on the 36 selected genes identified changes in correlation patterns between the selected genes under waterlogged versus control conditions, providing deeper insights into the regulatory networks and interactions among the selected genes. DGCA revealed significant changes in the correlation of 13 genes between control and waterlogging conditions. Finally, we validated 13 genes using the Random Forest (RF) classifier, which achieved 100% accuracy and a 1.0 Area Under the Curve (AUC) score. The SHapley Additive exPlanations (SHAP) values clearly showed the significant impact of LOC101209599, LOC101217277, and LOC101216320 on the model's predictive power. In addition, we employed the Boruta as a wrapper feature selection method to further validate our gene selection strategy. Eight of the 13 genes were common across the four feature weighting algorithms, LASSO, DGCA, and Boruta, underscoring the robustness and reliability of our gene selection strategy. Notably, the genes LOC101209599, LOC101217277, and LOC101216320 were among genes identified by multiple feature selection methods from different categories (filtering, wrapper, and embedded). Pathways associated with these specific genes play a pivotal role in regulating stress tolerance, root development, nutrient absorption, sugar metabolism, gene expression, protein degradation, and calcium signaling. These intricate regulatory mechanisms are crucial for cucumbers to adapt effectively to waterlogging conditions. These findings provide valuable insights for uncovering targets in breeding new cucumber varieties with enhanced stress tolerance.

miRNAs for crop improvement

Climate change significantly impacts crop production by inducing several abiotic and biotic stresses. The increasing world population, and their food and industrial demands require focused efforts to improve crop plants to ensure sustainable food production. Among various modern biotechnological tools, microRNAs (miRNAs) are one of the fascinating tools available for crop improvement. miRNAs belong to a class of small non-coding RNAs playing crucial roles in numerous biological processes. miRNAs regulate gene expression by post-transcriptional target mRNA degradation or by translation repression. Plant miRNAs have essential roles in plant development and various biotic and abiotic stress tolerance. In this review, we provide propelling evidence from previous studies conducted around miRNAs and provide a one-stop review of progress made for breeding stress-smart future crop plants. Specifically, we provide a summary of reported miRNAs and their target genes for improvement of plant growth and development, and abiotic and biotic stress tolerance. We also highlight miRNA-mediated engineering for crop improvement and sequence-based technologies available for the identification of miRNAs associated with stress tolerance and plant developmental events.

iTRAQ Proteomic Analysis of Wheat (Triticum aestivum L.) Genotypes Differing in Waterlogging Tolerance

Transient and chronic waterlogging constrains crop production in many regions of the world. Here, we invoke a novel iTRAQ-based proteomic strategy to elicit protein synthesis and regulation responses to waterlogging in tolerant (XM 55) and sensitive genotypes (YM 158). Of the 7,710 proteins identified, 16 were distinct between the two genotypes under waterlogging, partially defining a proteomic basis for waterlogging tolerance (and sensitivity). We found that 11 proteins were up-regulated and 5 proteins were down-regulated; the former included an Fe-S cluster assembly factor, heat shock cognate 70, GTP-binding protein SAR1A-like and CBS domain-containing protein. Down-regulated proteins contained photosystem II reaction center protein H, carotenoid 9, 10 (9', 10')-cleavage dioxygenase-like, psbP-like protein 1 and mitochondrial ATPase inhibitor. We showed that nine proteins responded to waterlogging with non-cultivar specificity: these included 3-isopropylmalate dehydratase large subunit, solanesyl-diphosphate synthase 2, DEAD-box ATP-dependent RNA helicase 3, and 3 predicted or uncharacterized proteins. Sixteen of the 28 selected proteins showed consistent expression patterns between mRNA and protein levels. We conclude that waterlogging stress may redirect protein synthesis, reduce chlorophyll synthesis and enzyme abundance involved in photorespiration, thus influencing synthesis of other metabolic enzymes. Collectively, these factors accelerate the accumulation of harmful metabolites in leaves in waterlogging-susceptible genotypes. The differentially expressed proteins enumerated here could be used as biological markers for enhancing waterlogging tolerance as part of future crop breeding programs.

MicroRNAs: Potential Targets for Developing Stress-Tolerant Crops

Crop yield is challenged every year worldwide by changing climatic conditions. The forecasted climatic scenario urgently demands stress-tolerant crop varieties to feed the ever-increasing global population. Molecular breeding and genetic engineering approaches have been frequently exploited for developing crops with desired agronomic traits. Recently, microRNAs (miRNAs) have emerged as powerful molecules, which potentially serve as expression markers during stress conditions. The miRNAs are small non-coding endogenous RNAs, usually 20-24 nucleotides long, which mediate post-transcriptional gene silencing and fine-tune the regulation of many abiotic- and biotic-stress responsive genes in plants. The miRNAs usually function by specifically pairing with the target mRNAs, inducing their cleavage or repressing their translation. This review focuses on the exploration of the functional role of miRNAs in regulating plant responses to abiotic and biotic stresses. Moreover, a methodology is also discussed to mine stress-responsive miRNAs from the enormous amount of transcriptome data available in the public domain generated using next-generation sequencing (NGS). Considering the functional role of miRNAs in mediating stress responses, these molecules may be explored as novel targets for engineering stress-tolerant crop varieties.

Characterization of leaf transcriptome, development and utilization of unigenes-derived microsatellite markers in sugarcane (Saccharum sp. hybrid)

Sugarcane (Saccharum species hybrid) is the major source of sugar (> 80% sugar) in the world and is cultivated in more than 115 countries. It has recently gained attention as a source of biofuel (ethanol). Due to genomic complexity, the development of new genomic resources is imperative in understanding the gene regulation and function, and to fine tune the genetic improvement of sugarcane. In this study, a cDNA library was constructed from mature leaves so as to develop ESTs resources which were further compared with nucleotide and protein databases to explore the functional identity of sugarcane genes. The non-redundant ESTs (unigenes) were categorized into 18 metabolic functions. The major categories were bioenergetics and photosynthesis (4%), cell metabolism (5%), development related protein (3%), membrane-related, mobile genetic elements (5%), signal transduction (2%), DNA (1%), RNA (1%) and protein (2%) metabolism, other metabolic processes (3%), transcription factors (1%), transport (4%) and proteins related to stress/defense (4%). From 540 unique ESTs, 212 simple sequence repeats were identified, of which 206 were from 463 singlets and six were mined from 77 contig sequences. A total of 540 unique EST sequences were used for SSR search of which 97 (17.9%) contained specified SSR motifs, generating 212 unique SSRs. The genes characterized in this study and the EST-derived microsatellite markers identified from the cDNA library will enrich genomic resources for association- and linkage-mapping studies in sugarcane.

MicroRNAs and Their Regulatory Role in Sugarcane

Sugarcane, one of the most photosynthetically efficient crops, is an important source of sugar and feedstock for green energy and co-generation. The high level of polyploidy and genomic peculiarities in this crop point towards a complex mechanism of regulation for the economically important traits like sugar content, cane yield related traits, resistance to biotic and abiotic stresses etc. The regulatory pathways for these traits comprise of a number of genes, transcription factors and different categories of RNAs like small interference RNAs (siRNAs), and Micro RNAs (miRNAs). MicroRNAs (miRNAs) are found to play an important regulatory role in many crops. As in other crops, several miRNAs have been identified in sugarcane too and these are speculated to have a role in regulating the various metabolic processes. Role of miRNAs in relation to drought tolerance has been studied to a great extent in this crop. miRNAs have been predicted to be linked to expression of other traits like disease resistance, salinity tolerance, waterlogging and axillary bud growth in sugarcane. miRNAs can have a significant role in biomass production in sugarcane, as reported in several biofuel crops. Till now, miRNAs linked to sugar accumulation have not been identified in sugarcane, but studies suggest an important role for miRNAs in sugar metabolic pathway in crops like Sorghum and switch grass. It is presumed that in sugarcane too, sugar accumulation as well as the other important metabolic pathways might be regulated to some extent by the miRNAs. The review examines the progress made in understanding the miRNA regulation in sugarcane and the extent to which miRNA mediated regulation can be utilized in sugarcane improvement.

Differentially Expressed microRNAs and Target Genes Associated with Plastic Internode Elongation in Alternanthera philoxeroides in Contrasting Hydrological Habitats

Phenotypic plasticity is crucial for plants to survive in changing environments. Discovering microRNAs, identifying their targets and further inferring microRNA functions in mediating plastic developmental responses to environmental changes have been a critical strategy for understanding the underlying molecular mechanisms of phenotypic plasticity. In this study, the dynamic expression patterns of microRNAs under contrasting hydrological habitats in the amphibious species Alternanthera philoxeroides were identified by time course expression profiling using high-throughput sequencing technology. A total of 128 known and 18 novel microRNAs were found to be differentially expressed under contrasting hydrological habitats. The microRNA:mRNA pairs potentially associated with plastic internode elongation were identified by integrative analysis of microRNA and mRNA expression profiles, and were validated by qRT-PCR and 5' RLM-RACE. The results showed that both the universal microRNAs conserved across different plants and the unique microRNAs novelly identified in A. philoxeroides were involved in the responses to varied water regimes. The results also showed that most of the differentially expressed microRNAs were transiently up-/down-regulated at certain time points during the treatments. The fine-scale temporal changes in microRNA expression highlighted the importance of time-series sampling in identifying stress-responsive microRNAs and analyzing their role in stress response/tolerance.

Suppression Subtractive Hybridization Versus Next-Generation Sequencing in Plant Genetic Engineering: Challenges and Perspectives

Suppression subtractive hybridization (SSH) is an effective method to identify different genes with different expression levels involved in a variety of biological processes. This method has often been used to study molecular mechanisms of plants in complex relationships with different pathogens and a variety of biotic stresses. Compared to other techniques used in gene expression profiling, SSH needs relatively smaller amounts of the initial materials, with lower costs, and fewer false positives present within the results. Extraction of total RNA from plant species rich in phenolic compounds, carbohydrates, and polysaccharides that easily bind to nucleic acids through cellular mechanisms is difficult and needs to be considered. Remarkable advancement has been achieved in the next-generation sequencing (NGS) field. As a result of progress within fields related to molecular chemistry and biology as well as specialized engineering, parallelization in the sequencing reaction has exceptionally enhanced the overall read number of generated sequences per run. Currently available sequencing platforms support an earlier unparalleled view directly into complex mixes associated with RNA in addition to DNA samples. NGS technology has demonstrated the ability to sequence DNA with remarkable swiftness, therefore allowing previously unthinkable scientific accomplishments along with novel biological purposes. However, the massive amounts of data generated by NGS impose a substantial challenge with regard to data safe-keeping and analysis. This review examines some simple but vital points involved in preparing the initial material for SSH and introduces this method as well as its associated applications to detect different novel genes from different plant species. This review evaluates general concepts, basic applications, plus the probable results of NGS technology in genomics, with unique mention of feasible potential tools as well as bioinformatics.

Transcriptional profiling in pearl millet (Pennisetum glaucum L.R. Br.) for identification of differentially expressed drought responsive genes

Pearl millet (Pennisetum glaucum) is an important cereal of traditional farming systems that has the natural ability to withstand various abiotic stresses. The present study aims at the identification and validation of major differentially expressed genes in response to drought stress in P. glaucum by Suppression Subtractive Hybridization (SSH) analysis. Twenty-two days old seedlings of P. glaucum cultivar PPMI741 were subjected to drought stress by treatment of 30 % Polyethylene glycol for different time periods 30 min (T1), 2 h (T2), 4 h (T3), 8 h (T4), 16 h (T5), 24 h (T6) and 48 h (T7) respectively, monitored by examining the RWC of seedlings. Total RNA was isolated to construct drought responsive subtractive cDNA library through SSH, sequenced to identify the differentially expressed genes in response to drought stress and validated by qRT-PCR.745 ESTs were assembled into a collection of 299 unigenes having 52 contigs and 247 singletons. All 745 ESTs were submitted to ENA-EMBL databases (Accession no. HG516611- HG517355). After analysis, 10 differentially expressed genes were validated namely Abscisic stress ripening protein, Ascorbate peroxidase, Inosine-5'-monophosphate dehydrogenase, Putative beta-1, 3-glucanase, Glyoxalase, Rab7, Aspartic proteinase Oryzasin, DnaJ-like protein and Calmodulin-like protein by qRT-PCR. The identified ESTs reveal a major portion of the stress responsive transcriptome that may prove to be a vent to unravel molecular basis underlying tolerance of pearl millet (Pennisetum glaucum) to drought stress. These genes could be utilized for transgenic breeding or transferred to crop plants through marker assisted selection for the development of better drought resistant cultivars having enhanced adaptability to survive harsh environmental conditions.