Role of bioinformatics in establishing microRNAs as modulators of abiotic stress responses: the new revolution

An intelligent model for prediction of abiotic stress-responsive microRNAs in plants using statistical moments based features and ensemble approaches

This study proposed an intelligent model for predicting abiotic stress-responsive microRNAs in plants. MicroRNAs (miRNAs) are short RNA molecules regulates the stress in genes. Experimental methods are costly and time-consuming, as compare to in-silico prediction. Addressing this gap, the study seeks to develop an efficient computational model for plant stress response prediction. The two benchmark datasets for MiRNA and Pre-MiRNA dataset have been acquired in this study. Four ensemble approaches such as bagging, boosting, stacking, and blending have been employed. Classifiers such as Random Forest (RF), Extra Trees (ET), Ada Boost (ADB), Light Gradient Boosting Machine (LGBM), and Support Vector Machine (SVM). Stacking and Blending employed all stated classifiers as base learners and Logistic Regression (LR) as Meta Classifier. There have been a total of four types of testing used, including independent set, self-consistency, cross-validation with 5 and 10 folds, and jackknife. This study has utilized evaluation metrics such as accuracy score, specificity, sensitivity, Mathew's correlation coefficient (MCC), and AUC. Our proposed methodology has outperformed existing state of the art study in both datasets based on independent set testing. The SVM-based approach has exhibited accuracy score of 0.659 for the MiRNA dataset, which is better than the previous study. The ET classifier has surpassed the accuracy of Pre-MiRNA dataset as compared to the existing benchmark study, achieving an impressive score of 0.67. The proposed method can be used in future research to predict abiotic stresses in plants.

Predicting abiotic stress-responsive miRNA in plants based on multi-source features fusion and graph neural network

BACKGROUND

More and more studies show that miRNA plays a crucial role in plants' response to different abiotic stresses. However, traditional experimental methods are often expensive and inefficient, so it is important to develop efficient and economical computational methods. Although researchers have developed machine learning-based method, the information of miRNAs and abiotic stresses has not been fully exploited. Therefore, we propose a novel approach based on graph neural networks for predicting potential miRNA-abiotic stress associations.

RESULTS

In this study, we fully considered the multi-source feature information from miRNAs and abiotic stresses, and calculated and integrated the similarity network of miRNA and abiotic stress from different feature perspectives using multiple similarity measures. Then, the above multi-source similarity network and association information between miRNAs and abiotic stresses are effectively fused through heterogeneous networks. Subsequently, the Restart Random Walk (RWR) algorithm is employed to extract global structural information from heterogeneous networks, providing feature vectors for miRNA and abiotic stress. After that, we utilized the graph autoencoder based on GIN (Graph Isomorphism Networks) to learn and reconstruct a miRNA-abiotic stress association matrix to obtain potential miRNA-abiotic stress associations. The experimental results show that our model is superior to all known methods in predicting potential miRNA-abiotic stress associations, and the AUPR and AUC metrics of our model achieve 98.24% and 97.43%, respectively, under five-fold cross-validation.

CONCLUSIONS

The robustness and effectiveness of our proposed model position it as a valuable approach for advancing the field of miRNA-abiotic stress association prediction.

ASmiR: a machine learning framework for prediction of abiotic stress-specific miRNAs in plants

Abiotic stresses have become a major challenge in recent years due to their pervasive nature and shocking impacts on plant growth, development, and quality. MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of specific abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational model for prediction of miRNAs associated with four specific abiotic stresses such as cold, drought, heat and salt. The pseudo K-tuple nucleotide compositional features of Kmer size 1 to 5 were used to represent miRNAs in numeric form. Feature selection strategy was employed to select important features. With the selected feature sets, support vector machine (SVM) achieved the highest cross-validation accuracy in all four abiotic stress conditions. The highest cross-validated prediction accuracies in terms of area under precision-recall curve were found to be 90.15, 90.09, 87.71, and 89.25% for cold, drought, heat and salt respectively. Overall prediction accuracies for the independent dataset were respectively observed 84.57, 80.62, 80.38 and 82.78%, for the abiotic stresses. The SVM was also seen to outperform different deep learning models for prediction of abiotic stress-responsive miRNAs. To implement our method with ease, an online prediction server "ASmiR" has been established at https://iasri-sg.icar.gov.in/asmir/ . The proposed computational model and the developed prediction tool are believed to supplement the existing effort for identification of specific abiotic stress-responsive miRNAs in plants.

ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo K-Tuple Nucleotide Compositional Features

MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set were 62.33, 64.85, 69.21 percentages, respectively, for the three datasets. The SVM also achieved higher accuracy than other learning methods such as random forest, extreme gradient boosting, and adaptive boosting. To implement our method with ease, an online prediction server “ASRmiRNA” has been developed. The proposed approach is believed to supplement the existing effort for identification of abiotic stress-responsive miRNAs and Pre-miRNAs.

Serotonin and Melatonin Biosynthesis in Plants: Genome-Wide Identification of the Genes and Their Expression Reveal a Conserved Role in Stress and Development

Serotonin (Ser) and melatonin (Mel) serve as master regulators of plant growth and development by influencing diverse cellular processes. The enzymes namely, tryptophan decarboxylase (TDC) and tryptamine 5-hydroxylase (T5H) catalyse the formation of Ser from tryptophan. Subsequently, serotonin N-acetyl transferase (SNAT) and acetyl-serotonin methyltransferase (ASMT) form Mel from Ser. Plant genomes harbour multiple genes for each of these four enzymes, all of which have not been identified. Therefore, to delineate information regarding these four gene families, we carried out a genome-wide analysis of the genes involved in Ser and Mel biosynthesis in Arabidopsis, tomato, rice and sorghum. Phylogenetic analysis unravelled distinct evolutionary relationships among these genes from different plants. Interestingly, no gene family except ASMTs showed monocot- or dicot-specific clustering of respective proteins. Further, we observed tissue-specific, developmental and stress/hormone-mediated variations in the expression of the four gene families. The light/dark cycle also affected their expression in agreement with our quantitative reverse transcriptase-PCR (qRT-PCR) analysis. Importantly, we found that miRNAs (miR6249a and miR-1846e) regulated the expression of Ser and Mel biosynthesis under light and stress by influencing the expression of OsTDC5 and OsASMT18, respectively. Thus, this study may provide opportunities for functional characterization of suitable target genes of the Ser and Mel pathway to decipher their exact roles in plant physiology.

Comprehensive analysis of the isomiRome in the vegetative organs of the conifer Pinus pinaster under contrasting water availability

An increasing number of microRNAs (miRNAs) and miRNA-related sequences produced during miRNA biogenesis, comprising the isomiRome, have been recently highlighted in different species as critical mediators of environmental stress responses. Conifers have some of the largest known genomes but an extensive characterization of the isomiRome from any conifer species has been lacking. We provide here a comprehensive overview of the Pinus pinaster isomiRome expressed in roots, stem and needles under well-watered and drought conditions. From the 13,441 unique small RNA sequences identified, 2,980 were annotated as canonical miRNAs or miRNA* and the remaining were classified as isomiRNA or miRNA-like sequences. A survey of their expression patterns highlighted roots as the most responsive organ under drought, where specific sequences of which a 24-nt novel miRNA stood out, were strongly down-regulated. Given the putative roles of the miRNA-targeted transcripts validated specifically in root tissues, some of the miRNAs, conserved and novel, are shortlisted as potential regulators of drought response. These results provide a valuable resource for comparative studies between gymnosperms and angiosperms. Furthermore, it evidences high transferability of the isomiRome between pine species being a useful basis for further molecular regulation and physiological studies, and especially those focused on adaptation to drought conditions.

Differences in toxicity, mitochondrial function and miRNome in human cells exposed in vitro to Cd as CdS quantum dots or ionic Cd

Cadmium is toxic to humans, although Cd-based quantum dots exerts less toxicity. Human hepatocellular carcinoma cells (HepG2) and macrophages (THP-1) were exposed to ionic Cd, Cd(II), and cadmium sulfide quantum dots (CdS QDs), and cell viability, cell integrity, Cd accumulation, mitochondrial function and miRNome profile were evaluated. Cell-type and Cd form-specific responses were found: CdS QDs affected cell viability more in HepG2 than in THP-1; respective IC₂₀ values were ∼3 and ∼50 μg ml^-1. In both cell types, Cd(II) exerted greater effects on viability. Mitochondrial membrane function in HepG2 cells was reduced 70 % with 40 μg ml^-1 CdS QDs but was totally inhibited by Cd(II) at corresponding amounts. In THP-1 cells, CdS QDs has less effect on mitochondrial function; 50 μg ml^-1 CdS QDs or equivalent Cd(II) caused 30 % reduction or total inhibition, respectively. The different in vitro effects of CdS QDs were unrelated to Cd uptake, which was greater in THP-1 cells. For both cell types, changes in the expression of miRNAs (miR-222, miR-181a, miR-142-3p, miR-15) were found with CdS QDs, which may be used as biomarkers of hazard nanomaterial exposure. The cell-specific miRNome profiles were indicative of a more conservative autophagic response in THP-1 and as apoptosis as in HepG2.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Overview of microRNA-199a Regulation in Cancer

microRNAs (miRNAs) are a class of endogenous short, non-coding RNAs that regulate a multitude of genes at the post-transcriptional level. miR-199, which is a highly conserved miRNA family, consists of miR-199a and miR-199b. Researchers mainly focused on miR-199a over the past few years. Functional studies have demonstrated that mature miR-199a is a key player in the maintenance of normal homeostasis and in the regulation of disease pathogenesis. Here, we summarize the biological functions of miR-199a and review recent research on its roles in the physiological processes of cancer cells, such as proliferation, migration, invasion, apoptosis, autophagy and glycometabolism.

miRNomes involved in imparting thermotolerance to crop plants

Thermal stress is one of the challenges to crop plants that negatively impacts crop yield. To overcome this ever-growing problem, utilization of regulatory mechanisms, especially microRNAs (miRNAs), that provide efficient and precise regulation in a targeted manner have been found to play determining roles. Besides their roles in plant growth and development, many recent studies have shown differential regulation of several miRNAs during abiotic stresses including heat stress (HS). Thus, understanding the underlying mechanism of miRNA-mediated gene expression during HS will enable researchers to exploit this regulatory mechanism to address HS responses. This review focuses on the miRNAs and regulatory networks that were involved in physiological, metabolic and morphological adaptations during HS in plant, specifically in crops. Illustrated examples including, the miR156-SPL, miR169-NF-YA5, miR395-APS/AST, miR396-WRKY, etc., have been discussed in specific relation to the crop plants. Further, we have also discussed the available plant miRNA databases and bioinformatics tools useful for miRNA identification and study of their regulatory role in response to HS. Finally, we have briefly discussed the future prospects about the miRNA-related mechanisms of HS for improving thermotolerance in crop plants.

Transcriptional regulation of osmotic stress tolerance in wheat (Triticum aestivum L.)

The current review provides an updated, new insights into the regulation of transcription mediated underlying mechanisms of wheat plants to osmotic stress perturbations. Osmotic stress tolerance mechanisms being complex are governed by multiple factors at physiological, biochemical and at the molecular level, hence approaches like "OMICS" that can underpin mechanisms behind osmotic tolerance in wheat is of paramount importance. The transcription factors (TFs) are a class of molecular proteins, which are involved in regulation, modulation and orchestrating the responses of plants to a variety of environmental stresses. Recent reports have provided novel insights on the role of TFs in osmotic stress tolerance via direct molecular links. However, our knowledge on the regulatory role TFs during osmotic stress tolerance in wheat remains limited. The present review in its first part sheds light on the importance of studying the role of osmotic stress tolerance in wheat plants and second aims to decipher molecular mechanisms of TFs belonging to several classes, including DREB, NAC, MYB, WRKY and bHLH, which have been reported to engage in osmotic stress mediated gene expression in wheat and third part covers the systems biology approaches to understand the transcriptional regulation of osmotic stress and the role of long non-coding RNAs in response to osmotic stress with special emphasis on wheat. The current concept may lead to an understanding in molecular regulation and signalling interaction of TFs under osmotic stress to clarify challenges and problems for devising potential strategies to improve complex regulatory events involved in plant tolerance to osmotic stress adaptive pathways in wheat.

ARMOUR - A Rice miRNA: mRNA Interaction Resource

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

Identification and comparative analysis of microRNAs from tomato varieties showing contrasting response to ToLCV infections

Increasing incidence of viral infections in crop plants adversely affects their growth and yield. Tomato (Solanum lycopersicum) is considered to be a favorite host for viruses with over 50 species of begomoviruses naturally infecting this crop. Tomato leaf curl virus (ToLCV) is among the most widespread and devastating begomoviruses affecting tomato production. microRNAs (miRs) have been established as key regulators of gene expression and plant development. The miR pathways are disturbed during infection by viruses. Thus, comprehension of regulatory miR networks is crucial in understanding the effect of viral pathogenicity. To identify key miRs involved in ToLCV infection, a high throughput approach involving next generation sequencing was employed. Healthy and infected leaf tissues of two tomato varieties, differing in their susceptibility to ToLCV infection were analyzed. NGS data analysis followed by computational predictions, led to identification of 91 known miRs, 15 novel homologs and 53 novel miRs covering two different varieties of tomato, susceptible (Pusa Ruby) and tolerant (LA1777) to ToLCV infection. The cleaved targets of these miRs were identified using online available degradome libraries from leaf, flower and fruit of tomato and showed their involvement in various biological pathways through KEGG Orthology. With detailed comparative profiling of expression pattern of these miRs, we could associate the specific miRs with the resistant and infected genotypes. This study depicted that in depth analysis of miR expression patterns and their functions will help in identification of molecules that can be used for manipulation of gene expression to increase crop production and developing resistance against diseases.

Mapping the microRNA Expression Profiles in Glyoxalase Over-expressing Salinity Tolerant Rice

In the recent years, glyoxalase pathway has been an active area of research in both human and plants. This pathway is reported to confer stress tolerance in plants, by modulating the glutathione homeostasis to achieve detoxification of a potent cytotoxic and mutagenic compound, methylglyoxal. The microRNAs (miRNAs) are also reported to play significant role in stress tolerance for plants. However, the cross-talk of miRNAs with the metabolism regulated by glyoxalase in the salinity-tolerance is unexplored. We therefore investigated whether expression profiles of miRNAs are altered in response to glyoxalase overexpression, and if any of these are also responsible for modulating the stress responses of plants. In this study, the Next Generation Sequencing (NGS) was employed to profile miRNA expression levels from glyoxalase overexpressing transgenic lines. The associated targets of differentially expressed miRNAs were predicted and their functional annotation was carried out using Gene Ontology (GO) and KEGG Orthology (KO), which showed their involvement in several crucial biological pathways. The analysis of NGS datasets also identified other isoforms or isomiRs of selected miRNAs, which may have an active role in developing tolerance against salt stress. Different aspects of miRNA modifications were also studied in glyoxalase overexpressing lines.

Plant small RNAs: the essential epigenetic regulators of gene expression for salt-stress responses and tolerance

Saline environment cues distort the plant growth, development and crop yield. Epigenetics has emerged as one of the prime themes in plant functional genomics for molecular-stress-physiology research, as copious studies have provided new visions into the epigenetic control of stress adaptations. The epigenetic control is associated with the regulation of the expression of stress-related genes which also comprises many steady alterations inherited in next cellular generation as stress memory. These epigenetic amendments also implicate induction of small RNA (sRNA)-mediated fine-tuning of transcriptional and post-transcriptional regulations of gene expression. These tiny (19-24 nt) RNA species, particularly microRNAs (miRNAs) besides endogenous small interfering RNA (siRNA) have emerged as important responsive entities for epigenetic modulation of salt-stress effects on plants. There is a recent upsurge in development of tools and databases useful for prediction, identification and validation of small RNAs (sRNAs) and their target messenger RNAs (mRNAs). Therefore, these small but key regulatory molecules have received a wide attention in post-genomic era as potential targets for engineering stress tolerance in major glycophytic crops, though it is yet to be explored optimally. This review aims to provide critical updates on plant sRNAs as key epigenetic regulators of plant salt-stress responses, their target prediction and validation, computational tools and databases available for plant small RNAs, besides discussing their roles in salt-stress regulatory networks and adaptive mechanisms in plants, with special emphasis on their exploration for engineering salinity tolerance in plants.

The miR172c-NNC1 module modulates root plastic development in response to salt in soybean

BACKGROUND

Plant roots are highly plastic to high salinity. However, the molecular mechanism by which root developmental plasticity is regulated remains largely unknown. Previously we reported that miR172c-NNC1 module plays a key role in soybean-rhizobial symbiosis. The fact that the miR172c promoter contains several stress-related cis elements indicates that miR172c may have a role in root response to abiotic stress.

RESULTS

Here we showed that miR172c is greatly induced by salt stress in soybean. Overexpression of miR172c and knockdown of miR172c activity resulted in substantially increased and reduced root sensitivity to salt stress, respectively. Furthermore, we show that the target gene NNC1 (Nodule Number Control 1) of miR172c was downregulated by salt stress. The transgenic roots overexpressing or knocking down NNC1 expression also exhibited the altered root sensitivity to salt stress.

CONCLUSION

The study reveals the crucial role of miR172c-NNC1 module in root stress tolerance to salt stress in soybean.

Uncovering microRNA-mediated response to SO2 stress in Arabidopsis thaliana by deep sequencing

Sulfur dioxide (SO2) is a major air pollutant and has significant impacts on plants. MicroRNAs (miRNAs) are a class of gene expression regulators that play important roles in response to environmental stresses. In this study, deep sequencing was used for genome-wide identification of miRNAs and their expression profiles in response to SO2 stress in Arabidopsis thaliana shoots. A total of 27 conserved miRNAs and 5 novel miRNAs were found to be differentially expressed under SO2 stress. qRT-PCR analysis showed mostly negative correlation between miRNA accumulation and target gene mRNA abundance, suggesting regulatory roles of these miRNAs during SO2 exposure. The target genes of SO2-responsive miRNAs encode transcription factors and proteins that regulate auxin signaling and stress response, and the miRNAs-mediated suppression of these genes could improve plant resistance to SO2 stress. Promoter sequence analysis of genes encoding SO2-responsive miRNAs showed that stress-responsive and phytohormone-related cis-regulatory elements occurred frequently, providing additional evidence of the involvement of miRNAs in adaption to SO2 stress. This study represents a comprehensive expression profiling of SO2-responsive miRNAs in Arabidopsis and broads our perspective on the ubiquitous regulatory roles of miRNAs under stress conditions.

Synthetic strategies for plant signalling studies: molecular toolbox and orthogonal platforms

Plants deploy a wide array of signalling networks integrating environmental cues with growth, defence and developmental responses. The high level of complexity, redundancy and connection between several pathways hampers a comprehensive understanding of involved functional and regulatory mechanisms. The implementation of synthetic biology approaches is revolutionizing experimental biology in prokaryotes, yeasts and animal systems and can likewise contribute to a new era in plant biology. This review gives an overview on synthetic biology approaches for the development and implementation of synthetic molecular tools and techniques to interrogate, understand and control signalling events in plants, ranging from strategies for the targeted manipulation of plant genomes up to the spatiotemporally resolved control of gene expression using optogenetic approaches. We also describe strategies based on the partial reconstruction of signalling pathways in orthogonal platforms, like yeast, animal and in vitro systems. This allows a targeted analysis of individual signalling hubs devoid of interconnectivity with endogenous interacting components. Implementation of the interdisciplinary synthetic biology tools and strategies is not exempt of challenges and hardships but simultaneously most rewarding in terms of the advances in basic and applied research. As witnessed in other areas, these original theoretical-experimental avenues will lead to a breakthrough in the ability to study and comprehend plant signalling networks.

MicroRNAs As Potential Targets for Abiotic Stress Tolerance in Plants

The microRNAs (miRNAs) are small (20-24 nt) sized, non-coding, single stranded riboregulator RNAs abundant in higher organisms. Recent findings have established that plants assign miRNAs as critical post-transcriptional regulators of gene expression in sequence-specific manner to respond to numerous abiotic stresses they face during their growth cycle. These small RNAs regulate gene expression via translational inhibition. Usually, stress induced miRNAs downregulate their target mRNAs, whereas, their downregulation leads to accumulation and function of positive regulators. In the past decade, investigations were mainly aimed to identify plant miRNAs, responsive to individual or multiple environmental factors, profiling their expression patterns and recognizing their roles in stress responses and tolerance. Altered expressions of miRNAs implicated in plant growth and development have been reported in several plant species subjected to abiotic stress conditions such as drought, salinity, extreme temperatures, nutrient deprivation, and heavy metals. These findings indicate that miRNAs may hold the key as potential targets for genetic manipulations to engineer abiotic stress tolerance in crop plants. This review is aimed to provide recent updates on plant miRNAs, their biogenesis and functions, target prediction and identification, computational tools and databases available for plant miRNAs, and their roles in abiotic stress-responses and adaptive mechanisms in major crop plants. Besides, the recent case studies for overexpressing the selected miRNAs for miRNA-mediated enhanced abiotic stress tolerance of transgenic plants have been discussed.