CropCircDB: a comprehensive circular RNA resource for crops in response to abiotic stress

Role of non-coding RNAs in quality improvement of horticultural crops: computational tools, databases, and algorithms for identification and analysis

Horticultural crops, including fruits, vegetables, flowers, and herbs, are essential for food security and economic sustainability. Advances in biotechnology, including genetic modification and omics approaches, have significantly improved these crops'traits. While initial transgenic efforts focused on protein-coding genes, recent research highlights the crucial roles of non-coding RNAs (ncRNAs) in plant growth, development, and gene regulation. ncRNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), influence key biological processes through transcriptional and post-transcriptional regulation. This review explores the classification, functions, and regulatory mechanisms of ncRNAs, emphasizing their potential in enhancing horticultural crop quality. This growing understanding offers promising avenues for enhancing crop performance and developing new horticultural varieties with improved traits. Additionally, we elucidate the role of ncRNA databases and predictive bioinformatics tools into modern horticultural crop improvement strategies.

PlantCircRNA: a comprehensive database for plant circular RNAs

Circular RNAs (circRNAs) represent recently discovered novel regulatory non-coding RNAs. While they are present in many eukaryotes, there has been limited research on plant circRNAs. We developed PlantCircRNA (https://plant.deepbiology.cn/PlantCircRNA/) to fill this gap. The two most important features of PlantCircRNA are (i) it incorporates circRNAs from 94 plant species based on 39 245 RNA-sequencing samples and (ii) it imports the original AtCircDB and CropCircDB databases. We manually curated all circRNAs from published articles, and imported them into the database. Furthermore, we added detailed information of tissue as well as abiotic stresses to the database. To help users understand these circRNAs, the database includes a detection score to measure their consistency and a naming system following the guidelines recently proposed for eukaryotes. Finally, we developed a comprehensive platform for users to visualize, analyze, and download data regarding specific circRNAs. This resource will serve as a home for plant circRNAs and provide the community with unprecedented insights into these mysterious molecule.

Confronting the data deluge: How artificial intelligence can be used in the study of plant stress

The advent of the genomics era enabled the generation of high-throughput data and computational methods that serve as powerful hypothesis-generating tools to understand the genomic and gene functional basis of plant stress resilience. The proliferation of experimental and analytical methods used in biology has resulted in a situation where plentiful data exists, but the volume and heterogeneity of this data has made analysis a significant challenge. Current advanced deep-learning models have displayed an unprecedented level of comprehension and problem-solving ability, and have been used to predict gene structure, function and expression based on DNA or protein sequence, and prominently also their use in high-throughput phenomics in agriculture. However, the application of deep-learning models to understand gene regulatory and signalling behaviour is still in its infancy. We discuss in this review the availability of data resources and bioinformatic tools, and several applications of these advanced ML/AI models in the context of plant stress response, and demonstrate the use of a publicly available LLM (ChatGPT) to derive a knowledge graph of various experimental and computational methods used in the study of plant stress. We hope this will stimulate further interest in collaboration between computer scientists, computational biologists and plant scientists to distil the deluge of genomic, transcriptomic, proteomic, metabolomic and phenomic data into meaningful knowledge that can be used for the benefit of humanity.

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.

CircRNA: An emerging star in plant research: A review

CircRNAs are a class of covalently closed non-coding RNA formed by linking the 5' terminus and the 3' terminus after reverse splicing. CircRNAs are widely found in eukaryotes, and they are highly conserved, with spatio-temporal expression specificity and stability. CircRNAs can act as miRNA sponges to regulate the expression of downstream target genes, regulating the transcription of parental genes and some can even be translated into peptides or proteins. Research on circRNAs in plants is still in its infancy compared to that in animals. With the deepening of research, the results of a variety of plant circRNAs suggest that they play an important role in growth and development, and tolerance towards abiotic stresses such as salt, drought, low temperature, high temperature and other adverse environments. In this review paper, we elaborated the molecular characteristics, mechanism of action, function and bioinformatics databases of plant circRNAs, combined with the progress of circRNA research in animals, discussed the potential mechanism of action of plant circRNAs, and proposed the unsolved problems and prospects for future application of plant circRNAs.

Computational approaches and challenges in the analysis of circRNA data

Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.

Role of non-coding RNAs against salinity stress in Oryza species: Strategies and challenges in analyzing miRNAs, tRFs and circRNAs

Salinity is an imbalanced concentration of mineral salts in the soil or water that causes yield loss in salt-sensitive crops. Rice plant is vulnerable to soil salinity stress at seedling and reproductive stages. Different non-coding RNAs (ncRNAs) post-transcriptionally regulate different sets of genes during different developmental stages under varying salinity tolerance levels. While microRNAs (miRNAs) are well known small endogenous ncRNAs, tRNA-derived RNA fragments (tRFs) are an emerging class of small ncRNAs derived from tRNA genes with a demonstrated regulatory role, like miRNAs, in humans but unexplored in plants. Circular RNA (circRNA), another ncRNA produced by back-splicing events, acts as target mimics by preventing miRNAs from binding with their target mRNAs, thereby reducing the miRNA's action upon its target. Same may hold true between circRNAs and tRFs. Hence, the work done on these ncRNAs was reviewed and no reports were found for circRNAs and tRFs under salinity stress in rice, either at seedling or reproductive stages. Even the reports on miRNAs are restricted to seedling stage only, in spite of severe effects on rice crop production due to salt stress during reproductive stage. Moreover, this review sheds light on strategies to predict and analyze these ncRNAs in an effective manner.

Intron-capture RNA-seq reveals the landscape of intronic RNAs in Arabidopsis

Intronic RNAs have been overlooked for a long time: They are functional, but treated as "junk." In this work, we designed a new sequencing strategy to investigate intronic RNAs. By using intron-capture RNA-seq, we systematically analyzed the intronic RNAs in Arabidopsis by zooming into the intronic regions an order of magnitude deeper than in previous work. Our key findings include: (1) Intron-capture RNA-seq is a much more efficient approach to analyze intronic RNAs than total RNA-seq and mRNA-seq. (2) We identified three types of intronic RNAs, and found that the GC pattern differs significantly between the introns with and without intronic RNAs. (3) We detected many hidden elements in introns, including circular RNAs, splice junctions, and transcripts that have previously been overlooked. (4) The expression of these intronic RNAs varies during the time course of pathogen infection, which indicates that an unknown mechanism may exist for these RNAs. (5) We also demonstrated that most of intronic RNAs are detectable in both Arabidopsis and rice, suggesting that these non-coding molecules are conserved. Taken together, this work proposes an efficient strategy to analyze intronic RNAs, and provides an unprecedented view of this essential component in biological pathways.

Beyond transcription factors: more regulatory layers affecting soybean gene expression under abiotic stress

Abiotic stresses such as nutritional imbalance, salt, light intensity, and high and low temperatures negatively affect plant growth and development. Through the course of evolution, plants developed multiple mechanisms to cope with environmental variations, such as physiological, morphological, and molecular adaptations. Epigenetic regulation, transcription factor activity, and post-transcriptional regulation operated by RNA molecules are mechanisms associated with gene expression regulation under stress. Epigenetic regulation, including histone and DNA covalent modifications, triggers chromatin remodeling and changes the accessibility of transcription machinery leading to alterations in gene activity and plant homeostasis responses. Soybean is a legume widely produced and whose productivity is deeply affected by abiotic stresses. Many studies explored how soybean faces stress to identify key elements and improve productivity through breeding and genetic engineering. This review summarizes recent progress in soybean gene expression regulation through epigenetic modifications and circRNAs pathways, and points out the knowledge gaps that are important to study by the scientific community. It focuses on epigenetic factors participating in soybean abiotic stress responses, and chromatin modifications in response to stressful environments and draws attention to the regulatory potential of circular RNA in post-transcriptional processing.

Identification, biogenesis, function, and mechanism of action of circular RNAs in plants

Circular RNAs (circRNAs) are a class of single-stranded, closed RNA molecules with unique functions that are ubiquitously expressed in all eukaryotes. The biogenesis of circRNAs is regulated by specific cis-acting elements and trans-acting factors in humans and animals. circRNAs mainly exert their biological functions by acting as microRNA sponges, forming R-loops, interacting with RNA-binding proteins, or being translated into polypeptides or proteins in human and animal cells. Genome-wide identification of circRNAs has been performed in multiple plant species, and the results suggest that circRNAs are abundant and ubiquitously expressed in plants. There is emerging compelling evidence to suggest that circRNAs play essential roles during plant growth and development as well as in the responses to biotic and abiotic stress. However, compared with recent advances in human and animal systems, the roles of most circRNAs in plants are unclear at present. Here we review the identification, biogenesis, function, and mechanism of action of plant circRNAs, which will provide a fundamental understanding of the characteristics and complexity of circRNAs in plants.

CircRNA: a rising star in plant biology

Circular RNAs (circRNAs) are covalently closed single-stranded RNA molecules, which are widespread in eukaryotic cells. As regulatory molecules, circRNAs have various functions, such as regulating gene expression, binding miRNAs or proteins, and being translated into proteins, which are important for cell proliferation and cell differentiation, individual growth and development, as well as many other biological processes. However, compared with that in animal models, studies of circRNAs in plants lags behind and, particularly, the regulatory mechanisms of biogenesis and molecular functions of plant circRNAs remain elusive. Recent studies have shown that circRNAs are wide spread in plants with tissue- or development-specific expression patterns and are responsive to a variety of environmental stresses. In this review, we summarize these advances, focusing on the regulatory mechanisms of biogenesis, molecular and biological functions of circRNAs, and the methods for investigating circRNAs. We also discuss the challenges and the prospects of plant circRNA studies.

Genomics and transcriptomics to protect rice (Oryza sativa. L.) from abiotic stressors: -pathways to achieving zero hunger

More over half of the world's population depends on rice as a major food crop. Rice (Oryza sativa L.) is vulnerable to abiotic challenges including drought, cold, and salinity since it grown in semi-aquatic, tropical, or subtropical settings. Abiotic stress resistance has bred into rice plants since the earliest rice cultivation techniques. Prior to the discovery of the genome, abiotic stress-related genes were identified using forward genetic methods, and abiotic stress-tolerant lines have developed using traditional breeding methods. Dynamic transcriptome expression represents the degree of gene expression in a specific cell, tissue, or organ of an individual organism at a specific point in its growth and development. Transcriptomics can reveal the expression at the entire genome level during stressful conditions from the entire transcriptional level, which can be helpful in understanding the intricate regulatory network relating to the stress tolerance and adaptability of plants. Rice (Oryza sativa L.) gene families found comparatively using the reference genome sequences of other plant species, allowing for genome-wide identification. Transcriptomics via gene expression profiling which have recently dominated by RNA-seq complements genomic techniques. The identification of numerous important qtl,s genes, promoter elements, transcription factors and miRNAs involved in rice response to abiotic stress was made possible by all of these genomic and transcriptomic techniques. The use of several genomes and transcriptome methodologies to comprehend rice (Oryza sativa, L.) ability to withstand abiotic stress have been discussed in this review.

Regulatory non-coding RNA: The core defense mechanism against plant pathogens

Plant pathogens damage crops and threaten global food security. Plants have evolved complex defense networks against pathogens, using crosstalk among various signaling pathways. Key regulators conferring plant immunity through signaling pathways include protein-coding genes and non-coding RNAs (ncRNAs). The discovery of ncRNAs in plant transcriptomes was first considered "transcriptional noise". Recent reviews have highlighted the importance of non-coding RNAs. However, understanding interactions among different types of noncoding RNAs requires additional research. This review attempts to consider how long-ncRNAs, small-ncRNAs and circular RNAs interact in response to pathogenic diseases within different plant species. Developments within genomics and bioinformatics could lead to the further discovery of plant ncRNAs, knowledge of their biological roles, as well as an understanding of their importance in exploiting the recent molecular-based technologies for crop protection.

PlantcircBase 7.0: Full-length transcripts and conservation of plant circRNAs

Circular RNA (circRNA) is a special type of non-coding RNA that participates in diverse biological processes in both animals and plants. Five years ago, we developed a comprehensive plant circRNA database (PlantcircBase), which has attracted much attention from the plant circRNA community. Here, we report an updated PlantcircBase (v.7.0), which contains 171,118 circRNAs from 21 plant species. Over 31,000 of the circRNAs have full-length sequences constructed based on analysis of 749 bulk RNA sequencing (RNA-seq) datasets downloaded from the public domain and Nanopore long-read sequencing results of rice RNAs newly generated in this study. A plant multiple conservation score (PMCS), based on the conservation of both sequence and expression profiles, was calculated for each circRNA to quantify and compare the conservation of all circRNAs. A new parameter, plant circRNA confidence level (PCCL), is introduced to measure the identity reliability of each circRNA based on experimental validation results and the number of references that support the circRNA. All this information and other details of circRNAs can be browsed, searched, and downloaded from PlantcircBase 7.0, which also provides online bioinformatics tools for visualization and sequence alignment. PlantcircBase 7.0 is publicly and freely accessible at http://ibi.zju.edu.cn/plantcircbase/.

CircR2Disease v2.0: An Updated Web Server for Experimentally Validated circRNA-disease Associations and Its Application

With accumulating dysregulated circular RNAs (circRNAs) in pathological processes, the regulatory functions of circRNAs, especially circRNAs as microRNA (miRNA) sponges and their interactions with RNA-binding proteins (RBPs), have been widely validated. However, the collected information on experimentally validated circRNA-disease associations is only preliminary. Therefore, an updated CircR2Disease database providing a comprehensive resource and web tool to clarify the relationships between circRNAs and diseases in diverse species is necessary. Here, we present an updated CircR2Disease v2.0 with the increased number of circRNA-disease associations and novel characteristics. CircR2Disease v2.0 provides more than 5-fold experimentally validated circRNA-disease associations compared to its previous version. This version includes 4201 entries between 3077 circRNAs and 312 disease subtypes. Secondly, the information of circRNA-miRNA, circRNA-miRNA-target, and circRNA-RBP interactions has been manually collected for various diseases. Thirdly, the gene symbols of circRNAs and disease name IDs can be linked with various nomenclature databases. Detailed descriptions such as samples and journals have also been integrated into the updated version. Thus, CircR2Disease v2.0 can serve as a platform for users to systematically investigate the roles of dysregulated circRNAs in various diseases and further explore the posttranscriptional regulatory function in diseases. Finally, we propose a computational method named circDis based on the graph convolutional network (GCN) and gradient boosting decision tree (GBDT) to illustrate the applications of the CircR2Disease v2.0 database. CircR2Disease v2.0 is available at http://bioinfo.snnu.edu.cn/CircR2Disease_v2.0 and https://github.com/bioinforlab/CircR2Disease-v2.0.

Biogenesis, Functions, Interactions, and Resources of Non-Coding RNAs in Plants

Plant transcriptomes encompass a large number of functional non-coding RNAs (ncRNAs), only some of which have protein-coding capacity. Since their initial discovery, ncRNAs have been classified into two broad categories based on their biogenesis and mechanisms of action, housekeeping ncRNAs and regulatory ncRNAs. With advances in RNA sequencing technology and computational methods, bioinformatics resources continue to emerge and update rapidly, including workflow for in silico ncRNA analysis, up-to-date platforms, databases, and tools dedicated to ncRNA identification and functional annotation. In this review, we aim to describe the biogenesis, biological functions, and interactions with DNA, RNA, protein, and microorganism of five major regulatory ncRNAs (miRNA, siRNA, tsRNA, circRNA, lncRNA) in plants. Then, we systematically summarize tools for analysis and prediction of plant ncRNAs, as well as databases. Furthermore, we discuss the silico analysis process of these ncRNAs and present a protocol for step-by-step computational analysis of ncRNAs. In general, this review will help researchers better understand the world of ncRNAs at multiple levels.

Biological Parts for Engineering Abiotic Stress Tolerance in Plants

It is vital to ramp up crop production dramatically by 2050 due to the increasing global population and demand for food. However, with the climate change projections showing that droughts and heatwaves becoming common in much of the globe, there is a severe threat of a sharp decline in crop yields. Thus, developing crop varieties with inbuilt genetic tolerance to environmental stresses is urgently needed. Selective breeding based on genetic diversity is not keeping up with the growing demand for food and feed. However, the emergence of contemporary plant genetic engineering, genome-editing, and synthetic biology offer precise tools for developing crops that can sustain productivity under stress conditions. Here, we summarize the systems biology-level understanding of regulatory pathways involved in perception, signalling, and protective processes activated in response to unfavourable environmental conditions. The potential role of noncoding RNAs in the regulation of abiotic stress responses has also been highlighted. Further, examples of imparting abiotic stress tolerance by genetic engineering are discussed. Additionally, we provide perspectives on the rational design of abiotic stress tolerance through synthetic biology and list various bioparts that can be used to design synthetic gene circuits whose stress-protective functions can be switched on/off in response to environmental cues.

Computational Analysis of Transposable Elements and CircRNAs in Plants

This chapter provides two main contributions: (1) a description of computational tools and databases used to identify and analyze transposable elements (TEs) and circRNAs in plants; and (2) data analysis on public TE and circRNA data. Our goal is to highlight the primary information available in the literature on circular noncoding RNAs and transposable elements in plants. The exploratory analysis performed on publicly available circRNA and TEs data help discuss four sequence features. Finally, we investigate the association on circRNAs:TE in plants in the model organism Arabidopsis thaliana.

NGS Methodologies and Computational Algorithms for the Prediction and Analysis of Plant Circular RNAs

Circular RNAs (circRNAs) are a class of single-stranded RNAs derived from exonic, intronic, and intergenic regions from precursor messenger RNAs (pre-mRNA), where a noncanonical back-splicing event occurs, in which the 5' and 3' ends are attached by covalent bond. CircRNAs participate in the regulation of gene expression at the transcriptional and posttranscriptional level primarily as miRNA and RNA-binding protein (RBP) sponges, but also involved in the regulation of alternative RNA splicing and transcription. CircRNAs are widespread and abundant in plants where they have been involved in stress responses and development. Through the analysis of all publications in this field in the last five years, we can summarize that the identification of these molecules is carried out through next generation sequencing studies, where samples have been previously treated to eliminate DNA, rRNA, and linear RNAs as a means to enrich circRNAs. Once libraries are prepared, they are sequenced and subsequently studied from a bioinformatics point of view. Among the different tools for identifying circRNAs, we can highlight CIRI as the most used (in 60% of the published studies), as well as CIRCExplorer (20%) and find_circ (20%). Although it is recommended to use more than one program in combination, and preferably developed specifically to treat with plant samples, this is not always the case. It should also be noted that after identifying these circular RNAs, most of the authors validate their findings in the laboratory in order to obtain bona fide results.

Circular RNA Databases

Circular RNAs (circRNAs) are a class of endogenous ncRNAs with covalently closed-loop structures, lacking of 5' caps and 3' tails. These novel ncRNAs are ubiquitously expressing in eukaryotes, exhibiting expression patterns of specific cell types, tissues, or developmental stages. CircRNAs have been reported to play important roles in various biological processes, such as regulating gene expression at transcriptional or post-transcriptional levels, modulating alternative splicing, and interacting with miRNAs or proteins. With the increasing amount of circRNA data, several databases have been established to organize and manage this information, such as circBase, CIRCpedia, CircAtlas, circRNADb, PlantCircNet, and CircFunBase. These diverse databases will help to explore circRNA characterization, and further investigate circRNA functions. In this chapter, we give a brief overview of the existing circRNA databases and focus on plant circRNA databases, introducing their key features.

Efficient deletion of multiple circle RNA loci by CRISPR-Cas9 reveals Os06circ02797 as a putative sponge for OsMIR408 in rice

CRISPR-Cas9 is an emerging genome editing tool for reverse genetics in plants. However, its application for functional study of non-coding RNAs in plants is still at its infancy. Despite being a major class of non-coding RNAs, the biological roles of circle RNAs (circRNAs) remain largely unknown in plants. Previous plant circRNA studies have focused on identification and annotation of putative circRNAs, with their functions largely uninvestigated by genetic approaches. Here, we applied a multiplexed CRISPR-Cas9 strategy to efficiently acquire individual null mutants for four circRNAs in rice. We showed each of these rice circRNA loci (Os02circ25329, Os06circ02797, Os03circ00204 and Os05circ02465) can be deleted at 10% or higher efficiency in both protoplasts and stable transgenic T0 lines. Such high efficiency deletion enabled the generation of circRNA null allele plants without the CRISPR-Cas9 transgene in the T1 generation. Characterization of the mutants reveals these circRNAs' participation in salt stress response during seed germination and in particular the Os05circ02465 null mutant showed high salt tolerance. Notably, the seedlings of the Os06circ02797 mutant showed rapid growth phenotype after seed germination with the seedlings containing higher chlorophyll A/B content. Further molecular and computational analyses suggested a circRNA-miRNA-mRNA regulatory network where Os06circ02797 functions to bind and sequester OsMIR408, an important and conserved microRNA in plants. This study not only presents genetic evidence for the first time in plants that certain circRNAs may serve as sponges to negatively regulate miRNAs, a phenomenon previously demonstrated in mammalian cells, but also provides important insights for improving agronomic traits through gene editing of circRNA loci in crops.

Stress-Induced Changes in Alternative Splicing Landscape in Rice: Functional Significance of Splice Isoforms in Stress Tolerance

Improvements in yield and quality of rice are crucial for global food security. However, global rice production is substantially hindered by various biotic and abiotic stresses. Making further improvements in rice yield is a major challenge to the rice research community, which can be accomplished through developing abiotic stress-resilient rice varieties and engineering durable agrochemical-independent pathogen resistance in high-yielding elite rice varieties. This, in turn, needs increased understanding of the mechanisms by which stresses affect rice growth and development. Alternative splicing (AS), a post-transcriptional gene regulatory mechanism, allows rapid changes in the transcriptome and can generate novel regulatory mechanisms to confer plasticity to plant growth and development. Mounting evidence indicates that AS has a prominent role in regulating rice growth and development under stress conditions. Several regulatory and structural genes and splicing factors of rice undergo different types of stress-induced AS events, and the functional significance of some of them in stress tolerance has been defined. Both rice and its pathogens use this complex regulatory mechanism to devise strategies against each other. This review covers the current understanding and evidence for the involvement of AS in biotic and abiotic stress-responsive genes, and its relevance to rice growth and development. Furthermore, we discuss implications of AS for the virulence of different rice pathogens and highlight the areas of further research and potential future avenues to develop climate-smart and disease-resistant rice varieties.

The bioinformatics toolbox for circRNA discovery and analysis

Circular RNAs (circRNAs) are a unique class of RNA molecule identified more than 40 years ago which are produced by a covalent linkage via back-splicing of linear RNA. Recent advances in sequencing technologies and bioinformatics tools have led directly to an ever-expanding field of types and biological functions of circRNAs. In parallel with technological developments, practical applications of circRNAs have arisen including their utilization as biomarkers of human disease. Currently, circRNA-associated bioinformatics tools can support projects including circRNA annotation, circRNA identification and network analysis of competing endogenous RNA (ceRNA). In this review, we collected about 100 circRNA-associated bioinformatics tools and summarized their current attributes and capabilities. We also performed network analysis and text mining on circRNA tool publications in order to reveal trends in their ongoing development.

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

Disease-Associated Circular RNAs: From Biology to Computational Identification

Circular RNAs (circRNAs) are endogenous RNAs with a covalently closed continuous loop, generated through various backsplicing events of pre-mRNA. An accumulating number of studies have shown that circRNAs are potential biomarkers for major human diseases such as cancer and Alzheimer's disease. Thus, identification and prediction of human disease-associated circRNAs are of significant importance. To this end, a computational analysis-assisted strategy is indispensable to detect, verify, and quantify circRNAs for downstream applications. In this review, we briefly introduce the biology of circRNAs, including the biogenesis, characteristics, and biological functions. In addition, we outline about 30 recent bioinformatic analysis tools that are publicly available for circRNA study. Principles for applying these computational strategies and considerations will be briefly discussed. Lastly, we give a complete survey on more than 20 key computational databases that are frequently used. To our knowledge, this is the most complete and updated summary on publicly available circRNA resources. In conclusion, this review summarizes key aspects of circRNA biology and outlines key computational strategies that will facilitate the genome-wide identification and prediction of circRNAs.

Characterization and Function of Circular RNAs in Plants

CircRNAs are covalently closed-loop single-stranded RNA molecules ubiquitously expressing in eukaryotes. As an important member of the endogenous ncRNA family, circRNAs are associated with diverse biological processes and can regulate transcription, modulate alternative splicing, and interact with miRNAs or proteins. Compared to abundant advances in animals, studies of circRNAs in plants are rapidly emerging. The databases and analysis tools for plant circRNAs are constantly being developed. Large numbers of circRNAs have been identified and characterized in plants and proved to play regulatory roles in plant growth, development, and stress responses. Here, we review the biogenesis, characteristics, bioinformatics resources, and biological functions of plant circRNAs, and summarize the distinct circularization features and differentially expression patterns comparison with animal-related results.

Transcriptome-wide identification of novel circular RNAs in soybean in response to low-phosphorus stress

Low-phosphorus (LP) stress is a major factor limiting the growth and yield of soybean. Circular RNAs (circRNAs) are novel noncoding RNAs that play a crucial role in plant responses to abiotic stress. However, how LP stress mediates the biogenesis of circRNAs in soybean remains unclear. Here, to explore the response mechanisms of circRNAs to LP stress, the roots of two representative soybean genotypes with different P-use efficiency, Bogao (a LP-sensitive genotype) and Nannong 94156 (a LP-tolerant genotype), were used for the construction of RNA sequencing (RNA-seq) libraries and circRNA identification. In total, 371 novel circRNA candidates, including 120 significantly differentially expressed (DE) circRNAs, were identified across different P levels and genotypes. More DE circRNAs were significantly regulated by LP stress in Bogao than in NN94156, suggesting that the tolerant genotype was less affected by LP stress than the sensitive genotype was; in other words, NN94156 may have a better ability to maintain P homeostasis under LP stress. Moreover, a positive correlation was observed between the expression patterns of P stress-induced circRNAs and their circRNA-host genes. Gene Ontology (GO) enrichment analysis of these circRNA-host genes and microRNA (miRNA)-targeted genes indicated that these DE circRNAs were involved mainly in defense responses, ADP binding, nucleoside binding, organic substance catabolic processes, oxidoreductase activity, and signal transduction. Together, our results revealed that LP stress can significantly alter the genome-wide profiles of circRNAs and indicated that the regulation of circRNAs was both genotype and environment specific in response to LP stress. LP-induced circRNAs might provide a rich resource for LP-responsive circRNA candidates for future studies.