plantDARIO: web based quantitative and qualitative analysis of small RNA-seq data in plants

Evaluation of efficacy of non-coding RNA in abiotic stress management of field crops: Current status and future prospective

Abiotic stresses are responsible for the major losses in crop yield all over the world. Stresses generate harmful ROS which can impair cellular processes in plants. Therefore, plants have evolved antioxidant systems in defence against the stress-induced damages. The frequency of occurrence of abiotic stressors has increased several-fold due to the climate change experienced in recent times and projected for the future. This had particularly aggravated the risk of yield losses and threatened global food security. Non-coding RNAs are the part of eukaryotic genome that does not code for any proteins. However, they have been recently found to have a crucial role in the responses of plants to both abiotic and biotic stresses. There are different types of ncRNAs, for example, miRNAs and lncRNAs, which have the potential to regulate the expression of stress-related genes at the levels of transcription, post-transcription, and translation of proteins. The lncRNAs are also able to impart their epigenetic effects on the target genes through the alteration of the status of histone modification and organization of the chromatins. The current review attempts to deliver a comprehensive account of the role of ncRNAs in the regulation of plants' abiotic stress responses through ROS homeostasis. The potential applications ncRNAs in amelioration of abiotic stresses in field crops also have been evaluated.

Regulatory role of microRNAs (miRNAs) in the recent development of abiotic stress tolerance of plants

MicroRNAs (miRNAs) are a distinct groups of single-stranded non-coding, tiny regulatory RNAs approximately 20-24 nucleotides in length. miRNAs negatively influence gene expression at the post-transcriptional level and have evolved considerably in the development of abiotic stress tolerance in a number of model plants and economically important crop species. The present review aims to deliver the information on miRNA-mediated regulation of the expression of major genes or Transcription Factors (TFs), as well as genetic and regulatory pathways. Also, the information on adaptive mechanisms involved in plant abiotic stress responses, prediction, and validation of targets, computational tools, and databases available for plant miRNAs, specifically focus on their exploration for engineering abiotic stress tolerance in plants. The regulatory function of miRNAs in plant growth, development, and abiotic stresses consider in this review, which uses high-throughput sequencing (HTS) technologies to generate large-scale libraries of small RNAs (sRNAs) for conventional screening of known and novel abiotic stress-responsive miRNAs adds complexity to regulatory networks in plants. The discoveries of miRNA-mediated tolerance to multiple abiotic stresses, including salinity, drought, cold, heat stress, nutritional deficiency, UV-radiation, oxidative stress, hypoxia, and heavy metal toxicity, are highlighted and discussed in this review.

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.

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.

Versatile interactions and bioinformatics analysis of noncoding RNAs

Advances in RNA sequencing technologies and computational methodologies have provided a huge impetus to noncoding RNA (ncRNA) study. Once regarded as inconsequential results of transcriptional promiscuity, ncRNAs were later found to exert great roles in various aspects of biological functions. They are emerging as key players in gene regulatory networks by interacting with other biomolecules (DNA, RNA or protein). Here, we provide an overview of ncRNA repertoire and highlight recent discoveries of their versatile interactions. To better investigate the ncRNA-mediated regulation, it is necessary to make full use of innovative sequencing techniques and computational tools. We further describe a comprehensive workflow for in silico ncRNA analysis, providing up-to-date platforms, databases and tools dedicated to ncRNA identification and functional annotation.

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.

Computational tools for plant small RNA detection and categorization

Small RNAs (sRNAs) are important short-length molecules with regulatory functions essential for plant development and plasticity. High-throughput sequencing of total sRNA populations has revealed that the largest share of sRNA remains uncategorized. To better understand the role of sRNA-mediated cellular regulation, it is necessary to create accurate and comprehensive catalogues of sRNA and their sequence features, a task that currently relies on nontrivial bioinformatic approaches. Although a large number of computational tools have been developed to predict features of sRNA sequences, these tools are mostly dedicated to microRNAs and none integrates the functionalities necessary to describe units from all sRNA pathways thus far discovered in plants. Here, we review the different classes of sRNA found in plants and describe available bioinformatics tools that can help in their detection and categorization.

Engineering salinity tolerance in plants: progress and prospects

There is a need to integrate conceptual framework based on the current understanding of salt stress responses with different approaches for manipulating and improving salt tolerance in crop plants. Soil salinity exerts significant constraints on global crop production, posing a serious challenge for plant breeders and biotechnologists. The classical transgenic approach for enhancing salinity tolerance in plants revolves by boosting endogenous defence mechanisms, often via a single-gene approach, and usually involves the enhanced synthesis of compatible osmolytes, antioxidants, polyamines, maintenance of hormone homeostasis, modification of transporters and/or regulatory proteins, including transcription factors and alternative splicing events. Occasionally, genetic manipulation of regulatory proteins or phytohormone levels confers salinity tolerance, but all these may cause undesired reduction in plant growth and/or yields. In this review, we present and evaluate novel and cutting-edge approaches for engineering salt tolerance in crop plants. First, we cover recent findings regarding the importance of regulatory proteins and transporters, and how they can be used to enhance salt tolerance in crop plants. We also evaluate the importance of halobiomes as a reservoir of genes that can be used for engineering salt tolerance in glycophytic crops. Additionally, the role of microRNAs as critical post-transcriptional regulators in plant adaptive responses to salt stress is reviewed and their use for engineering salt-tolerant crop plants is critically assessed. The potentials of alternative splicing mechanisms and targeted gene-editing technologies in understanding plant salt stress responses and developing salt-tolerant crop plants are also discussed.

Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome

microRNAs are evolutionarily conserved, endogenously produced, noncoding RNAs (ncRNAs) of approximately 19-24 nucleotides (nts) in length known to exhibit gene silencing of complementary target sequence. Their deregulated expression is reported in various disease conditions and thus has therapeutic implications. In the last decade, various computational resources are published in this field. In this chapter, we have reviewed bioinformatics resources, i.e., miRNA-centered databases, algorithms, and tools to predict miRNA targets. First section has enlisted more than 75 databases, which mainly covers information regarding miRNA registries, targets, disease associations, differential expression, interactions with other noncoding RNAs, and all-in-one resources. In the algorithms section, we have compiled about 140 algorithms from eight subcategories, viz. for the prediction of precursor (pre-) and mature miRNAs. These algorithms are developed on various sequence, structure, and thermodynamic based features incorporated into different machine learning techniques (MLTs). In addition, computational identification of miRNAs from high-throughput next generation sequencing (NGS) data and their variants, viz. isomiRs, differential expression, miR-SNPs, and functional annotation, are discussed. Prediction and analysis of miRNAs and their associated targets are also evaluated under miR-targets section providing knowledge regarding novel miRNA targets and complex host-pathogen interactions. In conclusion, we have provided comprehensive review of in silico resources published in miRNA research to help scientific community be updated and choose the appropriate tool according to their needs.

Exploring miRNAs for developing climate-resilient crops: A perspective review

Climate changes and environmental stresses have significant implications on global crop production and necessitate developing crops that can withstand an array of climate changes and environmental perturbations such as irregular water-supplies leading to drought or water-logging, hyper soil-salinity, extreme and variable temperatures, ultraviolet radiations and metal stress. Plants have intricate molecular mechanisms to cope with these dynamic environmental changes, one of the most common and effective being the reprogramming of expression of stress-responsive genes. Plant microRNAs (miRNAs) have emerged as key post-transcriptional and translational regulators of gene-expression for modulation of stress implications. Recent reports are establishing their key roles in epigenetic regulations of stress/adaptive responses as well as in providing plants genome-stability. Several stress responsive miRNAs are being identified from different crop plants and miRNA-driven RNA-interference (RNAi) is turning into a technology of choice for improving crop traits and providing phenotypic plasticity in challenging environments. Here we presents a perspective review on exploration of miRNAs as potent targets for engineering crops that can withstand multi-stress environments via loss-/gain-of-function approaches. This review also shed a light on potential roles plant miRNAs play in genome-stability and their emergence as potent target for genome-editing. Current knowledge on plant miRNAs, their biogenesis, function, their targets, and latest developments in bioinformatics approaches for plant miRNAs are discussed. Though there are recent reviews discussing primarily the individual miRNAs responsive to single stress factors, however, considering practical limitation of this approach, special emphasis is given in this review on miRNAs involved in responses and adaptation of plants to multi-stress environments including at epigenetic and/or epigenomic levels.

A comprehensive review of web-based resources of non-coding RNAs for plant science research

Non-coding RNAs (ncRNAs) are transcribed from genome but not translated into proteins. Many ncRNAs are key regulators of plants growth and development, metabolism and stress tolerance. In order to make the web-based ncRNA resources for plant science research be more easily accessible and understandable, we made a comprehensive review for 83 web-based resources of three types, including genome databases containing ncRNA data, microRNA (miRNA) databases and long non-coding RNA (lncRNA) databases. To facilitate effective usage of these resources, we also suggested some preferred resources of miRNAs and lncRNAs for performing meaningful analysis.

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.

Phylogenetic distribution of plant snoRNA families

Background

Small nucleolar RNAs (snoRNAs) are one of the most ancient families amongst non-protein-coding RNAs. They are ubiquitous in Archaea and Eukarya but absent in bacteria. Their main function is to target chemical modifications of ribosomal RNAs. They fall into two classes, box C/D snoRNAs and box H/ACA snoRNAs, which are clearly distinguished by conserved sequence motifs and the type of chemical modification that they govern. Similarly to microRNAs, snoRNAs appear in distinct families of homologs that affect homologous targets. In animals, snoRNAs and their evolution have been studied in much detail. In plants, however, their evolution has attracted comparably little attention.

Results

In order to chart the phylogenetic distribution of individual snoRNA families in plants, we applied a sophisticated approach for identifying homologs of known plant snoRNAs across the plant kingdom. In response to the relatively fast evolution of snoRNAs, information on conserved sequence boxes, target sequences, and secondary structure is combined to identify additional snoRNAs. We identified 296 families of snoRNAs in 24 species and traced their evolution throughout the plant kingdom. Many of the plant snoRNA families comprise paralogs. We also found that targets are well-conserved for most snoRNA families.

Conclusions

The sequence conservation of snoRNAs is sufficient to establish homologies between phyla. The degree of this conservation tapers off, however, between land plants and algae. Plant snoRNAs are frequently organized in highly conserved spatial clusters. As a resource for further investigations we provide carefully curated and annotated alignments for each snoRNA family under investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3301-2) contains supplementary material, which is available to authorized users.

Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques

The majority of the human transcriptome is defined as non-coding RNA (ncRNA), since only a small fraction of human DNA encodes for proteins, as reported by the ENCODE project. Several distinct classes of ncRNAs, such as transfer RNA, microRNA, and long non-coding RNA, have been classified, each with its own three-dimensional folding and specific function. As ncRNAs are highly abundant in living organisms and have been discovered to play important roles in many biological processes, there has been an ever increasing need to investigate the entire ncRNAome in further unbiased detail. Recently, the advent of next-generation sequencing (NGS) technologies has substantially increased the throughput of transcriptome studies, allowing an unprecedented investigation of ncRNAs, as regulatory pathways and novel functions involving ncRNAs are now also emerging. The huge amount of transcript data produced by NGS has progressively required the development and implementation of suitable bioinformatics workflows, complemented by knowledge-based approaches, to identify, classify, and evaluate the expression of hundreds of ncRNAs in normal and pathological conditions, such as cancer. In this mini-review, we present and discuss current bioinformatics advances in the development of such computational approaches to analyze and classify the ncRNA component of human transcriptome sequence data obtained from NGS technologies.