The plant noncoding transcriptome: a versatile environmental sensor.

Plant noncoding RNA transcripts have gained increasing attention in recent years due to growing evidence that they can regulate developmental plasticity. In this review article, we comprehensively analyze the relationship between noncoding RNA transcripts in plants and their response to environmental cues. We first provide an overview of the various noncoding transcript types, including long and small RNAs, and how the environment modulates their performance. We then highlight the importance of noncoding RNA secondary structure for their molecular and biological functions. Finally, we discuss recent studies that have unveiled the functional significance of specific long noncoding transcripts and their molecular partners within ribonucleoprotein complexes during development and in response to biotic and abiotic stress. Overall, this review sheds light on the fascinating and complex relationship between dynamic noncoding transcription and plant environmental responses, and highlights the need for further research to uncover the underlying molecular mechanisms and exploit the potential of noncoding transcripts for crop resilience in the context of global warming.

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure from a raw RNA sequence is a long-standing unsolved problem, which after decades of almost unchanged performance has now re-emerged due to deep learning. Traditional RNA secondary structure prediction algorithms have been mostly based on thermodynamic models and dynamic programming for free energy minimization. More recently deep learning methods have shown competitive performance compared with the classical ones, but there is still a wide margin for improvement. RESULTS: In this work we present sincFold, an end-to-end deep learning approach, that predicts the nucleotides contact matrix using only the RNA sequence as input. The model is based on 1D and 2D residual neural networks that can learn short- and long-range interaction patterns. We show that structures can be accurately predicted with minimal physical assumptions. Extensive experiments were conducted on several benchmark datasets, considering sequence homology and cross-family validation. sincFold was compared with classical methods and recent deep learning models, showing that it can outperform the state-of-the-art methods.

Principles of miRNA/miRNA* function in plant MIRNA processing.

MicroRNAs (miRNAs) are essential regulators of gene expression, defined by their unique biogenesis, which requires the precise excision of the small RNA from an imperfect fold-back precursor. Unlike their animal counterparts, plant miRNA precursors exhibit variations in sizes and shapes. Plant MIRNAs can undergo processing in a base-to-loop or loop-to-base direction, with DICER-LIKE1 (DCL1) releasing the miRNA after two cuts (two-step MIRNAs) or more (sequential MIRNAs). In this study, we demonstrate the critical role of the miRNA/miRNA* duplex region in the processing of miRNA precursors. We observed that endogenous MIRNAs frequently experience suboptimal processing in vivo due to mismatches in the miRNA/miRNA* duplex, a key region that fine-tunes miRNA levels. Enhancing the interaction energy of the miRNA/miRNA* duplex in two-step MIRNAs results in a substantial increase in miRNA levels. Conversely, sequential MIRNAs display distinct and specific requirements for the miRNA/miRNA* duplexes along their foldback structure. Our work establishes a connection between the miRNA/miRNA* structure and precursor processing mechanisms. Furthermore, we reveal a link between the biological function of miRNAs and the processing mechanism of their precursors with the evolution of plant miRNA/miRNA* duplex structures.

PhylomeDB V5: an expanding repository for genome-wide catalogues of annotated gene phylogenies.

PhylomeDB is a unique knowledge base providing public access to minable and browsable catalogues of pre-computed genome-wide collections of annotated sequences, alignments and phylogenies (i.e. phylomes) of homologous genes, as well as to their corresponding phylogeny-based orthology and paralogy relationships. In addition, PhylomeDB trees and alignments can be downloaded for further processing to detect and date gene duplication events, infer past events of inter-species hybridization and horizontal gene transfer, as well as to uncover footprints of selection, introgression, gene conversion, or other relevant evolutionary processes in the genes and organisms of interest. Here, we describe the latest evolution of PhylomeDB (version 5). This new version includes a newly implemented web interface and several new functionalities such as optimized searching procedures, the possibility to create user-defined phylome collections, and a fully redesigned data structure. This release also represents a significant core data expansion, with the database providing access to 534 phylomes, comprising over 8 million trees, and homology relationships for genes in over 6000 species. This makes PhylomeDB the largest and most comprehensive public repository of gene phylogenies. PhylomeDB is available at http://www.phylomedb.org.

A hybrid approach to assess the structural impact of long noncoding RNA mutations uncovers key NEAT1 interactions in colorectal cancer.

Long noncoding RNAs (lncRNAs) are emerging players in cancer and they entail potential as prognostic biomarkers or therapeutic targets. Earlier studies have identified somatic mutations in lncRNAs that are associated with tumor relapse after therapy, but the underlying mechanisms behind these associations remain unknown. Given the relevance of secondary structure for the function of some lncRNAs, some of these mutations may have a functional impact through structural disturbance. Here, we examined the potential structural and functional impact of a novel A > G point mutation in NEAT1 that has been recurrently observed in tumors of colorectal cancer patients experiencing relapse after treatment. Here, we used the nextPARS structural probing approach to provide first empirical evidence that this mutation alters NEAT1 structure. We further evaluated the potential effects of this structural alteration using computational tools and found that this mutation likely alters the binding propensities of several NEAT1-interacting miRNAs. Differential expression analysis on these miRNA networks shows upregulation of Vimentin, consistent with previous findings. We propose a hybrid pipeline that can be used to explore the potential functional effects of lncRNA somatic mutations.

MetaPhOrs 2.0: integrative, phylogeny-based inference of orthology and paralogy across the tree of life.

Inferring homology relationships across genes in different species is a central task in comparative genomics. Therefore, a large number of resources and methods have been developed over the years. Some public databases include phylogenetic trees of homologous gene families which can be used to further differentiate homology relationships into orthology and paralogy. MetaPhOrs is a web server that integrates phylogenetic information from different sources to provide orthology and paralogy relationships based on a common phylogeny-based predictive algorithm and associated with a consistency-based confidence score. Here we describe the latest version of the web server which includes major new implementations and provides orthology and paralogy relationships derived from ∼8.2 million gene family trees-from 13 different source repositories across ∼4000 species with sequenced genomes. MetaPhOrs server is freely available, without registration, at http://orthology.phylomedb.org/.

Evolutionary Footprints Reveal Insights into Plant MicroRNA Biogenesis.

MicroRNAs (miRNAs) are endogenous small RNAs that recognize target sequences by base complementarity and play a role in the regulation of target gene expression. They are processed from longer precursor molecules that harbor a fold-back structure. Plant miRNA precursors are quite variable in size and shape, and are recognized by the processing machinery in different ways. However, ancient miRNAs and their binding sites in target genes are conserved during evolution. Here, we designed a strategy to systematically analyze MIRNAs from different species generating a graphical representation of the conservation of the primary sequence and secondary structure. We found that plant MIRNAs have evolutionary footprints that go beyond the small RNA sequence itself, yet their location along the precursor depends on the specific MIRNA We show that these conserved regions correspond to structural determinants recognized during the biogenesis of plant miRNAs. Furthermore, we found that the members of the miR166 family have unusual conservation patterns and demonstrated that the recognition of these precursors in vivo differs from other known miRNAs. Our results describe a link between the evolutionary conservation of plant MIRNAs and the mechanisms underlying the biogenesis of these small RNAs and show that the MIRNA pattern of conservation can be used to infer the mode of miRNA biogenesis.

Efficiency and precision of microRNA biogenesis modes in plants.

Many evolutionarily conserved microRNAs (miRNAs) in plants regulate transcription factors with key functions in development. Hence, mutations in the core components of the miRNA biogenesis machinery cause strong growth defects. An essential aspect of miRNA biogenesis is the precise excision of the small RNA from its precursor. In plants, miRNA precursors are largely variable in size and shape and can be processed by different modes. Here, we optimized an approach to detect processing intermediates during miRNA biogenesis. We characterized a miRNA whose processing is triggered by a terminal branched loop. Plant miRNA processing can be initiated by internal bubbles, small terminal loops or branched loops followed by dsRNA segments of 15-17 bp. Interestingly, precision and efficiency vary with the processing modes. Despite the various potential structural determinants present in a single a miRNA precursor, DCL1 is mostly guided by a predominant structural region in each precursor in wild-type plants. However, our studies in fiery1, hyl1 and se mutants revealed the existence of cleavage signatures consistent with the recognition of alternative processing determinants. The results provide a general view of the mechanisms underlying the specificity of miRNA biogenesis in plants.

Spatial Control of Gene Expression by miR319-Regulated TCP Transcription Factors in Leaf Development.

The characteristic leaf shapes we see in all plants are in good part the outcome of the combined action of several transcription factor networks that translate into cell division activity during the early development of the organ. We show here that wild-type leaves have distinct transcriptomic profiles in center and marginal regions. Certain transcripts are enriched in margins, including those of CINCINNATA-like TCPs (TEOSINTE BRANCHED, CYCLOIDEA and PCF1/2) and members of the NGATHA and STYLISH gene families. We study in detail the contribution of microRNA319 (miR319)-regulated TCP transcription factors to the development of the center and marginal regions of Arabidopsis (Arabidopsis thaliana) leaves. We compare in molecular analyses the wild type, the tcp2 tcp4 mutant that has enlarged flat leaves, and the tcp2 tcp3 tcp4 tcp10 mutant with strongly crinkled leaves. The different leaf domains of the tcp mutants show changed expression patterns for many photosynthesis-related genes, indicating delayed differentiation, especially in the marginal parts of the organ. At the same time, we found an up-regulation of cyclin genes and other genes that are known to participate in cell division, specifically in the marginal regions of tcp2 tcp3 tcp4 tcp10 Using GUS reporter constructs, we confirmed extended mitotic activity in the tcp2 tcp3 tcp4 tcp10 leaf, which persisted in small defined foci in the margins when the mitotic activity had already ceased in wild-type leaves. Our results describe the role of miR319-regulated TCP transcription factors in the coordination of activities in different leaf domains during organ development.

Transcriptomic analyses reveal groups of co-expressed, syntenic lncRNAs in four species of the genus Caenorhabditis.

Long non-coding RNAs (lncRNAs) are a heterogeneous class of genes that do not code for proteins. Since lncRNAs (or a fraction thereof) are expected to be functional, many efforts have been dedicated to catalog lncRNAs in numerous organisms, but our knowledge of lncRNAs in non vertebrate species remains very limited. Here, we annotated lncRNAs using transcriptomic data from the same larval stage of four Caenorhabditis species. The number of annotated lncRNAs in self-fertile nematodes was lower than in out-crossing species. We used a combination of approaches to identify putatively homologous lncRNAs: synteny, sequence conservation, and structural conservation. We classified a total of 1,532 out of 7,635 genes from the four species into families of lncRNAs with conserved synteny and expression at the larval stage, suggesting that a large fraction of the predicted lncRNAs may be species specific. Despite both sequence and local secondary structure seem to be poorly conserved, sequences within families frequently shared BLASTn hits and short sequence motifs, which were more likely to be unpaired in the predicted structures. We provide the first multi-species catalog of lncRNAs in nematodes and identify groups of lncRNAs with conserved synteny and expression, that share exposed motifs.

Multiple RNA recognition patterns during microRNA biogenesis in plants.

MicroRNAs (miRNAs) derive from longer precursors with fold-back structures. While animal miRNA precursors have homogenous structures, plant precursors comprise a collection of fold-backs with variable size and shape. Here, we design an approach to systematically analyze miRNA processing intermediates and characterize the biogenesis of most of the evolutionarily conserved miRNAs present in Arabidopsis thaliana. We found that plant miRNAs are processed by four mechanisms, depending on the sequential direction of the processing machinery and the number of cuts required to release the miRNA. Classification of the precursors according to their processing mechanism revealed specific structural determinants for each group. We found that the complexity of the miRNA processing pathways occurs in both ancient and evolutionarily young sequences and that members of the same family can be processed in different ways. We observed that different structural determinants compete for the processing machinery and that alternative miRNAs can be generated from a single precursor. The results provide an explanation for the structural diversity of miRNA precursors in plants and new insights toward the understanding of the biogenesis of small RNAs.

comTAR: a web tool for the prediction and characterization of conserved microRNA targets in plants.

MOTIVATION: MicroRNAs (miRNAs) are major regulators of gene expression in plants and animals. They recognize their target messenger RNAs (mRNAs) by sequence complementarity and guide them to cleavage or translational arrest. So far, the prediction of plant miRNA-target pairs generally relies on the use of empirical parameters deduced from known miRNA-target interactions. RESULTS: We developed comTAR, a web tool for the prediction of miRNA targets that is mainly based on the conservation of the potential regulation in different species. We used data generated from a pipeline applied to transcript datasets of 33 angiosperms that was used to build a database of potential miRNA targets of different plant species. The database contains information describing each miRNA-target pair, their function and evolutionary conservation, while the results are displayed in a user-friendly interface. The tool also allows the search using new miRNAs. AVAILABILITY AND IMPLEMENTATION: The Web site is free to all users, with no login requirements, at http://rnabiology.ibr-conicet.gov.ar/comtar.

Identification of new microRNA-regulated genes by conserved targeting in plant species.

MicroRNAs (miRNAs) are major regulators of gene expression in multicellular organisms. They recognize their targets by sequence complementarity and guide them to cleavage or translational arrest. It is generally accepted that plant miRNAs have extensive complementarity to their targets and their prediction usually relies on the use of empirical parameters deduced from known miRNA-target interactions. Here, we developed a strategy to identify miRNA targets which is mainly based on the conservation of the potential regulation in different species. We applied the approach to expressed sequence tags datasets from angiosperms. Using this strategy, we predicted many new interactions and experimentally validated previously unknown miRNA targets in Arabidopsis thaliana. Newly identified targets that are broadly conserved include auxin regulators, transcription factors and transporters. Some of them might participate in the same pathways as the targets known before, suggesting that some miRNAs might control different aspects of a biological process. Furthermore, this approach can be used to identify targets present in a specific group of species, and, as a proof of principle, we analyzed Solanaceae-specific targets. The presented strategy can be used alone or in combination with other approaches to find miRNA targets in plants.

Probing RNA structural landscapes across Candida yeast genomes.

Understanding the intricate roles of RNA molecules in virulence and host-pathogen interactions can provide valuable insights into combatting infections and improving human health. Although much progress has been achieved in understanding transcriptional regulation during host-pathogen interactions in diverse species, more is needed to know about the structure of pathogen RNAs. This is particularly true for fungal pathogens, including pathogenic yeasts of the Candida genus, which are the leading cause of hospital-acquired fungal infections. Our work addresses the gap between RNA structure and their biology by employing genome-wide structure probing to comprehensively explore the structural landscape of mRNAs and long non-coding RNAs (lncRNAs) in the four major Candida pathogens. Specifically focusing on mRNA, we observe a robust correlation between sequence conservation and structural characteristics in orthologous transcripts, significantly when sequence identity exceeds 50%, highlighting structural feature conservation among closely related species. We investigate the impact of single nucleotide polymorphisms (SNPs) on mRNA secondary structure. SNPs within 5' untranslated regions (UTRs) tend to occur in less structured positions, suggesting structural constraints influencing transcript regulation. Furthermore, we compare the structural properties of coding regions and UTRs, noting that coding regions are generally more structured than UTRs, consistent with similar trends in other species. Additionally, we provide the first experimental characterization of lncRNA structures in Candida species. Most lncRNAs form independent subdomains, similar to human lncRNAs. Notably, we identify hairpin-like structures in lncRNAs, a feature known to be functionally significant. Comparing hairpin prevalence between lncRNAs and protein-coding genes, we find enrichment in lncRNAs across Candida species, humans, and Arabidopsis thaliana, suggesting a conserved role for these structures. In summary, our study offers valuable insights into the interplay between RNA sequence, structure, and function in Candida pathogens, with implications for gene expression regulation and potential therapeutic strategies against Candida infections.

EvolClustDB: Exploring Eukaryotic Gene Clusters with Evolutionarily Conserved Genomic Neighbourhoods.

Conservation of gene neighbourhood over evolutionary distances is generally indicative of shared regulation or functional association among genes. This concept has been broadly exploited in prokaryotes but its use on eukaryotic genomes has been limited to specific functional classes, such as biosynthetic gene clusters. We here used an evolutionary-based gene cluster discovery algorithm (EvolClust) to pre-compute evolutionarily conserved gene neighbourhoods, which can be searched, browsed and downloaded in EvolClustDB. We inferred ∼35,000 cluster families in 882 different species in genome comparisons of five taxonomically broad clades: Fungi, Plants, Metazoans, Insects and Protists. EvolClustDB allows browsing through the cluster families, as well as searching by protein, species, identifier or sequence. Visualization allows inspecting gene order per species in a phylogenetic context, so that relevant evolutionary events such as gain, loss or transfer, can be inferred. EvolClustDB is freely available, without registration, at http://evolclustdb.org/.

Structural characterization of NORAD reveals a stabilizing role of spacers and two new repeat units.

Long non-coding RNAs (lncRNAs) can perform a variety of key cellular functions by interacting with proteins and other RNAs. Recent studies have shown that the functions of lncRNAS are largely mediated by their structures. However, our structural knowledge for most lncRNAS is limited to sequence-based computational predictions. Non-coding RNA activated by DNA damage (NORAD) is an atypical lncRNA due to its abundant expression and high sequence conservation. NORAD regulates genomic stability by interacting with proteins and microRNAs. Previous sequence-based characterization has identified a modular organization of NORAD composed of several NORAD repeat units (NRUs). These units comprise the protein-binding elements and are separated by regular spacers. Here, we experimentally determine for the first time the secondary structure of NORAD using the nextPARS approach. Our results suggest that the spacer regions provide structural stability to NRUs. Furthermore, we uncover two previously unreported NRUs, and determine the core structural motifs conserved across NRUs. Overall, these findings will help to elucidate the function and evolution of NORAD.

Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS.

RNA molecules play important roles in almost every cellular process, and their functions are mediated by their sequence and structure. Determining the secondary structure of RNAs is central to understanding RNA function and evolution. RNA structure probing techniques coupled to high-throughput sequencing allow determining structural features of RNA molecules at transcriptome-wide scales. Our group recently developed a novel Illumina-based implementation of in vitro parallel probing of RNA structures called nextPARS.Here, we describe a protocol for the computation of the nextPARS scores and their use to obtain the structural profile (single- or double-stranded state) of an RNA sequence at single-nucleotide resolution.

Identification of key sequence features required for microRNA biogenesis in plants.

MicroRNAs (miRNAs) are endogenous small RNAs of ∼21 nt that regulate multiple biological pathways in multicellular organisms. They derive from longer transcripts that harbor an imperfect stem-loop structure. In plants, the ribonuclease type III DICER-LIKE1 assisted by accessory proteins cleaves the precursor to release the mature miRNA. Numerous studies highlight the role of the precursor secondary structure during plant miRNA biogenesis; however, little is known about the relevance of the precursor sequence. Here, we analyzed the sequence composition of plant miRNA primary transcripts and found specifically located sequence biases. We show that changes in the identity of specific nucleotides can increase or abolish miRNA biogenesis. Most conspicuously, our analysis revealed that the identity of the nucleotides at unpaired positions of the precursor plays a crucial role during miRNA biogenesis in Arabidopsis.

Identification of microRNA processing determinants by random mutagenesis of Arabidopsis MIR172a precursor.

MicroRNAs (miRNAs) are widespread posttranscriptional regulators of gene expression. They are processed from longer primary transcripts that contain foldback structures (reviewed in). In animals, a complex formed by Drosha and DGCR8/Pasha recognizes the transition between the single-stranded RNA sequences and the stem loop to produce the first cleavage step in miRNA biogenesis. Whereas animal precursors are of uniform size and shape, their plant counterparts comprise a collection of variable stem loops, and little is known about the structural clues recognized during their processing. Here, we designed an unbiased approach based on the random mutagenesis of the MIR172a precursor to study miRNA processing in plants. Randomly mutated precursors were overexpressed in Arabidopsis, and their activity was determined in vivo. We gathered sequence data from these transgenes and used it to build a MIR172a precursor map highlighting relevant and neutral positions for its processing. A 15 nucleotide stem segment below the miRNA/miRNA(*) duplex was essential for MIR172a processing. In contrast, mutations in the terminal-loop region were mostly neutral, yet a loop was required for miR172 biogenesis. The results could be extended to other precursors, suggesting the existence of common features in at least part of the plant precursors.