Identification and functional annotation of long intergenic non-coding RNAs in Brassicaceae

Long Noncoding RNAs in Response to Hyperosmolarity Stress, but Not Salt Stress, Were Mainly Enriched in the Rice Roots

Due to their immobility and possession of underground parts, plants have evolved various mechanisms to endure and adapt to abiotic stresses such as extreme temperatures, drought, and salinity. However, the contribution of long noncoding RNAs (lncRNAs) to different abiotic stresses and distinct rice seedling parts remains largely uncharacterized beyond the protein-coding gene (PCG) layer. Using transcriptomics and bioinformatics methods, we systematically identified lncRNAs and characterized their expression patterns in the roots and shoots of wild type (WT) and ososca1.1 (reduced hyperosmolality-induced [Ca2+]i increase in rice) seedlings under hyperosmolarity and salt stresses. Here, 2937 candidate lncRNAs were identified in rice seedlings, with intergenic lncRNAs representing the largest category. Although the detectable sequence conservation of lncRNAs was low, we observed that lncRNAs had more orthologs within the Oryza. By comparing WT and ososca1.1, the transcription level of OsOSCA1.1-related lncRNAs in roots was greatly enhanced in the face of hyperosmolality stress. Regarding regulation mode, the co-expression network revealed connections between trans-regulated lncRNAs and their target PCGs related to OsOSCA1.1 and its mediation of hyperosmolality stress sensing. Interestingly, compared to PCGs, the expression of lncRNAs in roots was more sensitive to hyperosmolarity stress than to salt stress. Furthermore, OsOSCA1.1-related hyperosmolarity stress-responsive lncRNAs were enriched in roots, and their potential cis-regulated genes were associated with transcriptional regulation and signaling transduction. Not to be ignored, we identified a motif-conserved and hyperosmolarity stress-activated lncRNA gene (OSlncRNA), speculating on its origin and evolutionary history in Oryza. In summary, we provide a global perspective and a lncRNA resource to understand hyperosmolality stress sensing in rice roots, which helps to decode the complex molecular networks involved in plant sensing and adaptation to stressful environments.

What, where, and how: Regulation of translation and the translational landscape in plants

Translation is a crucial step in gene expression and plays a vital role in regulating various aspects of plant development and environmental responses. It is a dynamic and complex program that involves interactions between mRNAs, transfer RNAs, and the ribosome machinery through both cis- and trans-regulation while integrating internal and external signals. Translational control can act in a global (transcriptome-wide) or mRNA-specific manner. Recent advances in genome-wide techniques, particularly ribosome profiling and proteomics, have led to numerous exciting discoveries in both global and mRNA-specific translation. In this review, we aim to provide a "primer" that introduces readers to this fascinating yet complex cellular process and provide a big picture of how essential components connect within the network. We begin with an overview of mRNA translation, followed by a discussion of the experimental approaches and recent findings in the field, focusing on unannotated translation events and translational control through cis-regulatory elements on mRNAs and trans-acting factors, as well as signaling networks through 3 conserved translational regulators TOR, SnRK1, and GCN2. Finally, we briefly touch on the spatial regulation of mRNAs in translational control. Here, we focus on cytosolic mRNAs; translation in organelles and viruses is not covered in this review.

From environmental responses to adaptation: the roles of plant lncRNAs

As sessile organisms, plants are continuously exposed to heterogeneous and changing environments and constantly need to adapt their growth strategies. They have evolved complex mechanisms to recognize various stress factors, activate appropriate signaling pathways, and respond accordingly by reprogramming the expression of multiple genes at the transcriptional, post-transcriptional, and even epigenome levels to tolerate stressful conditions such as drought, high temperature, nutrient deficiency, and pathogenic interactions. Apart from protein-coding genes, long non-coding RNAs (lncRNAs) have emerged as key players in plant adaptation to environmental stresses. They are transcripts larger than 200 nucleotides without protein-coding potential. Still, they appear to regulate a wide range of processes, including epigenetic modifications and chromatin reorganization, as well as transcriptional and post-transcriptional modulation of gene expression, allowing plant adaptation to various environmental stresses. LncRNAs can positively or negatively modulate stress responses, affecting processes such as hormone signaling, temperature tolerance, and nutrient deficiency adaptation. Moreover, they also seem to play a role in stress memory, wherein prior exposure to mild stress enhances plant ability to adapt to subsequent stressful conditions. In this review, we summarize the contribution of lncRNAs in plant adaptation to biotic and abiotic stresses, as well as stress memory. The complex evolutionary conservation of lncRNAs is also discussed and provides insights into future research directions in this field.

Composition and function of stress granules and P-bodies in plants

Stress Granules (SGs) and Processing-bodies (P-bodies) are biomolecular condensates formed in the cell with the highly conserved purpose of maintaining balance between storage, translation, and degradation of mRNA. This balance is particularly important when cells are exposed to different environmental conditions and adjustments have to be made in order for plants to respond to and tolerate stressful conditions. While P-bodies are constitutively present in the cell, SG formation is a stress-induced event. Typically thought of as protein-RNA aggregates, SGs and P-bodies are formed by a process called liquid-liquid phase separation (LLPS), and both their function and composition are very dynamic. Both foci are known to contain proteins involved in translation, protein folding, and ATPase activity, alluding to their roles in regulating mRNA and protein expression levels. From an RNA perspective, SGs and P-bodies primarily consist of mRNAs, though long non-coding RNAs (lncRNAs) have also been observed, and more focus is now being placed on the specific RNAs associated with these aggregates. Recently, metabolites such as nucleotides and amino acids have been reported in purified plant SGs with implications for the energetic dynamics of these condensates. Thus, even though the field of plant SGs and P-bodies is relatively nascent, significant progress has been made in understanding their composition and biological role in stress responses. In this review, we discuss the most recent discoveries centered around SG and P-body function and composition in plants.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

Population-level annotation of lncRNAs in Arabidopsis reveals extensive expression variation associated with transposable element-like silencing

Long noncoding RNAs (lncRNAs) are understudied and underannotated in plants. In mammals, lncRNA loci are nearly as ubiquitous as protein-coding genes, and their expression is highly variable between individuals of the same species. Using Arabidopsis thaliana as a model, we aimed to elucidate the true scope of lncRNA transcription across plants from different regions and study its natural variation. We used transcriptome deep sequencing data sets spanning hundreds of natural accessions and several developmental stages to create a population-wide annotation of lncRNAs, revealing thousands of previously unannotated lncRNA loci. While lncRNA transcription is ubiquitous in the genome, most loci appear to be actively silenced and their expression is extremely variable between natural accessions. This high expression variability is largely caused by the high variability of repressive chromatin levels at lncRNA loci. High variability was particularly common for intergenic lncRNAs (lincRNAs), where pieces of transposable elements (TEs) present in 50% of these lincRNA loci are associated with increased silencing and variation, and such lncRNAs tend to be targeted by the TE silencing machinery. We created a population-wide lncRNA annotation in Arabidopsis and improve our understanding of plant lncRNA genome biology, raising fundamental questions about what causes transcription and silencing across the genome.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Transcription factors KANADI 1, MYB DOMAIN PROTEIN 44, and PHYTOCHROME INTERACTING FACTOR 4 regulate long intergenic noncoding RNAs expressed in Arabidopsis roots

Thousands of long intergenic noncoding RNAs (lincRNAs) have been identified in plant genomes. While some lincRNAs have been characterized as important regulators in different biological processes, little is known about the transcriptional regulation for most plant lincRNAs. Through the integration of 8 annotation resources, we defined 6,599 high-confidence lincRNA loci in Arabidopsis (Arabidopsis thaliana). For lincRNAs belonging to different evolutionary age categories, we identified major differences in sequence and chromatin features, as well as in the level of conservation and purifying selection acting during evolution. Spatiotemporal gene expression profiles combined with transcription factor (TF) chromatin immunoprecipitation (ChIP) data were used to construct a TF-lincRNA regulatory network containing 2,659 lincRNAs and 15,686 interactions. We found that properties characterizing lincRNA expression, conservation, and regulation differ between plants and animals. Experimental validation confirmed the role of 3 TFs, KANADI 1, MYB DOMAIN PROTEIN 44, and PHYTOCHROME INTERACTING FACTOR 4, as key regulators controlling root-specific lincRNA expression, demonstrating the predictive power of our network. Furthermore, we identified 58 lincRNAs, regulated by these TFs, showing strong root cell type-specific expression or chromatin accessibility, which are linked with genome-wide association studies genetic associations related to root system development and growth. The multilevel genome-wide characterization covering chromatin state information, promoter conservation, and chromatin immunoprecipitation-based TF binding, for all detectable lincRNAs across 769 expression samples, permits rapidly defining the biological context and relevance of Arabidopsis lincRNAs through regulatory networks.

Plant long non-coding RNAs: identification and analysis to unveil their physiological functions

Eukaryotic genomes encode thousands of RNA molecules; however, only a minimal fraction is translated into proteins. Among the non-coding elements, long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. LncRNAs are associated mainly with the regulation of the expression of the genome; nonetheless, their study has just scratched the surface. This is somewhat due to the lack of widespread conservation at the sequence level, in addition to their relatively low and highly tissue-specific expression patterns, which makes their exploration challenging, especially in plant genomes where only a few of these molecules have been described completely. Recently published high-quality genomes of crop plants, along with new computational tools, are considered promising resources for studying these molecules in plants. This review briefly summarizes the characteristics of plant lncRNAs, their presence and conservation, the different protocols to find these elements, and the limitations of these protocols. Likewise, it describes their roles in different plant physiological phenomena. We believe that the study of lncRNAs can help to design strategies to reduce the negative effect of biotic and abiotic stresses on the yield of crop plants and, in the future, help create fruits and vegetables with improved nutritional content, higher amounts of compounds with positive effects on human health, better organoleptic characteristics, and fruits with a longer postharvest shelf life.

Analysis of lncRNAs in Lupinus mutabilis (Tarwi) and Their Potential Role in Drought Response

Lupinus mutabilis is a legume with high agronomic potential and available transcriptomic data for which lncRNAs have not been studied. Therefore, our objective was to identify, characterize, and validate the drought-responsive lncRNAs in L. mutabilis. To achieve this, we used a multilevel approach based on lncRNA prediction, annotation, subcellular location, thermodynamic characterization, structural conservation, and validation. Thus, 590 lncRNAs were identified by at least two algorithms of lncRNA identification. Annotation with the PLncDB database showed 571 lncRNAs unique to tarwi and 19 lncRNAs with homology in 28 botanical families including Solanaceae (19), Fabaceae (17), Brassicaceae (17), Rutaceae (17), Rosaceae (16), and Malvaceae (16), among others. In total, 12 lncRNAs had homology in more than 40 species. A total of 67% of lncRNAs were located in the cytoplasm and 33% in exosomes. Thermodynamic characterization of S03 showed a stable secondary structure with -105.67 kcal/mol. This structure included three regions, with a multibranch loop containing a hairpin with a SECIS-like element. Evaluation of the structural conservation by CROSSalign revealed partial similarities between L. mutabilis (S03) and S. lycopersicum (Solyc04r022210.1). RT-PCR validation demonstrated that S03 was upregulated in a drought-tolerant accession of L. mutabilis. Finally, these results highlighted the importance of lncRNAs in tarwi improvement under drought conditions.

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

Linking discoveries, mechanisms, and technologies to develop a clearer perspective on plant long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a large and diverse class of genes in eukaryotic genomes that contribute to a variety of regulatory processes. Functionally characterized lncRNAs play critical roles in plants, ranging from regulating flowering to controlling lateral root formation. However, findings from the past decade have revealed that thousands of lncRNAs are present in plant transcriptomes, and characterization has lagged far behind identification. In this setting, distinguishing function from noise is challenging. However, the plant community has been at the forefront of discovery in lncRNA biology, providing many functional and mechanistic insights that have increased our understanding of this gene class. In this review, we examine the key discoveries and insights made in plant lncRNA biology over the past two and a half decades. We describe how discoveries made in the pregenomics era have informed efforts to identify and functionally characterize lncRNAs in the subsequent decades. We provide an overview of the functional archetypes into which characterized plant lncRNAs fit and speculate on new avenues of research that may uncover yet more archetypes. Finally, this review discusses the challenges facing the field and some exciting new molecular and computational approaches that may help inform lncRNA comparative and functional analyses.

Rock, scissors, paper: How RNA structure informs function

RNA can fold back on itself to adopt a wide range of structures. These range from relatively simple hairpins to intricate 3D folds and can be accompanied by regulatory interactions with both metabolites and macromolecules. The last 50 yr have witnessed elucidation of an astonishing array of RNA structures including transfer RNAs, ribozymes, riboswitches, the ribosome, the spliceosome, and most recently entire RNA structuromes. These advances in RNA structural biology have deepened insight into fundamental biological processes including gene editing, transcription, translation, and structure-based detection and response to temperature and other environmental signals. These discoveries reveal that RNA can be relatively static, like a rock; that it can have catalytic functions of cutting bonds, like scissors; and that it can adopt myriad functional shapes, like paper. We relate these extraordinary discoveries in the biology of RNA structure to the plant way of life. We trace plant-specific discovery of ribozymes and riboswitches, alternative splicing, organellar ribosomes, thermometers, whole-transcriptome structuromes and pan-structuromes, and conclude that plants have a special set of RNA structures that confer unique types of gene regulation. We finish with a consideration of future directions for the RNA structure-function field.

LncRNA FLAIL affects alternative splicing and represses flowering in Arabidopsis

How the noncoding genome affects cellular functions is a key biological question. A particular challenge is to distinguish the effects of noncoding DNA elements from long noncoding RNAs (lncRNAs) that coincide at the same loci. Here, we identified the flowering-associated intergenic lncRNA (FLAIL) in Arabidopsis through early flowering flail mutants. Expression of FLAIL RNA from a different chromosomal location in combination with strand-specific RNA knockdown characterized FLAIL as a trans-acting RNA molecule. FLAIL directly binds to differentially expressed target genes that control flowering via RNA-DNA interactions through conserved sequence motifs. FLAIL interacts with protein and RNA components of the spliceosome to affect target mRNA expression through co-transcriptional alternative splicing (AS) and linked chromatin regulation. In the absence of FLAIL, splicing defects at the direct FLAIL target flowering gene LACCASE 8 (LAC8) correlated with reduced mRNA expression. Double mutant analyses support a model where FLAIL-mediated splicing of LAC8 promotes its mRNA expression and represses flowering. Our study suggests lncRNAs as accessory components of the spliceosome that regulate AS and gene expression to impact organismal development.

Nuclear and cytoplasmic lncRNAs in root tips of the model legume Medicago truncatula under control and submergence

In this study, we aimed to identify long noncoding RNAs (lncRNAs) in root tips of the model legume Medicago truncatula using previously generated nuclear, total polyA, ribosome-associated polyA, and Riboseq RNA datasets, which might shed light on their localization and potential regulatory roles. RNA-seq data were mapped to the version 5 of the M. truncatula A17 genome and analyzed to identify genome annotated lncRNAs and putative new root tip (NRT) lncRNAs. lncRNAs were classified according to their genomic location relative to chromatin accessible regions, protein-coding genes and transposable elements (TE), finding differences between annotated lncRNAs and NRT lncRNAs, both in their genomic position as well as in the type of TEs in their vicinity. We investigated their response to submergence and found a set of regulated lncRNAs that were preferentially upregulated in the nucleus, some of which were located nearby genes of the conserved submergence upregulated gene families, and chromatin accessible regions suggesting a potential regulatory role. Finally, the accumulation of lncRNAs under submergence was validated by reverse transcription quantitative polymerase chain reaction on nuclear RNA, providing additional evidence of their localization, which could ultimately be required for their function.

Epigenetic modifications: Allusive clues of lncRNA functions in plants

Long non-coding RNAs (lncRNAs) have been verified as flexible and important factors in various biological processes of multicellular eukaryotes, including plants. The respective intricate crosstalk among multiple epigenetic modifications has been examined to some extent. However, only a small proportion of lncRNAs has been functionally well characterized. Moreover, the relationship between lncRNAs and other epigenetic modifications has not been systematically studied. In this mini-review, we briefly summarize the representative biological functions of lncRNAs in developmental programs and environmental responses in plants. In addition, we particularly discuss the intimate relationship between lncRNAs and other epigenetic modifications, and we outline the underlying avenues and challenges for future research on plant lncRNAs.

Genome-wide identification of antisense lncRNAs and their association with susceptibility to Flavobacterium psychrophilum in rainbow trout

Eukaryotic genomes encode long noncoding natural antisense transcripts (lncNATs) that have been increasingly recognized as regulatory members of gene expression. Recently, we identified a few antisense transcripts correlating in expression with immune-related genes. However, a systematic genome-wide analysis of lncNATs in rainbow trout is lacking. This study used 134 RNA-Seq datasets from five different projects to identify antisense transcripts. A total of 13,503 lncNATs were identified genome-wide. About 75% of lncNATs showed multiple exons compared to 36.5% of the intergenic lncRNAs. RNA-Seq datasets from resistant, control, and susceptible rainbow trout genetic lines with significant differences in survival rate following Flavobacterium psychrophilum (Fp) infection were analyzed to investigate the potential role of the lncNATs during infection. Twenty-four pairwise comparisons between the different genetic lines, infectious status, and time points revealed 581 differentially expressed (DE) lncNATs and 179 differentially used exons (DUEs). Most of the DE lncNATs strongly and positively correlated in expression with their corresponding sense transcripts across 24 RNA-Seq datasets. LncNATs complementary to genes related to immunity, muscle contraction, proteolysis, and iron/heme metabolism were DE following infection. LncNATs complementary to hemolysis-related genes were DE in the resistant fish compared to susceptible fish on day 5 post-infection, suggesting enhanced clearance of free hemoglobin (Hb) and heme and increased erythropoiesis. LncNATs complementary to hepcidin, a master negative regulator of the plasma iron concentration, were the most downregulated lncNATs on day 5 of bacterial infection in the resistant fish. Ninety-four DE lncNAT, including five complementary to hepcidin, are located within 26 QTL regions previously identified in association with bacterial cold water disease (BCWD) in rainbow trout. Collectively, lncNATs are involved in the molecular architecture of fish immunity and should be further investigated for potential applications in genomic selection and genetic manipulation in aquaculture.

Transcriptome-guided annotation and functional classification of long non-coding RNAs in Arabidopsis thaliana

Long non-coding RNAs (lncRNAs) are a prominent class of eukaryotic regulatory genes. Despite the numerous available transcriptomic datasets, the annotation of plant lncRNAs remains based on dated annotations that have been historically carried over. We present a substantially improved annotation of Arabidopsis thaliana lncRNAs, generated by integrating 224 transcriptomes in multiple tissues, conditions, and developmental stages. We annotate 6764 lncRNA genes, including 3772 that are novel. We characterize their tissue expression patterns and find 1425 lncRNAs are co-expressed with coding genes, with enriched functional categories such as chloroplast organization, photosynthesis, RNA regulation, transcription, and root development. This improved transcription-guided annotation constitutes a valuable resource for studying lncRNAs and the biological processes they may regulate.