Distinct types of short open reading frames are translated in plant cells

Predicted roles of long non-coding RNAs in abiotic stress tolerance responses of plants

The plant genome exhibits a significant amount of transcriptional activity, with most of the resulting transcripts lacking protein-coding potential. Non-coding RNAs play a pivotal role in the development and regulatory processes in plants. Long non-coding RNAs (lncRNAs), which exceed 200 nucleotides, may play a significant role in enhancing plant resilience to various abiotic stresses, such as excessive heat, drought, cold, and salinity. In addition, the exogenous application of chemicals, such as abscisic acid and salicylic acid, can augment plant defense responses against abiotic stress. While how lncRNAs play a role in abiotic stress tolerance is relatively well-studied in model plants, this review provides a comprehensive overview of the current understanding of this function in horticultural crop plants. It also delves into the potential role of lncRNAs in chemical priming of plants in order to acquire abiotic stress tolerance, although many limitations exist in proving lncRNA functionality under such conditions.

Biological Activity of Artificial Plant Peptides Corresponding to the Translational Products of Small ORFs in Primary miRNAs and Other Long "Non-Coding" RNAs

Generally, lncPEPs (peptides encoded by long non-coding RNAs) have been identified in many plant species of several families and in some animal species. Importantly, molecular mechanisms of the miPEPs (peptides encoded by primary microRNAs, pri-miRNAs) are often poorly understood in different flowering plants. Requirement for the additional studies in these directions is highlighted by alternative findings concerning positive regulation of pri-miRNA/miRNA expression by synthetic miPEPs in plants. Further extensive studies are also needed to understand the full set of their roles in eukaryotic organisms. This review mainly aims to consider the available data on the regulatory functions of the synthetic miPEPs. Studies of chemically synthesized miPEPs and analyzing the fine molecular mechanisms of their functional activities are reviewed. Brief description of the studies to identify lncORFs (open reading frames of long non-coding RNAs) and the encoded protein products is also provided.

miPEPPred-FRL: A Novel Method for Predicting Plant MiRNA-Encoded Peptides Using Adaptive Feature Representation Learning

MicroRNAs (miRNAs) are an essential type of small molecule RNAs that play significant regulatory roles in organisms. Recent studies have demonstrated that small open reading frames (sORFs) harbored in primary miRNAs (pri-miRNAs) can encode small peptides, known as miPEPs. Plant miPEPs can increase the abundance and activity of cognate miRNAs by promoting the transcription of their corresponding pri-miRNAs, thereby modulating plant traits. Biological experiments are the most effective way to accurately identify miPEPs; however, they are time-consuming and expensive. Hence, an efficient computational method for the identification of miPEPs on a large scale is highly desirable. Up to now, there have been no specialized computational tools for identifying miPEPs. In this work, a novel predictor named miPEPPred-FRL based on an adaptive feature representation learning framework that consists of the feature transformation module and the cascade architecture has been proposed. The feature transformation module integrating a newly designed feature selection method and classifier selection rule is developed to convert sequence-based features into primary class and probabilistic features, which are then fed into the improved cascade architecture to obtain more stable and discriminative augmented features. Finally, the augmented features are utilized to construct the final predictor. Cross-validation experiments illustrate that the novel feature selection method and classifier selection rule contribute to boosting the feature representation ability of the framework. Furthermore, the high accuracy of miPEPPred-FRL on independent testing data suggests that it is a trustworthy and valuable tool for the identification of miPEPs.

sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

Translatome and Transcriptome Analyses Reveal the Mechanism that Underlies the Enhancement of Salt Stress by the Small Peptide Ospep5 in Plants

Salt stress significantly impedes plant growth and the crop yield. This study utilized de novo transcriptome assembly and ribosome profiling to explore mRNA translation's role in rice salt tolerance. We identified unrecognized translated open reading frames (ORFs), including 42 upstream transcripts and 86 unannotated transcripts. A noteworthy discovery was the role of a small ORF, Ospep5, in conferring salt tolerance. Overexpression of Ospep5 in plants increased salt tolerance, while its absence led to heightened sensitivity. This hypothesis was corroborated by the findings that exogenous application of the synthetic small peptide Ospep5 bolstered salt tolerance in both rice and Arabidopsis. We found that the mechanism underpinning the Ospep5-mediated salt tolerance involves the maintenance of intracellular Na+/K+ homeostasis, facilitated by upregulation of high-affinity potassium transporters (HKT) and Na+/H+ exchangers (SOS1). Furthermore, a comprehensive multiomics approach, particularly ribosome profiling, is instrumental in uncovering unannotated ORFs and elucidating their functions in plant stress responses.

Improved super-resolution ribosome profiling reveals prevalent translation of upstream ORFs and small ORFs in Arabidopsis

A crucial step in functional genomics is identifying actively translated ORFs and linking them to biological functions. The challenge lies in identifying short ORFs, as their identification is greatly influenced by data quality and depth. Here, we improved the coverage of super-resolution Ribo-seq in Arabidopsis (Arabidopsis thaliana), revealing uncharacterized translation events for nuclear, chloroplastic, and mitochondrial genes. Assisted by a transcriptome assembly, we identified 7,751 unconventional translation events, comprising 6,996 upstream ORFs (uORFs) and 209 downstream ORFs on annotated protein-coding genes, as well as 546 ORFs in presumed noncoding RNAs. Proteomic data confirmed the production of stable proteins from some of these unannotated translation events. We present evidence of active translation from primary transcripts of trans-acting small interfering RNAs (TAS1-4) and microRNAs (pri-MIR163 and pri-MIR169) and periodic ribosome stalling supporting cotranslational decay. Additionally, we developed a method for identifying extremely short uORFs, including 370 minimum uORFs (AUG-stop), and 2,921 tiny uORFs (2 to 10 amino acids) and 681 uORFs that overlap with each other. Remarkably, these short uORFs exhibit strong translational repression as do longer uORFs. We also systematically discovered 594 uORFs regulated by alternative splicing, suggesting widespread isoform-specific translational control. Finally, these prevalent uORFs are associated with numerous important pathways. In summary, our improved Arabidopsis translational landscape provides valuable resources to study gene expression regulation.

The Cryptic Bacterial Microproteome

Microproteins encoded by small open reading frames (smORFs) comprise the "dark matter" of proteomes. Although functional microproteins were identified in diverse organisms from all three domains of life, bacterial smORFs remain poorly characterized. In this comprehensive study of intergenic smORFs (ismORFs, 15-70 codons) in 5,668 bacterial genomes of the family Enterobacteriaceae, we identified 67,297 clusters of ismORFs subject to purifying selection. The ismORFs mainly code for hydrophobic, potentially transmembrane, unstructured, or minimally structured microproteins. Using AlphaFold Multimer, we predicted interactions of some of the predicted microproteins encoded by transcribed ismORFs with proteins encoded by neighboring genes, revealing the potential of microproteins to regulate the activity of various proteins, particularly, under stress. We compiled a catalog of predicted microprotein families with different levels of evidence from synteny analysis, structure prediction, and transcription and translation data. This study offers a resource for investigation of biological functions of microproteins.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

LncRNAs exert indispensable roles in orchestrating the interaction among diverse noncoding RNAs and enrich the regulatory network of plant growth and its adaptive environmental stress response

With the advent of advanced sequencing technologies, non-coding RNAs (ncRNAs) are increasingly pivotal and play highly regulated roles in the modulation of diverse aspects of plant growth and stress response. This includes a spectrum of ncRNA classes, ranging from small RNAs to long non-coding RNAs (lncRNAs). Notably, among these, lncRNAs emerge as significant and intricate components within the broader ncRNA regulatory networks. Here, we categorize ncRNAs based on their length and structure into small RNAs, medium-sized ncRNAs, lncRNAs, and circle RNAs. Furthermore, the review delves into the detailed biosynthesis and origin of these ncRNAs. Subsequently, we emphasize the diverse regulatory mechanisms employed by lncRNAs that are located at various gene regions of coding genes, embodying promoters, 5'UTRs, introns, exons, and 3'UTR regions. Furthermore, we elucidate these regulatory modes through one or two concrete examples. Besides, lncRNAs have emerged as novel central components that participate in phase separation processes. Moreover, we illustrate the coordinated regulatory mechanisms among lncRNAs, miRNAs, and siRNAs with a particular emphasis on the central role of lncRNAs in serving as sponges, precursors, spliceosome, stabilization, scaffolds, or interaction factors to bridge interactions with other ncRNAs. The review also sheds light on the intriguing possibility that some ncRNAs may encode functional micropeptides. Therefore, the review underscores the emergent roles of ncRNAs as potent regulatory factors that significantly enrich the regulatory network governing plant growth, development, and responses to environmental stimuli. There are yet-to-be-discovered roles of ncRNAs waiting for us to explore.

Shining in the dark: the big world of small peptides in plants

Small peptides represent a subset of dark matter in plant proteomes. Through differential expression patterns and modes of action, small peptides act as important regulators of plant growth and development. Over the past 20 years, many small peptides have been identified due to technical advances in genome sequencing, bioinformatics, and chemical biology. In this article, we summarize the classification of plant small peptides and experimental strategies used to identify them as well as their potential use in agronomic breeding. We review the biological functions and molecular mechanisms of small peptides in plants, discuss current problems in small peptide research and highlight future research directions in this field. Our review provides crucial insight into small peptides in plants and will contribute to a better understanding of their potential roles in biotechnology and agriculture.

smAMPsTK: a toolkit to unravel the smORFome encoding AMPs of plant species

The pervasive repertoire of plant molecules with the potential to serve as a substitute for conventional antibiotics has led to obtaining better insights into plant-derived antimicrobial peptides (AMPs). The massive distribution of Small Open Reading Frames (smORFs) throughout eukaryotic genomes with proven extensive biological functions reflects their practicality as antimicrobials. Here, we have developed a pipeline named smAMPsTK to unveil the underlying hidden smORFs encoding AMPs for plant species. By applying this pipeline, we have elicited AMPs of various functional activity of lengths ranging from 5 to 100 aa by employing publicly available transcriptome data of five different angiosperms. Later, we studied the coding potential of AMPs-smORFs, the inclusion of diverse translation initiation start codons, and amino acid frequency. Codon usage study signifies no such codon usage biases for smORFs encoding AMPs. Majorly three start codons are prominent in generating AMPs. The evolutionary and conservational study proclaimed the widespread distribution of AMPs encoding genes throughout the plant kingdom. Domain analysis revealed that nearly all AMPs have chitin-binding ability, establishing their role as antifungal agents. The current study includes a developed methodology to characterize smORFs encoding AMPs, and their implications as antimicrobial, antibacterial, antifungal, or antiviral provided by SVM score and prediction status calculated by machine learning-based prediction models. The pipeline, complete package, and the results derived for five angiosperms are freely available at https://github.com/skbinfo/smAMPsTK.Communicated by Ramaswamy H. Sarma.

Fungal strain improvement for efficient cellulase production and lignocellulosic biorefinery: Current status and future prospects

Lignocellulosic biomass (LCB) has been recognized as a valuable carbon source for the sustainable production of biofuels and value-added biochemicals. Crude enzymes produced by fungal cell factories benefit economic LCB degradation. However, high enzyme production cost remains a great challenge. Filamentous fungi have been widely used to produce cellulolytic enzymes. Metabolic engineering of fungi contributes to efficient cellulase production for LCB biorefinery. Here the latest progress in utilizing fungal cell factories for cellulase production was summarized, including developing genome engineering tools to improve the efficiency of fungal cell factories, manipulating promoters, and modulating transcription factors. Multi-omics analysis of fungi contributes to identifying novel genetic elements for enhancing cellulase production. Furthermore, the importance of translation regulation of cellulase production are emphasized. Efficient development of fungal cell factories based on integrative strain engineering would benefit the overall bioconversion efficacy of LCB for sustainable bioproduction.

Small Open Reading Frame-Encoded Micro-Peptides: An Emerging Protein World

Small open reading frames (sORFs) are often overlooked features in genomes. In the past, they were labeled as noncoding or "transcriptional noise". However, accumulating evidence from recent years suggests that sORFs may be transcribed and translated to produce sORF-encoded polypeptides (SEPs) with less than 100 amino acids. The vigorous development of computational algorithms, ribosome profiling, and peptidome has facilitated the prediction and identification of many new SEPs. These SEPs were revealed to be involved in a wide range of basic biological processes, such as gene expression regulation, embryonic development, cellular metabolism, inflammation, and even carcinogenesis. To effectively understand the potential biological functions of SEPs, we discuss the history and development of the newly emerging research on sORFs and SEPs. In particular, we review a range of recently discovered bioinformatics tools for identifying, predicting, and validating SEPs as well as a variety of biochemical experiments for characterizing SEP functions. Lastly, this review underlines the challenges and future directions in identifying and validating sORFs and their encoded micropeptides, providing a significant reference for upcoming research on sORF-encoded peptides.

Unveiling the secrets of non-coding RNA-encoded peptides in plants: A comprehensive review of mining methods and research progress

Non-coding RNAs (ncRNAs) are not conventionally involved in protein encoding. However, recent findings indicate that ncRNAs possess the capacity to code for proteins or peptides. These ncRNA-encoded peptides (ncPEPs) are vital for diverse plant life processes and exhibit significant potential value. Despite their importance, research on plant ncPEPs is limited, with only a few studies conducted and less information on the underlying mechanisms, and the field remains in its nascent stage. This manuscript provides a comprehensive overview of ncPEPs mining methods in plants, focusing on prediction, identification, and functional analysis. We discuss the strengths and weaknesses of various techniques, identify future research directions in the ncPEPs domain, and elucidate the biological functions and agricultural application prospects of plant ncPEPs. By highlighting the immense potential and research value of ncPEPs, we aim to lay a solid foundation for more in-depth studies in plant science.

Identification of small open reading frames in plant lncRNA using class-imbalance learning

Recently, small open reading frames (sORFs) in long noncoding RNA (lncRNA) have been demonstrated to encode small peptides that can help study the mechanisms of growth and development in organisms. Since machine learning-based computational methods are less costly compared with biological experiments, they can be used to identify sORFs and provide a basis for biological experiments. However, few computational methods and data resources have been exploited for identifying sORFs in plant lncRNA. Besides, machine learning models produce underperforming classifiers when faced with a class-imbalance problem. In this study, an alternative method called SMOTE based on weighted cosine distance (WCDSMOTE) which enables interaction with feature selection is put forward to synthesize minority class samples and weighted edited nearest neighbor (WENN) is applied to clean up majority class samples, thus, hybrid sampling WCDSMOTE-ENN is proposed to deal with imbalanced datasets with the multi-angle feature. A heterogeneous classifier ensemble is introduced to complete the classification task. Therefore, a novel computational method that is based on class-imbalance learning to identify the sORFs with coding potential in plant lncRNA (sORFplnc) is presented. Experimental results manifest that sORFplnc outperforms existing computational methods in identifying sORFs with coding potential. We anticipate that the proposed work can be a reference for relevant research and contribute to agriculture and biomedicine.

Prediction of protein-coding small ORFs in multi-species using integrated sequence-derived features and the random forest model

Proteins encoded by small open reading frames (sORFs) can serve as functional elements playing important roles in vivo. Such sORFs also constitute the potential pool for facilitating the de novo gene birth, driving evolutionary innovation and species diversity. Therefore, their theoretical and experimental identification has become a critical issue. Herein, we proposed a protein-coding sORFs prediction method merely based on integrative sequence-derived features. Our prediction performance is better or comparable compared with other nine prevalent methods, which shows that our method can provide a relatively reliable research tool for the prediction of protein-coding sORFs. Our method allows users to estimate the potential expression of a queried sORF, which has been demonstrated by the correlation analysis between our possibility estimation and codon adaption index (CAI). Based on the features that we used, we demonstrated that the sequence features of the protein-coding sORFs in the two domains have significant differences implying that it might be a relatively hard task in terms of cross-domain prediction, hence domain-specific models were developed, which allowed users to predict protein-coding sORFs both in eukaryotes and prokaryotes. Finally, a web-server was developed and provided to boost and facilitate the study of the related field, which is freely available at http://guolab.whu.edu.cn/codingCapacity/index.html.

RALF peptides modulate immune response in the moss Physcomitrium patens

BACKGROUND

RAPID ALKALINIZATION FACTOR (RALFs) are cysteine-rich peptides that regulate multiple physiological processes in plants. This peptide family has considerably expanded during land plant evolution, but the role of ancient RALFs in modulating stress responses is unknown.Results: Here, we used the moss Physcomitrium patens as a model to gain insight into the role of RALF peptides in the coordination of plant growth and stress response in non-vascular plants. The quantitative proteomic analysis revealed concerted downregulation of M6 metalloprotease and some membrane proteins, including those involved in stress response, in PpRALF1, 2 and 3 knockout (KO) lines. The subsequent analysis revealed the role of PpRALF3 in growth regulation under abiotic and biotic stress conditions, implying the importance of RALFs in responding to various adverse conditions in bryophytes. We found that knockout of the PpRALF2 and PpRALF3 genes resulted in increased resistance to bacterial and fungal phytopathogens, Pectobacterium carotovorum and Fusarium solani, suggesting the role of these peptides in negative regulation of the immune response in P. patens. Comparing the transcriptomes of PpRALF3 KO and wild-type plants infected by F. solani showed that the regulation of genes in the phenylpropanoid pathway and those involved in cell wall modification and biogenesis was different in these two genotypes.

CONCLUSION

Thus, our study sheds light on the function of the previously uncharacterized PpRALF3 peptide and gives a clue to the ancestral functions of RALF peptides in plant stress response.

Comprehensive analysis of peptide-coding genes and initial characterization of an LRR-only microprotein in Marchantia polymorpha

In the past two decades, many plant peptides have been found to play crucial roles in various biological events by mediating cell-to-cell communications. However, a large number of small open reading frames (sORFs) or short genes capable of encoding peptides remain uncharacterized. In this study, we examined several candidate genes for peptides conserved between two model plants: Arabidopsis thaliana and Marchantia polymorpha. We examined their expression pattern in M. polymorpha and subcellular localization using a transient assay with Nicotiana benthamiana. We found that one candidate, MpSGF10B, was expressed in meristems, gemma cups, and male reproductive organs called antheridiophores. MpSGF10B has an N-terminal signal peptide followed by two leucine-rich repeat (LRR) domains and was secreted to the extracellular region in N. benthamiana and M. polymorpha. Compared with the wild type, two independent Mpsgf10b mutants had a slightly increased number of antheridiophores. It was revealed in gene ontology enrichment analysis that MpSGF10B was significantly co-expressed with genes related to cell cycle and development. These results suggest that MpSGF10B may be involved in the reproductive development of M. polymorpha. Our research should shed light on the unknown role of LRR-only proteins in land plants.

Complementary peptides represent a credible alternative to agrochemicals by activating translation of targeted proteins

The current agriculture main challenge is to maintain food production while facing multiple threats such as increasing world population, temperature increase, lack of agrochemicals due to health issues and uprising of weeds resistant to herbicides. Developing novel, alternative, and safe methods is hence of paramount importance. Here, we show that complementary peptides (cPEPs) from any gene can be designed to target specifically plant coding genes. External application of synthetic peptides increases the abundance of the targeted protein, leading to related phenotypes. Moreover, we provide evidence that cPEPs can be powerful tools in agronomy to improve plant traits, such as growth, resistance to pathogen or heat stress, without the needs of genetic approaches. Finally, by combining their activity they can also be used to reduce weed growth.

Peptidomics Methods Applied to the Study of Flower Development

Understanding the global and dynamic nature of plant developmental processes requires not only the study of the transcriptome, but also of the proteome, including its largely uncharacterized peptidome fraction. Recent advances in proteomics and high-throughput analyses of translating RNAs (ribosome profiling) have begun to address this issue, evidencing the existence of novel, uncharacterized, and possibly functional peptides. To validate the accumulation in tissues of sORF-encoded polypeptides (SEPs), the basic setup of proteomic analyses (i.e., LC-MS/MS) can be followed. However, the detection of peptides that are small (up to ~100 aa, 6-7 kDa) and novel (i.e., not annotated in reference databases) presents specific challenges that need to be addressed both experimentally and with computational biology resources. Several methods have been developed in recent years to isolate and identify peptides from plant tissues. In this chapter, we outline two different peptide extraction protocols and the subsequent peptide identification by mass spectrometry using the database search or the de novo identification methods.

Mosaic translation hypothesis: chimeric polypeptides produced via multiple ribosomal frameshifting as a basis for adaptability

How many different proteins can be produced from a single spliced transcript? Genome annotation projects overlook the coding potential of reading frames other than that of the reference open reading frames (refORFs). Recently, alternative open reading frames (altORFs) and their translational products, alternative proteins, have been shown to carry out important functions in various organisms. AltORFs overlapping refORFs or other altORFs in a different reading frame may be involved in one fundamental mechanism so far overlooked. A few years ago, it was proposed that altORFs may act as building blocks for chimeric (mosaic) polypeptides, which are produced via multiple ribosomal frameshifting events from a single mature transcript. We adopt terminology from that earlier discussion and call this mechanism mosaic translation. This way of extracting and combining genetic information may significantly increase proteome diversity. Thus, we hypothesize that this mechanism may have contributed to the flexibility and adaptability of organisms to a variety of environmental conditions. Specialized ribosomes acting as sensors probably played a central role in this process. Importantly, mosaic translation may be the main source of protein diversity in genomes that lack alternative splicing. The idea of mosaic translation is a testable hypothesis, although its direct demonstration is challenging. Should mosaic translation occur, we would currently highly underestimate the complexity of translation mechanisms and thus the proteome.

Identifying LncRNA-Encoded Short Peptides Using Optimized Hybrid Features and Ensemble Learning

Long non-coding RNA (lncRNA) contains short open reading frames (sORFs), and sORFs-encoded short peptides (SEPs) have become the focus of scientific studies due to their crucial role in life activities. The identification of SEPs is vital to further understanding their regulatory function. Bioinformatics methods can quickly identify SEPs to provide credible candidate sequences for verifying SEPs by biological experimenrts. However, there is a lack of methods for identifying SEPs directly. In this study, a machine learning method to identify SEPs of plant lncRNA (ISPL) is proposed. Hybrid features including sequence features and physicochemical features are extracted manually or adaptively to construct different modal features. In order to keep the stability of feature selection, the non-linear correction applied in Max-Relevance-Max-Distance (nocRD) feature selection method is proposed, which integrates multiple feature ranking results and uses the iterative random forest for different modal features dimensionality reduction. Classification models with different modal features are constructed, and their outputs are combined for ensemble classification. The experimental results show that the accuracy of ISPL is 89.86% percent on the independent test set, which will have important implications for further studies of functional genomic.

Identification and analysis of smORFs in Chlamydomonas reinhardtii

Small open reading frames (smORFs) have been acknowledged as an important partner in organism functions ranging from bacteria to higher eukaryotes. However, lack of investigation of smORFs in green algae, despite their importance in ecology and evolution. We applied bioinformatic analysis, ribosome profiling, and small peptide proteomics to provide a genome-wide and high-confident smORF database in the model green alga Chlamydomonas reinhardtii. The whole genome was screened first to mine potential coding smORFs. Then conservative analysis, ribosome profiling, and proteomics data were processed to identify conserved smORFs and generate translation evidence. The combination of procedures resulted in 2014 smORFs that might exist in the C. reinhardtii genome. The expression of smORFs in Cd treatment suggested that two smORFs might participate in redox reaction, three in inorganic phosphate transport, and one in DNA repair under stress. Our study built a genome-widely database in C. reinhardtii, providing target smORFs for further research.

Large-scale discovery of non-conventional peptides in grape (Vitis vinifera L.) through peptidogenomics

Non-conventional peptides (NCPs), which are peptides derived from previously unannotated coding sequences, play important biological roles in plants. In this study, we used peptidogenomic methods that integrated mass spectrometry (MS) peptidomics and a six-frame translation database to extensively identify NCPs in grape. In total, 188 and 2021 non-redundant peptides from the Arabidopsis thaliana and Vitis vinifera L. protein database at Ensembl/URGI and an individualized peptidogenomic database were identified. Unlike conventional peptides, these NCPs derived mainly from intergenic, intronic, upstream ORF, 5'UTR, 3'UTR, and downstream ORF regions. These results show that unannotated regions are translated more broadly than we thought. We also found that most NCPs were derived from regions related to phenotypic variations, LTR retrotransposons, and domestication selection, indicating that the NCPs have an important function in complex biological processes. We also found that the NCPs were developmentally specific and had transient and specific functions in grape berry development. In summary, our study is the first to extensively identify NCPs in grape. It demonstrated that there was a large amount of translation in the genome. These results lay a foundation for studying the functions of NCPs and also provide a reference for the discovery of new functional genes in grape.

Small open reading frames in plant research: from prediction to functional characterization

Gene prediction is a laborious and time-consuming task. The advancement of sequencing technologies and bioinformatics tools, coupled with accelerated rate of ribosome profiling and mass spectrometry development, have made identification of small open reading frames (sORFs) (< 100 codons) in various plant genomes possible. The past 50 years have seen sORFs being isolated from many organisms. However, to date, a comprehensive sORF annotation pipeline is as yet unavailable, hence, addressed in our review. Here, we also provide current information on classification and functions of plant sORFs and their potential applications in crop improvement programs.

The dark proteome: translation from noncanonical open reading frames

Omics-based technologies have revolutionized our understanding of the coding potential of the genome. In particular, these studies revealed widespread unannotated open reading frames (ORFs) throughout genomes and that these regions have the potential to encode novel functional (micro-)proteins and/or hold regulatory roles. However, despite their genomic prevalence, relatively few of these noncanonical ORFs have been functionally characterized, likely in part due to their under-recognition by the broader scientific community. The few that have been investigated in detail have demonstrated their essentiality in critical and divergent biological processes. As such, here we aim to discuss recent advances in understanding the diversity of noncanonical ORFs and their roles, as well as detail biologically important examples within the context of the mammalian genome.

Quantitative proteomic dataset of the moss Physcomitrium patens PSEP3 KO and OE mutant lines

Small open reading frames (<100 codons) that are located on long noncoding RNAs (lncRNAs) can encode functional microproteins. These microproteins are shown to play important roles in different cellular processes, such as cell proliferation, development and disease response [1], [2], [3], [4], [5], [6]. However, there are only a few known lncRNA-encoded functional microproteins in plants. One such microprotein that was named PSEP3, was identified in the moss Physcomitrium patens by mass-spectrometry analysis. 57-aa PSEP3 contains Low Complexity Region (LCR) enriched with proline. We have previously shown that PSEP3 is translated in protonemata and gametophores of P. patens, and its knockout (KO line) or overexpression (OE line) affects protonemata growth [7]. We performed a quantitative proteomic analysis of the mutant lines with PSEP3 knockout and overexpression. 7-days old protonemata of wild type (WT line) and both mutant lines (KO and OE) were collected and used for iTRAQ-based proteomic experiments. LC-MS/MS data were processed using PEAKS Studio v.8 software with protein identification based on a Phytozome protein database. More analysis of PSEP3 effects on plant growth can be obtained in the paper published in Nucleic Acid Research [8].

Peptidome: Chaos or Inevitability

Thousands of naturally occurring peptides differing in their origin, abundance and possible functions have been identified in the tissue and biological fluids of vertebrates, insects, fungi, plants and bacteria. These peptide pools are referred to as intracellular or extracellular peptidomes, and besides a small proportion of well-characterized peptide hormones and defense peptides, are poorly characterized. However, a growing body of evidence suggests that unknown bioactive peptides are hidden in the peptidomes of different organisms. In this review, we present a comprehensive overview of the mechanisms of generation and properties of peptidomes across different organisms. Based on their origin, we propose three large peptide groups-functional protein "degradome", small open reading frame (smORF)-encoded peptides (smORFome) and specific precursor-derived peptides. The composition of peptide pools identified by mass-spectrometry analysis in human cells, plants, yeast and bacteria is compared and discussed. The functions of different peptide groups, for example the role of the "degradome" in promoting defense signaling, are also considered.

The Small Open Reading Frame-Encoded Peptides: Advances in Methodologies and Functional Studies

Small open reading frames (sORFs) are an important class of genes with less than 100 codons. They were historically annotated as noncoding or even junk sequences. In recent years, accumulating evidence suggests that sORFs could encode a considerable number of polypeptides, many of which play important roles in both physiology and disease pathology. However, it has been technically challenging to directly detect sORF-encoded peptides (SEPs). Here, we discuss the latest advances in methodologies for identifying SEPs with mass spectrometry, as well as the progress on functional studies of SEPs.

Long non-coding RNAs as possible therapeutic targets in protozoa, and in Schistosoma and other helminths

Long non-coding RNAs (lncRNAs) emerged in the past 20 years due to massive amounts of scientific data regarding transcriptomic analyses. They have been implicated in a plethora of cellular processes in higher eukaryotes. However, little is known about lncRNA possible involvement in parasitic diseases, with most studies only detecting their presence in parasites of human medical importance. Here, we review the progress on lncRNA studies and their functions in protozoans and helminths. In addition, we show an example of knockdown of one lncRNA in Schistosoma mansoni, SmLINC156349, which led to in vitro parasite adhesion, motility, and pairing impairment, with a 20% decrease in parasite viability and 33% reduction in female oviposition. Other observed phenotypes were a decrease in the proliferation rate of both male and female worms and their gonads, and reduced female lipid and vitelline droplets that are markers for well-developed vitellaria. Impairment of female worms' vitellaria in SmLINC156349-silenced worms led to egg development deficiency. All those results demonstrate the great potential of the tools and methods to characterize lncRNAs as potential new therapeutic targets. Further, we discuss the challenges and limitations of current methods for studying lncRNAs in parasites and possible solutions to overcome them, and we highlight the future directions of this exciting field.

A vast pool of lineage-specific microproteins encoded by long non-coding RNAs in plants

Pervasive transcription of eukaryotic genomes results in expression of long non-coding RNAs (lncRNAs) most of which are poorly conserved in evolution and appear to be non-functional. However, some lncRNAs have been shown to perform specific functions, in particular, transcription regulation. Thousands of small open reading frames (smORFs, <100 codons) located on lncRNAs potentially might be translated into peptides or microproteins. We report a comprehensive analysis of the conservation and evolutionary trajectories of lncRNAs-smORFs from the moss Physcomitrium patens across transcriptomes of 479 plant species. Although thousands of smORFs are subject to substantial purifying selection, the majority of the smORFs appear to be evolutionary young and could represent a major pool for functional innovation. Using nanopore RNA sequencing, we show that, on average, the transcriptional level of conserved smORFs is higher than that of non-conserved smORFs. Proteomic analysis confirmed translation of 82 novel species-specific smORFs. Numerous conserved smORFs containing low complexity regions (LCRs) or transmembrane domains were identified, the biological functions of a selected LCR-smORF were demonstrated experimentally. Thus, microproteins encoded by smORFs are a major, functionally diverse component of the plant proteome.

Understanding small ORF diversity through a comprehensive transcription feature classification

Small open reading frames (small ORFs/sORFs/smORFs) are potentially coding sequences smaller than 100 codons that have historically been considered junk DNA by gene prediction software and in annotation screening; however, the advent of next-generation sequencing has contributed to the deeper investigation of junk DNA regions and their transcription products, resulting in the emergence of smORFs as a new focus of interest in systems biology. Several smORF peptides were recently reported in noncanonical mRNAs as new players in numerous biological contexts; however, their relevance is still overlooked in coding potential analysis. Hence, this review proposes a smORF classification based on transcriptional features, discussing the most promising approaches to investigate smORFs based on their different characteristics. First, smORFs were divided into nonexpressed (intergenic) and expressed (genic) smORFs. Second, genic smORFs were classified as smORFs located in noncoding RNAs (ncRNAs) or canonical mRNAs. Finally, smORFs in ncRNAs were further subdivided into sequences located in small or long RNAs, whereas smORFs located in canonical mRNAs were subdivided into several specific classes depending on their localization along the gene. We hope that this review provides new insights into large-scale annotations and reinforces the role of smORFs as essential components of a hidden coding DNA world.

Possible role of small secreted peptides (SSPs) in immune signaling in bryophytes

Plants utilize a plethora of peptide signals to regulate their immune response. Peptide ligands and their cognate receptors involved in immune signaling share common motifs among many species of vascular plants. However, the origin and evolution of immune peptides is still poorly understood. Here, we searched for genes encoding small secreted peptides in the genomes of three bryophyte lineages-mosses, liverworts and hornworts-that occupy a critical position in the study of land plant evolution. We found that bryophytes shared common predicted small secreted peptides (SSPs) with vascular plants. The number of SSPs is higher in the genomes of mosses than in both the liverwort Marchantia polymorpha and the hornwort Anthoceros sp. The synthetic peptide elicitors-AtPEP and StPEP-specific for vascular plants, triggered ROS production in the protonema of the moss Physcomitrella patens, suggesting the possibility of recognizing peptide ligands from angiosperms by moss receptors. Mass spectrometry analysis of the moss Physcomitrella patens, both the wild type and the Δcerk mutant secretomes, revealed peptides that specifically responded to chitosan treatment, suggesting their role in immune signaling.

Full-Length Transcriptome Analysis of Plasmodium falciparum by Single-Molecule Long-Read Sequencing

Malaria, an infectious disease caused by Plasmodium parasites, still accounts for amounts of deaths annually in last decades. Despite the significance of Plasmodium falciparum as a model organism of malaria parasites, our understanding of gene expression of this parasite remains largely elusive since lots of progress on its genome and transcriptome are based on assembly with short sequencing reads. Herein, we report the new version of transcriptome dataset containing all full-length transcripts over the whole asexual blood stages by adopting a full-length sequencing approach with optimized experimental conditions of cDNA library preparation. We have identified a total of 393 alternative splicing (AS) events, 3,623 long non-coding RNAs (lncRNAs), 1,555 alternative polyadenylation (APA) events, 57 transcription factors (TF), 1,721 fusion transcripts in P. falciparum. Furthermore, the shotgun proteome was performed to validate the full-length transcriptome of P. falciparum. More importantly, integration of full-length transcriptomic and proteomic data identified 160 novel small proteins in lncRNA regions. Collectively, this full-length transcriptome dataset with high quality and accuracy and the shotgun proteome analyses shed light on the complex gene expression in malaria parasites and provide a valuable resource for related functional and mechanistic researches on P. falciparum genes.

Revisiting sORFs: overcoming challenges to identify and characterize functional microproteins

Short ORFs (sORFs), that is, occurrences of a start and stop codon within 100 codons or less, can be found in organisms of all domains of life, outnumbering annotated protein-coding ORFs by orders of magnitude. Even though functional proteins smaller than 100 amino acids are known, the coding potential of sORFs has often been overlooked, as it is not trivial to predict and test for functionality within the large number of sORFs. Recent advances in ribosome profiling and mass spectrometry approaches, together with refined bioinformatic predictions, have enabled a huge leap forward in this field and identified thousands of likely coding sORFs. A relatively low number of small proteins or microproteins produced from these sORFs have been characterized so far on the molecular, structural, and/or mechanistic level. These however display versatile and, in some cases, essential cellular functions, allowing for the exciting possibility that many more, previously unknown small proteins might be encoded in the genome, waiting to be discovered. This review will give an overview of the steadily growing microprotein field, focusing on eukaryotic small proteins. We will discuss emerging themes in the molecular action of microproteins, as well as advances and challenges in microprotein identification and characterization.

OpenProt 2021: deeper functional annotation of the coding potential of eukaryotic genomes

OpenProt (www.openprot.org) is the first proteogenomic resource supporting a polycistronic annotation model for eukaryotic genomes. It provides a deeper annotation of open reading frames (ORFs) while mining experimental data for supporting evidence using cutting-edge algorithms. This update presents the major improvements since the initial release of OpenProt. All species support recent NCBI RefSeq and Ensembl annotations, with changes in annotations being reported in OpenProt. Using the 131 ribosome profiling datasets re-analysed by OpenProt to date, non-AUG initiation starts are reported alongside a confidence score of the initiating codon. From the 177 mass spectrometry datasets re-analysed by OpenProt to date, the unicity of the detected peptides is controlled at each implementation. Furthermore, to guide the users, detectability statistics and protein relationships (isoforms) are now reported for each protein. Finally, to foster access to deeper ORF annotation independently of one's bioinformatics skills or computational resources, OpenProt now offers a data analysis platform. Users can submit their dataset for analysis and receive the results from the analysis by OpenProt. All data on OpenProt are freely available and downloadable for each species, the release-based format ensuring a continuous access to the data. Thus, OpenProt enables a more comprehensive annotation of eukaryotic genomes and fosters functional proteomic discoveries.

Recent advances in mass spectrometry-based peptidomics workflows to identify short-open-reading-frame-encoded peptides and explore their functions

Short open reading frame (sORF)-encoded polypeptides (SEPs) have recently emerged as key regulators of major cellular processes. Computational methods for the annotation of sORFs combined with transcriptomics and ribosome profiling approaches predicted the existence of tens of thousands of SEPs across the kingdom of life. Although, we still lack unambiguous evidence for most of them. The method of choice to validate the expression of SEPs is mass spectrometry (MS)-based peptidomics. Peptides are less abundant than proteins, which tends to hinder their detection. Therefore, optimization and enrichment methods are necessary to validate the existence of SEPs. In this article, we discuss the challenges for the detection of SEPs by MS and recent developments of biochemical approaches applied to the study of these peptides. We detail the advances made in the different key steps of a typical peptidomics workflow and highlight possible alternatives that have not been explored yet.

RNA-Based Technologies for Engineering Plant Virus Resistance

In recent years, non-coding RNAs (ncRNAs) have gained unprecedented attention as new and crucial players in the regulation of numerous cellular processes and disease responses. In this review, we describe how diverse ncRNAs, including both small RNAs and long ncRNAs, may be used to engineer resistance against plant viruses. We discuss how double-stranded RNAs and small RNAs, such as artificial microRNAs and trans-acting small interfering RNAs, either produced in transgenic plants or delivered exogenously to non-transgenic plants, may constitute powerful RNA interference (RNAi)-based technology that can be exploited to control plant viruses. Additionally, we describe how RNA guided CRISPR-CAS gene-editing systems have been deployed to inhibit plant virus infections, and we provide a comparative analysis of RNAi approaches and CRISPR-Cas technology. The two main strategies for engineering virus resistance are also discussed, including direct targeting of viral DNA or RNA, or inactivation of plant host susceptibility genes. We also elaborate on the challenges that need to be overcome before such technologies can be broadly exploited for crop protection against viruses.

Nanopore RNA Sequencing Revealed Long Non-Coding and LTR Retrotransposon-Related RNAs Expressed at Early Stages of Triticale SEED Development

The intergenic space of plant genomes encodes many functionally important yet unexplored RNAs. The genomic loci encoding these RNAs are often considered “junk”, DNA as they are frequently associated with repeat-rich regions of the genome. The latter makes the annotations of these loci and the assembly of the corresponding transcripts using short RNAseq reads particularly challenging. Here, using long-read Nanopore direct RNA sequencing, we aimed to identify these “junk” RNA molecules, including long non-coding RNAs (lncRNAs) and transposon-derived transcripts expressed during early stages (10 days post anthesis) of seed development of triticale (AABBRR, 2n = 6x = 42), an interspecific hybrid between wheat and rye. Altogether, we found 796 lncRNAs and 20 LTR retrotransposon-related transcripts (RTE-RNAs) expressed at this stage, with most of them being previously unannotated and located in the intergenic as well as intronic regions. Sequence analysis of the lncRNAs provide evidence for the frequent exonization of Class I (retrotransposons) and class II (DNA transposons) transposon sequences and suggest direct influence of “junk” DNA on the structure and origin of lncRNAs. We show that the expression patterns of lncRNAs and RTE-related transcripts have high stage specificity. In turn, almost half of the lncRNAs located in Genomes A and B have the highest expression levels at 10–30 days post anthesis in wheat. Detailed analysis of the protein-coding potential of the RTE-RNAs showed that 75% of them carry open reading frames (ORFs) for a diverse set of GAG proteins, the main component of virus-like particles of LTR retrotransposons. We further experimentally demonstrated that some RTE-RNAs originate from autonomous LTR retrotransposons with ongoing transposition activity during early stages of triticale seed development. Overall, our results provide a framework for further exploration of the newly discovered lncRNAs and RTE-RNAs in functional and genome-wide association studies in triticale and wheat. Our study also demonstrates that Nanopore direct RNA sequencing is an indispensable tool for the elucidation of lncRNA and retrotransposon transcripts.

Large-Scale Discovery of Non-conventional Peptides in Maize and Arabidopsis through an Integrated Peptidogenomic Pipeline

Non-conventional peptides (NCPs), which include small open reading frame-encoded peptides, play critical roles in fundamental biological processes. In this study, we developed an integrated peptidogenomic pipeline using high-throughput mass spectra to probe a customized six-frame translation database and applied it to large-scale identification of NCPs in plants.A total of 1993 and 1860 NCPs were unambiguously identified in maize and Arabidopsis, respectively. These NCPs showed distinct characteristics compared with conventional peptides and were derived from introns, 3' UTRs, 5' UTRs, junctions, and intergenic regions. Furthermore, our results showed that translation events in unannotated transcripts occur more broadly than previously thought. In addition, we found that dozens of maize NCPs are enriched within regions associated with phenotypic variations and domestication selection, indicating that they potentially are involved in genetic regulation of complex traits and domestication in maize. Taken together, our study developed an integrated peptidogenomic pipeline for large-scale identification of NCPs in plants, which would facilitate global characterization of NCPs from other plants. The identification of large-scale NCPs in both monocot (maize) and dicot (Arabidopsis) plants indicates that a large portion of plant genome can be translated into biologically functional molecules, which has important implications for functional genomic studies.