Differentiating protein-coding and noncoding RNA: challenges and ambiguities

Multi-omics analysis reveals an endogenous competitive regulatory mechanism for resistance to Vibrio parahaemolyticus in the swimming crab, Portunus trituberculatus

Vibrio parahaemolyticus is the main pathogen responsible for acute hepatopancreatic necrosis disease in crustaceans. To further understand the immune regulatory mechanisms against V. parahaemolyticus in crustaceans, we employed multi-omics to elucidate the competitive endogenous RNAs (ceRNAs) regulatory network in V. parahaemolyticus-infected Portunus trituberculatus. A total of 8,093 long non-coding RNAs (lncRNAs) in the hepatopancreas of P. trituberculatus were identified, among which 739 were differentially expressed after infection. The target genes of the differentially expressed lncRNAs were enriched in immune-related pathways, including NOD-like receptor signaling and TNF signaling pathways. Further investigation demonstrated that lncRNAs may modulate immune responses by interacting with microRNAs and mRNAs to form complex ceRNA networks. Of particular interest, lncRNA MSTRG.2618.5 was identified acts as a molecular sponge for novel0095, thereby enhancing the expression of interferon regulatory factor 2 gene. The present study provides novel insights into the immune regulatory mechanisms of P. trituberculatus, highlighting the significant role of lncRNAs in crustacean immunity. The findings contribute to our understanding of disease resistance in aquatic animals and offer potential molecular targets for the selective breeding of disease-resistant strains in aquaculture.

Comprehensive genome annotation of the model ciliate Tetrahymena thermophila by in-depth epigenetic and transcriptomic profiling

The ciliate Tetrahymena thermophila is a well-established unicellular model eukaryote, contributing significantly to foundational biological discoveries. Despite its acknowledged importance, current studies on Tetrahymena biology face challenges due to gene annotation inaccuracy, particularly the notable absence of untranslated regions (UTRs). To comprehensively annotate the Tetrahymena macronuclear genome, we collected extensive transcriptomic data spanning various cell stages. To ascertain transcript orientation and transcription start/end sites, we incorporated data on epigenetic marks displaying enrichment towards the 5' end of gene bodies, including H3 lysine 4 tri-methylation (H3K4me3), histone variant H2A.Z, nucleosome positioning and N6-methyldeoxyadenine (6mA). Cap-seq data was subsequently applied to validate the accuracy of identified transcription start sites. Additionally, we integrated Nanopore direct RNA sequencing (DRS), strand-specific RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data. Using a newly developed bioinformatic pipeline, coupled with manual curation and experimental validation, our work yielded substantial improvements to the current gene models, including the addition of 2,481 new genes, updates to 23,936 existing genes, and the incorporation of 8,339 alternatively spliced isoforms. Furthermore, novel UTR information was annotated for 26,687 high-confidence genes. Intriguingly, 20% of protein-coding genes were identified to have natural antisense transcripts characterized by high diversity in alternative splicing, thus offering insights into understanding transcriptional regulation. Our work will enhance the utility of Tetrahymena as a robust genetic toolkit for advancing biological research, and provides a promising framework for genome annotation in other eukaryotes.

Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches

Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing. Recent improvements in the accuracy of long-read sequencing technologies have expanded the scope for novel splice isoform detection and have also enabled a far more accurate reconstruction of complex splicing patterns and transcriptomes. Additionally, the incorporation and advancements of machine learning and deep learning algorithms in bioinformatic software have significantly improved the reliability of long-read sequencing transcriptomic studies. However, there is a lack of consensus on what bioinformatic tools and pipelines produce the most precise and consistent results. Thus, this review aims to discuss and compare the performance of available methods for novel isoform discovery with long-read sequencing technologies, with 25 tools being presented. Furthermore, this review intends to demonstrate the need for developing standard analytical pipelines, tools, and transcript model conventions for novel isoform discovery and transcriptomic studies.

Microscopic marvels: Decoding the role of micropeptides in innate immunity

The innate immune response is under selection pressures from changing environments and pathogens. While sequence evolution can be studied by comparing rates of amino acid mutations within and between species, how a gene's birth and death contribute to the evolution of immunity is less known. Short open reading frames, once regarded as untranslated or transcriptional noise, can often produce micropeptides of <100 amino acids with a wide array of biological functions. Some micropeptide sequences are well conserved, whereas others have no evolutionary conservation, potentially representing new functional compounds that arise from species-specific adaptations. To date, few reports have described the discovery of novel micropeptides of the innate immune system. The diversity of immune-related micropeptides is a blind spot for gene and functional annotation. Immune-related micropeptides represent a potential reservoir of untapped compounds for understanding and treating disease. This review consolidates what is currently known about the evolution and function of innate immune-related micropeptides to facilitate their investigation.

Dynamic role of exosomal long non-coding RNA in liver diseases: pathogenesis and diagnostic aspects

BACKGROUND

Liver disease has emerged as a significant health concern, characterized by high rates of morbidity and mortality. Circulating exosomes have garnered attention as important mediators of intercellular communication, harboring protein and stable mRNAs, microRNAs, and long non-coding RNAs (lncRNA). This review highlights the involvement of exosomal lncRNA in the pathogenesis and diagnosis of various liver diseases. Notably, exosomal lncRNAs exhibit therapeutic potential as targets for conditions including hepatic carcinoma, hepatic fibrosis, and hepatic viral infections.

METHOD

An online screening process was employed to identify studies investigating the association between exosomal lncRNA and various liver diseases.

RESULT

Our study revealed a diverse array of lncRNAs carried by exosomes, including H19, Linc-ROR, VLDLR, MALAT1, DANCR, HEIH, ENSG00000248932.1, ENST00000457302.2, ZSCAN16-AS1, and others, exhibiting varied levels across different liver diseases compared to normal liver tissue. These exosomal-derived lncRNAs are increasingly recognized as pivotal biomarkers for diagnosing and prognosticating liver diseases, supported by emerging evidence. However, the precise mechanisms underlying the involvement of certain exosomal lncRNAs remain incompletely understood. Furthermore, the combined analysis of serum exosomes using ENSG00000258332.1, LINC00635, and serum AFP may serve as novel and valuable biomarker for HCC. Clinically, exosomal ATB expression is upregulated in HCC, while exosomal HEIH and RP11-513I15.6 have shown potential for distinguishing HCC related to HCV infection.

CONCLUSION

The lack of reliable biomarkers for liver diseases, coupled with the high specificity and sensitivity of exosomal lncRNA and its non-invasive detection, promotes exploring their role in pathogenesis and biomarker for diagnosis, prognosis, and response to treatment liver diseases.

Small ORFs, Big Insights: Drosophila as a Model to Unraveling Microprotein Functions

Recently developed experimental and computational approaches to identify putative coding small ORFs (smORFs) in genomes have revealed thousands of smORFs localized within coding and non-coding RNAs. They can be translated into smORF peptides or microproteins, which are defined as less than 100 amino acids in length. The identification of such a large number of potential biological regulators represents a major challenge, notably for elucidating the in vivo functions of these microproteins. Since the emergence of this field, Drosophila has proved to be a valuable model for studying the biological functions of microproteins in vivo. In this review, we outline how the smORF field emerged and the nomenclature used in this domain. We summarize the technical challenges associated with identifying putative coding smORFs in the genome and the relevant translated microproteins. Finally, recent findings on one of the best studied smORF peptides, Pri, and other microproteins studied so far in Drosophila are described. These studies highlight the diverse roles that microproteins can fulfil in the regulation of various molecular targets involved in distinct cellular processes during animal development and physiology. Given the recent emergence of the microprotein field and the associated discoveries, the microproteome represents an exquisite source of potentially bioactive molecules, whose in vivo biological functions can be explored in the Drosophila model.

ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks

Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.

LncRNA 4930581F22Rik promotes myogenic differentiation by regulating the ERK/MAPK signaling pathway

The skeletal muscle is the largest organ in mammals and is the primary motor function organ of the body. Our previous research has shown that long non-coding RNAs (lncRNAs) are significant in the epigenetic control of skeletal muscle development. Here, we observed progressive upregulation of lncRNA 4930581F22Rik expression during skeletal muscle differentiation. Knockdown of lncRNA 4930581F22Rik hindered skeletal muscle differentiation and resulted in the inhibition of the myogenic markers MyHC and MEF2C. Furthermore, we found that lncRNA 4930581F22Rik regulates myogenesis via the ERK/MAPK signaling pathway, and this effect could be attenuated by the ERK-specific inhibitor PD0325901. Additionally, in vivo mice injury model results revealed that lncRNA 4930581F22Rik is involved in skeletal muscle regeneration. These results establish a theoretical basis for understanding the contribution of lncRNAs in skeletal muscle development and regeneration.

Small but mighty: the rise of microprotein biology in neuroscience

The mammalian central nervous system coordinates a network of signaling pathways and cellular interactions, which enable a myriad of complex cognitive and physiological functions. While traditional efforts to understand the molecular basis of brain function have focused on well-characterized proteins, recent advances in high-throughput translatome profiling have revealed a staggering number of proteins translated from non-canonical open reading frames (ncORFs) such as 5' and 3' untranslated regions of annotated proteins, out-of-frame internal ORFs, and previously annotated non-coding RNAs. Of note, microproteins < 100 amino acids (AA) that are translated from such ncORFs have often been neglected due to computational and biochemical challenges. Thousands of putative microproteins have been identified in cell lines and tissues including the brain, with some serving critical biological functions. In this perspective, we highlight the recent discovery of microproteins in the brain and describe several hypotheses that have emerged concerning microprotein function in the developing and mature nervous system.

Rules and impacts of nonsense-mediated mRNA decay in the degradation of long noncoding RNAs

Nonsense-mediated mRNA decay (NMD) is a quality-control process that selectively degrades mRNAs having premature termination codon, upstream open reading frame, or unusually long 3'UTR. NMD detects such mRNAs and rapidly degrades them during initial rounds of translation in the eukaryotic cells. Since NMD is a translation-dependent cytoplasmic mRNA surveillance process, the noncoding RNAs were initially believed to be NMD-resistant. The sequence feature-based analysis has revealed that many putative long noncoding RNAs (lncRNAs) have short open reading frames, most of which have translation potential. Subsequent transcriptome-based molecular studies showed an association of a large set of such putative lncRNAs with translating ribosomes, and some of them produce stable and functionally active micropeptides. The translationally active lncRNAs typically have relatively longer and unprotected 3'UTR, which can induce their NMD-dependent degradation. This review defines the mechanism and regulation of NMD-dependent degradation of lncRNAs and its impact on biological processes related to the functions of lncRNAs or their encoded micropeptides. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease.

Negative Regulation of LINC01013 by METTL3 and YTHDF2 Enhances the Osteogenic Differentiation of Senescent Pre-Osteoblast Cells Induced by Hydrogen Peroxide

Senescent pre-osteoblasts have a reduced ability to differentiate, which leads to a reduction in bone formation. It is critical to identify the keys that regulate the differentiation fate of senescent pre-osteoblasts. LINC01013 has an essential role in cell stemness, differentiation, and senescence regulation. This study aims to examine the role and mechanism of LINC01013 in regulating osteogenic differentiation in senescent human embryonic osteoblast cell line (hFOB1.19) cells induced by hydrogen peroxide (H2O2). The results show that LINC01013 decreased alkaline phosphatase activity, mineralization of hFOB1.19 cells in vitro, and the expression of collagen II, osteocalcin, and bone sialoprotein. LINC01013 knockdown enhances the osteogenesis of hFOB1.19 cells and rescues osteogenic differentiation impaired by H2O2. METTL3 negatively regulates LINC01013 expression, enhancing hFOB1.19 cells' osteogenesis in vitro and in vivo. METTL3 overexpression can enhance hFOB1.19 cells' osteogenic differentiation impaired by H2O2. YTHDF2 promotes LINC01013 decay, facilitating osteogenic differentiation. YTHDF2 overexpression rescues hFOB1.19 cells osteogenic differentiation impaired by H2O2. Taken together, METTL3 upregulates osteogenic differentiation by inhibiting LINC01013, and YTHDF2 accelerates LINC01013 degradation, reducing its inhibitory effect. This study highlights LINC01013 as a key regulator in the fate switching process of senescent hFOB1.19 cells, impacting osteogenic differentiation.

Exploration of lncRNA/circRNA-miRNA-mRNA network in patients with chronic atrophic gastritis in Tibetan plateau areas based on DNBSEQ-G99 RNA sequencing

A higher incidence of chronic atrophic gastritis (CAG) is generally considered as a precancerous lesion in gastric cancer (GC). The aim of this study was to identify potential molecules involved in the pathogenesis of CAG in the Tibetan plateau, hoping to help the diagnosis and management of the disease. Atrophic and non-atrophic gastric mucosal tissue samples were collected from seven patients with chronic gastritis (CG). Differentially expressed lncRNAs, circRNAs, miRNAs, and mRNAs between CAG and chronic non-atrophic gastritis (CNAG) groups were identified based on DNBSEQ-G99 RNA sequencing. Subsequently, competitive endogenous RNA (ceRNA) regulatory networks (lncRNA/circRNA-miRNA-mRNA networks) were constructed. Two datasets (GSE153224 and GSE163416), involving data from non-Tibetan plateau areas, were used to further screen out Tibetan plateau key mRNAs, followed by the common genes of Tibetan plateau key and ferroptosis-related mRNAs were also identified. Functional enrichment analyses were performed to investigate the biological functions of Tibetan plateau mRNAs in the CAG. A total of seven lncRNA-miRNA-mRNA relationship pairs and 424 circRNA-miRNA-mRNA relationship pairs were identified in this study. The relationship pairs of hsa_circ_0082984-hsa-miR-204-5p-CACNG8, lncRNA DRAIC/has_circ_0008561-hsa-miR-34a-5p-AR/GXYLT2, lncRNA GAS1RR/RGMB-AS1/hsa_circ_0008561-hsa-miR-3614-5p-TMEM216/SUSD5, and LINC00941/hsa_circ_0082984-hsa-miR-873-3p-TMC5 can be involved in the pathogenesis of CAG. Additionally, eight common genes of Tibetan plateau key and ferroptosis-related differentially expressed mRNAs (DEmRNAs) (CBS, SLC2A4, STAT3, ALOX15B, ATF3, IDO1, NOX4, and SOCS1) were identified in CAG. The common genes of Tibetan plateau key and ferroptosis-related DEmRNAs can play a role in the JAK-STAT signaling pathway. This study identified important molecular biomarkers that may be involved in regulating the pathological mechanisms of CAG in the Tibetan plateau, which provides potential research directions for future research.

Truncated protein isoforms generate diversity of protein localization and function in yeast

Genome-wide measurement of ribosome occupancy on mRNAs has enabled empirical identification of translated regions, but high-confidence detection of coding regions that overlap annotated coding regions has remained challenging. Here, we report a sensitive and robust algorithm that revealed the translation of 388 N-terminally truncated proteins in budding yeast-more than 30-fold more than previously known. We extensively experimentally validated them and defined two classes. The first class lacks large portions of the annotated protein and tends to be produced from a truncated transcript. We show that two such cases, Yap5truncation and Pus1truncation, have condition-specific regulation and distinct functions from their respective annotated isoforms. The second class of truncated protein isoforms lacks only a small region of the annotated protein and is less likely to be produced from an alternative transcript isoform. Many display different subcellular localizations than their annotated counterpart, representing a common strategy for dual localization of otherwise functionally identical proteins. A record of this paper's transparent peer review process is included in the supplemental information.

ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach.

miR-306-5p is involved in chitin metabolism in Aedes albopictus pupae via linc8338-miR-306-5p-XM_019678125.2 axis

Aedes albopictus can transmit several lethal arboviruses. This mosquito has become a sever public health threat due to its rapidly changing global distribution. Chitin, which is the major component of the cuticle and peritrophic membrane (PM), is crucial for the growth and development of insect. microRNAs (miRNAs) play important roles in the posttranscriptional level regulation of gene expression, thereby influencing many biological processes in insects. In this study, an attempt was made to evaluate the role of miR-306-5p in regulating chitin metabolism in Ae. albopictus pupae. Overexpression of miR-306-5p resulted in a significantly reduced survival rate in pupae and an increased malformation rate in adults. Both in vivo and in vitro evidence confirmed the presence of the competing endogenous RNA (ceRNA) regulatory axis (linc8338-miR-306-5p-XM_019678125.2). RNAi of linc8338 and XM_019678125.2 had effects on pupae similar to those of miR-306-5p. The highest expression level of miR-306-5p was found in the midgut, and alteration in the expression of miR-306-5p, XM_019678125.2 and linc8338 induced increased transcript levels of chitin synthase 2 (AaCHS2) and decreased chitinase 10 (AaCht10); as well as increased thickness of the midgut and enlarged midgut epithelial cells. The results of this study highlight the potential of miR-306-5p as a prospective target in mosquito control and confirm that the ceRNA mechanism is involved in chitin metabolism. These findings will provide a basis for further studies to uncover the molecular mechanisms through which ncRNAs regulate chitin metabolism.

Emerging role of microRNAs as regulators of protein kinase C substrate MARCKS and MARCKSL1 in cancer

MicroRNAs (miRNAs) have emerged as pivotal regulators of gene expression, playing essential roles in diverse cellular processes, including the development and progression of cancer. Among the numerous proteins influenced by miRNAs, the MARCKS/MARCKSL1 protein, a key regulator of cellular cytoskeletal dynamics and membrane-cytosol communication, has garnered significant attention due to its multifaceted involvement in various cancer-related processes, including cell migration, invasion, metastasis, and drug resistance. Motivated by the encouraging early clinical success of peptides targeting MARCKS in several pathological conditions, this review article delves into the intricate interplay between miRNAs and the MARCKS protein in cancer. Herein, we have highlighted the latest findings on specific miRNAs that modulate MARCKS/MARCKSL1 expression, providing a comprehensive overview of their roles in different cancer types. We have underscored the need for in-depth investigations into the therapeutic feasibility of targeting the miRNA-MARCKS axis in cancer, taking cues from the successes witnessed in related fields. Unlocking the full potential of miRNA-mediated MARCKS regulation could pave the way for innovative and effective therapeutic interventions against various cancer types.

Small proteins in bacteria - Big challenges in prediction and identification

Proteins with up to 100 amino acids have been largely overlooked due to the challenges associated with predicting and identifying them using traditional methods. Recent advances in bioinformatics and machine learning, DNA sequencing, RNA and Ribo-seq technologies, and mass spectrometry (MS) have greatly facilitated the detection and characterisation of these elusive proteins in recent years. This has revealed their crucial role in various cellular processes including regulation, signalling and transport, as toxins and as folding helpers for protein complexes. Consequently, the systematic identification and characterisation of these proteins in bacteria have emerged as a prominent field of interest within the microbial research community. This review provides an overview of different strategies for predicting and identifying these proteins on a large scale, leveraging the power of these advanced technologies. Furthermore, the review offers insights into the future developments that may be expected in this field.

Microproteins-Discovery, structure, and function

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.

StORF-Reporter: finding genes between genes

Large regions of prokaryotic genomes are currently without any annotation, in part due to well-established limitations of annotation tools. For example, it is routine for genes using alternative start codons to be misreported or completely omitted. Therefore, we present StORF-Reporter, a tool that takes an annotated genome and returns regions that may contain missing CDS genes from unannotated regions. StORF-Reporter consists of two parts. The first begins with the extraction of unannotated regions from an annotated genome. Next, Stop-ORFs (StORFs) are identified in these unannotated regions. StORFs are open reading frames that are delimited by stop codons and thus can capture those genes most often missing in genome annotations. We show this methodology recovers genes missing from canonical genome annotations. We inspect the results of the genomes of model organisms, the pangenome of Escherichia coli, and a set of 5109 prokaryotic genomes of 247 genera from the Ensembl Bacteria database. StORF-Reporter extended the core, soft-core and accessory gene collections, identified novel gene families and extended families into additional genera. The high levels of sequence conservation observed between genera suggest that many of these StORFs are likely to be functional genes that should now be considered for inclusion in canonical annotations.

Circular RNAs-mediated angiogenesis in human cancers

Circular RNAs (circRNAs) as small non-coding RNAs with cell, tissue, or organ-specific expression accomplish a broad array of functions in physiological and pathological processes such as cancer development. Angiogenesis, a complicated multistep process driving a formation of new blood vessels, speeds up tumor progression by supplying nutrients as well as energy. Abnormal expression of circRNAs reported to affect tumor development through impressing angiogenesis. Such impacts are introduced as constant with different tumorigenic features known as "hallmarks of cancer". In addition, deregulated circRNAs show possibilities to prognosis and diagnosis both in the prophecy of prognosis in malignancies and also their prejudice from healthy individuals. In the present review article, we have evaluated the angiogenic impacts and anti-angiogenic managements of circRNAs in human cancers.

Assessing Global-Local Secondary Structure Fingerprints to Classify RNA Sequences With Deep Learning

RNA elements that are transcribed but not translated into proteins are called non-coding RNAs (ncRNAs). They play wide-ranging roles in biological processes and disorders. Just like proteins, their structure is often intimately linked to their function. Many examples have been documented where structure is conserved across taxa despite sequence divergence. Thus, structure is often used to identify function. Specifically, the secondary structure is predicted and ncRNAs with similar structures are assumed to have same or similar functions. However, a strand of RNA can fold into multiple possible structures, and some strands even fold differently in vivo and in vitro. Furthermore, ncRNAs often function as RNA-protein complexes, which can affect structure. Because of these, we hypothesized using one structure per sequence may discard information, possibly resulting in poorer classification accuracy. Therefore, we propose using secondary structure fingerprints, comprising two categories: a higher-level representation derived from RNA-As-Graphs (RAG), and free energy fingerprints based on a curated repertoire of small structural motifs. The fingerprints take into account the difference between global and local structural matches. We also evaluated our deep learning architecture with k-mers. By combining our global-local fingerprints with 6-mer, we achieved an accuracy, precision, and recall of 91.04%, 91.10%, and 91.00%.

A Kuhnian revolution in molecular biology: Most genes in complex organisms express regulatory RNAs

Thomas Kuhn described the progress of science as comprising occasional paradigm shifts separated by interludes of 'normal science'. The paradigm that has held sway since the inception of molecular biology is that genes (mainly) encode proteins. In parallel, theoreticians posited that mutation is random, inferred that most of the genome in complex organisms is non-functional, and asserted that somatic information is not communicated to the germline. However, many anomalies appeared, particularly in plants and animals: the strange genetic phenomena of paramutation and transvection; introns; repetitive sequences; a complex epigenome; lack of scaling of (protein-coding) genes and increase in 'noncoding' sequences with developmental complexity; genetic loci termed 'enhancers' that control spatiotemporal gene expression patterns during development; and a plethora of 'intergenic', overlapping, antisense and intronic transcripts. These observations suggest that the original conception of genetic information was deficient and that most genes in complex organisms specify regulatory RNAs, some of which convey intergenerational information. Also see the video abstract here: https://youtu.be/qxeGwahBANw.

Truncated protein isoforms generate diversity of protein localization and function in yeast

Genome-wide measurements of ribosome occupancy on mRNA transcripts have enabled global empirical identification of translated regions. These approaches have revealed an unexpected diversity of protein products, but high-confidence identification of new coding regions that entirely overlap annotated coding regions - including those that encode truncated protein isoforms - has remained challenging. Here, we develop a sensitive and robust algorithm focused on identifying N-terminally truncated proteins genome-wide, identifying 388 truncated protein isoforms, a more than 30-fold increase in the number known in budding yeast. We perform extensive experimental validation of these truncated proteins and define two general classes. The first set lack large portions of the annotated protein sequence and tend to be produced from a truncated transcript. We show two such cases, Yap5 truncation and Pus1 truncation , to have condition-specific regulation and functions that appear distinct from their respective annotated isoforms. The second set of N-terminally truncated proteins lack only a small region of the annotated protein and are less likely to be regulated by an alternative transcript isoform. Many localize to different subcellular compartments than their annotated counterpart, representing a common strategy for achieving dual localization of otherwise functionally identical proteins.

Long non-coding RNAs in non-small cell lung cancer: implications for EGFR-TKI resistance

Non-small cell lung cancer (NSCLC) is one of the most common types of malignant tumors as well as the leading cause of cancer-related deaths in the world. The application of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) has dramatically improved the prognosis of NSCLC patients who harbor EGFR mutations. However, despite an excellent initial response, NSCLC inevitably becomes resistant to EGFR-TKIs, leading to irreversible disease progression. Hence, it is of great significance to shed light on the molecular mechanisms underlying the EGFR-TKI resistance in NSCLC. Long non-coding RNAs (lncRNAs) are critical gene modulators that are able to act as oncogenes or tumor suppressors that modulate tumorigenesis, invasion, and metastasis. Recently, extensive evidence demonstrates that lncRNAs also have a significant function in modulating EGFR-TKI resistance in NSCLC. In this review, we present a comprehensive summary of the lncRNAs involved in EGFR-TKI resistance in NSCLC and focus on their detailed mechanisms of action, including activation of alternative bypass signaling pathways, phenotypic transformation, intercellular communication in the tumor microenvironment, competing endogenous RNAs (ceRNAs) networks, and epigenetic modifications. In addition, we briefly discuss the limitations and the clinical implications of current lncRNAs research in this field.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset, thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental genes. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

lncRNAs-EZH2 interaction as promising therapeutic target in cutaneous melanoma

Melanoma is the most lethal skin cancer with increasing incidence worldwide. Despite a great improvement of diagnostics and treatment of melanoma patients, this disease is still a serious clinical problem. Therefore, novel druggable targets are in focus of research. EZH2 is a component of the PRC2 protein complex that mediates epigenetic silencing of target genes. Several mutations activating EZH2 have been identified in melanoma, which contributes to aberrant gene silencing during tumor progression. Emerging evidence indicates that long non-coding RNAs (lncRNAs) are molecular "address codes" for EZH2 silencing specificity, and targeting lncRNAs-EZH2 interaction may slow down the progression of many solid cancers, including melanoma. This review summarizes current knowledge regarding the involvement of lncRNAs in EZH2-mediated gene silencing in melanoma. The possibility of blocking lncRNAs-EZH2 interaction in melanoma as a novel therapeutic option and plausible controversies and drawbacks of this approach are also briefly discussed.

Identification of immunotherapy-related lncRNA signature for predicting prognosis, immunotherapy responses and drug candidates in bladder cancer

BACKGROUND

Bladder cancer (BC) is one of the most common malignant diseases and the most common causes of cancer death worldwide. Immunotherapy has opened new avenues for precision treatment of bladder tumours, and immune checkpoint inhibitors (ICIs) have revolutionized the clinical treatment strategy of bladder tumours. In addition, long non-coding RNA (lncRNA) plays an important role in regulating tumour development and immunotherapy efficacy.

METHODS

We obtained genes with significant differences between anti-PD-L1 response and non-response from the Imvogor210 data set and combined with the bladder cancer expression data in the TCGA cohort to obtain immunotherapy-related lncRNA. Based on these lncRNAs, the prognostic risk model of bladder cancer was constructed and verified by GEO external data set. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analysed. We predicted the ceRNA network and performed molecular docking of key target proteins. The functional experiments verified the function of SBF2-AS1.

RESULTS

Three immunotherapy-related lncRNAs were identified as independent prognostic biomarkers for bladder cancer and a prognostic model of immunotherapy-related prognosis was constructed. Prognosis, immune cell infiltration, and immunotherapy efficacy were significantly different between high- and low-risk groups based on risk scores. Additionally, we established a ceRNA network of lncRNA(SBF2-AS1)-miRNA(has-miR-582-5p)-mRNA (HNRNPA2B1). Targeting the protein HNRNPA2B1 identified the top eight small molecule drugs with the highest affinity.

CONCLUSION

We developed a prognostic risk score model based on immune-therapy-related lncRNA, which was subsequently determined to be significantly associated with immune cell infiltration and immunotherapy response. This study not only helps to promote our understanding of immunotherapy-related lncRNA in the prognosis of BC, but also provides new ideas for clinical immunotherapy and the development of novel therapeutic drugs for patients.

Microprotein Dysregulation in the Serum of Patients with Atrial Fibrillation

The incidence rate of atrial fibrillation (AF) has stayed at a high level in recent years. Despite the intensive efforts to study the pathologic changes of AF, the molecular mechanism of disease development remains unclarified. Microproteins are ribosomally translated gene products from small open reading frames (sORFs) and are found to play crucial biological functions, while remain rare attention and indistinct in AF study. In this work, we recruited 65 AF patients and 65 healthy subjects for microproteomic profiling. By differential analysis and cross-validation between independent datasets, a total of 4 microproteins were identified as significantly different, including 3 annotated ones and 1 novel one. Additionally, we established a diagnostic model with either microproteins or global proteins by machine learning methods and found the model with microproteins achieved comparable and excellent performance as that with global proteins. Our results confirmed the abnormal expression of microproteins in AF and may provide new perspectives on the mechanism study of AF.

Molecular Mechanisms of Regulation of Root Development by Plant Peptides

Peptides perform many functions, participating in the regulation of cell differentiation, regulating plant growth and development, and also involved in the response to stress factors and in antimicrobial defense. Peptides are an important class biomolecules for intercellular communication and in the transmission of various signals. The intercellular communication system based on the ligand-receptor bond is one of the most important molecular bases for creating complex multicellular organisms. Peptide-mediated intercellular communication plays a critical role in the coordination and determination of cellular functions in plants. The intercellular communication system based on the receptor-ligand is one of the most important molecular foundations for creating complex multicellular organisms. Peptide-mediated intercellular communication plays a critical role in the coordination and determination of cellular functions in plants. The identification of peptide hormones, their interaction with receptors, and the molecular mechanisms of peptide functioning are important for understanding the mechanisms of both intercellular communications and for regulating plant development. In this review, we drew attention to some peptides involved in the regulation of root development, which implement this regulation by the mechanism of a negative feedback loop.

RNA out of the mist

RNA has long been regarded primarily as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences interrupted by large tracts of transcribed but untranslated sequences, and that multicellular organisms also express many long 'intergenic' and antisense noncoding RNAs (lncRNAs). The identification of small RNAs that regulate mRNA translation and half-life did not disturb the prevailing view that animals and plant genomes are full of evolutionary debris and that their development is mainly supervised by transcription factors. Gathering evidence to the contrary involved addressing the low conservation, expression, and genetic visibility of lncRNAs, demonstrating their cell-specific roles in cell and developmental biology, and their association with chromatin-modifying complexes and phase-separated domains. The emerging picture is that most lncRNAs are the products of genetic loci termed 'enhancers', which marshal generic effector proteins to their sites of action to control cell fate decisions during development.

ncDENSE: a novel computational method based on a deep learning framework for non-coding RNAs family prediction

BACKGROUND

Although research on non-coding RNAs (ncRNAs) is a hot topic in life sciences, the functions of numerous ncRNAs remain unclear. In recent years, researchers have found that ncRNAs of the same family have similar functions, therefore, it is important to accurately predict ncRNAs families to identify their functions. There are several methods available to solve the prediction problem of ncRNAs family, whose main ideas can be divided into two categories, including prediction based on the secondary structure features of ncRNAs, and prediction according to sequence features of ncRNAs. The first type of prediction method requires a complicated process and has a low accuracy in obtaining the secondary structure of ncRNAs, while the second type of method has a simple prediction process and a high accuracy, but there is still room for improvement. The existing methods for ncRNAs family prediction are associated with problems such as complicated prediction processes and low accuracy, in this regard, it is necessary to propose a new method to predict the ncRNAs family more perfectly.

RESULTS

A deep learning model-based method, ncDENSE, was proposed in this study, which predicted ncRNAs families by extracting ncRNAs sequence features. The bases in ncRNAs sequences were encoded by one-hot coding and later fed into an ensemble deep learning model, which contained the dynamic bi-directional gated recurrent unit (Bi-GRU), the dense convolutional network (DenseNet), and the Attention Mechanism (AM). To be specific, dynamic Bi-GRU was used to extract contextual feature information and capture long-term dependencies of ncRNAs sequences. AM was employed to assign different weights to features extracted by Bi-GRU and focused the attention on information with greater weights. Whereas DenseNet was adopted to extract local feature information of ncRNAs sequences and classify them by the full connection layer. According to our results, the ncDENSE method improved the Accuracy, Sensitivity, Precision, F-score, and MCC by 2.08[Formula: see text], 2.33[Formula: see text], 2.14[Formula: see text], 2.16[Formula: see text], and 2.39[Formula: see text], respectively, compared with the suboptimal method.

CONCLUSIONS

Overall, the ncDENSE method proposed in this paper extracts sequence features of ncRNAs by dynamic Bi-GRU and DenseNet and improves the accuracy in predicting ncRNAs family and other data.

Revealing the small proteome of Haloferax volcanii by combining ribosome profiling and small-protein optimized mass spectrometry

In contrast to extensively studied prokaryotic 'small' transcriptomes (encompassing all small noncoding RNAs), small proteomes (here defined as including proteins ≤70 aa) are only now entering the limelight. The absence of a complete small protein catalogue in most prokaryotes precludes our understanding of how these molecules affect physiology. So far, archaeal genomes have not yet been analyzed broadly with a dedicated focus on small proteins. Here, we present a combinatorial approach, integrating experimental data from small protein-optimized mass spectrometry (MS) and ribosome profiling (Ribo-seq), to generate a high confidence inventory of small proteins in the model archaeon Haloferax volcanii. We demonstrate by MS and Ribo-seq that 67% of the 317 annotated small open reading frames (sORFs) are translated under standard growth conditions. Furthermore, annotation-independent analysis of Ribo-seq data showed ribosomal engagement for 47 novel sORFs in intergenic regions. A total of seven of these were also detected by proteomics, in addition to an eighth novel small protein solely identified by MS. We also provide independent experimental evidence in vivo for the translation of 12 sORFs (annotated and novel) using epitope tagging and western blotting, underlining the validity of our identification scheme. Several novel sORFs are conserved in Haloferax species and might have important functions. Based on our findings, we conclude that the small proteome of H. volcanii is larger than previously appreciated, and that combining MS with Ribo-seq is a powerful approach for the discovery of novel small protein coding genes in archaea.

Activity-Dependent Non-Coding RNA MAPK Interactome of the Human Epileptic Brain

The human brain has evolved to have extraordinary capabilities, enabling complex behaviors. The uniqueness of the human brain is increasingly posited to be due in part to the functions of primate-specific, including human-specific, long non-coding RNA (lncRNA) genes, systemically less conserved than protein-coding genes in evolution. Patients who have surgery for drug-resistant epilepsy are subjected to extensive electrical recordings of the brain tissue that is subsequently removed in order to treat their epilepsy. Precise localization of brain tissues with distinct electrical properties offers a rare opportunity to explore the effects of brain activity on gene expression. Here, we identified 231 co-regulated, activity-dependent lncRNAs within the human MAPK signaling cascade. Six lncRNAs, four of which were antisense to known protein-coding genes, were further examined because of their high expression and potential impact on the disease phenotype. Using a model of repeated depolarizations in human neuronal-like cells (Sh-SY5Y), we show that five out of six lncRNAs were electrical activity-dependent, with three of four antisense lncRNAs having reciprocal expression patterns relative to their protein-coding gene partners. Some were directly regulated by MAPK signaling, while others effectively downregulated the expression of the protein-coding genes encoded on the opposite strands of their genomic loci. These lncRNAs, therefore, likely contribute to highly evolved and primate-specific human brain regulatory functions that could be therapeutically modulated to treat epilepsy.

Anesthetic‑specific lncRNA and mRNA profile changes in blood during colorectal cancer resection: A prospective, matched‑case pilot study

Prometastatic and antitumor effects of different anesthetics have been previously analyzed in several studies with conflicting results. Thus, the underlying perioperative molecular mechanisms mediated by anesthetics potentially affecting tumor phenotype and metastasis remain unclear. It was hypothesized that anesthetic‑specific long non‑coding RNA (lncRNA) expression changes are induced in the blood circulation and play a crucial role in tumor outcome. In the present study, high‑throughput sequencing and quantitative PCR were performed in order to identify lncRNA and mRNA expression changes affected by two therapeutic regimes, total intravenous anesthesia (TIVA) and volatile anesthetic gas (VAG) in patients undergoing colorectal cancer (CRC) resection. Total blood RNA was isolated prior to and following resection and characterized using RNA sequencing. mRNA‑lncRNA interactions and their roles in cancer‑related signaling of differentially expressed lncRNAs were identified using bioinformatics analyses. The comparison of these two time points revealed 35 differentially expressed lncRNAs in the TIVA‑group, and 25 in the VAG‑group, whereas eight were shared by both groups. Two lncRNAs in the TIVA‑group, and 23 in the VAG‑group of in silico identified target‑mRNAs were confirmed as differentially regulated in the NGS dataset of the present study. Pathway analysis was performed and cancer relevant canonical pathways for TIVA were identified. Target‑mRNA analysis of VAG revealed a markedly worsened immunological response against cancer. In this proof‑of‑concept study, anesthesic‑specific expression changes in lncRNA and mRNA profiles in blood were successfully identified. Moreover, the data of the present study provide the first evidence that anesthesia‑induced lncRNA pattern changes may contribute further in the observed differences in CRC outcome following tumor resection.

Genome-wide identification and comprehensive analysis reveal potential roles of long non-coding RNAs in fruit development of southern highbush blueberry (Vaccinium corymbosum L.)

Introduction

Blueberries have a high antioxidant content and are produced as healthy food worldwide. Long non-coding RNAs (lncRNAs) are a type of regulatory RNAs that play a variety of roles in plants. Nonetheless, information on lncRNAs and their functions during blueberry fruit development is scarce in public databases.

Methods

In the present study, we performed genome-wide identification of lncRNAs in a southern highbush blueberry using strand-specific RNA sequencing (ssRNA-Seq). Differentially expressed lncRNAs (DE-lncRNAs) and their potential target genes were analyzed at four stages of fruit development. Cis-regulatory DE-lncRNAs were predicted using co-localization analysis.

Results

These findings included a total of 25,036 lncRNAs from 17,801 loci. Blueberry lncRNAs had shorter transcript lengths, smaller open reading frame (ORF) sizes, fewer exons, and fewer isoforms than protein-coding RNAs, as well as lower expression levels and higher stage-specificity during fruit development. A total of 105 DE-lncRNAs were identified among the comparison group of PAD vs. CUP, 443 DE-lncRNAs were detected when comparing CUP with PINK fruits, and 285 DE-lncRNAs were revealed when comparing PINK and BLUE fruits. According to Kyoto Encyclopedia of Genes and Genomes annotation, target genes of DE-lncRNAs were primarily enriched in the "Autophagy-other", "DNA replication", "Endocytosis", 'photosynthesis' and 'chlorophyll metabolism' pathways, suggesting that lncRNAs may pay potential roles in fruit expansion and ripening. Moreover, several lncRNAs have been proposed as cis-regulators of the key genes involved in flavonoid biosynthesis. MSTRG.107242.6, and its putative target gene, BTB/POZ and TAZ domain-containing protein, might play critical roles in anthocyanin accumulation in blueberries.

Discussion

These findings highlight the regulatory function of lncRNAs and aid in elucidating the molecular mechanism underlying blueberry fruit growth.

Dynamic landscape of long noncoding RNAs during leaf aging in Arabidopsis

Leaf senescence, the last stage of leaf development, is essential for whole-plant fitness as it marks the relocation of nutrients from senescing leaves to reproductive or other developing organs. Temporally coordinated physiological and functional changes along leaf aging are fine-tuned by a highly regulated genetic program involving multi-layered regulatory mechanisms. Long noncoding RNAs (lncRNAs) are newly emerging as hidden players in many biological processes; however, their contribution to leaf senescence has been largely unknown. Here, we performed comprehensive analyses of RNA-seq data representing all developmental stages of leaves to determine the genome-wide lncRNA landscape along leaf aging. A total of 771 lncRNAs, including 232 unannotated lncRNAs, were identified. Time-course analysis revealed 446 among 771 developmental age-related lncRNAs (AR-lncRNAs). Intriguingly, the expression of AR-lncRNAs was regulated more dynamically in senescing leaves than in growing leaves, revealing the relevant contribution of these lncRNAs to leaf senescence. Further analyses enabled us to infer the function of lncRNAs, based on their interacting miRNA or mRNA partners. We considered functionally diverse lncRNAs including antisense lncRNAs (which regulate overlapping protein-coding genes), competitive endogenous RNAs (ceRNAs; which regulate paired mRNAs using miRNAs as anchors), and mRNA-interacting lncRNAs (which affect the stability of mRNAs). Furthermore, we experimentally validated the senescence regulatory function of three novel AR-lncRNAs including one antisense lncRNA and two mRNA-interacting lncRNAs through molecular and phenotypic analyses. Our study provides a valuable resource of AR-lncRNAs and potential regulatory networks that link the function of coding mRNA and AR-lncRNAs. Together, our results reveal AR-lncRNAs as important elements in the leaf senescence process.

LncRNA GAS5 represses stemness and malignancy of gliomas via elevating the SPACA6-miR-125a/let-7e Axis

Glioblastoma (GBM) is a highly invasive neurological malignancy with poor prognosis. LncRNA-GAS5 (growth arrest-specific transcript 5) is a tumor suppressor involved in multiple cancers. In this study, we explored the clinical significance, biological function, and underlying mechanisms of GAS5 in GBM. We showed that lncRNA-GAS5 expression decreased in high-grade glioma tissues and cells, which might be associated with poor prognosis. GAS5 overexpression lowered cell viability, suppressed GBM cell migration and invasion, and impaired the stemness and proliferation of glioma stem cells (GSCs). We further discovered that GAS5 inhibited the viability of glioma cells through miR-let-7e and miR-125a by protecting SPACA6 from degradation. Moreover, GAS5 played an anti-oncogenic role in GBM through the combined involvement of let-7e and miR-125a in vivo and in vitro. Notably, these two miRNAs block the IL-6/STAT3 pathway in tumor tissues extracted from a xenograft model. Taken together, our study provides evidence for an important role of GAS5 in GBM by affecting the proliferation and migration of GSCs, thus providing a new potential prognostic biomarker and treatment strategy for GBM.

miRacle of microRNA-Driven Cancer Nanotherapeutics

MicroRNAs (miRNAs) are non-protein-coding RNA molecules 20-25 nucleotides in length that can suppress the expression of genes involved in numerous physiological processes in cells. Accumulating evidence has shown that dysregulation of miRNA expression is related to the pathogenesis of various human diseases and cancers. Thus, stragegies involving either restoring the expression of tumor suppressor miRNAs or inhibiting overexpressed oncogenic miRNAs hold potential for targeted cancer therapies. However, delivery of miRNAs to tumor tissues is a challenging task. Recent advances in nanotechnology have enabled successful tumor-targeted delivery of miRNA therapeutics through newly designed nanoparticle-based carrier systems. As a result, miRNA therapeutics have entered human clinical trials with promising results, and they are expected to accelerate the transition of miRNAs from the bench to the bedside in the next decade. Here, we present recent perspectives and the newest developments, describing several engineered natural and synthetic novel miRNA nanocarrier formulations and their key in vivo applications and clinical trials.

B, Iquebal MA, Bhattacharya RC, Rai A, Kumar D. Genome wide identification of lncRNAs and circRNAs having regulatory role in fruit shelf life in health crop cucumber (Cucumis sativus L.)

Cucumber is an extremely perishable vegetable; however, under room conditions, the fruits become unfit for consumption 2-3 days after harvesting. One natural variant, DC-48 with an extended shelf-life was identified, fruits of which can be stored up to 10-15 days under room temperature. The genes involved in this economically important trait are regulated by non-coding RNAs. The study aims to identify the long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) by taking two contrasting genotypes, DC-48 and DC-83, at two different fruit developmental stages. The upper epidermis of the fruits was collected at 5 days and 10 days after pollination (DAP) for high throughput RNA sequencing. The differential expression analysis was performed to identify differentially expressed (DE) lncRNAs and circRNAs along with the network analysis of lncRNA, miRNA, circRNA, and mRNA interactions. A total of 97 DElncRNAs were identified where 18 were common under both the developmental stages (8 down regulated and 10 upregulated). Based on the back-spliced reads, 238 circRNAs were found to be distributed uniformly throughout the cucumber genomes with the highest numbers (71) in chromosome 4. The majority of the circRNAs (49%) were exonic in origin followed by inter-genic (47%) and intronic (4%) origin. The genes related to fruit firmness, namely, polygalacturonase, expansin, pectate lyase, and xyloglucan glycosyltransferase were present in the target sites and co-localized networks indicating the role of the lncRNA and circRNAs in their regulation. Genes related to fruit ripening, namely, trehalose-6-phosphate synthase, squamosa promoter binding protein, WRKY domain transcription factors, MADS box proteins, abscisic stress ripening inhibitors, and different classes of heat shock proteins (HSPs) were also found to be regulated by the identified lncRNA and circRNAs. Besides, ethylene biosynthesis and chlorophyll metabolisms were also found to be regulated by DElncRNAs and circRNAs. A total of 17 transcripts were also successfully validated through RT PCR data. These results would help the breeders to identify the complex molecular network and regulatory role of the lncRNAs and circRNAs in determining the shelf-life of cucumbers.

Competing endogenous RNA-networks reveal key regulatory microRNAs involved in the response of Atlantic salmon to a novel orthomyxovirus

One of the most intriguing discoveries of the genomic era is that only a small fraction of the genome is dedicated to protein coding. The remaining fraction of the genome contains, amongst other elements, a number of non-coding transcripts that regulate the transcription of protein coding genes. Here we used transcriptome sequencing data to explore these gene regulatory networks using RNA derived from gill tissue of Atlantic salmon (Salmo salar) infected with Pilchard orthomyxovirus (POMV), but showing no clinical signs of disease. We examined fish sampled early during the challenge trial (8-12 days after infection) to uncover potential biomarkers of early infection and innate immunity, and fish sampled late during the challenge trial (19 dpi) to elucidate potential markers of resistance to POMV. We analysed total RNA-sequencing data to find differentially expressed messenger RNAs (mRNA) and identify new long-noncoding RNAs (lncRNAs). We also evaluated small RNA sequencing data to find differentially transcribed microRNAs (miRNAs) and explore their role in gene regulatory networks. Whole-genome expression data (both coding and non-coding transcripts) were used to explore the crosstalk between RNA molecules by constructing competing endogenous RNA networks (ceRNA). The teleost specific miR-462/miR-731 cluster was strongly induced in POMV infected fish and deemed a potential biomarker of early infection. Gene networks also identified a selenoprotein (selja), downregulated in fish sampled late during the challenge, which may be associated to viral clearance and the return to homeostasis after infection. This study provides the basis for further investigations using molecular tools to overexpress or inhibit miRNAs to confirm the functional impact of the interactions presented here on gene expression and their potential application at commercial level.

Expression Profiles and Characteristics of Apple lncRNAs in Roots, Phloem, Leaves, Flowers, and Fruit

LncRNAs impart crucial effects on various biological processes, including biotic stress responses, abiotic stress responses, fertility and development. The apple tree is one of the four major fruit trees in the world. However, lncRNAs's roles in different tissues of apple are unknown. We identified the lncRNAs in five tissues of apples including the roots, phloem, leaves, flowers, and fruit, and predicted the intricate regulatory networks. A total of 9440 lncRNAs were obtained. LncRNA target prediction revealed 10,628 potential lncRNA-messenger RNA (mRNA) pairs, 9410 pairs functioning in a cis-acting fashion, and 1218 acting in a trans-acting fashion. Functional enrichment analysis showed that the targets were significantly enriched in molecular functions related to photosynthesis-antenna proteins, single-organism metabolic process and glutathione metabolism. Additionally, a total of 88 lncRNAs have various functions related to microRNAs (miRNAs) as miRNA precursors. Interactions between lncRNAs and miRNAs were predicted, 1341 possible interrelations between 187 mdm-miRNAs and 174 lncRNAs (1.84%) were identified. MSTRG.121644.5, MSTRG.121644.8, MSTRG.2929.2, MSTRG.3953.2, MSTRG.63448.2, MSTRG.9870.2, and MSTRG.9870.3 could participate in the functions in roots as competing endogenous RNAs (ceRNAs). MSTRG.11457.2, MSTRG.138614.2, and MSTRG.60895.2 could adopt special functions in the fruit by working with miRNAs. A further analysis showed that different tissues formed special lncRNA-miRNA-mRNA networks. MSTRG.60895.2-mdm-miR393-MD17G1009000 may participate in the anthocyanin metabolism in the fruit. These findings provide a comprehensive view of potential functions for lncRNAs, corresponding target genes, and related lncRNA-miRNA-mRNA networks, which will increase our knowledge of the underlying development mechanism in apple.

Deep learning tools are top performers in long non-coding RNA prediction

The increasing amount of transcriptomic data has brought to light vast numbers of potential novel RNA transcripts. Accurately distinguishing novel long non-coding RNAs (lncRNAs) from protein-coding messenger RNAs (mRNAs) has challenged bioinformatic tool developers. Most recently, tools implementing deep learning architectures have been developed for this task, with the potential of discovering sequence features and their interactions still not surfaced in current knowledge. We compared the performance of deep learning tools with other predictive tools that are currently used in lncRNA coding potential prediction. A total of 15 tools representing the variety of available methods were investigated. In addition to known annotated transcripts, we also evaluated the use of the tools in actual studies with real-life data. The robustness and scalability of the tools' performance was tested with varying sized test sets and test sets with different proportions of lncRNAs and mRNAs. In addition, the ease-of-use for each tested tool was scored. Deep learning tools were top performers in most metrics and labelled transcripts similarly with each other in the real-life dataset. However, the proportion of lncRNAs and mRNAs in the test sets affected the performance of all tools. Computational resources were utilized differently between the top-ranking tools, thus the nature of the study may affect the decision of choosing one well-performing tool over another. Nonetheless, the results suggest favouring the novel deep learning tools over other tools currently in broad use.

Hidden in plain sight: challenges in proteomics detection of small ORF-encoded polypeptides

Genomic studies of bacteria have long pointed toward widespread prevalence of small open reading frames (sORFs) encoding for short proteins, <100 amino acids in length. Despite the mounting genomic evidence of their robust expression, relatively little progress has been made in their mass spectrometry-based detection and various blanket statements have been used to explain this observed discrepancy. In this study, we provide a large-scale riboproteogenomics investigation of the challenging nature of proteomic detection of such small proteins as informed by conditional translation data. A panel of physiochemical properties alongside recently developed mass spectrometry detectability metrics was interrogated to provide a comprehensive evidence-based assessment of sORF-encoded polypeptide (SEP) detectability. Moreover, a large-scale proteomics and translatomics compendium of proteins produced by Salmonella Typhimurium (S. Typhimurium), a model human pathogen, across a panel of growth conditions is presented and used in support of our in silico SEP detectability analysis. This integrative approach is used to provide a data-driven census of small proteins expressed by S. Typhimurium across growth phases and infection-relevant conditions. Taken together, our study pinpoints current limitations in proteomics-based detection of novel small proteins currently missing from bacterial genome annotations.

Functional investigation of lncRNAs and target cytochrome P450 genes related to spirotetramat resistance in Aphis gossypii Glover

BACKGROUND

Spirotetramat is a tetramic acid derivative insecticide with novel modes of action for controlling Aphis gossypii Glover in the field. Previous studies have shown that long noncoding RNAs (lncRNAs) and cytochrome P450 monooxygenases (P450s) are involved in the detoxification process. However, the functions of lncRNAs in regulating P450 gene expression in spirotetramat resistance in A. gossypii are unknown.

RESULTS

In this study, we found CYP4CJ1, CYP6CY7 and CYP6CY21 expression levels to be significantly upregulated in a spirotetramat-resistant (SR) strain compared with a susceptible (SS) strain. Furthermore, knockdown of CYP4CJ1, CYP6CY7 and CYP6CY21 increased nymph and adult mortality in the SR strain following exposure to spirotetramat. Drosophila ectopically expressing CYP380C6, CYP4CJ1, CYP6DA2, CYP6CY7 and CYP6CY21 showed significantly decreased mortality after spirotetramat exposure, and CYP380C6, CYP4CJ1 and CYP6CY21 are putative targets of six lncRNAs. Silencing of lncRNAs MSTRG.36649.2/5 and MSTRG.71880.1 changed CYP6CY21 and CYP380C6 expression, altering the sensitivity of the SR strain to spirotetramat. Moreover, MSTRG.36649.2/5 did not compete for microRNA (miRNA) binding to regulate CYP6CY21 expression.

CONCLUSION

Our results confirm that CYP380C6, CYP4CJ1, CYP6DA2, CYP6CY7 and CYP6CY21 are potentially involved in the development of spirotetramat resistance in A. gossypii, and MSTRG.36649.2/5 and MSTRG.71880.1 probably regulate CYP6CY21 and CYP380C6 expression other than through the "sponge effect" of competing for miRNA binding. Our results provide a favorable molecular basis for studying cotton aphid P450 genes and lncRNA functions in spirotetramat resistance development.

The Genome-Wide Identification of Long Non-Coding RNAs Involved in Floral Thermogenesis in Nelumbo nucifera Gaertn

The sacred lotus (Nelumbo nucifera Gaertn.) can maintain a stable floral chamber temperature when blooming, despite ambient temperature fluctuations; however, the long non-coding RNAs (lncRNAs) involved in floral thermogenesis remain unclear. In the present study, we obtain comprehensive lncRNAs expression profiles from receptacles at five developmental stages by strand-specific RNA sequencing to reveal the lncRNAs regulatory mechanism of the floral thermogenesis of N. nucifera. A total of 22,693 transcripts were identified as lncRNAs, of which approximately 44.78% had stage-specific expression patterns. Subsequently, we identified 2579 differential expressed lncRNAs (DELs) regulating 2367 protein-coding genes mainly involved in receptacle development and reproductive process. Then, lncRNAs with floral thermogenesis identified by weighted gene co-expression network analysis (WGCNA) were mainly related to sulfur metabolism and mitochondrial electron transport chains. Meanwhile, 70 lncRNAs were predicted to act as endogenous target mimics (eTMs) for 29 miRNAs and participate in the regulation of 16 floral thermogenesis-related genes. Our dual luciferase reporter assays indicated that lncRNA LTCONS_00068702 acted as eTMs for miR164a_4 to regulate the expression of TrxL2 gene. These results deepen our understanding of the regulation mechanism of floral thermogenesis by lncRNAs and accumulate data for further research.

Characterization of Oligopeptides in Solanum lycopersicum Xylem Exudates

The xylem is the main pathway for the transport of water and molecules from roots to shoots. To date, it has been reported that secreted oligopeptides mediate root-to-shoot signaling, and some long-distance mobile oligopeptides have been detected in xylem exudates. However, the conservation of a number of oligopeptides and the overall features of peptide fragments contained in xylem exudates are poorly understood. Here, we conducted a comprehensive analysis of small proteins and peptides in tomato (Solanum lycopersicum) xylem exudates and characterized the identified peptide fragments. We found that putative secreted proteins were enriched in xylem exudates compared with all proteins in the tomato protein database. We identified seven oligopeptides that showed common features of bioactive oligopeptides, including homologs of CLV3/ESR-related (CLE), C-TERMINALLY ENCODED PEPTIDE (CEP), and CASPARIAN STRIP INTEGRITY FACTOR (CIF) peptides. Furthermore, five of the identified oligopeptides were homologs of the soybean xylem exudate-associated oligopeptides that we previously reported. Our results suggest that oligopeptides in xylem exudates are conserved across plant species and provide insights into not only root-to-shoot signaling but also the maintenance of the xylem conduit.

Targeting autophagy in prostate cancer: preclinical and clinical evidence for therapeutic response

Prostate cancer is a leading cause of death worldwide and new estimates revealed prostate cancer as the leading cause of death in men in 2021. Therefore, new strategies are pertinent in the treatment of this malignant disease. Macroautophagy/autophagy is a “self-degradation” mechanism capable of facilitating the turnover of long-lived and toxic macromolecules and organelles. Recently, attention has been drawn towards the role of autophagy in cancer and how its modulation provides effective cancer therapy. In the present review, we provide a mechanistic discussion of autophagy in prostate cancer. Autophagy can promote/inhibit proliferation and survival of prostate cancer cells. Besides, metastasis of prostate cancer cells is affected (via induction and inhibition) by autophagy. Autophagy can affect the response of prostate cancer cells to therapy such as chemotherapy and radiotherapy, given the close association between autophagy and apoptosis. Increasing evidence has demonstrated that upstream mediators such as AMPK, non-coding RNAs, KLF5, MTOR and others regulate autophagy in prostate cancer. Anti-tumor compounds, for instance phytochemicals, dually inhibit or induce autophagy in prostate cancer therapy. For improving prostate cancer therapy, nanotherapeutics such as chitosan nanoparticles have been developed. With respect to the context-dependent role of autophagy in prostate cancer, genetic tools such as siRNA and CRISPR-Cas9 can be utilized for targeting autophagic genes. Finally, these findings can be translated into preclinical and clinical studies to improve survival and prognosis of prostate cancer patients.

• Prostate cancer is among the leading causes of death in men where targeting autophagy is of importance in treatment;

• Autophagy governs proliferation and metastasis capacity of prostate cancer cells;

• Autophagy modulation is of interest in improving the therapeutic response of prostate cancer cells;

• Molecular pathways, especially involving non-coding RNAs, regulate autophagy in prostate cancer;

• Autophagy possesses both diagnostic and prognostic roles in prostate cancer, with promises for clinical application.

Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures

A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.

Identification of Microproteins in Hep3B Cells at Different Cell Cycle Stages

Microproteins are generated from small open reading frames and turn out to play various vital biological functions. As an essential biological event of eukaryotic cells, the cell cycle is involved in cell replication and division. For such a highly regulated event, microproteins associated with cell cycle regulation remained unclarified. Utilizing a combination of bottom-up and top-down proteomics, we analyzed microproteins at specific cell cycle stages of Hep3B cells. A total of 657 microproteins were identified under three cell cycle stages, including 151 in the G0/G1 stage, 163 in the S stage, and 132 in the G2/M stage. The annotation of these microproteins showed their cell cycle-specific functions, such as translation, nuclear assembly, chromatin organization, and the G2/M transition of the mitotic cell cycle. Meanwhile, more than 50% of identified microproteins were ncRNA-encoded. These nonannotated novel microproteins contain several function domains, such as the nucleoside diphosphate kinase domain, the high mobility group domain, and the DNA-binding domain. This suggested the potential functions of these novel microproteins in specific cell cycle stages. This study presented a large-scale profile of microproteins at different cell cycle stages from Hep3B and may provide new perspectives on the regulation mechanism of the cell cycle. Liquid chromatography-mass spectrometry data were deposited to ProteomeXchange using the identifier PXD030286.