tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by high-throughput small RNA-Seq and CLIP-Seq data.

tRNA-derived small RNA (tsRNA), a novel type of regulatory small noncoding RNA, plays an important role in physiological and pathological processes. However, the understanding of the functional mechanism of tsRNAs in cells and their role in the occurrence and development of diseases is limited. Here, we integrated multiomics data such as transcriptome, epitranscriptome, and targetome data, and developed novel computer tools to establish tsRFun, a comprehensive platform to facilitate tsRNA research (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/). tsRFun evaluated tsRNA expression profiles and the prognostic value of tsRNAs across 32 types of cancers, identified tsRNA target molecules utilizing high-throughput CLASH/CLEAR or CLIP sequencing data, and constructed the interaction networks among tsRNAs, microRNAs, and mRNAs. In addition to its data presentation capabilities, tsRFun offers multiple real-time online tools for tsRNA identification, target prediction, and functional enrichment analysis. In summary, tsRFun provides a valuable data resource and multiple analysis tools for tsRNA investigation.

Comprehensive annotation and characterization of planarian tRNA and tRNA-derived fragments (tRFs).

tRNA-derived fragments (tRFs) have recently gained a lot of scientific interest due to their diverse regulatory roles in several cellular processes. However, their function in dynamic biological processes such as development and regeneration remains unexplored. Here, we show that tRFs are dynamically expressed during planarian regeneration, suggesting a possible role for these small RNAs in the regulation of regeneration. In order to characterize planarian tRFs, we first annotated 457 tRNAs in S. mediterranea combining two tRNA prediction algorithms. Annotation of tRNAs facilitated the identification of three main species of tRFs in planarians-the shorter tRF-5s and itRFs, and the abundantly expressed 5'-tsRNAs. Spatial profiling of tRFs in sequential transverse sections of planarians revealed diverse expression patterns of these small RNAs, including those that are enriched in the head and pharyngeal regions. Expression analysis of these tRF species revealed dynamic expression of these small RNAs over the course of regeneration suggesting an important role in planarian anterior and posterior regeneration. Finally, we show that 5'-tsRNA in planaria interact with all three SMEDWI proteins and an involvement of AGO1 in the processing of itRFs. In summary, our findings implicate a novel role for tRFs in planarian regeneration, highlighting their importance in regulating complex systemic processes. Our study adds to the catalog of posttranscriptional regulatory systems in planaria, providing valuable insights on the biogenesis and the function of tRFs in neoblasts and planarian regeneration.

Synthetase of the methyl donor S-adenosylmethionine from nitrogen-fixing α-rhizobia can bind functionally diverse RNA species.

Function of bacterial small non-coding RNAs (sRNAs) and overall RNA metabolism is largely shaped by a vast diversity of RNA-protein interactions. However, in non-model bacteria with defined non-coding transcriptomes the sRNA interactome remains almost unexplored. We used affinity chromatography to capture proteins associated in vivo with MS2-tagged trans-sRNAs that regulate nutrient uptake (AbcR2 and NfeR1) and cell cycle (EcpR1) mRNAs by antisense-based translational inhibition in the nitrogen-fixing α-rhizobia Sinorhizobium meliloti. The three proteomes were rather distinct, with that of EcpR1 particularly enriched in cell cycle-related enzymes, whilst sharing several transcription/translation-related proteins recurrently identified associated with sRNAs. Strikingly, MetK, the synthetase of the major methyl donor S-adenosylmethionine, was reliably recovered as a binding partner of the three sRNAs, which reciprocally co-immunoprecipitated with a FLAG-tagged MetK variant. Induced (over)expression of the trans-sRNAs and MetK depletion did not influence canonical riboregulatory traits, `for example, protein titration or sRNA stability, respectively. An in vitro filter assay confirmed binding of AbcR2, NfeR1 and EcpR1 to MetK and further revealed interaction of the protein with other non-coding and coding transcripts but not with the 5S rRNA. These findings uncover a broad specificity for RNA binding as an unprecedented feature of this housekeeping prokaryotic enzyme.

Identification of a Functional Small Noncoding RNA of African Swine Fever Virus.

African swine fever virus (ASFV) causes a lethal hemorrhagic disease of domestic pigs, against which no vaccine is available. ASFV has a large, double-stranded DNA genome that encodes over 150 proteins. Replication takes place predominantly in the cytoplasm of the cell and involves complex interactions with host cellular components, including small noncoding RNAs (sncRNAs). A number of DNA viruses are known to manipulate sncRNA either by encoding their own or disrupting host sncRNA. To investigate the interplay between ASFV and sncRNAs, a study of host and viral small RNAs extracted from ASFV-infected primary porcine macrophages (PAMs) was undertaken. We discovered that ASFV infection had only a modest effect on host miRNAs, with only 6 miRNAs differentially expressed during infection. The data also revealed 3 potential novel small RNAs encoded by ASFV, ASFVsRNA1-3. Further investigation of ASFVsRNA2 detected it in lymphoid tissue from pigs with ASF. Overexpression of ASFVsRNA2 led to an up to 1-log reduction in ASFV growth, indicating that ASFV utilizes a virus-encoded small RNA to disrupt its own replication.IMPORTANCE African swine fever (ASF) poses a major threat to pig populations and food security worldwide. The disease is endemic to Africa and Eastern Europe and is rapidly emerging into Asia, where it has led to the deaths of millions of pigs in the last 12 months. The development of safe and effective vaccines to protect pigs against ASF has been hindered by lack of understanding of the complex interactions between ASFV and the host cell. We focused our work on characterizing the interactions between ASFV and sncRNAs. Although comparatively modest changes to host sncRNA abundances were observed upon ASFV infection, we discovered and characterized a novel functional ASFV-encoded sncRNA. The results from this study add important insights into ASFV host-pathogen interactions. This knowledge may be exploited to develop more effective ASFV vaccines that take advantage of the sncRNA system.

Manatee: detection and quantification of small non-coding RNAs from next-generation sequencing data.

Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing (NGS) technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq (sRNA-Seq) data analysis proved to be challenging due to non-unique genomic origin, short length, and abundant post-transcriptional modifications of sRNA species. Here, we present Manatee, an algorithm for the quantification of sRNA classes and the detection of novel expressed non-coding loci. Manatee combines prior annotation of sRNAs with reliable alignment density information and extensive rescue of usually neglected multimapped reads to provide accurate transcriptome-wide sRNA expression quantification. Comparison of Manatee against state-of-the-art implementations using real and simulated data demonstrates its high accuracy across diverse sRNA classes. Manatee also goes beyond common pipelines by identifying and quantifying expression from unannotated loci and microRNA isoforms (isomiRs). It is user-friendly, can be easily incorporated in pipelines, and provides a simplified output suitable for direct usage in downstream analyses and functional studies.

Compensatory sequence variation between trans-species small RNAs and their target sites.

Trans-species small regulatory RNAs (sRNAs) are delivered to host plants from diverse pathogens and parasites and can target host mRNAs. How trans-species sRNAs can be effective on diverse hosts has been unclear. Multiple species of the parasitic plant Cuscuta produce trans-species sRNAs that collectively target many host mRNAs. Confirmed target sites are nearly always in highly conserved, protein-coding regions of host mRNAs. Cuscuta trans-species sRNAs can be grouped into superfamilies that have variation in a three-nucleotide period. These variants compensate for synonymous-site variation in host mRNAs. By targeting host mRNAs at highly conserved protein-coding sites, and simultaneously expressing multiple variants to cover synonymous-site variation, Cuscuta trans-species sRNAs may be able to successfully target multiple homologous mRNAs from diverse hosts.

3D cell culture stimulates the secretion of in vivo like extracellular vesicles.

For studying cellular communications ex-vivo, a two-dimensional (2D) cell culture model is currently used as the "gold standard". 2D culture models are also widely used in the study of RNA expression profiles from tumor cells secreted extracellular vesicles (EVs) for tumor biomarker discovery. Although the 2D culture system is simple and easily accessible, the culture environment is unable to represent in vivo extracellular matrix (ECM) microenvironment. Our study observed that 2D- culture derived EVs showed significantly different profiles in terms of secretion dynamics and essential signaling molecular contents (RNAs and DNAs), when compared to the three-dimensional (3D) culture derived EVs. By performing small RNA next-generation sequencing (NGS) analysis of cervical cancer cells and their EVs compared with cervical cancer patient plasma EV-derived small RNAs, we observed that 3D- culture derived EV small RNAs differ from their parent cell small RNA profile which may indicate a specific sorting process. Most importantly, the 3D- culture derived EV small RNA profile exhibited a much higher similarity (~96%) to in vivo circulating EVs derived from cervical cancer patient plasma. However, 2D- culture derived EV small RNA profile correlated better with only their parent cells cultured in 2D. On the other hand, DNA sequencing analysis suggests that culture and growth conditions do not affect the genomic information carried by EV secretion. This work also suggests that tackling EV molecular alterations secreted into interstitial fluids can provide an alternative, non-invasive approach for investigating 3D tissue behaviors at the molecular precision. This work could serve as a foundation for building precise models employed in mimicking in vivo tissue system with EVs as the molecular indicators or transporters. Such models could be used for investigating tumor biomarkers, drug screening, and understanding tumor progression and metastasis.

Deep sequencing of small non-coding RNA highlights brain-specific expression patterns and RNA cleavage.

With the advance of high-throughput sequencing technology numerous new regulatory small RNAs have been identified, that broaden the variety of processing mechanisms and functions of non-coding RNA. Here we explore small non-coding RNA (sncRNA) expression in central parts of the physiological stress and anxiety response system. Therefore, we characterize the sncRNA profile of tissue samples from Amygdala, Hippocampus, Hypothalamus and Adrenal Gland, obtained from 20 pigs. Our analysis reveals that all tissues but Amygdala and Hippocampus possess distinct, tissue-specific expression pattern of miRNA that are associated with Hypoxia, stress responses as well as memory and fear conditioning. In particular, we observe marked differences in the expression profile of limbic tissues compared to those associated to the HPA/stress axis, with a surprisingly high aggregation of 3´-tRNA halves in Amygdala and Hippocampus. Since regulation of sncRNA and RNA cleavage plays a pivotal role in the central nervous system, our work provides seminal insights in the role/involvement of sncRNA in the transcriptional and post-transcriptional regulation of negative emotion, stress and coping behaviour in pigs, and mammals in general.

Genetic Regulation of Streptococci by Small RNAs.

Streptococcal species constitute a large group of commensal and pathogenic Gram-positive bacteria that exist in a wide variety of habitats. The family of small RNAs is typically ranged in size from 50 to 300 nucleotides, and acts as regulators in bacteria. The last decade has witnessed the increasing findings of small RNAs (sRNAs), which play important regulatory roles in the variety of biological processes in streptococci. In this review, we summarized the recent achievements in the identification of streptococcal sRNAs, mainly in Streptococcus pyogenes and Streptococcus pneumoniae. In addition, we particularly focused on the functions that sRNAs exert in the regulatory networks of both phenotypical traits and pathogenicity. The fact that sRNAs act as a critical fine-tuning regulator of streptococci may not only reveal in-depth mechanisms of bacterial post-transcriptional regulations in response to environmental perturbance, but also provide promising approaches to the better management of streptococcal infections.

APERO: a genome-wide approach for identifying bacterial small RNAs from RNA-Seq data.

Small non-coding RNAs (sRNAs) regulate numerous cellular processes in all domains of life. Several approaches have been developed to identify them from RNA-seq data, which are efficient for eukaryotic sRNAs but remain inaccurate for the longer and highly structured bacterial sRNAs. We present APERO, a new algorithm to detect small transcripts from paired-end bacterial RNA-seq data. In contrast to previous approaches that start from the read coverage distribution, APERO analyzes boundaries of individual sequenced fragments to infer the 5' and 3' ends of all transcripts. Since sRNAs are about the same size as individual fragments (50-350 nucleotides), this algorithm provides a significantly higher accuracy and robustness, e.g., with respect to spontaneous internal breaking sites. To demonstrate this improvement, we develop a comparative assessment on datasets from Escherichia coli and Salmonella enterica, based on experimentally validated sRNAs. We also identify the small transcript repertoire of Dickeya dadantii including putative intergenic RNAs, 5' UTR or 3' UTR-derived RNA products and antisense RNAs. Comparisons to annotations as well as RACE-PCR experimental data confirm the precision of the detected transcripts. Altogether, APERO outperforms all existing methods in terms of sRNA detection and boundary precision, which is crucial for comprehensive genome annotations. It is freely available as an open source R package on https://github.com/Simon-Leonard/APERO.

The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.

The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses.

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

Deep genome annotation of the opportunistic human pathogen Streptococcus pneumoniae D39.

A precise understanding of the genomic organization into transcriptional units and their regulation is essential for our comprehension of opportunistic human pathogens and how they cause disease. Using single-molecule real-time (PacBio) sequencing we unambiguously determined the genome sequence of Streptococcus pneumoniae strain D39 and revealed several inversions previously undetected by short-read sequencing. Significantly, a chromosomal inversion results in antigenic variation of PhtD, an important surface-exposed virulence factor. We generated a new genome annotation using automated tools, followed by manual curation, reflecting the current knowledge in the field. By combining sequence-driven terminator prediction, deep paired-end transcriptome sequencing and enrichment of primary transcripts by Cappable-Seq, we mapped 1015 transcriptional start sites and 748 termination sites. We show that the pneumococcal transcriptional landscape is complex and includes many secondary, antisense and internal promoters. Using this new genomic map, we identified several new small RNAs (sRNAs), RNA switches (including sixteen previously misidentified as sRNAs), and antisense RNAs. In total, we annotated 89 new protein-encoding genes, 34 sRNAs and 165 pseudogenes, bringing the S. pneumoniae D39 repertoire to 2146 genetic elements. We report operon structures and observed that 9% of operons are leaderless. The genome data are accessible in an online resource called PneumoBrowse (https://veeninglab.com/pneumobrowse) providing one of the most complete inventories of a bacterial genome to date. PneumoBrowse will accelerate pneumococcal research and the development of new prevention and treatment strategies.

Transfer RNA-derived small RNAs in plants.

Rather than random degradation products, the 18 to 40 nucleotides (nt) transfer RNA-derived small RNAs (tsRNAs) are RNA species generated specifically from pre-RNAs or mature tRNAs in archaea, bacteria and eukaryotes. Recent studies from animal systems have shown that tsRNAs are important non-coding RNAs that regulate gene expression at the transcriptional and/or post-transcriptional levels. They are involved in various biological processes, such as cell proliferation, tumor genesis, stress response and intergenerational epigenetic inheritance. In this review, we will summarize the discovery, biogenesis, and function of tsRNAs in higher plants. In addition, analysis on tsRNAs from lower plants is shown.

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria.

Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

The discovery potential of RNA processing profiles.

Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.

Varicella-Zoster Virus Expresses Multiple Small Noncoding RNAs.

Many herpesviruses express small noncoding RNAs (sncRNAs), including microRNAs (miRNAs), that may play roles in regulating lytic and latent infections. None have yet been reported in varicella-zoster virus (VZV; also known as human herpesvirus 3 [HHV-3]). Here we analyzed next-generation sequencing (NGS) data for small RNAs in VZV-infected fibroblasts and human embryonic stem cell-derived (hESC) neurons. Two independent bioinformatics analyses identified more than 20 VZV-encoded 20- to 24-nucleotide RNAs, some of which are predicted to have stem-loop precursors potentially representing miRNAs. These sequences are perfectly conserved between viruses from three clades of VZV. One NGS-identified sequence common to both bioinformatics analyses mapped to the repeat regions of the VZV genome, upstream of the predicted promoter of the immediate early gene open reading frame 63 (ORF63). This miRNA candidate was detected in each of 3 independent biological repetitions of NGS of RNA from fibroblasts and neurons productively infected with VZV using TaqMan quantitative PCR (qPCR). Importantly, transfected synthetic RNA oligonucleotides antagonistic to the miRNA candidate significantly enhanced VZV plaque growth rates. The presence of 6 additional small noncoding RNAs was also verified by TaqMan qPCR in productively infected fibroblasts and ARPE19 cells. Our results show VZV, like other human herpesviruses, encodes several sncRNAs and miRNAs, and some may regulate infection of host cells.IMPORTANCE Varicella-zoster virus is an important human pathogen, with herpes zoster being a major health issue in the aging and immunocompromised populations. Small noncoding RNAs (sncRNAs) are recognized as important actors in modulating gene expression, and this study demonstrates the first reported VZV-encoded sncRNAs. Many are clustered to a small genomic region, as seen in other human herpesviruses. At least one VZV sncRNA was expressed in productive infection of neurons and fibroblasts that is likely to reduce viral replication. Since sncRNAs have been suggested to be potential targets for antiviral therapies, identification of these molecules in VZV may provide a new direction for development of treatments for painful herpes zoster.

The sibling sRNAs NgncR_162 and NgncR_163 of Neisseria gonorrhoeae participate in the expression control of metabolic, transport and regulatory proteins.

Neisseria gonorrhoeae is the causative agent of gonorrhoea, the second most common bacterial sexually transmitted disease. Riboregulation mediated by small regulatory RNAs (sRNAs) is increasingly recognized as an important means of gene expression control in this human-restricted pathogen. sRNAs act at the post-transcriptional level by base-pairing with their target mRNAs which affects translation initiation and/or mRNA stability. In this study we initiated the characterization of a pair of highly conserved sRNAs of N. gonorrhoeae which exhibit redundant functions in the control of a common set of target genes. The identified targets of the sibling sRNAs NgncR_162 and NgncR_163 participate in basic metabolic processes including the methylcitrate and citrate cycle, aa uptake and degradation, and also in transcription regulation. Our data indicate that the sibling sRNAs control their targets via direct base-pairing between the same single-stranded domain(s) of the sRNA and the ribosome binding site in the 5'-untranslated region of the mRNA.

Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells--Evidence of unique microRNA cargos.

Melanoma cells release different types of extracellular vesicles (EVs) into the extracellular milieu that are involved with communication and signaling in the tumor microenvironment. Subsets of EVs include exosomes, microvesicles, and apoptotic bodies that carry protein and genetic (RNA) cargos. To define the contribution of the RNA cargo of melanoma cell derived EVs we performed small RNA sequencing to identify different small RNAs in the EV subsets. Using validated centrifugation protocols, we separated these EV subsets released by the melanoma cell line MML-1, and performed RNA sequencing with the Ion Torrent platform. Various, but different, non-coding RNAs were detected in the EV subsets, including microRNA, mitochondrial associated tRNA, small nucleolar RNA, small nuclear RNA, Ro associated Y-RNA, vault RNA and Y-RNA. We identified in total 1041 miRNAs in cells and EV subsets. Hierarchical clustering showed enrichment of specific miRNAs in exosomes, including hsa-miR-214-3p, hsa-miR-199a-3p and hsa-miR-155-5p, all being associated with melanoma progression. Comparison of exosomal miRNAs with miRNAs in clinical melanoma samples indicate that multiple miRNAs in exosomes also are expressed specifically in melanoma tissues, but not in benign naevi. This study shows for the first time the presence of distinct small RNAs in subsets of EVs released by melanoma cells, with significant similarities to clinical melanoma tissue, and provides unique insights into the contribution of EV associated extracellular RNA in cancer.

Quantification and quality control of a small non-coding RNA preparation.

Recent advances in high-throughput sequencing have shed some new light on the diversity of small non-coding RNA (sncRNA) classes and their crucial role in gene regulation and diseases. RNA quantification and control of RNA integrity are two key steps in sncRNA profiling. In this chapter, we will describe different gold standard methods used to achieve both purposes before the use of the RNAs in downstream applications.