Small RNA Sequencing Datasets Research Articles

Viral and host small RNA transcriptome analysis of SARS-CoV-1 and SARS-CoV-2-infected human cells reveals novel viral short RNAs

RNA viruses have been shown to express various short RNAs, some of which have regulatory roles during replication, transcription, and translation of viral genomes. However, short viral RNAs generated from SARS-CoV-1 and SARS-CoV-2 genomic RNAs remained largely unexplored, possibly due limitations of the widely used library preparation methods for small RNA deep sequencing and corresponding data processing. By analyzing publicly available small RNA sequencing datasets, we observed that human Calu-3 cells infected by SARS-CoV-1 or SARS-CoV-2 accumulate multiple previously unreported short viral RNAs. In addition, we verified the presence of the five most abundant SARS-CoV-2 short viral RNAs in SARS-CoV-2-infected human lung adenocarcinoma cells by quantitative PCR. Interestingly, the copy number of the observed SARS-CoV-2 short viral RNAs dramatically exceeded the expression of previously reported viral microRNAs in the same cells. We hypothesize that the reported SARS-CoV-2 short viral RNAs could serve as biomarkers for early infection stages due to their high abundance. Furthermore, unlike SARS-CoV-1, the SARS-CoV-2 infection induced significant (Benjamini-Hochberg-corrected p-value <0.05) deregulation of Y-RNA, transfer RNA, vault RNA, as well as more than 300 endogenous short RNAs that aligned predominantly to human protein-coding and long noncoding RNA transcripts. In particular, more than 20-fold upregulation of reads derived from Y-RNA (and several transfer RNAs) have been documented in RNA-seq datasets from SARS-CoV-2 infected cells. Finally, a significant proportion of short RNAs derived from full-length viral genomes also aligned to various human genome (hg38) sequences, suggesting opportunities to investigate regulatory roles of short viral RNAs during infection. Further characterization of the small RNA landscape of both viral and host genomes is clearly warranted to improve our understanding of molecular events related to infection and to design more efficient strategies for therapeutic interventions as well as early diagnosis.

Stress Response in Entamoeba histolytica Is Associated with Robust Processing of tRNA to tRNA Halves.

tRNA-derived fragments have been reported in many different organisms and have diverse cellular roles, such as regulating gene expression, inhibiting protein translation, silencing transposable elements, and modulating cell proliferation. In particular, tRNA halves, a class of tRNA fragments produced by the cleavage of tRNAs in the anti-codon loop, have been widely reported to accumulate under stress and regulate translation in cells. Here, we report the presence of tRNA-derived fragments in Entamoeba, with tRNA halves being the most abundant. We further established that tRNA halves accumulate in the parasites upon different stress stimuli such as oxidative stress, heat shock, and serum starvation. We also observed differential expression of tRNA halves during developmental changes of trophozoite-to-cyst conversion, with various tRNA halves accumulating during early encystation. In contrast to other systems, the stress response does not appear to be mediated by a few specific tRNA halves, as multiple tRNAs appear to be processed during the various stresses. Furthermore, we identified some tRNA-derived fragments associated with Entamoeba Argonaute proteins, EhAgo2-2 and EhAgo2-3, which have a preference for different tRNA-derived fragment species. Finally, we show that tRNA halves are packaged inside extracellular vesicles secreted by amoebas. The ubiquitous presence of tRNA-derived fragments, their association with the Argonaute proteins, and the accumulation of tRNA halves during multiple different stresses, including encystation, suggest a nuanced level of gene expression regulation mediated by different tRNA-derived fragments in Entamoeba. IMPORTANCE In the present study, we report for the first time the presence of tRNA-derived fragments in Entamoeba. tRNA-derived fragments were identified by bioinformatics analyses of small-RNA sequencing data sets from the parasites and also confirmed experimentally. We found that tRNA halves accumulated in parasites exposed to environmental stress or during the developmental process of encystation. We also found that shorter tRNA-derived fragments are bound to Entamoeba Argonaute proteins, indicating that they may have a potential role in the Argonaute-mediated RNA-interference pathway, which mediates robust gene silencing in Entamoeba. We noticed that in response to heat shock, the protein translation levels were elevated in the parasites. This effect was reversed in the presence of an analog of leucine, which also reduced the levels of the tRNA halves in the stressed cells. Our results suggest that tRNA-derived fragments in Entamoeba have a possible role in regulating gene expression during environmental stress.

The sheep miRNAome: Characterization and distribution of miRNAs in 21 tissues

MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that regulate gene expression. In livestock species, miRNAs also show great potential as biomarkers for animal health and product quality. In sheep, few miRNAs have been described in comparison with other livestock species or model organisms. We uniformly analyzed 172 public ovine small RNA sequencing datasets from 21 different tissues in order to predict conserved and novel miRNA precursors and profile their expression patterns. In addition to the 106 annotated sheep miRNAs, 1047 previously unannotated miRNA precursor sequences were detected and 41 % of them were assigned an orthologue from other close species. Considering expression levels, a set of miRNAs with high sequence conservation were detected in all tissues, while 733 mature miRNAs were robustly expressed in at least one tissue. 270 miRNAs showed high tissue specificity index values. Brain, male reproductive tissues and PBMCs showed the most distinct expression patterns. Strikingly, over one hundred precursors from the ruminant specific family of mir-2284/mir-2285 miRNAs were found, which were enriched in immune related tissues. This work supports the known high conservation of many miRNAs, but also highlights the potential of clade-specific innovations in ruminant evolution.

A curated human cellular microRNAome based on 196 primary cell types.

BackgroundAn incomplete picture of the expression distribution of microRNAs (miRNAs) across human cell types has long hindered our understanding of this important regulatory class of RNA. With the continued increase in available public small RNA sequencing datasets, there is an opportunity to more fully understand the general distribution of miRNAs at the cell level.ResultsFrom the NCBI Sequence Read Archive, we obtained 6,054 human primary cell datasets and processed 4,184 of them through the miRge3.0 small RNA sequencing alignment software. This dataset was curated down, through shared miRNA expression patterns, to 2,077 samples from 196 unique cell types derived from 175 separate studies. Of 2,731 putative miRNAs listed in miRBase (v22.1), 2,452 (89.8%) were detected. Among reasonably expressed miRNAs, 108 were designated as cell specific/near specific, 59 as infrequent, 52 as frequent, 54 as near ubiquitous, and 50 as ubiquitous. The complexity of cellular microRNA expression estimates recapitulates tissue expression patterns and informs on the miRNA composition of plasma.ConclusionsThis study represents the most complete reference, to date, of miRNA expression patterns by primary cell type. The data are available through the human cellular microRNAome track at the UCSC Genome Browser (https://genome.ucsc.edu/cgi-bin/hgHubConnect) and an R/Bioconductor package (https://bioconductor.org/packages/microRNAome/).

RNA Sequencing Unveils Very Small RNAs With Potential Regulatory Functions in Bacteria.

RNA sequencing (RNA-seq) is the gold standard for the discovery of small non-coding RNAs. Following a long-standing approach, reads shorter than 16 nucleotides (nt) are removed from the small RNA sequencing libraries or datasets. The serendipitous discovery of an eukaryotic 12 nt-long RNA species capable of modulating the microRNA from which they derive prompted us to challenge this dogma and, by expanding the window of RNA sizes down to 8 nt, to confirm the existence of functional very small RNAs (vsRNAs <16 nt). Here we report the detailed profiling of vsRNAs in Escherichia coli, E. coli-derived outer membrane vesicles (OMVs) and five other bacterial strains (Pseudomonas aeruginosa PA7, P. aeruginosa PAO1, Salmonella enterica serovar Typhimurium 14028S, Legionella pneumophila JR32 Philadelphia-1 and Staphylococcus aureus HG001). vsRNAs of 8–15 nt in length [RNAs (8-15 nt)] were found to be more abundant than RNAs of 16–30 nt in length [RNAs (16–30 nt)]. vsRNA biotypes were distinct and varied within and across bacterial species and accounted for one third of reads identified in the 8–30 nt window. The tRNA-derived fragments (tRFs) have appeared as a major biotype among the vsRNAs, notably Ile-tRF and Ala-tRF, and were selectively loaded in OMVs. tRF-derived vsRNAs appear to be thermodynamically stable with at least 2 G-C basepairs and stem-loop structure. The analyzed tRF-derived vsRNAs are predicted to target several human host mRNAs with diverse functions. Bacterial vsRNAs and OMV-derived vsRNAs could be novel players likely modulating the intricate relationship between pathogens and their hosts.

Ancient viral integrations in marsupials: a potential antiviral defence.

Marsupial viruses are understudied compared to their eutherian mammal counterparts, although they may pose severe threats to vulnerable marsupial populations. Genomic viral integrations, termed ‘endogenous viral elements’ (EVEs), could protect the host from infection. It is widely known past viral infections and EVEs play an active role in antiviral defence in invertebrates and plants. This study aimed to characterise actively transcribed EVEs in Australian marsupial species, because they may play an integral role in cellular defence against viruses. This study screened publicly available RNA sequencing data sets (n = 35) and characterised 200 viral transcripts from thirteen Australian marsupial species. Of the 200 transcripts, 188 originated from either Bornaviridae, Filoviridae, or Parvoviridae EVEs. The other twelve transcripts were from putative active infections from members of the Herpesviridae and Anelloviridae, and Hepadnaviridae. EVE transcripts (n = 188) were mapped to marsupial genomes (where available, n = 5/13) to identify the genomic insertion sites. Of the 188 transcripts, 117 mapped to 39 EVEs within the koala, bare-nosed wombat, tammar wallaby, brushtail possum, and Tasmanian devil genomes. The remaining eight animals had no available genome (transcripts n = 71). Every marsupial has Bornaviridae, Filoviridae, and Parvoviridae EVEs, a trend widely observed in eutherian mammals. Whilst eutherian bornavirus EVEs are predominantly nucleoprotein-derived, marsupial bornavirus EVEs demonstrate a surprising replicase gene bias. We predicted these widely distributed EVEs were conserved within marsupials from ancient germline integrations, as many were over 65 million years old. One bornavirus replicase EVE, present in six marsupial genomes, was estimated to be 160 million years old, predating the American–Australian marsupial split. We considered transcription of these EVEs through small non-coding RNA as an ancient viral defence. Consistent with this, in koala small RNA sequence data sets, we detected Bornaviridae replicase and Filoviridae nucleoprotein produced small RNA. These were enriched in testis tissue, suggesting they could protect marsupials from vertically transmitted viral integrations.

MiREV: An Online Database and Tool to Uncover Potential Reference RNAs and Biomarkers in Small-RNA Sequencing Data Sets from Extracellular Vesicles Enriched Samples

Extracellular vesicles (EVs) are nano-sized, membrane-enclosed vesicles released by cells for intercellular communication. EVs are involved in pathological processes and miRNAs in EVs have gained interest as easily accessible biomolecules in liquid biopsies for diagnostic purposes. To validate potential miRNA biomarker, transcriptome analyses must be carried out to detect suitable reference miRNAs. miREV is a database with over 400 miRNA sequencing data sets and helps the researcher to find suitable reference miRNAs for their individual experimental setup. The researcher can put together a specific sample set in miREV, which is similar to his own experimental concept in order to find the most suitable references. This allows to run validation experiments without having to carry out a complex and costly transcriptome analysis priorly. Additional read count tables of each generated sample set are downloadable for further analysis. miREV is freely available at https://www.physio.wzw.tum.de/mirev/.

Computational meta-analysis of ribosomal RNA fragments: potential targets and interaction mechanisms.

The most abundant cellular RNA species, ribosomal RNA (rRNA), appears to be a source of massive amounts of non-randomly generated fragments. We found rRNA fragments (rRFs) in immunoprecipitated Argonaute (Ago-IP) complexes in human and mouse cells and in small RNA sequencing datasets. In human Ago1-IP, guanine-rich rRFs were preferentially cut in single-stranded regions of mature rRNAs between pyrimidines and adenosine, and non-randomly paired with cellular transcripts in crosslinked chimeras. Numerous identical rRFs were found in the cytoplasm and nucleus in mouse Ago2-IP. We report specific interaction motifs enriched in rRF-target pairs. Locations of such motifs on rRFs were compatible with the Ago structural features and patterns of the Ago-RNA crosslinking in both species. Strikingly, many of these motifs may bind to double-stranded regions on target RNAs, suggesting a potential pathway for regulating translation by unwinding mRNAs. Occurring on either end of rRFs and matching intronic, untranslated or coding regions in targets, such interaction sites extend the concept of microRNA seed regions. Targeting both borders of certain short introns, rRFs may be involved in their biogenesis or function, facilitated by Ago. Frequently dismissed as noise, rRFs are poised to greatly enrich the known functional spectrum of small RNA regulation.

Edible plant-derived exosomal microRNAs: Exploiting a cross-kingdom regulatory mechanism for targeting SARS-CoV-2

BackgroundThe current COVID-19 pandemic is caused by SARS-CoV-2 which belongs to coronaviridae family. Despite the global prevalence, there are currently no vaccines or drugs. Dietary plant derived exosome-like vesicles are known as edible nanoparticles (ENPs). ENPs are filled with microRNAs (miRNAs), in bioavailable form. Recently, cross-kingdom regulation of human transcripts by plant miRNAs have been demonstrated. However, ENP derived miRNAs targeting SARS-CoV-2 has not been described. Study designMature ENP-derived miRNA sequences were retrieved from small RNA sequencing datasets available in the literature. In silico target prediction was performed to identify miRNAs that could target SARS-CoV-2. ENPs were isolated from ginger and grapefruit plants and the expression of SARS-CoV-2 targeting miRNAs were confirmed by qRT-PCR. ResultsFrom a total of 260 ENP-derived miRNAs, we identified 22 miRNAs that could potentially target SARS-CoV-2 genome. 11 miRNAs showed absolute target specificity towards SARS-CoV-2 but not SARS-CoV. ENPs from soybean, ginger, hamimelon, grapefruit, tomato and pear possess multiple miRNAs targeting different regions within SARS-CoV-2. Interestingly, osa/cme miR-530b-5p specifically targeted the ribosomal slippage site between ORF1a and ORF1b. We validated the relative expression of six miRNAs (miR-5077, miR-6300, miR-156a, miR-169, miR-5059 and miR-166 m) in ginger and grapefruit ENPs by RT-PCR which showed differential enrichment of specific miRNAs in ginger and grapefruit ENPs. ConclusionSince administration of ENPs leads to their accumulation into lung tissues in vivo, ENP derived miRNAs targeting SARS-CoV-2 genome has the potential to be developed as an alternative therapy.

Abstract LB-249: PiRADL: An advanced deep learning tool for piRNA detection and its application in cancer biomarker identification

Abstract PIWI-interacting RNAs (piRNAs) are a large class of non-coding RNAs expressed in animal cells. Although many programs involved in identifying piRNAs from small RNA sequencing datasets, the boundaries are still hard to overcome. Here we developed a new tool called piRADL, by using deep learning to identify piRNA sequences. We transform the sequences into the 3D Numpy arrays(16X32X256), then the conventional neural network classifier was applied to train on the datasets from four different species (rat, human Caenorhabditis elegans, and Drosophila melanogaster). In the validation dataset, the piRADL shows better performance in comparison with other programs in accuracy, precision, sensitivity, and specificity. It is user-friendly, the user only needs to submit the sequences to the software. Based on this tool, we have found some interesting PiRNA prognosis biomarkers to predict colorectal, lung and breast cancer patient survival. Citation Format: Shaoqiu Chen, Youping Deng. PiRADL: An advanced deep learning tool for piRNA detection and its application in cancer biomarker identification [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-249.

PAREameters: a tool for computational inference of plant miRNA-mRNA targeting rules using small RNA and degradome sequencing data.

MicroRNAs (miRNAs) are short, non-coding RNAs that modulate the translation-rate of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to sequence-specific targets. In plants, this typically results in cleavage and subsequent degradation of the mRNA. Degradome sequencing is a high-throughput technique developed to capture cleaved mRNA fragments and thus can be used to support miRNA target prediction. The current criteria used for miRNA target prediction were inferred on a limited number of experimentally validated A. thaliana interactions and were adapted to fit these specific interactions; thus, these fixed criteria may not be optimal across all datasets (organisms, tissues or treatments). We present a new tool, PAREameters, for inferring targeting criteria from small RNA and degradome sequencing datasets. We evaluate its performance using a more extensive set of experimentally validated interactions in multiple A. thaliana datasets. We also perform comprehensive analyses to highlight and quantify the differences between subsets of miRNA–mRNA interactions in model and non-model organisms. Our results show increased sensitivity in A. thaliana when using the PAREameters inferred criteria and that using data-driven criteria enables the identification of additional interactions that further our understanding of the RNA silencing pathway in both model and non-model organisms.

Expanding the Transcriptome of Head and Neck Squamous Cell Carcinoma Through Novel MicroRNA Discovery.

Head and neck squamous cell carcinoma (HNSCC) has a poor survival rate mainly due to late stage diagnosis and recurrence. Despite genomic efforts to identify driver mutations and changes in protein-coding gene expression, developing effective diagnostic and prognostic biomarkers remains a priority to guide disease management and improve patient outcome. Recent reports of previously-unannotated microRNAs (miRNAs) from multiple somatic tissues have raised the possibility of HNSCC-specific miRNAs. In this study, we applied a customized in-silico analysis pipeline to identify novel miRNAs from raw small-RNA sequencing datasets from public repositories. We discovered 146 previously-unannotated sequences expressed in head and neck samples that share structural properties highly characteristic of miRNAs. The combined expression of the novel miRNAs revealed tissue and context-specific patterns. Furthermore, comparison of tumor with non-malignant tissue samples (n = 43 pairs) revealed 135 of these miRNAs as differentially expressed, most of which were overexpressed or exclusively found in tumor samples. Additionally, a subset of novel miRNAs was significantly associated with HPV infection status and patient outcome. A prognostic-model combining novel and known miRNA was developed (multivariate Cox regression analysis) leading to an improved death and relapse risk stratification (log rank p < 1e-7). The presence of these miRNAs was corroborated both in an independent dataset and by RT-qPCR analysis, supporting their potential involvement in HNSCC. In this study, we report the discovery of 146 novel miRNAs in head and neck tissues and demonstrate their potential biological significance and clinical relevance to head and neck cancer, providing a new resource for the study of HNSCC.

MiRWoods: Enhanced precursor detection and stacked random forests for the sensitive detection of microRNAs.

MicroRNAs are conserved, endogenous small RNAs with critical post-transcriptional regulatory functions throughout eukaryota, including prominent roles in development and disease. Despite much effort, microRNA annotations still contain errors and are incomplete due especially to challenges related to identifying valid miRs that have small numbers of reads, to properly locating hairpin precursors and to balancing precision and recall. Here, we present miRWoods, which solves these challenges using a duplex-focused precursor detection method and stacked random forests with specialized layers to detect mature and precursor microRNAs, and has been tuned to optimize the harmonic mean of precision and recall. We trained and tuned our discovery pipeline on data sets from the well-annotated human genome, and evaluated its performance on data from mouse. Compared to existing approaches, miRWoods better identifies precursor spans, and can balance sensitivity and specificity for an overall greater prediction accuracy, recalling an average of 10% more annotated microRNAs, and correctly predicts substantially more microRNAs with only one read. We apply this method to the under-annotated genomes of Felis catus (domestic cat) and Bos taurus (cow). We identified hundreds of novel microRNAs in small RNA sequencing data sets from muscle and skin from cat, from 10 tissues from cow and also from human and mouse cells. Our novel predictions include a microRNA in an intron of tyrosine kinase 2 (TYK2) that is present in both cat and cow, as well as a family of mirtrons with two instances in the human genome. Our predictions support a more expanded miR-2284 family in the bovine genome, a larger mir-548 family in the human genome, and a larger let-7 family in the feline genome.

Previously undescribed thyroid-specific miRNA sequences in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, wherein diagnostic limitations and lack of accurate prognostic factors are important clinical challenges. In this study, we report the discovery of 234 novel miRNAs in non-neoplastic thyroid and PTC samples, obtained from publicly available small RNA sequencing datasets (TCGA and GEO). These sequences were observed to display similar molecular features compared to currently annotated miRNAs. These potentially novel miRNAs presented tissue-specificity and largely decreased expression in PTC compared to non-neoplastic samples. We showed that the disrupted novel miRNAs have diagnostic and prognostic potential, and were associated with BRAF mutation, a frequent alteration related to more aggressive PTC. In conclusion, our results expand the miRNA repertoire in thyroid tissues and highlight the potential biological role and clinical utility of previously unannotated miRNAs.

An estimate of the total number of true human miRNAs.

While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

Small RNA expression from viruses, bacteria and human miRNAs in colon cancer tissue and its association with microsatellite instability and tumor location

BackgroundMicroRNAs (miRNA) and other small RNAs are frequently dysregulated in cancer and are promising biomarkers for colon cancer. Here we profile human, virus and bacteria small RNAs in normal and tumor tissue from early stage colon cancer and correlate the expression with clinical parameters.MethodsSmall RNAs from colon cancer tissue and adjacent normal mucosa of 48 patients were sequenced using Illumina high-throughput sequencing. Clinical parameters were correlated with the small RNA expression data using linear models. We performed a meta-analysis by comparing publicly available small RNA sequencing datasets with our original sequencing data to confirm the main findings.ResultsWe identified 331 differentially expressed miRNAs between tumor and normal samples. We found that the major changes in miRNA expression between left and right colon are due to miRNAs located within the Hox-developmental genes, including miR-10b, miR-196b and miR-615. Further, we identified new miRNAs associated with microsatellite instability (MSI), including miR-335, miR-26 and miR-625. We performed a meta-analysis on all publicly available miRNA-seq datasets and identified 117 common miRNAs that were differentially expressed between tumor and normal tissue. The miRNAs miR-135b and miR-31 were the most significant upregulated miRNA in tumor across all datasets. The miRNA miR-133a was the most strongly downregulated miRNA in our dataset and also showed consistent downregulation in the other datasets. The miRNAs associated with MSI and tumor location in our data showed similar changes in the other datasets. Finally, we show that small RNAs from Epstein-Barr virus and Fusobacterium nucleatum are differentially expressed between tumor and normal adjacent tissue.ConclusionsSmall RNA profiling in colon cancer tissue revealed novel RNAs associated with MSI and tumor location. We show that Fusobacterium nucleatum are detectable at the RNA-level in colon tissue, and that both Fusobacterium nucleatum and Epstein-Barr virus separate tumor and normal tissue.

Unitas: the universal tool for annotation of small RNAs

BackgroundNext generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.ResultsHere we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that map to publicly available ncRNA databases.Conclusionsunitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.

Plant miRNAs found in human circulating system provide evidences of cross kingdom RNAi

BackgroundEmerging evidence indicates that plant miRNAs can present within human circulating system through dietary intake and regulate human gene expression. Hence we deduced that comestible plants miRNAs can be identified in the public available small RNA sequencing data sets.ResultsIn this study, we identified abundant plant miRNAs sequences from 410 human plasma small RNA sequencing data sets. One particular plant miRNA miR2910, conserved in fruits and vegetables, was found to present in high relative amount in the plasma samples. This miRNA, with same 6mer and 7mer-A1 target seed sequences as hsa-miR-4259 and hsa-miR-4715-5p, was predicted to target human JAK-STAT signaling pathway gene SPRY4 and transcription regulation genes.ConclusionsThrough analysis of public available plasma small RNA sequencing data, we found the supporting evidence for the plant miRNAs cross kingdom RNAi within human circulating system.

YM500v3: a database for small RNA sequencing in human cancer research.

We previously presented the YM500 database, which contains >8000 small RNA sequencing (smRNA-seq) data sets and integrated analysis results for various cancer miRNome studies. In the updated YM500v3 database (http://ngs.ym.edu.tw/ym500/) presented herein, we not only focus on miRNAs but also on other functional small non-coding RNAs (sncRNAs), such as PIWI-interacting RNAs (piRNAs), tRNA-derived fragments (tRFs), small nuclear RNAs (snRNAs) and small nucleolar RNAs (snoRNAs). There is growing knowledge of the role of sncRNAs in gene regulation and tumorigenesis. We have also incorporated >10 000 cancer-related RNA-seq and >3000 more smRNA-seq data sets into the YM500v3 database. Furthermore, there are two main new sections, ‘Survival' and ‘Cancer', in this updated version. The ‘Survival’ section provides the survival analysis results in all cancer types or in a user-defined group of samples for a specific sncRNA. The ‘Cancer’ section provides the results of differential expression analyses, miRNA–gene interactions and cancer miRNA-related pathways. In the ‘Expression’ section, sncRNA expression profiles across cancer and sample types are newly provided. Cancer-related sncRNAs hold potential for both biotech applications and basic research.

DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data

With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were “ready-to-map” small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.