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

Scalable Approach to Evaluate Plant microRNA Trimming and Tailing from Small RNA-Seq Data

MicroRNAs are small regulatory RNAs of 20-24 nt, which guide the RNA-induced silencing complex to silence several genes post-transcriptionally. Plant miRNA biogenesis involves many steps, including their 2'-O-methylation at their 3' end, which protects them from degradation. In addition, there are two other types of modifications involved in miRNA turnover: trimming and tailing. This method describes a bioinformatics analysis procedure to evaluate miRNA trimming and tailing from sRNA-Seq data. The pipeline includes the steps required to download the raw data from public repositories and important considerations to analyze a large number of samples. It starts from the raw sequencing reads and involves 3' adaptor removal, quality filtering, alignment to a masked reference genome to discard unwanted reads, and the assessment of the degree of trimming and tailing for each miRNA. Finally, an index for these modifications is calculated, and the results are evaluated graphically and statistically. In conclusion, this scalable pipeline allows researchers to begin with raw data from various sRNA-seq studies and progress to meaningful results and visual representations.

FindAdapt: A python package for fast and accurate adapter detection in small RNA sequencing

Adapter trimming is an essential step for analyzing small RNA sequencing data, where reads are generally longer than target RNAs ranging from 18 to 30 bp. Most adapter trimming tools require adapter information as input. However, adapter information is hard to access, specified incorrectly, or not provided with publicly available datasets, hampering their reproducibility and reusability. Manual identification of adapter patterns from raw reads is labor-intensive and error-prone. Moreover, the use of randomized adapters to reduce ligation biases during library preparation makes adapter detection even more challenging. Here, we present FindAdapt, a Python package for fast and accurate detection of adapter patterns without relying on prior information. We demonstrated that FindAdapt was far superior to existing approaches. It identified adapters successfully in 180 simulation datasets with diverse read structures and 3,184 real datasets covering a variety of commercial and customized small RNA library preparation kits. FindAdapt is stand-alone software that can be easily integrated into small RNA sequencing analysis pipelines.

PhasiHunter: a robust phased siRNA regulatory cascade mining tool based on multiple reference sequences

SUMMARY

In recent years, phased small interfering RNA has been found to play crucial roles in many biological processes in plants. However, efficiently predicting phasiRNA regulatory cascades with computational methods is still challenging. Here, we introduce PhasiHunter, a phasiRNA regulatory network prediction tool that has several distinctive features compared to existing tools: (i) PhasiHunter employs two major phasiRNA prediction algorithms, namely phase score and hypergeometric distribution-based methods, to ensure the integrity and accuracy of prediction; (ii) PhasiHunter can identify phasiRNAs and their regulatory networks based on multiple reference sequences and the predicted results can be automatically integrated; (iii) PhasiHunter can efficiently identify the phasiRNAs generated through alternative splicing events; and (iv) the excellent data structure and parallel computing architecture allow PhasiHunter to predict phasiRNAs and their regulatory pathways with high efficiency.

AVAILABILITY AND IMPLEMENTATION

PhasiHunter is an open-source tool that is available at https://github.com/HuangLab-CBI/PhasiHunter.

The miRNA-mRNA Regulatory Modules of Pinus massoniana Lamb. in Response to Drought Stress

Masson pine (Pinus massoniana Lamb.) is a major fast-growing woody tree species and pioneer species for afforestation in barren sites in southern China. However, the regulatory mechanism of gene expression in P. massoniana under drought remains unclear. To uncover candidate microRNAs, their expression profiles, and microRNA-mRNA interactions, small RNA-seq was used to investigate the transcriptome from seedling roots under drought and rewatering in P. massoniana. A total of 421 plant microRNAs were identified. Pairwise differential expression analysis between treatment and control groups unveiled 134, 156, and 96 differential expressed microRNAs at three stages. These constitute 248 unique microRNAs, which were subsequently categorized into six clusters based on their expression profiles. Degradome sequencing revealed that these 248 differentially expressed microRNAs targeted 2069 genes. Gene Ontology enrichment analysis suggested that these target genes were related to translational and posttranslational regulation, cell wall modification, and reactive oxygen species scavenging. miRNAs such as miR482, miR398, miR11571, miR396, miR166, miRN88, and miRN74, along with their target genes annotated as F-box/kelch-repeat protein, 60S ribosomal protein, copper-zinc superoxide dismutase, luminal-binding protein, S-adenosylmethionine synthase, and Early Responsive to Dehydration Stress may play critical roles in drought response. This study provides insights into microRNA responsive to drought and rewatering in Masson pine and advances the understanding of drought tolerance mechanisms in Pinus.

Multiomics of Tissue Extracellular Vesicles Identifies Unique Modulators of Atherosclerosis and Calcific Aortic Valve Stenosis

BACKGROUND

Fewer than 50% of patients who develop aortic valve calcification have concomitant atherosclerosis, implying differential pathogenesis. Although circulating extracellular vesicles (EVs) act as biomarkers of cardiovascular diseases, tissue-entrapped EVs are associated with early mineralization, but their cargoes, functions, and contributions to disease remain unknown.

METHODS

Disease stage-specific proteomics was performed on human carotid endarterectomy specimens (n=16) and stenotic aortic valves (n=18). Tissue EVs were isolated from human carotid arteries (normal, n=6; diseased, n=4) and aortic valves (normal, n=6; diseased, n=4) by enzymatic digestion, (ultra)centrifugation, and a 15-fraction density gradient validated by proteomics, CD63-immunogold electron microscopy, and nanoparticle tracking analysis. Vesiculomics, comprising vesicular proteomics and small RNA-sequencing, was conducted on tissue EVs. TargetScan identified microRNA targets. Pathway network analyses prioritized genes for validation in primary human carotid artery smooth muscle cells and aortic valvular interstitial cells.

RESULTS

Disease progression drove significant convergence (P<0.0001) of carotid artery plaque and calcified aortic valve proteomes (2318 proteins). Each tissue also retained a unique subset of differentially enriched proteins (381 in plaques; 226 in valves; q<0.05). Vesicular gene ontology terms increased 2.9-fold (P<0.0001) among proteins modulated by disease in both tissues. Proteomics identified 22 EV markers in tissue digest fractions. Networks of proteins and microRNA targets changed by disease progression in both artery and valve EVs revealed shared involvement in intracellular signaling and cell cycle regulation. Vesiculomics identified 773 proteins and 80 microRNAs differentially enriched by disease exclusively in artery or valve EVs (q<0.05); multiomics integration found tissue-specific EV cargoes associated with procalcific Notch and Wnt signaling in carotid arteries and aortic valves, respectively. Knockdown of tissue-specific EV-derived molecules FGFR2, PPP2CA, and ADAM17 in human carotid artery smooth muscle cells and WNT5A, APP, and APC in human aortic valvular interstitial cells significantly modulated calcification.

CONCLUSIONS

The first comparative proteomics study of human carotid artery plaques and calcified aortic valves identifies unique drivers of atherosclerosis versus aortic valve stenosis and implicates EVs in advanced cardiovascular calcification. We delineate a vesiculomics strategy to isolate, purify, and study protein and RNA cargoes from EVs entrapped in fibrocalcific tissues. Integration of vesicular proteomics and transcriptomics by network approaches revealed novel roles for tissue EVs in modulating cardiovascular disease.

Bioinformatics Analysis of miRNA Sequencing Data

The bioinformatics analysis of miRNA is a complicated task with multiple operations and steps involved from processing of raw sequence data to finally identifying accurate microRNAs associated with the phenotypes of interest. A complete analysis process demands a high level of technical expertise in programming, statistics, and data management. The goal of this chapter is to reduce the burden of technical expertise and provide readers the opportunity to understand crucial steps involved in the analysis of miRNA sequencing data.In this chapter, we describe methods and tools employed in processing of miRNA reads, quality control, alignment, quantification, and differential expression analysis.

Virome and nrEVEome diversity of Aedes albopictus mosquitoes from La Reunion Island and China

Background

Aedes albopictus is a public health threat for its worldwide spread and ability to transmit arboviruses. Understanding mechanisms of mosquito immunity can provide new tools to control arbovirus spread. The genomes of Aedes mosquitoes contain hundreds of nonretroviral endogenous viral elements (nrEVEs), which are enriched in piRNA clusters and produce piRNAs, with the potential to target cognate viruses. Recently, one nrEVE was shown to limit cognate viral infection through nrEVE-derived piRNAs. These findings suggest that nrEVEs constitute an archive of past viral infection and that the landscape of viral integrations may be variable across populations depending on their viral exposure.

Methods

We used bioinformatics and molecular approaches to identify known and novel (i.e. absent in the reference genome) viral integrations in the genome of wild collected Aedes albopictus mosquitoes and characterize their virome.

Results

We showed that the landscape of viral integrations is dynamic with seven novel viral integrations being characterized, but does not correlate with the virome, which includes both viral species known and unknown to infect mosquitoes. However, the small RNA coverage profile of nrEVEs and the viral genomic contigs we identified confirmed an interaction among these elements and the piRNA and siRNA pathways in mosquitoes.

Conclusions

Mosquitoes nrEVEs have been recently described as a new form of heritable, sequence-specific mechanism of antiviral immunity. Our results contribute to understanding the dynamic distribution of nrEVEs in the genomes of wild Ae. albopictus and their interaction with mosquito viruses.

MicroRNAs and the Diagnosis of Childhood Acute Lymphoblastic Leukemia: Systematic Review, Meta-Analysis and Re-Analysis with Novel Small RNA-Seq Tools

Simple Summary

MicroRNAs (miRNAs) have been under the spotlight for the last three decades. These non-coding RNAs seem to be dynamic regulators of mRNA stability and translation, in addition to interfering with transcription. Circulating miRNAs play a critical role in cell-to-cell interplay; therefore, they can serve as disease biomarkers. Meta-analysis of published data revealed that the CC genotype of rs4938723 in pri-miR-34b/c and the TT genotype of rs543412 in miR-100 confer protection against acute lymphoblastic leukemia (ALL) in children. Reanalysis of small RNA-seq data with novel tools identified significantly overexpressed members of the miR-128, miR-181, miR-130 and miR-17 families and significantly lower expression of miR-30, miR-24-2 and miR143~145 clusters, miR-574 and miR-618 in pediatric T-ALL cases compared with controls. Inconsistencies in methodology and study designs in most published material preclude reproducibility, and further cohort studies need to be conducted in order to empower novel tools, such as ALLSorts and RNAseqCNV.

Abstract

MicroRNAs (miRNAs) have been implicated in childhood acute lymphoblastic leukemia (ALL) pathogenesis. We performed a systematic review and meta-analysis of miRNA single-nucleotide polymorphisms (SNPs) in childhood ALL compared with healthy children, which revealed (i) that the CC genotype of rs4938723 in pri-miR-34b/c and the TT genotype of rs543412 in miR-100 confer protection against ALL occurrence in children; (ii) no significant association between rs2910164 genotypes in miR-146a and childhood ALL; and (iii) SNPs in DROSHA, miR-449b, miR-938, miR-3117 and miR-3689d-2 genes seem to be associated with susceptibility to B-ALL in childhood. A review of published literature on differential expression of miRNAs in children with ALL compared with controls revealed a significant upregulation of the miR-128 family, miR-130b, miR-155, miR-181 family, miR-210, miR-222, miR-363 and miR-708, along with significant downregulation of miR-143 and miR-148a, seem to have a definite role in childhood ALL development. MicroRNA signatures among childhood ALL subtypes, along with differential miRNA expression patterns between B-ALL and T-ALL cases, were scrutinized. With respect to T-ALL pediatric cases, we reanalyzed RNA-seq datasets with a robust and sensitive pipeline and confirmed the significant differential expression of hsa-miR-16-5p, hsa-miR-19b-3p, hsa-miR-92a-2-5p, hsa-miR-128-3p (ranked first), hsa-miR-130b-3p and -5p, hsa-miR-181a-5p, -2-3p and -3p, hsa-miR-181b-5p and -3p, hsa-miR-145-5p and hsa-miR-574-3p, as described in the literature, along with novel identified miRNAs.

Integrated Degradome and Srna Sequencing Revealed miRNA-mRNA Regulatory Networks between the Phloem and Developing Xylem of Poplar

Lignin and cellulose are the most abundant natural organic polymers in nature. MiRNAs are a class of regulatory RNAs discovered in mammals, plants, viruses, and bacteria. Studies have shown that miRNAs play a role in lignin and cellulose biosynthesis by targeting key enzymes. However, the specific miRNAs functioning in the phloem and developing xylem of Populus deltoides are still unknown. In this study, a total of 134 miRNAs were identified via high-throughput small RNA sequencing, including 132 known and two novel miRNAs, six of which were only expressed in the phloem. A total of 58 differentially expressed miRNAs (DEmiRNAs) were identified between the developing xylem and the phloem. Among these miRNAs, 21 were significantly upregulated in the developing xylem in contrast to the phloem and 37 were significantly downregulated. A total of 2431 target genes of 134 miRNAs were obtained via high-throughput degradome sequencing. Most target genes of these miRNAs were transcription factors, including AP2, ARF, bHLH, bZIP, GRAS, GRF, MYB, NAC, TCP, and WRKY genes. Furthermore, 13 and nine miRNAs were involved in lignin and cellulose biosynthesis, respectively, and we validated the miRNAs via qRT-PCR. Our study explores these miRNAs and their regulatory networks in the phloem and developing xylem of P.deltoides and provides new insight into wood formation.

Uncovering miRNA-mRNA Regulatory Modules in Developing Xylem of Pinus massoniana via Small RNA and Degradome Sequencing

Xylem is required for the growth and development of higher plants to provide water and mineral elements. The thickening of the xylem secondary cell wall (SCW) not only improves plant survival, but also provides raw materials for industrial production. Numerous studies have found that transcription factors and non-coding RNAs regulate the process of SCW thickening. Pinus massoniana is an important woody tree species in China and is widely used to produce materials for construction, furniture, and packaging. However, the target genes of microRNAs (miRNAs) in the developing xylem of P. massoniana are not known. In this study, a total of 25 conserved miRNAs and 173 novel miRNAs were identified via small RNA sequencing, and 58 differentially expressed miRNAs were identified between the developing xylem (PM_X) and protoplasts isolated from the developing xylem (PM_XP); 26 of these miRNAs were significantly up-regulated in PM_XP compared with PM_X, and 32 were significantly down-regulated. A total of 153 target genes of 20 conserved miRNAs and 712 target genes of 113 novel miRNAs were verified by degradome sequencing. There may be conserved miRNA-mRNA modules (miRNA-MYB, miRNA-ARF, and miRNA-LAC) involved in softwood and hardwood formation. The results of qRT-PCR-based parallel validation were in relatively high agreement. This study explored the potential regulatory network of miRNAs in the developing xylem of P. massoniana and provides new insights into wood formation in coniferous species.

DIANA-miTED: a microRNA tissue expression database

microRNAs (miRNAs) are short (∼23nt) single-stranded non-coding RNAs that act as potent post-transcriptional gene expression regulators. Information about miRNA expression and distribution across cell types and tissues is crucial to the understanding of their function and for their translational use as biomarkers or therapeutic targets. DIANA-miTED is the most comprehensive and systematic collection of miRNA expression values derived from the analysis of 15 183 raw human small RNA-Seq (sRNA-Seq) datasets from the Sequence Read Archive (SRA) and The Cancer Genome Atlas (TCGA). Metadata quality maximizes the utility of expression atlases, therefore we manually curated SRA and TCGA-derived information to deliver a comprehensive and standardized set, incorporating in total 199 tissues, 82 anatomical sublocations, 267 cell lines and 261 diseases. miTED offers rich instant visualizations of the expression and sample distributions of requested data across variables, as well as study-wide diagrams and graphs enabling efficient content exploration. Queries also generate links towards state-of-the-art miRNA functional resources, deeming miTED an ideal starting point for expression retrieval, exploration, comparison, and downstream analysis, without requiring bioinformatics support or expertise. DIANA-miTED is freely available at http://www.microrna.gr/mited.

DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

MirCure: a tool for quality control, filter and curation of microRNAs of animals and plants

MOTIVATION

microRNAs (miRNAs) are essential components of gene expression regulation at the post-transcriptional level. miRNAs have a well-defined molecular structure and this has facilitated the development of computational and high-throughput approaches to predict miRNAs genes. However, due to their short size, miRNAs have often been incorrectly annotated in both plants and animals. Consequently, published miRNA annotations and miRNA databases are enriched for false miRNAs, jeopardizing their utility as molecular information resources. To address this problem, we developed MirCure, a new software for quality control, filtering and curation of miRNA candidates. MirCure is an easy-to-use tool with a graphical interface that allows both scoring of miRNA reliability and browsing of supporting evidence by manual curators.

RESULTS

Given a list of miRNA candidates, MirCure evaluates a number of miRNA-specific features based on gene expression, biogenesis and conservation data, and generates a score that can be used to discard poorly supported miRNA annotations. MirCure can also curate and adjust the annotation of the 5p and 3p arms based on user-provided small RNA-seq data. We evaluated MirCure on a set of manually curated animal and plant miRNAs and demonstrated great accuracy. Moreover, we show that MirCure can be used to revisit previous bona fide miRNAs annotations to improve miRNA databases.

AVAILABILITY AND IMPLEMENTATION

The MirCure software and all the additional scripts used in this project are publicly available at https://github.com/ConesaLab/MirCure. A Docker image of MirCure is available at https://hub.docker.com/r/conesalab/mircure.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Date palm virus A: first plant virus found in date palm trees

In this work, a novel ssRNA (+) viral genomic sequence with gene organization typical of members of the subfamily Quinvirinae (family Betaflexiviridae) was identified using high- throughput sequencing data of date palm obtained from the Sequence Read Archive database. The viral genome sequence consists of 7860 nucleotides and contains five ORFs encoding for the replication protein (Rep), triple gene block proteins 1, 2, 3 (TGB 1, 2, and 3), and coat protein (CP). Phylogenetic analysis based on the Rep and the CP amino acid sequences showed the closest relationship to garlic yellow mosaic-associated virus (GYMaV). Based on the demarcation criteria of the family Betaflexiviridae, this new virus, provisionally named date palm virus A (DPVA), could constitute a member of a novel genus. However, considering that DPVA and GYMaV share the same genomic organization and that they cluster together on the Rep phylogenetic analysis, they could also constitute a novel genus together, highlighting the necessity of a revision of the taxonomic criteria of the family Betaflexiviridae.

Are Antisense Proteins in Prokaryotes Functional?

Many prokaryotic RNAs are transcribed from loci outside of annotated protein coding genes. Across bacterial species hundreds of short open reading frames antisense to annotated genes show evidence of both transcription and translation, for instance in ribosome profiling data. Determining the functional fraction of these protein products awaits further research, including insights from studies of molecular interactions and detailed evolutionary analysis. There are multiple lines of evidence, however, that many of these newly discovered proteins are of use to the organism. Condition-specific phenotypes have been characterized for a few. These proteins should be added to genome annotations, and the methods for predicting them standardized. Evolutionary analysis of these typically young sequences also may provide important insights into gene evolution. This research should be prioritized for its exciting potential to uncover large numbers of novel proteins with extremely diverse potential practical uses, including applications in synthetic biology and responding to pathogens.

High-Throughput Identification of Adapters in Single-Read Sequencing Data

Sequencing datasets available in public repositories are already high in number, and their growth is exponential. Raw sequencing data files constitute a substantial portion of these data, and they need to be pre-processed for any downstream analyses. The removal of adapter sequences is the first essential step. Tools available for the automated detection of adapters in single-read sequencing protocol datasets have certain limitations. To explore these datasets, one needs to retrieve the information on adapter sequences from the methods sections of appropriate research articles. This can be time-consuming in metadata analyses. Moreover, not all research articles provide the information on adapter sequences. We have developed adapt_find, a tool that automates the process of adapter sequences identification in raw single-read sequencing datasets. We have verified adapt_find through testing a number of publicly available datasets. adapt_find secures a robust, reliable and high-throughput process across different sequencing technologies and various adapter designs. It does not need prior knowledge of the adapter sequences. We also produced associated tools: random_mer, for the detection of random N bases either on one or both termini of the reads, and fastqc_parser, for consolidating the results from FASTQC outputs. Together, this is a valuable tool set for metadata analyses on multiple sequencing datasets.

A Novel pH-Regulated, Unusual 603 bp Overlapping Protein Coding Gene pop Is Encoded Antisense to ompA in Escherichia coli O157:H7 (EHEC)

Antisense transcription is well known in bacteria. However, translation of antisense RNAs is typically not considered, as the implied overlapping coding at a DNA locus is assumed to be highly improbable. Therefore, such overlapping genes are systematically excluded in prokaryotic genome annotation. Here we report an exceptional 603 bp long open reading frame completely embedded in antisense to the gene of the outer membrane protein ompA. An active σ70 promoter, transcription start site (TSS), Shine-Dalgarno motif and rho-independent terminator were experimentally validated, providing evidence that this open reading frame has all the structural features of a functional gene. Furthermore, ribosomal profiling revealed translation of the mRNA, the protein was detected in Western blots and a pH-dependent phenotype conferred by the protein was shown in competitive overexpression growth experiments of a translationally arrested mutant versus wild type. We designate this novel gene pop (pH-regulated overlapping protein-coding gene), thus adding another example to the growing list of overlapping, protein coding genes in bacteria.

An Online Database for Exploring Over 2,000 Arabidopsis Small RNA Libraries

Small RNAs (sRNAs) play a wide range of important roles in plants, from maintaining genome stability and enhancing disease resistance to regulating developmental processes. Over the past decade, next-generation sequencing technologies have allowed us to explore the sRNA populations with unprecedented depth and accuracy. The community has accumulated a tremendous amount of sRNA sequencing (sRNA-seq) data from various genotypes, tissues, and treatments. However, it has become increasingly challenging to access these "big data" and extract useful information, particularly for researchers lacking sophisticated bioinformatics tools and expensive computational resources. Here, we constructed an online website, Arabidopsis Small RNA Database (ASRD, http://ipf.sustech.edu.cn/pub/asrd), that allows users to easily explore the information from publicly available Arabidopsis (Arabidopsis thaliana) sRNA libraries. Our database contains ∼2.3 billion sRNA reads, representing ∼250 million unique sequences from 2,024 sRNA-seq libraries. We downloaded the raw data for all libraries and reprocessed them with a unified pipeline so that the normalized abundance of any particular sRNA or the sum of abundances of sRNAs from a genic or transposable element region can be compared across all libraries. We also integrated an online Integrative Genomics Viewer browser into our Web site for convenient visualization. ASRD is a free, web-accessible, and user-friendly database that supports the direct query of over 2,000 Arabidopsis sRNA-seq libraries. We believe this resource will help plant researchers take advantage of the vast next-generation sequencing datasets available in the public domain.

Accurate Adapter Information Is Crucial for Reproducibility and Reusability in Small RNA Seq Studies

A necessary pre-processing data analysis step is the removal of adapter sequences from the raw reads. While most adapter trimming tools require adapter sequence as an essential input, adapter information is often incomplete or missing. This can impact quantification of features, reproducibility of the study and might even lead to erroneous conclusions. Here, we provide examples to highlight the importance of specifying the adapter sequence by demonstrating the effect of using similar but different adapter sequences and identify additional potential sources of errors in the adapter trimming step. Finally, we propose solutions by which users can ensure their small RNA-seq data is fully annotated with adapter information.

Visualization of the small RNA transcriptome using seqclusterViz

The study of small RNAs provides us with a deeper understanding of the complexity of gene regulation within cells. Of the different types of small RNAs, the most important in mammals are miRNA, tRNA fragments and piRNAs. Using small RNA-seq analysis, we can study all small RNA types simultaneously, with the potential to detect novel small RNA types. We describe SeqclusterViz, an interactive HTML-javascript webpage for visualizing small noncoding RNAs (small RNAs) detected by Seqcluster. The SeqclusterViz tool allows users to visualize known and novel small RNA types in model or non-model organisms, and to select small RNA candidates for further validation. SeqclusterViz is divided into three panels: i) query-ready tables showing detected small RNA clusters and their genomic locations, ii) the expression profile over the precursor for all the samples together with RNA secondary structures, and iii) the mostly highly expressed sequences. Here, we show the capabilities of the visualization tool and its validation using human brain samples from patients with Parkinson’s disease.

Bioinformatic Analysis of Small RNA Sequencing Libraries

Bioinformatic analysis of small RNA sequencing libraries consists of transforming a series of small RNA sequencing experiment fastq files into a table containing small RNA sequences and their abundance. This is achieved by cleaning the reads, aligning the cleaned reads to a reference, and parsing the alignment results. In this protocol we present the most common option, and the rationale, for each of these steps.

unitas: the universal tool for annotation of small RNAs

BACKGROUND

Next 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.

RESULTS

Here 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.

CONCLUSIONS

unitas 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.