The limits of human microRNA annotation have been met.

Over the last few years, the number of microRNAs in the human genome has become a controversially debated issue. Several publications reported thousands of putative novel microRNAs not included in the curated microRNA gene database MirGeneDB and the repository miRBase. Recently, by using sequencing of ∼300 human tissues and cell lines, the human RNA atlas, an expanded inventory of human RNA annotations, was published, reporting thousands of putative microRNAs. We, the developers of established microRNA prediction tools and hosts of MirGeneDB, raise concerns about the frequently applied prediction and functional validation strategies, briefly discussing the drawbacks of false positive detections. By means of quantifying well-established biogenesis-derived features, we show that the reported novel microRNAs essentially represent false-positives and argue that the human microRNA complement, at about 550 microRNA genes, is already near complete. Output of available tools must be curated as false predictions will misguide scientists looking for biomarkers or therapeutic targets.

MirGeneDB 2.1: toward a complete sampling of all major animal phyla.

We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.

MicroRNA Expression Differences in Blood-Derived CD19+ B Cells of Methotrexate Treated Rheumatoid Arthritis Patients.

Rheumatoid arthritis (RA) is a complex disease with a wide range of underlying susceptibility factors. Recently, dysregulation of microRNAs (miRNAs) in RA have been reported in several immune cell types from blood. However, B cells have not been studied in detail yet. Given the autoimmune nature of RA with the presence of autoantibodies, CD19+ B cells are a key cell type in RA pathogenesis and alterations in CD19+ B cell subpopulations have been observed in patient blood. Therefore, we aimed to reveal the global miRNA repertoire and to analyze miRNA expression profile differences in homogenous RA patient phenotypes in blood-derived CD19+ B cells. Small RNA sequencing was performed on CD19+ B cells of newly diagnosed untreated RA patients (n=10), successfully methotrexate (MTX) treated RA patients in remission (MTX treated RA patients, n=18) and healthy controls (n=9). The majority of miRNAs was detected across all phenotypes. However, significant expression differences between MTX treated RA patients and controls were observed for 27 miRNAs, while no significant differences were seen between the newly diagnosed patients and controls. Several of the differentially expressed miRNAs were previously found to be dysregulated in RA including miR-223-3p, miR-486-3p and miR-23a-3p. MiRNA target enrichment analysis, using the differentially expressed miRNAs and miRNA-target interactions from miRTarBase as input, revealed enriched target genes known to play important roles in B cell activation, differentiation and B cell receptor signaling, such as STAT3, PRDM1 and PTEN. Interestingly, many of those genes showed a high degree of correlated expression in CD19+ B cells in contrast to other immune cell types. Our results suggest important regulatory functions of miRNAs in blood-derived CD19+ B cells of MTX treated RA patients and motivate for future studies investigating the interactive mechanisms between miRNA and gene targets, as well as the possible predictive power of miRNAs for RA treatment response.

An extension to: Systematic assessment of commercially available low-input miRNA library preparation kits.

High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits.

Systematic assessment of commercially available low-input miRNA library preparation kits.

High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.

Jasmine: a Java pipeline for isomiR characterization in miRNA-Seq Data.

MOTIVATION: The existence of complex subpopulations of miRNA isoforms, or isomiRs, is well established. While many tools exist for investigating isomiR populations, they differ in how they characterize an isomiR, making it difficult to compare results across different tools. Thus, there is a need for a more comprehensive and systematic standard for defining isomiRs. Such a standard would allow investigation of isomiR population structure in progressively more refined sub-populations, permitting the identification of more subtle changes between conditions and leading to an improved understanding of the processes that generate these differences. RESULTS: We developed Jasmine, a software tool that incorporates a hierarchal framework for characterizing isomiR populations. Jasmine is a Java application that can process raw read data in fastq/fasta format, or mapped reads in SAM format to produce a detailed characterization of isomiR populations. Thus, Jasmine can reveal structure not apparent in a standard miRNA-Seq analysis pipeline. AVAILABILITY: Jasmine is implemented in Java and R and freely available at bitbucket https://bitbucket.org/bipous/jasmine/src/master/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

miRBaseMiner, a tool for investigating miRBase content.

microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for experienced users, the size of the resource can make it difficult to explore annotation to determine features such as species coverage, the impact of specific characteristics and changes between successive releases. A further consideration is that each new miRBase release contains entries that have had limited review and which may subsequently be removed in a future release to ensure the quality of annotation. To aid the miRBase user, we developed a software tool, miRBaseMiner, for investigating miRBase annotation and generating custom annotation sets. We apply the tool to characterize each release from v9.2 to v22 to examine how annotation has changed across releases and highlight some of the annotation features that users should keep in mind when using for miRBase for data analysis. These include: (1) entries with identical or very similar sequences; (2) entries with multiple annotated genome locations; (3) hairpin precursor entries with extremely low-estimated minimum free energy; (4) entries possessing reverse complementary; (5) entries with 3' poly(A) ends. As each of these factors can impact the identification of dysregulated features and subsequent clinical or biological conclusions, miRBaseMiner is a valuable resource for any user using miRBase as a reference source.

miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3'UTR of their target genes. Computational methods play an important role in target prediction and assume that the miRNA "seed region" (nt 2 to 8) is required for functional targeting, but typically only identify ∼80% of known bindings. Recent studies have highlighted a role for the entire miRNA, suggesting that a more flexible methodology is needed. We present a novel approach for miRNA target prediction based on Deep Learning (DL) which, rather than incorporating any knowledge (such as seed regions), investigates the entire miRNA and 3'TR mRNA nucleotides to learn a uninhibited set of feature descriptors related to the targeting process. We collected more than 150,000 experimentally validated homo sapiens miRNA:gene targets and cross referenced them with different CLIP-Seq, CLASH and iPAR-CLIP datasets to obtain ∼20,000 validated miRNA:gene exact target sites. Using this data, we implemented and trained a deep neural network-composed of autoencoders and a feed-forward network-able to automatically learn features describing miRNA-mRNA interactions and assess functionality. Predictions were then refined using information such as site location or site accessibility energy. In a comparison using independent datasets, our DL approach consistently outperformed existing prediction methods, recognizing the seed region as a common feature in the targeting process, but also identifying the role of pairings outside this region. Thermodynamic analysis also suggests that site accessibility plays a role in targeting but that it cannot be used as a sole indicator for functionality. Data and source code available at: https://bitbucket.org/account/user/bipous/projects/MIRAW.

Found in translation: functions and evolution of a recently discovered alternative proteome.

A major goal in biology is to map entire proteomes to better understand the biology and evolution of cells. However, our current views of proteomes are conservative and biased against small proteins. Besides serendipitous discoveries of small proteins, it has been largely assumed that eukaryotic mature mRNAs contain a single ORF and that non-coding RNAs are not translated because their ORFs are too short to play a functional role. A flurry of recent studies brought to light an unexplored proteome that is mainly translated from short ORFs in non-coding regions and from alternative ORFs (AltORFs) in reference genes. The detection of these small proteins and the elucidation of their functions remain challenging and open a new dimension of eukaryotic proteomes, including the birth of novel genes and proteins.

Comparison of genotypes I and III in Japanese encephalitis virus reveals distinct differences in their genetic and host diversity.

UNLABELLED: Japanese encephalitis (JE) is an arthropod-borne disease associated with the majority of viral encephalitis cases in the Asia-Pacific region. The causative agent, Japanese encephalitis virus (JEV), has been phylogenetically divided into five genotypes. Recent surveillance data indicate that genotype I (GI) is gradually replacing genotype III (GIII) as the dominant genotype. To investigate the mechanism behind the genotype shift and the potential consequences in terms of vaccine efficacy, human cases, and virus dissemination, we collected (i) all full-length and partial JEV molecular sequences and (ii) associated genotype and host information comprising a data set of 873 sequences. We then examined differences between the two genotypes at the genetic and epidemiological level by investigating amino acid mutations, positive selection, and host range. We found that although GI is dominant, it has fewer sites predicted to be under positive selection, a narrower host range, and significantly fewer human isolates. For the E protein, the sites under positive selection define a haplotype set for each genotype that shows striking differences in their composition and diversity, with GIII showing significantly more variety than GI. Our results suggest that GI has displaced GIII by achieving a replication cycle that is more efficient but is also more restricted in its host range. IMPORTANCE: Japanese encephalitis is an arthropod-borne disease associated with the majority of viral encephalitis cases in the Asia-Pacific region. The causative agent, Japanese encephalitis virus (JEV), has been divided into five genotypes based on sequence similarity. Recent data indicate that genotype I (GI) is gradually replacing genotype III (GIII) as the dominant genotype. Understanding the reasons behind this shift and the potential consequences in terms of vaccine efficacy, human cases, and virus dissemination is important for controlling the spread of the virus and reducing human fatalities. We collected all available full-length and partial JEV molecular sequences and associated genotype and host information. We then examined differences between the two genotypes at the genetic and epidemiological levels by investigating amino acid mutations, positive selection, and host range. Our results suggest that GI has displaced GIII by achieving a replication cycle that is more efficient but more restricted in host range.

Comparison of complete genome sequences of dog rabies viruses isolated from China and Mexico reveals key amino acid changes that may be associated with virus replication and virulence.

Rabies is a global problem, but its impact and prevalence vary across different regions. In some areas, such as parts of Africa and Asia, the virus is prevalent in the domestic dog population, leading to epidemic waves and large numbers of human fatalities. In other regions, such as the Americas, the virus predominates in wildlife and bat populations, with sporadic spillover into domestic animals. In this work, we attempted to investigate whether these distinct environments led to selective pressures that result in measurable changes within the genome at the amino acid level. To this end, we collected and sequenced the full genome of two isolates from divergent environments. The first isolate (DRV-AH08) was from China, where the virus is present in the dog population and the country is experiencing a serious epidemic. The second isolate (DRV-Mexico) was taken from Mexico, where the virus is present in both wildlife and domestic dog populations, but at low levels as a consequence of an effective vaccination program. We then combined and compared these with other full genome sequences to identify distinct amino acid changes that might be associated with environment. Phylogenetic analysis identified strain DRV-AH08 as belonging to the China-I lineage, which has emerged to become the dominant lineage in the current epidemic. The Mexico strain was placed in the D11 Mexico lineage, associated with the West USA-Mexico border clade. Amino acid sequence analysis identified only 17 amino acid differences in the N, G and L proteins. These differences may be associated with virus replication and virulence-for example, the short incubation period observed in the current epidemic in China.

Genetic characterization and transmitted drug resistance of the HIV type 1 epidemic in men who have sex with men in Beijing, China.

A rapid increase in the number of HIV cases in the men who have sex with men (MSM) population has been observed in China; however, little information is available on the genetic characterization of HIV prevalent in this population. In this study, 95 HIV-1-seropositive drug-naive patients from the Beijing MSM population were enrolled. The genetic characterization and transmission of drug resistance of HIV-1 were examined based on full-length gag, pol, and partial env gene sequences. Three subtypes, including CRF01_AE (56.0%), B (30.8%), and CRF07_BC (12.6%), were identified. Close phylogenetic relationships were found among these strains with isolates from other populations in Beijing and MSM isolates from Hebei province, which suggested that the Beijing MSM population might act as a bridge for HIV transmission between MSM and other high-risk populations. Drug-resistant mutations were identified in 5.3% of sampled individuals. Our results provided detailed genetic data and would be helpful for understanding the transmitting pattern of HIV strains between MSM and other populations.