CPSS 2.0: a computational platform update for the analysis of small RNA sequencing data

Technical considerations and review of urinary microRNAs as biomarkers for chronic kidney disease in dogs and cats

MicroRNAs (miRNAs or miRs) are small, non-coding RNAs that play a crucial role in gene regulation, making them potential biomarkers for various diseases. In the field of veterinary medicine, there is a growing interest in exploring the diagnostic and therapeutic potential of miRNAs in kidney diseases affecting dogs and cats. This review focuses on the use of urinary miRNAs as biomarkers for chronic kidney disease (CKD) in these companion animals. We introduce miRNAs, their biogenesis, and their presence in biofluids, particularly within exosomes, and discuss studies investigating miRNAs in kidney tissue and urine. We acknowledge the challenges associated with miRNA studies, including preanalytical factors such as biological variation, sample collection/processing, storage conditions, and experimental design. We highlight the importance of technical considerations, such as sample pooling, sequencing depth, multiplexing, and the various steps of the miRNA experimental workflow. Furthermore, we discuss RNA isolation methods, small RNA sequencing data analysis, and the use of quantitative reverse transcription PCR (qRT-PCR) and droplet digital PCR for verification. We emphasize the importance of internal controls, spike-ins, and normalization methods to minimize technical variation and ensure reliable results in qRT-PCR analysis. This review concludes that while urinary miRNAs hold promise as non-invasive biomarkers for CKD in dogs and cats, addressing the challenges and standardization of protocols is vital for the successful translation of this research into clinical practice.

A Glimpse of Noncoding RNAs: Secondary Structure, Emerging Trends, and Potential Applications in Human Diseases

An appealing strategy for the treatment of several diseases is the therapeutic targeting of noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). Many antisense oligonucleotides and small interfering RNAs have been tested in clinical studies over the past 10 years, and several of these have received FDA approval. However, trial results have thus far been mixed, with some studies reporting strong effects and others showing low effectiveness or side effects, including toxicity. Clinical trials for alternative entities like antimiRNAs are underway, and interest in lncRNA-based therapies is constantly growing. From this perspective, we discuss the basic overview of ncRNAs, their significant role as therapeutic biomarkers against different diseases, and the role of secondary structure in noncoding RNAs.

Databases and computational methods for the identification of piRNA-related molecules: A survey

Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNAs (ncRNAs) that plays important roles in many biological processes and major cancer diagnosis and treatment, thus becoming a hot research topic. This study aims to provide an in-depth review of computational piRNA-related research, including databases and computational models. Herein, we perform literature analysis and use comparative evaluation methods to summarize and analyze three aspects of computational piRNA-related research: (i) computational models for piRNA-related molecular identification tasks, (ii) computational models for piRNA-disease association prediction tasks, and (iii) computational resources and evaluation metrics for these tasks. This study shows that computational piRNA-related research has significantly progressed, exhibiting promising performance in recent years, whereas they also suffer from the emerging challenges of inconsistent naming systems and the lack of data. Different from other reviews on piRNA-related identification tasks that focus on the organization of datasets and computational methods, we pay more attention to the analysis of computational models, algorithms, and performances that aim to provide valuable references for computational piRNA-related identification tasks. This study will benefit the theoretical development and practical application of piRNAs by better understanding computational models and resources to investigate the biological functions and clinical implications of piRNA.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

MicroRNA-126 in dogs with immune complex-mediated glomerulonephritis

BACKGROUND

Most proteinuric dogs with naturally occurring chronic kidney disease have amyloidosis (AMYL), glomerulosclerosis (GS), or immune complex-mediated glomerulonephritis (ICGN), each with different treatment and prognosis. A noninvasive and disease-specific biomarker is lacking.

HYPOTHESIS

We hypothesized that the expression pattern of biofluid microRNA (miRNAs and miRs) would correlate with disease progression and categorization.

ANIMALS

Archived serum and urine samples from 18 dogs with glomerular disease and 6 clinically healthy dogs; archived urine samples from 49 dogs with glomerular disease and 13 clinically healthy dogs.

METHODS

Retrospective study. Archived biofluid samples from adult dogs with biopsy-confirmed glomerular disease submitted to the International Veterinary Renal Pathology Service between 2008 and 2016 were selected. Serum and urinary miRNAs were isolated and profiled using RNA sequencing. Urinary miR-126, miR-21, miR-182, and miR-486 were quantified using quantitative reverse transcription PCR.

RESULTS

When comparing more advanced disease with earlier disease, no serum miRNAs were differentially expressed, but urinary miR-21 and miR-182 were 1.63 (95% CI: .86-3.1) and 1.45 (95% CI: .82-2.6) times higher in azotemic dogs, respectively (adjusted P < .05) and weakly correlated with tubulointerstitial fibrosis (miR-21: r = .32, P = .03; miR-182: r = .28, P = .05). Expression of urinary miR-126 was 10.5 (95% CI: 4.1-26.7), 28.9 (95% CI: 10.5-79.8), and 126.2 (95% CI: 44.7-356.3) times higher in dogs with ICGN compared with dogs with GS, AMYL, and healthy controls, respectively (P < .001).

CONCLUSIONS AND CLINICAL IMPORTANCE

The miR-126 could help identify dogs that might benefit from immunosuppressive therapy in the absence of a biopsy. MiR-21 and miR-182 are potential markers of disease severity and fibrosis.

New insight into circRNAs: characterization, strategies, and biomedical applications

Circular RNAs (circRNAs) are a class of covalently closed, endogenous ncRNAs. Most circRNAs are derived from exonic or intronic sequences by precursor RNA back-splicing. Advanced high-throughput RNA sequencing and experimental technologies have enabled the extensive identification and characterization of circRNAs, such as novel types of biogenesis, tissue-specific and cell-specific expression patterns, epigenetic regulation, translation potential, localization and metabolism. Increasing evidence has revealed that circRNAs participate in diverse cellular processes, and their dysregulation is involved in the pathogenesis of various diseases, particularly cancer. In this review, we systematically discuss the characterization of circRNAs, databases, challenges for circRNA discovery, new insight into strategies used in circRNA studies and biomedical applications. Although recent studies have advanced the understanding of circRNAs, advanced knowledge and approaches for circRNA annotation, functional characterization and biomedical applications are continuously needed to provide new insights into circRNAs. The emergence of circRNA-based protein translation strategy will be a promising direction in the field of biomedicine.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

Genome-wide profiling of dysregulated piRNAs and their target genes implicated in oncogenicity of Tongue Squamous Cell Carcinoma

PIWI-interacting RNAs (piRNAs) are single-stranded, 23-36 nucleotide long RNAs that regulate gene expression in the germline but are also detected in some cancers. However, there are no reports yet on piRNA expression in tongue squamous cell carcinoma (TSCC), the most common oral cancer (80-90% percent of all oral cancers). We performed small RNA and whole transcriptome sequencing in H357 tongue cancer and HOK cells (GEO database accession numbers: GSE196674 and GSE196688). We also examined nine published sets of gene expression array data of TSCC tissues from the GEO database to decode piRNAs and their putative targets that may be involved in tumorigenesis. We identified a pool of 16058 and 25677 piRNAs in H357 and HOK, respectively, among which 406 are differentially expressed. We also found that 2094 protein-coding genes are differentially expressed in either TSCC tissues or cell lines. We performed target predictions for these piRNA, pathway and disease function (DF) analyses, as well as qRT-PCR validation of piRNA-target pairs. These experiments revealed one up-regulated (FDFT1) and four down-regulated (OGA, BDH1, TAT, HYAL4) target genes that are enriched in 11 canonical pathways (CPs), with postulated roles in the initiation and progression of TSCC. Downregulation of piR-33422 is predicted to upregulate the FDFT1 gene, which encodes a mevalonate/cholesterol-pathway related farnesyl-diphosphate farnesyltransferase. The FDFT1 appears to be involved in the largest number of oncogenesis-related processes and is interacting with statins, which is a classical cancer drug. This study provides the first evidence of the piRNome of TSCC, which could be investigated further to decode piRNA-mediated gene regulations in malignancy and potential drug targets, such as FDFT1.

Identification and expression analysis of ten novel small non-coding RNAs (sncRNAs) in cancer cells using a high-throughput sequencing approach

Non-coding RNAs are characterized as RNA molecules, which lack the capacity to encode protein structures and appear to include a level of internal signals. Moreover, they control various stages of gene expression, thus controlling the cell physiology and development. In this study, we implemented a high-throughput sequencing approach based on the primary semi-conductor technology and computational tools, in order to identity novel small non-coding RNAs. Fourteen human cancer cell lines were cultured, and RNA samples were enriched for small RNAs following semi-conductor next generation sequencing (NGS). Bioinformatics analysis of NGS data revealed the existence of several classes of ncRNAs using the miRDeep* and CPSS 2.0 software. To investigate the existence of the predicted non-coding RNA sequences in cDNA pools of cell lines, a developed qPCR-based assay was implemented. The structure of each novel small ncRNA was visualized, using the RNAfold algorithm. Our results support the existence of twenty (20) putative new small ncRNAs, ten (10) of which have had their expression experimentally validated and presented differential profiles in cancerous and normal cells. A deeper comprehension of the ncRNAs interactive network and its role in cancer can therefore be translated into a wide range of clinical applications. Despite this progress, further scientific research from different perspectives and in different fields is needed, so that the riddle of the human transcriptome can be solved.

Small RNA sequencing evaluation of renal microRNA biomarkers in dogs with X-linked hereditary nephropathy

Dogs with X-linked hereditary nephropathy (XLHN) are an animal model for Alport syndrome in humans and progressive chronic kidney disease (CKD). Using mRNA sequencing (mRNA-seq), we have characterized the gene expression profile affecting the progression of XLHN; however, the microRNA (miRNA, miR) expression remains unknown. With small RNA-seq and quantitative RT-PCR (qRT-PCR), we used 3 small RNA-seq analysis tools (QIAGEN OmicSoft Studio, miRDeep2, and CPSS 2.0) to profile differentially expressed renal miRNAs, top-ranked miRNA target genes, and enriched biological processes and pathways in CKD progression. Twenty-three kidney biopsies were collected from 5 dogs with XLHN and 4 age-matched, unaffected littermates at 3 clinical time points (T1: onset of proteinuria, T2: onset of azotemia, and T3: advanced azotemia). We identified up to 23 differentially expressed miRNAs at each clinical time point. Five miRNAs (miR-21, miR-146b, miR-802, miR-142, miR-147) were consistently upregulated in affected dogs. We identified miR-186 and miR-26b as effective reference miRNAs for qRT-PCR. This study applied small RNA-seq to identify differentially expressed miRNAs that might regulate critical pathways contributing to CKD progression in dogs with XLHN.

miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale

Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2.

Computational Methods and Online Resources for Identification of piRNA-Related Molecules

piRNAs are a class of small non-coding RNA molecules, which interact with the PIWI family and have many important and diverse biological functions. The present review is aimed to provide guidelines and contribute to piRNA research. We focused on the four types of identification models on piRNA-related molecules, including piRNA, piRNA cluster, piRNA target, and disease-related piRNA. We evaluated the types of tools for the identification of piRNAs based on five aspects: datasets, features, classifiers, performance, and usability. We found the precision of 2lpiRNApred was the highest in datasets of model organisms, piRNN had a better performance of datasets of non-model organisms, and 2L-piRNA had the fastest recognition speed of all tools. In addition, we presented an overview of piRNA databases. The databases were divided into six categories: basic annotation, comprehensive annotation, isoform, cluster, target, and disease. We found that piRNA data of non-model organisms, piRNA target data, and piRNA-disease-associated data should be strengthened. Our review might assist researchers in selecting appropriate tools or datasets for their studies, reveal potential problems and shed light on future bioinformatics studies.

The bioinformatics toolbox for circRNA discovery and analysis

Circular RNAs (circRNAs) are a unique class of RNA molecule identified more than 40 years ago which are produced by a covalent linkage via back-splicing of linear RNA. Recent advances in sequencing technologies and bioinformatics tools have led directly to an ever-expanding field of types and biological functions of circRNAs. In parallel with technological developments, practical applications of circRNAs have arisen including their utilization as biomarkers of human disease. Currently, circRNA-associated bioinformatics tools can support projects including circRNA annotation, circRNA identification and network analysis of competing endogenous RNA (ceRNA). In this review, we collected about 100 circRNA-associated bioinformatics tools and summarized their current attributes and capabilities. We also performed network analysis and text mining on circRNA tool publications in order to reveal trends in their ongoing development.

IsomiR_Window: a system for analyzing small-RNA-seq data in an integrative and user-friendly manner

BACKGROUND

IsomiRs are miRNA variants that vary in length and/or sequence when compared to their canonical forms. These variants display differences in length and/or sequence, including additions or deletions of one or more nucleotides (nts) at the 5' and/or 3' end, internal editings or untemplated 3' end additions. Most available tools for small RNA-seq data analysis do not allow the identification of isomiRs and often require advanced knowledge of bioinformatics. To overcome this, we have developed IsomiR Window, a platform that supports the systematic identification, quantification and functional exploration of isomiR expression in small RNA-seq datasets, accessible to users with no computational skills.

METHODS

IsomiR Window enables the discovery of isomiRs and identification of all annotated non-coding RNAs in RNA-seq datasets from animals and plants. It comprises two main components: the IsomiR Window pipeline for data processing; and the IsomiR Window Browser interface. It integrates over ten third-party softwares for the analysis of small-RNA-seq data and holds a new algorithm that allows the detection of all possible types of isomiRs. These include 3' and 5'end isomiRs, 3' end tailings, isomiRs with single nucleotide polymorphisms (SNPs) or potential RNA editings, as well as all possible fuzzy combinations. IsomiR Window includes all required databases for analysis and annotation, and is freely distributed as a Linux virtual machine, including all required software.

RESULTS

IsomiR Window processes several datasets in an automated manner, without restrictions of input file size. It generates high quality interactive figures and tables which can be exported into different formats. The performance of isomiR detection and quantification was assessed using simulated small-RNA-seq data. For correctly mapped reads, it identified different types of isomiRs with high confidence and 100% accuracy. The analysis of a small RNA-seq data from Basal Cell Carcinomas (BCCs) using isomiR Window confirmed that miR-183-5p is up-regulated in Nodular BCCs, but revealed that this effect was predominantly due to a novel 5'end variant. This variant displays a different seed region motif and 1756 isoform-exclusive mRNA targets that are significantly associated with disease pathways, underscoring the biological relevance of isomiR-focused analysis. IsomiR Window is available at https://isomir.fc.ul.pt/ .

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

Encyclopedia of tools for the analysis of miRNA isoforms

RNA sequencing data sets rapidly increase in quantity. For microRNAs (miRNAs), frequently dozens to hundreds of billion reads are generated per study. The quantification of annotated miRNAs and the prediction of new miRNAs are leading computational tasks. Now, the increased depth of coverage allows to gain deeper insights into the variability of miRNAs. The analysis of isoforms of miRNAs (isomiRs) is a trending topic, and a range of computational tools for the analysis of isomiRs has been developed. We provide an overview on 27 available computational solutions for the analysis of isomiRs. These include both stand-alone programs (17 tools) and web-based solutions (10 tools) and span a publication time range from 2010 to 2020. Seven of the tools were published in 2019 and 2020, confirming the rising importance of the topic. While most of the analyzed tools work for a broad range of organisms or are completely independent of a reference organism, several tools have been tailored for the analysis of human miRNA data or for plants. While 14 of the tools are general analysis tools of miRNAs, and isomiR analysis is one of their features, the remaining 13 tools have specifically been developed for isomiR analysis. A direct comparison on 20 deep sequencing data sets for selected tools provides insights into the heterogeneity of results. With our work, we provide users a comprehensive overview on the landscape of isomiR analysis tools and in that support the selection of the most appropriate tool for their respective research task.

HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data

For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer's miRNAs.

Versatile interactions and bioinformatics analysis of noncoding RNAs

Advances in RNA sequencing technologies and computational methodologies have provided a huge impetus to noncoding RNA (ncRNA) study. Once regarded as inconsequential results of transcriptional promiscuity, ncRNAs were later found to exert great roles in various aspects of biological functions. They are emerging as key players in gene regulatory networks by interacting with other biomolecules (DNA, RNA or protein). Here, we provide an overview of ncRNA repertoire and highlight recent discoveries of their versatile interactions. To better investigate the ncRNA-mediated regulation, it is necessary to make full use of innovative sequencing techniques and computational tools. We further describe a comprehensive workflow for in silico ncRNA analysis, providing up-to-date platforms, databases and tools dedicated to ncRNA identification and functional annotation.

Computational tools for plant small RNA detection and categorization

Small RNAs (sRNAs) are important short-length molecules with regulatory functions essential for plant development and plasticity. High-throughput sequencing of total sRNA populations has revealed that the largest share of sRNA remains uncategorized. To better understand the role of sRNA-mediated cellular regulation, it is necessary to create accurate and comprehensive catalogues of sRNA and their sequence features, a task that currently relies on nontrivial bioinformatic approaches. Although a large number of computational tools have been developed to predict features of sRNA sequences, these tools are mostly dedicated to microRNAs and none integrates the functionalities necessary to describe units from all sRNA pathways thus far discovered in plants. Here, we review the different classes of sRNA found in plants and describe available bioinformatics tools that can help in their detection and categorization.

Identification of microRNAs that Regulate the MAPK Pathway in Human Cumulus Cells from PCOS Women with Insulin Resistance

Polycystic ovary syndrome (PCOS) is one of the most common gynaecological endocrine disorders, and more than 60% of PCOS patients have varying degrees of insulin resistance (IR). The regulatory role of microRNAs (miRNAs) at post-transcriptional levels in human cumulus cells relating to IR in PCOS remains unclear. In this case-control study, 26 PCOS patients with IR (PCOS-IR) and 24 patients without IR (PCOS-control) were enrolled. We determined the differentially expressed miRNA and mRNA using next-generation sequencing technology, and these miRNAs and mRNAs were validated by quantitative real-time polymerase chain reaction (PCR). These miRNA regulating pathways (e.g., MAPK pathway) were analysed by bioinformatics analysis, and the Rap1b was demonstrated to be targeted by miR-612 based on quantitative real-time PCR, western blot and luciferase activity assay. A total of 59 known miRNAs and 617 differentially expressed genes were identified that differentially expressed between PCOS-IR and PCOS-control cumulus cells. Moreover, the potential regulating roles of miRNAs and their targeting genes in pathophysiology of IR and PCOS were analysed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and several key processes were enriched, such as MAPK activity. Furthermore, Rap1b, a regulator of the MAPK pathway, was demonstrated to be suppressed directly by miR-612 in PCOS-IR cumulus cells based on negative expression correlation validation, dual luciferase activity assay and reduction of Rap1b expression after miR-612 mimics transfection. Our results suggested that miRNAs and their targeted pathways in ovarian cumulus cells may play important roles in the aetiology and pathophysiology of PCOS with IR.

Small noncoding RNA discovery and profiling with sRNAtools based on high-throughput sequencing

Small noncoding RNAs (sRNA/sncRNAs) are generated from different genomic loci and play important roles in biological processes, such as cell proliferation and the regulation of gene expression. Next-generation sequencing (NGS) has provided an unprecedented opportunity to discover and quantify diverse kinds of sncRNA, such as tRFs (tRNA-derived small RNA fragments), phasiRNAs (phased, secondary, small-interfering RNAs), Piwi-interacting RNA (piRNAs) and plant-specific 24-nt short interfering RNAs (siRNAs). However, currently available web-based tools do not provide approaches to comprehensively analyze all of these diverse sncRNAs. This study presents a novel integrated platform, sRNAtools (https://bioinformatics.caf.ac.cn/sRNAtools), that can be used in conjunction with high-throughput sequencing to identify and functionally annotate sncRNAs, including profiling microRNAss, piRNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs and rRNAs and discovering isomiRs, tRFs, phasiRNAs and plant-specific 24-nt siRNAs for up to 21 model organisms. Different modules, including single case, batch case, group case and target case, are developed to provide users with flexible ways of studying sncRNA. In addition, sRNAtools supports different ways of uploading small RNA sequencing data in a very interactive queue system, while local versions based on the program package/Docker/virtureBox are also available. We believe that sRNAtools will greatly benefit the scientific community as an integrated tool for studying sncRNAs.

Deciphering miRNAs' Action through miRNA Editing

MicroRNAs (miRNAs) are small non-coding RNAs with the capability of modulating gene expression at the post-transcriptional level either by inhibiting messenger RNA (mRNA) translation or by promoting mRNA degradation. The outcome of a myriad of physiological processes and pathologies, including cancer, cardiovascular and metabolic diseases, relies highly on miRNAs. However, deciphering the precise roles of specific miRNAs in these pathophysiological contexts is challenging due to the high levels of complexity of their actions. Indeed, regulation of mRNA expression by miRNAs is frequently cell/organ specific; highly dependent on the stress and metabolic status of the organism; and often poorly correlated with miRNA expression levels. Such biological features of miRNAs suggest that various regulatory mechanisms control not only their expression, but also their activity and/or bioavailability. Several mechanisms have been described to modulate miRNA action, including genetic polymorphisms, methylation of miRNA promoters, asymmetric miRNA strand selection, interactions with RNA-binding proteins (RBPs) or other coding/non-coding RNAs. Moreover, nucleotide modifications (A-to-I or C-to-U) within the miRNA sequences at different stages of their maturation are also critical for their functionality. This regulatory mechanism called "RNA editing" involves specific enzymes of the adenosine/cytidine deaminase family, which trigger single nucleotide changes in primary miRNAs. These nucleotide modifications greatly influence a miRNA's stability, maturation and activity by changing its specificity towards target mRNAs. Understanding how editing events impact miRNA's ability to regulate stress responses in cells and organs, or the development of specific pathologies, e.g., metabolic diseases or cancer, should not only deepen our knowledge of molecular mechanisms underlying complex diseases, but can also facilitate the design of new therapeutic approaches based on miRNA targeting. Herein, we will discuss the current knowledge on miRNA editing and how this mechanism regulates miRNA biogenesis and activity.

Comparison of RNA isolation and library preparation methods for small RNA sequencing of canine biofluids

BACKGROUND

Small RNA sequencing (RNA-seq) of biofluids is challenging due to the relative scarcity of microRNAs (miRNAs), limited sample volumes, and the lack of a gold standard isolation method. Additionally, few comparisons exist for the RNA isolation and sequencing methods of biofluids.

OBJECTIVES

We aimed to compare the performance of six commercial RNA isolation kits and two library preparation methods for small RNA-seq using canine serum and urine.

METHODS

Serum and urine were collected from seven dogs with protein-losing nephropathy, and the samples were pooled. Total RNA from serum (2 mL) and urine (10 mL) was isolated in triplicate using three methods each for serum (Zymo Direct-zol, mirVana PARIS, miRCURY Biofluids) and urine (Qiagen exoRNeasy, Norgen Urine Exosome, miRCURY Exosome). For each sample type, the two kits yielding the highest RNA concentration were selected, and small RNA-seq was performed using TruSeq and NEXTflex library preparations. Data were analyzed by CPSS 2.0 and DESeq2.

RESULTS

For serum, Zymo Direct-zol combined with NEXTflex was the only combination that enabled successful library preparation, while for urine, Qiagen exoRNeasy combined with NEXTflex outperformed other combinations for detecting miRNAs. The total number of miRNAs detected in serum and urine was 198 and up to 115, respectively. miRNA expression in serum was distinct from urine. Furthermore, the library preparation method introduced a higher variation of urine results than the RNA isolation method.

CONCLUSIONS

Different isolation and library preparation methods show significant differences in miRNA results that could affect biomarker discovery. Small RNA-seq provides an unbiased, global assessment to compare these methods in canine biofluids.

Automated analysis of small RNA datasets with RAPID

Understanding the role of short-interfering RNA (siRNA) in diverse biological processes is of current interest and often approached through small RNA sequencing. However, analysis of these datasets is difficult due to the complexity of biological RNA processing pathways, which differ between species. Several properties like strand specificity, length distribution, and distribution of soft-clipped bases are few parameters known to guide researchers in understanding the role of siRNAs. We present RAPID, a generic eukaryotic siRNA analysis pipeline, which captures information inherent in the datasets and automatically produces numerous visualizations as user-friendly HTML reports, covering multiple categories required for siRNA analysis. RAPID also facilitates an automated comparison of multiple datasets, with one of the normalization techniques dedicated for siRNA knockdown analysis, and integrates differential expression analysis using DESeq2.

IsopiRBank: a research resource for tracking piRNA isoforms

PIWI-interacting RNAs (piRNAs) are essential for transcriptional and post-transcriptional regulation of transposons and coding genes in germline. With the development of sequencing technologies, length variations of piRNAs have been identified in several species. However, the extent to which, piRNA isoforms exist, and whether these isoforms are functionally distinct from canonical piRNAs remain uncharacterized. Through data mining from 2154 datasets of small RNA sequencing data from four species (Homo sapiens, Mus musculus, Danio rerio and Drosophila melanogaster), we have identified 8 749 139 piRNA isoforms from 175 454 canonical piRNAs, and classified them on the basis of variations on 5' or 3' end via the alignment of isoforms with canonical sequence. We thus established a database named IsopiRBank. Each isoforms has detailed annotation as follows: normalized expression data, classification, spatiotemporal expression data and genome origin. Users can also select interested isoforms for further analysis, including target prediction and Enrichment analysis. Taken together, IsopiRBank is an interactive database that aims to present the first integrated resource of piRNA isoforms, and broaden the research of piRNA biology. IsopiRBank can be accessed at http://mcg.ustc.edu.cn/bsc/isopir/index.html without any registration or log in requirement. Database URL: http://mcg.ustc.edu.cn/bsc/isopir/index.html.