Bias in ligation-based small RNA sequencing library construction is determined by adaptor and RNA structure

A robust method for measuring aminoacylation through tRNA-Seq

Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge transfer RNA sequencing (tRNA-Seq) method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.

SingmiR: a single-cell miRNA alignment and analysis tool

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

The novel pre-rRNA detection workflow "Riboprobing" allows simple identification of undescribed RNA species

Ribosomes translate mRNA into proteins and are essential for every living organism. In eukaryotes, both ribosomal subunits are rapidly assembled in a strict hierarchical order, starting in the nucleolus with the transcription of a common precursor ribosomal RNA (pre-rRNA). This pre-rRNA encodes three of the four mature rRNAs, which are formed by several, consecutive endonucleolytic and exonucleolytic processing steps. Historically, northern blots are used to analyze the variety of different pre-rRNA species, only allowing rough length estimations. Although this limitation can be overcome with primer extension, both approaches often use radioactivity and are time-consuming and costly. Here, we present "Riboprobing," a linker ligation-based workflow followed by reverse transcription and PCR for easy and fast detection and characterization of pre-rRNA species and their 5' as well as 3' ends. Using standard molecular biology laboratory equipment, "Riboprobing" allows reliable discrimination of pre-rRNA species not resolved by northern blot (e.g., 27SA2, 27SA3, and 27SB pre-rRNA). The method can successfully be used for the analysis of total cell extracts as well as purified pre-ribosomes for a straightforward evaluation of the impact of mutant gene versions or inhibitors. In the course of method development, we identified and characterized a hitherto undescribed aberrant pre-rRNA arising from LiCl inhibition. This pre-rRNA fragment spans from processing site A1 to E, forming a small RNP that lacks most early joining assembly factors. This finding expands our knowledge of how the cell deals with severe pre-rRNA processing defects and demonstrates the strict requirement for the 5'ETS (external transcribed spacer) for the assembly process.

Characterisation and engineering of a thermophilic RNA ligase from Palaeococcus pacificus

RNA ligases are important enzymes in molecular biology and are highly useful for the manipulation and analysis of nucleic acids, including adapter ligation in next-generation sequencing of microRNAs. Thermophilic RNA ligases belonging to the RNA ligase 3 family are gaining attention for their use in molecular biology, for example a thermophilic RNA ligase from Methanobacterium thermoautotrophicum is commercially available for the adenylation of nucleic acids. Here we extensively characterise a newly identified RNA ligase from the thermophilic archaeon Palaeococcus pacificus (PpaRnl). PpaRnl exhibited significant substrate adenylation activity but low ligation activity across a range of oligonucleotide substrates. Mutation of Lys92 in motif I to alanine, resulted in an enzyme that lacked adenylation activity, but demonstrated improved ligation activity with pre-adenylated substrates (ATP-independent ligation). Subsequent structural characterisation revealed that in this mutant enzyme Lys238 was found in two alternate positions for coordination of the phosphate tail of ATP. In contrast mutation of Lys238 in motif V to glycine via structure-guided engineering enhanced ATP-dependent ligation activity via an arginine residue compensating for the absence of Lys238. Ligation activity for both mutations was higher than the wild-type, with activity observed across a range of oligonucleotide substrates with varying sequence and secondary structure.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.

A robust method for measuring aminoacylation through tRNA-Seq

Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge tRNA-Seq method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.

An improved method for the highly specific detection of transcription start sites

Precise detection of the transcriptional start site (TSS) is a key for characterizing transcriptional regulation of genes and for annotation of newly sequenced genomes. Here, we describe the development of an improved method, designated 'TSS-seq2.' This method is an iterative improvement of TSS-seq, a previously published enzymatic cap-structure conversion method to detect TSSs in base sequences. By modifying the original procedure, including by introducing split ligation at the key cap-selection step, the yield and the accuracy of the reaction has been substantially improved. For example, TSS-seq2 can be conducted using as little as 5 ng of total RNA with an overall accuracy of 96%; this yield a less-biased and more precise detection of TSS. We then applied TSS-seq2 for TSS analysis of four plant species that had not yet been analyzed by any previous TSS method.

Single Cell Micro RNA Sequencing Library Preparation

Micro RNAs represent important post-transcriptional regulators in health and are involved in the onset of many diseases. Therefore, the further characterization of physiological miRNA functions is an important basic research question, and miRNAs even have high potential as biomarkers both for prognosis and diagnosis. In order to exploit this potential, it is mandatory to accurately quantify the miRNA expression not only in bulk but also on the single-cell level. Here, we describe a protocol, which facilitates miRNA sequencing library preparation of very low input samples, single cells, and even clinical samples such as circulating tumor cells. The protocol can be combined with different single-cell isolation methods (e.g., micromanipulation and FACS sorting). After cell lysis, sequencing adapters are ligated to the miRNAs, other ncRNA species, and adapter dimers are reduced by exonuclease digest, the miRNA library is reverse transcribed, amplified, and purified. Furthermore, quality controls are described to select only high-quality samples for sequencing.

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.

PRO-seq: Precise Mapping of Engaged RNA Pol II at Single-Nucleotide Resolution

Gene regulation is dependent on the production of mRNAs and a repertoire of non-coding RNAs by RNA polymerase II (RNAPII). Precision run-on sequencing (PRO-seq) maps the position of engaged RNAPII complexes at single-nucleotide resolution and can reveal direct targets of regulation, locations of enhancers, and transcription mechanisms that are difficult or impossible to measure by analysis of total cellular RNA. Briefly, this method first involves permeabilizing cells with mild detergents to remove intracellular NTPs and halt transcription. Transcription is then resumed in the presence of biotin-NTPs and sarkosyl to allow transcriptional incorporation of a single biotinylated NTP by RNAPII. The biotin moiety is then bound to streptavidin beads to stringently enrich for nascent RNAs. Sequencing libraries are then generated such that the first base read corresponds to the 3' end of the nascent transcript. Here, we describe our current protocol for generating PRO-seq libraries from metazoan cells, including adaptations of previously published protocols to incorporate unique molecular identifiers, reduce ligation bias, and improve library yields. Additional commentary describes quality control and processing of PRO-seq data and references for more advanced downstream analysis such as gene and enhancer identification. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Cell permeabilization for PRO-seq Basic Protocol 2: Construction of PRO-seq libraries Support Protocol: Adenylation of 3' adapter.

Benchmarking of bioinformatics tools for NGS-based microRNA profiling with RT-qPCR method

MicroRNAs are vital gene expression regulators, extensively studied worldwide. The large-scale characterization of miRNAomes is possible using next-generation sequencing (NGS). This technology offers great opportunities, but these cannot be fully exploited without proper and comprehensive bioinformatics analysis. This may be achieved by the use of reliable dedicated software; however, different programs may generate divergent results, leading to additional discrepancies. Thus, the aim of this study was to compare three bioinformatic algorithms dedicated to NGS-based microRNA profiling and validate them using an alternative method, namely RT-qPCR. The comparison analysis revealed differences in the number and sets of identified miRNAs. The qPCR confirmed the expression of the investigated microRNAs. The correlation analysis of NGS and qPCR measurements showed strong and significant coefficients for a subset of the tested miRNAs, including those detected by all three algorithms. Single miRNA variants (isomiRs) showed different levels of correlation with the qPCR data. The obtained results revealed the good performance of all tested programs, despite the observed differences. Moreover, they implied that some specific miRNAs may be differentially estimated using NGS technology and the qPCR method, regardless of the used bioinformatics software. These discrepancies may stem from many factors, including the composition of the isomiR profile, their abundance, length, and investigated species. In conclusion, in this study, we shed light on the bioinformatics aspects of miRNAome profiling, elucidating its complexity and pinpointing potential features influencing validation. Thus, qPCR validation results should be open to interpretation when not fully concordant with NGS results until further, additional analyses are conducted.

Preparation and processing of dried blood spots for microRNA sequencing

Dried blood spots (DBS) are biological samples commonly collected from newborns and in geographic areas distanced from laboratory settings for the purposes of disease testing and identification. MicroRNAs (miRNAs)-small non-coding RNAs that regulate gene activity at the post-transcriptional level-are emerging as critical markers and mediators of disease, including cancer, infectious diseases, and mental disorders. This protocol describes optimized procedural steps for utilizing DBS as a reliable source of biological material for obtaining peripheral miRNA expression profiles. We outline key practices, such as the method of DBS rehydration that maximizes RNA extraction yield, and the use of degenerate oligonucleotide adapters to mitigate ligase-dependent biases that are associated with small RNA sequencing. The standardization of miRNA readout from DBS offers numerous benefits: cost-effectiveness in sample collection and processing, enhanced reliability and consistency of miRNA profiling, and minimal invasiveness that facilitates repeated testing and retention of participants. The use of DBS-based miRNA sequencing is a promising method to investigate disease mechanisms and to advance personalized medicine.

Led-Seq: ligation-enhanced double-end sequence-based structure analysis of RNA

Structural analysis of RNA is an important and versatile tool to investigate the function of this type of molecules in the cell as well as in vitro. Several robust and reliable procedures are available, relying on chemical modification inducing RT stops or nucleotide misincorporations during reverse transcription. Others are based on cleavage reactions and RT stop signals. However, these methods address only one side of the RT stop or misincorporation position. Here, we describe Led-Seq, a new approach based on lead-induced cleavage of unpaired RNA positions, where both resulting cleavage products are investigated. The RNA fragments carrying 2', 3'-cyclic phosphate or 5'-OH ends are selectively ligated to oligonucleotide adapters by specific RNA ligases. In a deep sequencing analysis, the cleavage sites are identified as ligation positions, avoiding possible false positive signals based on premature RT stops. With a benchmark set of transcripts in Escherichia coli, we show that Led-Seq is an improved and reliable approach based on metal ion-induced phosphodiester hydrolysis to investigate RNA structures in vivo.

Adapter dimer contamination in sRNA-sequencing datasets predicts sequencing failure and batch effects and hampers extracellular vesicle-sRNA analysis

Small RNA (sRNA) profiling of Extracellular Vesicles (EVs) by Next-Generation Sequencing (NGS) often delivers poor outcomes, independently of reagents, platforms or pipelines used, which contributes to poor reproducibility of studies. Here we analysed pre/post-sequencing quality controls (QC) to predict issues potentially biasing biological sRNA-sequencing results from purified human milk EVs, human and mouse EV-enriched plasma and human paraffin-embedded tissues. Although different RNA isolation protocols and NGS platforms were used in these experiments, all datasets had samples characterized by a marked removal of reads after pre-processing. The extent of read loss between individual samples within a dataset did not correlate with isolated RNA quantity or sequenced base quality. Rather, cDNA electropherograms revealed the presence of a constant peak whose intensity correlated with the degree of read loss and, remarkably, with the percentage of adapter dimers, which were found to be overrepresented sequences in high read-loss samples. The analysis through a QC pipeline, which allowed us to monitor quality parameters in a step-by-step manner, provided compelling evidence that adapter dimer contamination was the main factor causing batch effects. We concluded this study by summarising peer-reviewed published workflows that perform consistently well in avoiding adapter dimer contamination towards a greater likelihood of sequencing success.

Small RNA transcriptome analysis using parallel single-cell small RNA sequencing

miRNA and other forms of small RNAs are known to regulate many biological processes. Single-cell small RNA sequencing can be used to profile small RNAs of individual cells; however, limitations of efficiency and scale prevent its widespread application. Here, we developed parallel single-cell small RNA sequencing (PSCSR-seq), which can overcome the limitations of existing methods and enable high-throughput small RNA expression profiling of individual cells. Analysis of PSCSR-seq data indicated that diverse cell types could be identified based on patterns of miRNA expression, and showed that miRNA content in nuclei is informative (for example, cell type marker miRNAs can be detected in isolated nuclei). PSCSR-seq is very sensitive: analysis of only 732 peripheral blood mononuclear cells (PBMCs) detected 774 miRNAs, whereas bulk small RNA analysis would require input RNA from approximately 10⁶ cells to detect as many miRNAs. We identified 42 miRNAs as markers for PBMC subpopulations. Moreover, we analyzed the miRNA profiles of 9,533 cells from lung cancer biopsies, and by dissecting cell subpopulations, we identified potentially diagnostic and therapeutic miRNAs for lung cancers. Our study demonstrates that PSCSR-seq is highly sensitive and reproducible, thus making it an advanced tool for miRNA analysis in cancer and life science research.

Reassessing the Abundance of miRNAs in the Human Pancreas and Rodent Cell Lines and Its Implication

miRNAs are critical for pancreas development and function. However, we found that there are discrepancies regarding pancreatic miRNA abundance in published datasets. To obtain a more relevant profile that is closer to the true profile, we profiled small RNAs from human islets cells, acini, and four rodent pancreatic cell lines routinely used in diabetes and pancreatic research using a bias reduction protocol for small RNA sequencing. In contrast to the previous notion that miR-375-3p is the most abundant pancreatic miRNA, we found that miR-148a-3p and miR-7-5p were also abundant in islets. In silico studies using predicted and validated targets of these three miRNAs revealed that they may work cooperatively in endocrine and exocrine cells. Our results also suggest, compared to the most-studied miR-375, that both miR-148a-3p and miR-7-5p may play more critical roles in the human pancreas. Moreover, according to in silico-predicted targets, we found that miR-375-3p had a much broader target spectrum by targeting the coding sequence and the 5' untranslated region, rather than the conventional 3' untranslated region, suggesting additional unexplored roles of miR-375-3p beyond the pancreas. Our study provides a valuable new resource for studying miRNAs in pancreata.

BaM-seq and TBaM-seq, highly multiplexed and targeted RNA-seq protocols for rapid, low-cost library generation from bacterial samples

The ability to profile transcriptomes and characterize global gene expression changes has been greatly enabled by the development of RNA sequencing technologies (RNA-seq). However, the process of generating sequencing-compatible cDNA libraries from RNA samples can be time-consuming and expensive, especially for bacterial mRNAs which lack poly(A)-tails that are often used to streamline this process for eukaryotic samples. Compared to the increasing throughput and decreasing cost of sequencing, library preparation has had limited advances. Here, we describe bacterial-multiplexed-seq (BaM-seq), an approach that enables simple barcoding of many bacterial RNA samples that decreases the time and cost of library preparation. We also present targeted-bacterial-multiplexed-seq (TBaM-seq) that allows for differential expression analysis of specific gene panels with over 100-fold enrichment in read coverage. In addition, we introduce the concept of transcriptome redistribution based on TBaM-seq that dramatically reduces the required sequencing depth while still allowing for quantification of both highly and lowly abundant transcripts. These methods accurately measure gene expression changes with high technical reproducibility and agreement with gold standard, lower throughput approaches. Together, use of these library preparation protocols allows for fast, affordable generation of sequencing libraries.

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies

INTRODUCTION

The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approved risdiplam, the biopharmaceutical industry is gaining confidence in the field. This review, based on the literature obtained from PubMed, aims to disseminate information about the various technologies developed for targeting RNA with small molecules and propose areas for improvement to develop drugs more efficiently, particularly those linked to diseases with unmet medical needs.

AREAS COVERED

The technologies for the identification of RNA targets, screening of chemical libraries against RNA, assessing the bioactivity and target engagement of the hit compounds, structure determination, and hit-to-lead optimization are reviewed. Along with the description of the technologies, their strengths, limitations, and examples of how they can impact drug discovery are provided.

EXPERT OPINION

Many existing technologies employed for protein targets have been repurposed for use in the discovery of RNA-targeted small molecules. In addition, technologies tailored for RNA targets have been developed. Nevertheless, more improvements are necessary, such as artificial intelligence to dissect important RNA structures and RNA-small-molecule interactions and more powerful chemical probing and structure prediction techniques.

Cardiac microRNA expression profile in response to estivation

Couch's spadefoot toad (Scaphiopus couchii) spends most of the year underground in a hypometabolic state known as estivation. During this time, they overcome significant dehydration and lack of food through many mechanisms including employing metabolic rate depression (MRD), increasing urea concentration, switching to lipid oxidation as the primary energy source, and decreasing their breathing and heart rate. MicroRNA (miRNA) are known to regulate translation by targeting messenger RNA (mRNA) for degradation or temporary storage, with several studies having reported that miRNA is differentially expressed during MRD, including estivation. Thus, we hypothesized that miRNA would be involved in gene regulation during estivation in S. couchii heart. Next-generation sequencing and bioinformatic analyses were used to assess changes in miRNA expression in response to two-month estivation and to predict the downstream effects of this expression. KEGG and GO analyses indicated that ribosome and cardiac muscle contraction are among the pathways predicted to be upregulated, whereas cell signaling and fatty acid metabolism were predicted to be downregulated. Together these results suggest that miRNAs contribute to the regulation of gene expression related to cardiac muscle physiology and energy metabolism during estivation.

Current challenges and best practices for cell-free long RNA biomarker discovery

The analysis of biomarkers in biological fluids, also known as liquid biopsies, is seen with great potential to diagnose complex diseases such as cancer with a high sensitivity and minimal invasiveness. Although it can target any biomolecule, most liquid biopsy studies have focused on circulating nucleic acids. Historically, studies have aimed at the detection of specific mutations on cell-free DNA (cfDNA), but recently, the study of cell-free RNA (cfRNA) has gained traction. Since 2020, a handful of cfDNA tests have been approved for therapy selection by the FDA, however, no cfRNA tests are approved to date. One of the main drawbacks in the field of RNA-based liquid biopsies is the low reproducibility of the results, often caused by technical and biological variability, a lack of standardized protocols and insufficient cohorts. In this review, we will identify the main challenges and biases introduced during the different stages of biomarker discovery in liquid biopsies with cfRNA and propose solutions to minimize them.

Tailer: a pipeline for sequencing-based analysis of nonpolyadenylated RNA 3' end processing

Post-transcriptional trimming and tailing of RNA 3' ends play key roles in the processing and quality control of noncoding RNAs (ncRNAs). However, bioinformatic tools to examine changes in the RNA 3' "tailome" are sparse and not standardized. Here we present Tailer, a bioinformatic pipeline in two parts that allows for robust quantification and analysis of tail information from next-generation sequencing experiments that preserve RNA 3' end information. The first part of Tailer, Tailer-processing, uses genome annotation or reference FASTA gene sequences to quantify RNA 3' ends from SAM-formatted alignment files or FASTQ sequence read files produced from sequencing experiments. The second part, Tailer-analysis, uses the output of Tailer-processing to identify statistically significant RNA targets of trimming and tailing and create graphs for data exploration. We apply Tailer to RNA 3' end sequencing experiments from three published studies and find that it accurately and reproducibly recapitulates key findings. Thus, Tailer should be a useful and easily accessible tool to globally investigate tailing dynamics of nonpolyadenylated RNAs and conditions that perturb them.

Small RNA-Sequencing for Analysis of Circulating miRNAs: Benchmark Study

Small RNA-sequencing (RNA-Seq) is being increasingly used for profiling of circulating microRNAs (miRNAs), a new group of promising biomarkers. Unfortunately, small RNA-Seq protocols are prone to biases limiting quantification accuracy, which motivated development of several novel methods. Here, we present comparison of all small RNA-Seq library preparation approaches that are commercially available for quantification of miRNAs in biofluids. Using synthetic and human plasma samples, we compared performance of traditional two-adaptor ligation protocols (Lexogen, Norgen), as well as methods using randomized adaptors (NEXTflex), polyadenylation (SMARTer), circularization (RealSeq), capture probes (EdgeSeq), or unique molecular identifiers (QIAseq). There was no single protocol outperforming others across all metrics. Limited overlap of measured miRNA profiles was documented between methods largely owing to protocol-specific biases. Methods designed to minimize bias largely differ in their performance, and contributing factors were identified. Usage of unique molecular identifiers has rather negligible effect and, if designed incorrectly, can even introduce spurious results. Together, these results identify strengths and weaknesses of all current methods and provide guidelines for applications of small RNA-Seq in biomarker research.

Identification of high-confidence human poly(A) RNA isoform scaffolds using nanopore sequencing

Nanopore sequencing devices read individual RNA strands directly. This facilitates identification of exon linkages and nucleotide modifications; however, using conventional direct RNA nanopore sequencing, the 5' and 3' ends of poly(A) RNA cannot be identified unambiguously. This is due in part to RNA degradation in vivo and in vitro that can obscure transcription start and end sites. In this study, we aimed to identify individual full-length human RNA isoforms among ∼4 million nanopore poly(A)-selected RNA reads. First, to identify RNA strands bearing 5' m⁷G caps, we exchanged the biological cap for a modified cap attached to a 45-nt oligomer. This oligomer adaptation method improved 5' end sequencing and ensured correct identification of the 5' m⁷G capped ends. Second, among these 5'-capped nanopore reads, we screened for features consistent with a 3' polyadenylation site. Combining these two steps, we identified 294,107 individual high-confidence full-length RNA scaffolds from human GM12878 cells, most of which (257,721) aligned to protein-coding genes. Of these, 4876 scaffolds indicated unannotated isoforms that were often internal to longer, previously identified RNA isoforms. Orthogonal data for m⁷G caps and open chromatin, such as CAGE and DNase-HS seq, confirmed the validity of these high-confidence RNA scaffolds.

A MicroRNA Next-Generation-Sequencing Discovery Assay (miND) for Genome-Scale Analysis and Absolute Quantitation of Circulating MicroRNA Biomarkers

The plasma levels of tissue-specific microRNAs can be used as diagnostic, disease severity and prognostic biomarkers for chronic and acute diseases and drug-induced injury. Thereby, the combination of diverse microRNAs into biomarker signatures using multivariate statistics seems especially powerful from the perspective of tissue and condition specific microRNA shedding into the plasma. Although next-generation sequencing (NGS) technology enables one to analyse circulating microRNAs on a genome-scale level, it suffers from potential biases (e.g., adapter ligation bias) and lacks absolute transcript quantitation as well as tailor-made quality controls. In order to develop a robust NGS discovery assay for genome-scale quantitation of circulating microRNAs, we first evaluated the sensitivity, repeatability and ligation bias of four commercially available small RNA library preparation protocols. The protocol from RealSeq Biosciences was selected based on its performance and usability and coupled with a novel panel of exogenous small RNA spike-in controls to enable quality control and absolute quantitation, thus ensuring comparability of data across independent NGS experiments. The established microRNA Next-Generation-Sequencing Discovery Assay (miND) was validated for its relative accuracy, precision, analytical measurement range and sequencing bias and was considered fit-for-purpose for microRNA biomarker discovery. Summarized, all these criteria were met, and thus, our analytical platform is considered fit-for-purpose for microRNA biomarker discovery from biofluids in the setting of any diagnostic, prognostic or patient stratification need. The established miND assay was tested on serum, cerebrospinal fluid (CSF), synovial fluid (SF) and extracellular vesicles (EV) extracted from cell culture medium of primary cells and proved its potential to be used across different sample types.

Rolling circle reverse transcription enables high fidelity nanopore sequencing of small RNA

Small RNAs (sRNAs) are an important group of non-coding RNAs that have great potential as diagnostic and prognostic biomarkers for treatment of a wide variety of diseases. The portability and affordability of nanopore sequencing technology makes it ideal for point of care and low resource settings. Currently sRNAs can't be reliably sequenced on the nanopore platform due to the short size of sRNAs and high error rate of the nanopore sequencer. Here, we developed a highly efficient nanopore-based sequencing strategy for sRNAs (SR-Cat-Seq) in which sRNAs are ligated to an adapter, circularized, and undergo rolling circle reverse transcription to generate concatemeric cDNA. After sequencing, the resulting tandem repeat sequences within the individual cDNA can be aligned to generate highly accurate consensus sequences. We compared our sequencing strategy with other sRNA sequencing methods on a short-read sequencing platform and demonstrated that SR-Cat-Seq can obtain low bias and highly accurate sRNA transcriptomes. Therefore, our method could enable nanopore sequencing for sRNA-based diagnostics and other applications.

A high-quality genome and comparison of short- versus long-read transcriptome of the palaearctic duck Aythya fuligula (tufted duck)

BACKGROUND

The tufted duck is a non-model organism that experiences high mortality in highly pathogenic avian influenza outbreaks. It belongs to the same bird family (Anatidae) as the mallard, one of the best-studied natural hosts of low-pathogenic avian influenza viruses. Studies in non-model bird species are crucial to disentangle the role of the host response in avian influenza virus infection in the natural reservoir. Such endeavour requires a high-quality genome assembly and transcriptome.

FINDINGS

This study presents the first high-quality, chromosome-level reference genome assembly of the tufted duck using the Vertebrate Genomes Project pipeline. We sequenced RNA (complementary DNA) from brain, ileum, lung, ovary, spleen, and testis using Illumina short-read and Pacific Biosciences long-read sequencing platforms, which were used for annotation. We found 34 autosomes plus Z and W sex chromosomes in the curated genome assembly, with 99.6% of the sequence assigned to chromosomes. Functional annotation revealed 14,099 protein-coding genes that generate 111,934 transcripts, which implies a mean of 7.9 isoforms per gene. We also identified 246 small RNA families.

CONCLUSIONS

This annotated genome contributes to continuing research into the host response in avian influenza virus infections in a natural reservoir. Our findings from a comparison between short-read and long-read reference transcriptomics contribute to a deeper understanding of these competing options. In this study, both technologies complemented each other. We expect this annotation to be a foundation for further comparative and evolutionary genomic studies, including many waterfowl relatives with differing susceptibilities to avian influenza viruses.

Transposable elements and Piwi‑interacting RNAs in hemato‑oncology with a focus on myelodysplastic syndrome (Review)

Our current understanding of hematopoietic stem cell differentiation and the abnormalities that lead to leukemogenesis originates from the accumulation of knowledge regarding protein‑coding genes. However, the possible impact of transposable element (TE) mobilization and the expression of P‑element‑induced WImpy testis‑interacting RNAs (piRNAs) on leukemogenesis has been beyond the scope of scientific interest to date. The expression profiles of these molecules and their importance for human health have only been characterized recently due to the rapid progress of high‑throughput sequencing technology development. In the present review, current knowledge on the expression profile and function of TEs and piRNAs was summarized, with specific focus on their reported involvement in leukemogenesis and pathogenesis of myelodysplastic syndrome.

5´XP sRNA-seq: efficient identification of transcripts with and without 5´ phosphorylation reveals evolutionary conserved small RNA

Small RNA (sRNA) sequencing has been critical for our understanding of many cellular processes, including gene regulation. Nonetheless, the varying biochemical properties of sRNA, such as 5´ nucleotide modifications, make many sRNA subspecies incompatible with common protocols for sRNA sequencing. Here we describe 5XP-seq that outlines a novel strategy that captures a more complete picture of sRNA. By tagging 5´P sRNA during library preparation, 5XP-seq combines an open approach that includes all types of 5'-terminal modifications (5´X), with a selective approach for 5-phosphorylated sRNA (5´P). We show that 5XP-seq not only enriches phosphorylated miRNA and piRNA but successfully discriminates these sRNA from all other sRNA species. We further demonstrate the importance of this strategy by successful inter-species validation of sRNAs that would have otherwise failed, including human to insect translation of several tRNA (tRFs) and rRNA (rRFs) fragments. By combining 5´ insensitive library strategies with 5´ sensitive tagging, we have successfully tackled an intrinsic bias in modern sRNA sequencing that will help us reveal the true complexity and the evolutionary significance of the sRNA world.

Chemical capping improves template switching and enhances sequencing of small RNAs

Template-switching reverse transcription is widely used in RNA sequencing for low-input and low-quality samples, including RNA from single cells or formalin-fixed paraffin-embedded (FFPE) tissues. Previously, we identified the native eukaryotic mRNA 5′ cap as a key structural element for enhancing template switching efficiency. Here, we introduce CapTS-seq, a new strategy for sequencing small RNAs that combines chemical capping and template switching. We probed a variety of non-native synthetic cap structures and found that an unmethylated guanosine triphosphate cap led to the lowest bias and highest efficiency for template switching. Through cross-examination of different nucleotides at the cap position, our data provided unequivocal evidence that the 5′ cap acts as a template for the first nucleotide in reverse transcriptase-mediated post-templated addition to the emerging cDNA—a key feature to propel template switching. We deployed CapTS-seq for sequencing synthetic miRNAs, human total brain and liver FFPE RNA, and demonstrated that it consistently improves library quality for miRNAs in comparison with a gold standard template switching-based small RNA-seq kit.

Global approaches for profiling transcription initiation

Transcription start site (TSS) selection influences transcript stability and translation as well as protein sequence. Alternative TSS usage is pervasive in organismal development, is a major contributor to transcript isoform diversity in humans, and is frequently observed in human diseases including cancer. In this review, we discuss the breadth of techniques that have been used to globally profile TSSs and the resulting insights into gene regulation, as well as future prospects in this area of inquiry.

Identifying transcript 5' capped ends in Plasmodium falciparum

Background

The genome of the human malaria parasite Plasmodium falciparum is poorly annotated, in particular, the 5' capped ends of its mRNA transcripts. New approaches are needed to fully catalog P. falciparum transcripts for understanding gene function and regulation in this organism.

Methods

We developed a transcriptomic method based on next-generation sequencing of complementary DNA (cDNA) enriched for full-length fragments using eIF4E, a 5' cap-binding protein, and an unenriched control. DNA sequencing adapter was added after enrichment of full-length cDNA using two different ligation protocols. From the mapped sequence reads, enrichment scores were calculated for all transcribed nucleotides and used to calculate P-values of 5' capped nucleotide enrichment. Sensitivity and accuracy were increased by combining P-values from replicate experiments. Data were obtained for P. falciparum ring, trophozoite and schizont stages of intra-erythrocytic development.

Results

5' capped nucleotide signals were mapped to 17,961 non-overlapping P. falciparum genomic intervals. Analysis of the dominant 5' capped nucleotide in these genomic intervals revealed the presence of two groups with distinctive epigenetic features and sequence patterns. A total of 4,512 transcripts were annotated as 5' capped based on the correspondence of 5' end with 5' capped nucleotide annotated from full-length cDNA data.

Discussion

The presence of two groups of 5' capped nucleotides suggests that alternative mechanisms may exist for producing 5' capped transcript ends in P. falciparum. The 5' capped transcripts that are antisense, outside of, or partially overlapping coding regions may be important regulators of gene function in P. falciparum.

RNA Structures and Their Role in Selective Genome Packaging

To generate infectious viral particles, viruses must specifically select their genomic RNA from milieu that contains a complex mixture of cellular or non-genomic viral RNAs. In this review, we focus on the role of viral encoded RNA structures in genome packaging. We first discuss how packaging signals are constructed from local and long-range base pairings within viral genomes, as well as inter-molecular interactions between viral and host RNAs. Then, how genome packaging is regulated by the biophysical properties of RNA. Finally, we examine the impact of RNA packaging signals on viral evolution.

Multiplexed profiling facilitates robust m6A quantification at site, gene and sample resolution

N⁶-methyladenosine (m6A) is the most prevalent modification of messenger RNA in mammals. To interrogate its functions and dynamics, there is a critical need to quantify m6A at three levels: site, gene and sample. Current approaches address these needs in a limited manner. Here we develop m6A-seq2, relying on multiplexed m6A-immunoprecipitation of barcoded and pooled samples. m6A-seq2 allows a big increase in throughput while reducing technical variability, requirements of input material and cost. m6A-seq2 is furthermore uniquely capable of providing sample-level relative quantitations of m6A, serving as an orthogonal alternative to mass spectrometry-based approaches. Finally, we develop a computational approach for gene-level quantitation of m6A. We demonstrate that using this metric, roughly 30% of the variability in RNA half life in mouse embryonic stem cells can be explained, establishing m6A as a main driver of RNA stability. m6A-seq2 thus provides an experimental and analytic framework for dissecting m6A-mediated regulation at three different levels.

Finding differentially expressed sRNA-Seq regions with srnadiff

Small RNAs (sRNAs) encompass a great variety of molecules of different kinds, such as microRNAs, small interfering RNAs, Piwi-associated RNA, among others. These sRNAs have a wide range of activities, which include gene regulation, protection against virus, transposable element silencing, and have been identified as a key actor in determining the development of the cell. Small RNA sequencing is thus routinely used to assess the expression of the diversity of sRNAs, usually in the context of differentially expression, where two conditions are compared. Tools that detect differentially expressed microRNAs are numerous, because microRNAs are well documented, and the associated genes are well defined. However, tools are lacking to detect other types of sRNAs, which are less studied, and whose precursor RNA is not well characterized. We present here a new method, called srnadiff, which finds all kinds of differentially expressed sRNAs. To the extent of our knowledge, srnadiff is the first tool that detects differentially expressed sRNAs without the use of external information, such as genomic annotation or additional sequences of sRNAs.

Quantitative mapping of the cellular small RNA landscape with AQRNA-seq

Current next-generation RNA-sequencing (RNA-seq) methods do not provide accurate quantification of small RNAs within a sample, due to sequence-dependent biases in capture, ligation and amplification during library preparation. We present a method, absolute quantification RNA-sequencing (AQRNA-seq), that minimizes biases and provides a direct, linear correlation between sequencing read count and copy number for all small RNAs in a sample. Library preparation and data processing were optimized and validated using a 963-member microRNA reference library, oligonucleotide standards of varying length, and RNA blots. Application of AQRNA-seq to a panel of human cancer cells revealed >800 detectable miRNAs that varied during cancer progression, while application to bacterial transfer RNA pools, with the challenges of secondary structure and abundant modifications, revealed 80-fold variation in tRNA isoacceptor levels, stress-induced site-specific tRNA fragmentation, quantitative modification maps, and evidence for stress-induced, tRNA-driven, codon-biased translation. AQRNA-seq thus provides a versatile means to quantitatively map the small RNA landscape in cells.

Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells

Molecular single cell analyses provide insights into physiological and pathological processes. Here, in a stepwise approach, we first evaluate 19 protocols for single cell small RNA sequencing on MCF7 cells spiked with 1 pg of 1,006 miRNAs. Second, we analyze MCF7 single cell equivalents of the eight best protocols. Third, we sequence single cells from eight different cell lines and 67 circulating tumor cells (CTCs) from seven SCLC patients. Altogether, we analyze 244 different samples. We observe high reproducibility within protocols and reads covered a broad spectrum of RNAs. For the 67 CTCs, we detect a median of 68 miRNAs, with 10 miRNAs being expressed in 90% of tested cells. Enrichment analysis suggested the lung as the most likely organ of origin and enrichment of cancer-related categories. Even the identification of non-annotated candidate miRNAs was feasible, underlining the potential of single cell small RNA sequencing.

Technologies for small non-coding RNA sequencing at the single-cell level are less mature than for sequencing mRNAs. Here the authors evaluate available protocols for analysis of circulating lung cancer tumour cells.

Methyltransferase-directed orthogonal tagging and sequencing of miRNAs and bacterial small RNAs

Background

Targeted installation of designer chemical moieties on biopolymers provides an orthogonal means for their visualisation, manipulation and sequence analysis. Although high-throughput RNA sequencing is a widely used method for transcriptome analysis, certain steps, such as 3′ adapter ligation in strand-specific RNA sequencing, remain challenging due to structure- and sequence-related biases introduced by RNA ligases, leading to misrepresentation of particular RNA species. Here, we remedy this limitation by adapting two RNA 2′-O-methyltransferases from the Hen1 family for orthogonal chemo-enzymatic click tethering of a 3′ sequencing adapter that supports cDNA production by reverse transcription of the tagged RNA.

Results

We showed that the ssRNA-specific DmHen1 and dsRNA-specific AtHEN1 can be used to efficiently append an oligonucleotide adapter to the 3′ end of target RNA for sequencing library preparation. Using this new chemo-enzymatic approach, we identified miRNAs and prokaryotic small non-coding sRNAs in probiotic Lactobacillus casei BL23. We found that compared to a reference conventional RNA library preparation, methyltransferase-Directed Orthogonal Tagging and RNA sequencing, mDOT-seq, avoids misdetection of unspecific highly-structured RNA species, thus providing better accuracy in identifying the groups of transcripts analysed. Our results suggest that mDOT-seq has the potential to advance analysis of eukaryotic and prokaryotic ssRNAs.

Conclusions

Our findings provide a valuable resource for studies of the RNA-centred regulatory networks in Lactobacilli and pave the way to developing novel transcriptome and epitranscriptome profiling approaches in vitro and inside living cells. As RNA methyltransferases share the structure of the AdoMet-binding domain and several specific cofactor binding features, the basic principles of our approach could be easily translated to other AdoMet-dependent enzymes for the development of modification-specific RNA-seq techniques.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01053-w.

Distinct Extracellular RNA Profiles in Different Plasma Components

Circulating extracellular RNAs (exRNAs) have great potential to serve as biomarkers for a wide range of diagnostic, therapeutic, and prognostic applications. So far, knowledge of the difference among different sources of exRNAs is limited. To address this issue, we performed a sequential physical and biochemical precipitation to collect four fractions (platelets and cell debris, the thrombin-induced precipitates, extracellular vesicles, and supernatant) from each of 10 plasma samples. From total RNAs of the 40 fractions, we prepared ligation-free libraries to profile full spectrum of all RNA species, without size selection and rRNA reduction. Due to complicated RNA composition in these libraries, we utilized a successive stepwise alignment strategy to map the RNA sequences to different RNA categories, including miRNAs, piwi-interacting RNAs, tRNAs, rRNAs, lincRNAs, snoRNAs, snRNAs, other ncRNAs, protein coding RNAs, and circRNAs. Our data showed that each plasma fraction had its own unique distribution of RNA species. Hierarchical cluster analyses using transcript abundance demonstrated similarities in the same plasma fraction and significant differences between different fractions. In addition, we observed various unique transcripts, and novel predicted miRNAs among these plasma fractions. These results demonstrate that the distribution of RNA species and functional RNA transcripts is plasma fraction-dependent. Appropriate plasma preparation and thorough inspection of different plasma fractions are necessary for an exRNA-based biomarker study.

Multisite Evaluation of Next-Generation Methods for Small RNA Quantification

Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs in vivo. Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.

Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis

MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol's performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research.

A novel platform for discovery of differentially expressed microRNAs in patients with repeated implantation failure

OBJECTIVE

To identify predictor microRNAs (miRNAs) from patients with repeated implantation failure (RIF).

DESIGN

Systemic analysis of miRNA profiles from the endometrium of patients undergoing in vitro fertilization (IVF).

SETTING

University research institute, private IVF center, and molecular testing laboratory.

PATIENT(S)

Twenty five infertile patients in the discovery cohort and 11 patients in the validation cohort.

INTERVENTIONS(S)

None.

MAIN OUTCOME MEASURE(S)

A signature set of miRNA associated with the risk of RIF.

RESULT(S)

We designed a reproductive disease-related PanelChip to access endometrium miRNA profiles in patients undergoing IVF. Three major miRNA signatures, including hsa-miR-20b-5p, hsa-miR-155-5p, and hsa-miR-718, were identified using infinite combination signature search algorithm analysis from 25 patients in the discovery cohort undergoing IVF. These miRNAs were used as biomarkers in the validation cohort of 11 patients. Finally, the 3-miRNA signature was capable of predicting patients with RIF with an accuracy >90%.

CONCLUSION(S)

Our findings indicated that specific endometrial miRNAs can be applied as diagnostic biomarkers to predict RIF. Such information will definitely help to increase the success rate of implantation practice.

Diagnostic Potential of MicroRNAs as Biomarkers in the Detection of Preeclampsia

Preeclampsia is a multisystemic disorder that occurs in 5-8% of pregnant women and remains a leading cause of both maternal and fetal morbidity and mortality. The disease is characterized by the abnormal vascular response to placentation, but the exact pathophysiology and pathogenesis of preeclampsia remain unknown. Risk factors for preeclampsia include increased maternal age, obesity, multiple gestations, and a history of preeclampsia. Several studies have suggested that altered expression of some microRNAs (miRNAs) in placental tissue, and maternal circulation, may be associated with several types of pregnancy complications such as preeclampsia, preterm birth, and spontaneous abortion. It is assumed that these miRNAs play an important role in various cellular processes important for maintaining a healthy pregnancy, including promoting angiogenesis and the differentiation of trophoblast cells. In this review, we discuss the role of miRNAs as potential biomarkers of preeclampsia.

Advances in multiplexed techniques for the detection and quantification of microRNAs

MicroRNA detection is currently a crucial analytical chemistry challenge: almost 2000 papers were referenced in PubMed in 2018 and 2019 for the keywords "miRNA detection method". MicroRNAs are potential biomarkers for multiple diseases including cancers, neurodegenerative and cardiovascular diseases. Since miRNAs are stably released in bodily fluids, they are of prime interest for the development of non-invasive diagnosis methods, such as liquid biopsies. Their detection is however challenging, as high levels of sensitivity, specificity and robustness are required. The analysis also needs to be quantitative, since the aim is to detect miRNA concentration changes. Moreover, a high multiplexing capability is also of crucial importance, since the clinical potential of miRNAs probably lays in our ability to perform parallel mapping of multiple miRNA concentrations and recognize typical disease signature from this profile. A plethora of biochemical innovative detection methods have been reported recently and some of them provide new solutions to the problem of sensitive multiplex detection. In this review, we propose to analyze in particular the new developments in multiplexed approaches to miRNA detection. The main aspects of these methods (including sensitivity and specificity) will be analyzed, with a particular focus on the demonstrated multiplexing capability and potential of each of these methods.

Extracellular vesicle-associated repetitive element DNAs as candidate osteosarcoma biomarkers

Osteosarcoma (OS) is the most common malignant bone tumor in children and young adults. Despite that high-risk factors have been identified, no test for early detection is available. This study aimed to identify circulating nucleic acid sequences associated with serum extracellular vesicle (EV) preparations at the time of OS diagnosis, as a step towards an OS early detection assay. Sequencing of small nucleic acids extracted from serum EV preparations revealed increased representation of diverse repetitive element sequences in OS patient versus control sera. Analysis of a validation cohort using qPCR of PEG-precipitated EV preparations revealed the over-representation of HSATI, HSATII, LINE1-P1, and Charlie 3 at the DNA but not RNA level, with receiver operating characteristic (ROC) area under the curve (AUC) ≥ 0.90. HSATI and HSATII DNAs co-purified with EVs prepared by precipitation and size exclusion chromatography but not by exosome immunocapture, indicative of packaging in a non-exosomal complex. The consistent over-representation of EV-associated repetitive element DNA sequences suggests their potential utility as biomarkers for OS and perhaps other cancers.

Disome-seq reveals widespread ribosome collisions that promote cotranslational protein folding

BACKGROUND

The folding of proteins is challenging in the highly crowded and sticky environment of a cell. Regulation of translation elongation may play a crucial role in ensuring the correct folding of proteins. Much of our knowledge regarding translation elongation comes from the sequencing of mRNA fragments protected by single ribosomes by ribo-seq. However, larger protected mRNA fragments have been observed, suggesting the existence of an alternative and previously hidden layer of regulation.

RESULTS

In this study, we performed disome-seq to sequence mRNA fragments protected by two stacked ribosomes, a product of translational pauses during which the 5'-elongating ribosome collides with the 3'-paused one. We detected widespread ribosome collisions that are related to slow ribosome release when stop codons are at the A-site, slow peptide bond formation from proline, glycine, asparagine, and cysteine when they are at the P-site, and slow leaving of polylysine from the exit tunnel of ribosomes. The structure of disomes obtained by cryo-electron microscopy suggests a different conformation from the substrate of the ribosome-associated protein quality control pathway. Collisions occurred more frequently in the gap regions between α-helices, where a translational pause can prevent the folding interference from the downstream peptides. Paused or collided ribosomes are associated with specific chaperones, which can aid in the cotranslational folding of the nascent peptides.

CONCLUSIONS

Therefore, cells use regulated ribosome collisions to ensure protein homeostasis.

Combining tRNA sequencing methods to characterize plant tRNA expression and post-transcriptional modification

Differences in tRNA expression have been implicated in a remarkable number of biological processes. There is growing evidence that tRNA genes can play dramatically different roles depending on both expression and post-transcriptional modification, yet sequencing tRNAs to measure abundance and detect modifications remains challenging. Their secondary structure and extensive post-transcriptional modifications interfere with RNA-seq library preparation methods and have limited the utility of high-throughput sequencing technologies. Here, we combine two modifications to standard RNA-seq methods by treating with the demethylating enzyme AlkB and ligating with tRNA-specific adapters in order to sequence tRNAs from four species of flowering plants, a group that has been shown to have some of the most extensive rates of post-transcriptional tRNA modifications. This protocol has the advantage of detecting full-length tRNAs and sequence variants that can be used to infer many post-transcriptional modifications. We used the resulting data to produce a modification index of almost all unique reference tRNAs in Arabidopsis thaliana, which exhibited many anciently conserved similarities with humans but also positions that appear to be 'hot spots' for modifications in angiosperm tRNAs. We also found evidence based on northern blot analysis and droplet digital PCR that, even after demethylation treatment, tRNA-seq can produce highly biased estimates of absolute expression levels most likely due to biased reverse transcription. Nevertheless, the generation of full-length tRNA sequences with modification data is still promising for assessing differences in relative tRNA expression across treatments, tissues or subcellular fractions and help elucidate the functional roles of tRNA modifications.

A Small RNA-Seq Protocol with Less Bias and Improved Capture of 2'-O-Methyl RNAs

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNAs such as plant microRNAs (miRNAs) carry a 2'-O-methyl (2'-OMe) modification at their 3' terminal nucleotide. This modification adds another level of difficulty as it inhibits 3' adapter ligation. We previously demonstrated that modified versions of the "TruSeq (TS)" protocol have less bias and an improved detection of 2'-OMe RNAs. Here we describe in detail protocol "TS5," which showed the best overall performance. We also provide guidelines for bioinformatics analysis of the sequencing data.

Liquid biopsy technologies based on membrane microfluidics: High-yield purification and selective quantification of biomarkers in nanocarriers

Liquid biopsy, screening cancer non-invasively and frequently by detecting and quantifying molecular markers in physiological fluids, would significantly improve cancer survival rate but it remains a distant goal. The key obstacles presented by the highly heterogeneous samples are rapid/high-yield purification and precise/selective marker capture by their antibody and oligo probes. As irregular expressions of these molecular biomarkers are the key signals, quantifying only those from the cancer cells would greatly enhance the performance of the screening tests. The recent discovery that the biomarkers are carried by nanocarriers, such as exosomes, with cell-specific membrane proteins suggests that such selection may be possible, although a new suite of fractionation and quantification technologies would need to be developed. Although under-appreciated, membrane microfluidics has made considerable contributions to resolving these issues. We review the progress made so far, based on ion-selective, track-etched, and gel membranes and advanced electrophoretic and nano-filtration designs, in this perspective and suggest future directions.

A low-bias and sensitive small RNA library preparation method using randomized splint ligation

Small RNAs are important regulators of gene expression and are involved in human development and disease. Next generation sequencing (NGS) allows for scalable, genome-wide studies of small RNA; however, current methods are challenged by low sensitivity and high bias, limiting their ability to capture an accurate representation of the cellular small RNA population. Several studies have shown that this bias primarily arises during the ligation of single-strand adapters during library preparation, and that this ligation bias is magnified by 2′-O-methyl modifications (2′OMe) on the 3′ terminal nucleotide. In this study, we developed a novel library preparation process using randomized splint ligation with a cleavable adapter, a design which resolves previous challenges associated with this ligation strategy. We show that a randomized splint ligation based workflow can reduce bias and increase the sensitivity of small RNA sequencing for a wide variety of small RNAs, including microRNA (miRNA) and tRNA fragments as well as 2′OMe modified RNA, including Piwi-interacting RNA and plant miRNA. Finally, we demonstrate that this workflow detects more differentially expressed miRNA between tumorous and matched normal tissues. Overall, this library preparation process allows for highly accurate small RNA sequencing and will enable studies of 2′OMe modified RNA with new levels of detail.