Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling

miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential expression and uncovers variable differential expression between isomiRs

MicroRNA-seq data is produced by aligning small RNA sequencing reads of different miRNA transcript isoforms, called isomiRs, to known microRNAs. Aggregation to microRNA-level counts discards information and violates core assumptions of differential expression (DE) methods developed for mRNA-seq data. We establish miRglmm, a DE method for microRNA-seq data, that uses a generalized linear mixed model of isomiR-level counts, facilitating detection of miRNA with differential expression or differential isomiR usage. We demonstrate that miRglmm outperforms current DE methods in estimating DE for miRNA, whether or not there is significant isomiR variability, and simultaneously provides estimates of isomiR-level DE.

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.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Full-length tRNAs lacking a functional CCA tail are selectively sorted into the lumen of extracellular vesicles

Small extracellular vesicles (sEVs) are heterogenous lipid membrane particles typically less than 200 nm in size and secreted by most cell types either constitutively or upon activation signals. sEVs isolated from biofluids contain RNAs, including small non-coding RNAs (ncRNAs), that can be either encapsulated within the EV lumen or bound to the EV surface. EV-associated microRNAs (miRNAs) are, despite a relatively low abundance, extensively investigated for their selective incorporation and their role in cell-cell communication. In contrast, the sorting of highly-structured ncRNA species is understudied, mainly due to technical limitations of traditional small RNA sequencing protocols. Here, we adapted ALL-tRNAseq to profile the relative abundance of highly structured and potentially methylated small ncRNA species, including transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and Y RNAs in bulk EV preparations. We determined that full-length tRNAs, typically 75 to 90 nucleotides in length, were the dominant small ncRNA species (>60% of all reads in the 18-120 nucleotides size-range) in all cell culture-derived EVs, as well as in human plasma-derived EV samples, vastly outnumbering 21 nucleotides-long miRNAs. Nearly all EV-associated tRNAs were protected from external RNAse treatment, indicating a location within the EV lumen. Strikingly, the vast majority of luminal-sorted, full-length, nucleobase modification-containing EV-tRNA sequences, harbored a dysfunctional 3' CCA tail, 1 to 3 nucleotides truncated, rendering them incompetent for amino acid loading. In contrast, in non-EV associated extracellular particle fractions (NVEPs), tRNAs appeared almost exclusively fragmented or 'nicked' into tRNA-derived small RNAs (tsRNAs) with lengths between 18 to 35 nucleotides. We propose that in mammalian cells, tRNAs that lack a functional 3' CCA tail are selectively sorted into EVs and shuttled out of the producing cell, offering a new perspective into the physiological role of secreted EVs and luminal cargo-selection.

Highly Multiplexed, Efficient, and Automated Single-Cell MicroRNA Sequencing with Digital Microfluidics

Single-cell microRNA (miRNA) sequencing has allowed for comprehensively studying the abundance and complex networks of miRNAs, which provides insights beyond single-cell heterogeneity into the dynamic regulation of cellular events. Current benchtop-based technologies for single-cell miRNA sequencing are low throughput, limited reaction efficiency, tedious manual operations, and high reagent costs. Here, a highly multiplexed, efficient, integrated, and automated sample preparation platform is introduced for single-cell miRNA sequencing based on digital microfluidics (DMF), named Hiper-seq. The platform integrates major steps and automates the iterative operations of miRNA sequencing library construction by digital control of addressable droplets on the DMF chip. Based on the design of hydrophilic micro-structures and the capability of handling droplets of DMF, multiple single cells can be selectively isolated and subject to sample processing in a highly parallel way, thus increasing the throughput and efficiency for single-cell miRNA measurement. The nanoliter reaction volume of this platform enables a much higher miRNA detection ability and lower reagent cost compared to benchtop methods. It is further applied Hiper-seq to explore miRNAs involved in the ossification of mouse skeletal stem cells after bone fracture and discovered unreported miRNAs that regulate bone repairing.

Small RNA structural biochemistry in a post-sequencing era

High-throughput sequencing has had an enormous impact on small RNA research during the past decade. However, sequencing only offers a one-dimensional view of the transcriptome and is often highly biased. Additionally, the 'sequence, map and annotate' approach, used widely in small RNA research, can lead to flawed interpretations of the data, lacking biological plausibility, due in part to database issues. Even in the absence of technical biases, the loss of three-dimensional information is a major limitation to understanding RNA stability, turnover and function. For example, noncoding RNA-derived fragments seem to exist mainly as dimers, tetramers or as nicked forms of their parental RNAs, contrary to widespread assumptions. In this perspective, we will discuss main sources of bias during small RNA-sequencing, present several useful bias-reducing strategies and provide guidance on the interpretation of small RNA-sequencing results, with emphasis on RNA fragmentomics. As sequencing offers a one-dimensional projection of a four-dimensional reality, prior structure-level knowledge is often needed to make sense of the data. Consequently, while less-biased sequencing methods are welcomed, integration of orthologous experimental techniques is also strongly recommended.

Profiling Small RNA From Brain Extracellular Vesicles in Individuals With Depression

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability with significant mortality risk. Despite progress in our understanding of the etiology of MDD, the underlying molecular changes in the brain remain poorly understood. Extracellular vesicles (EVs) are lipid-bound particles that can reflect the molecular signatures of the tissue of origin. We aimed to optimize a streamlined EV isolation protocol from postmortem brain tissue and determine whether EV RNA cargo, particularly microRNAs (miRNAs), have an MDD-specific profile.

METHODS

EVs were isolated from postmortem human brain tissue. Quality was assessed using western blots, transmission electron microscopy, and microfluidic resistive pulse sensing. EV RNA was extracted and sequenced on Illumina platforms. Functional follow-up was performed in silico.

RESULTS

Quality assessment showed an enrichment of EV markers, as well as a size distribution of 30 to 200 nm in diameter, and no contamination with cellular debris. Small RNA profiling indicated the presence of several RNA biotypes, with miRNAs and transfer RNAs being the most prominent. Exploring miRNA levels between groups revealed decreased expression of miR-92a-3p and miR-129-5p, which was validated by qPCR and was specific to EVs and not seen in bulk tissue. Finally, in silico functional analyses indicate potential roles for these 2 miRNAs in neurotransmission and synaptic plasticity.

CONCLUSION

We provide a streamlined isolation protocol that yields EVs of high quality that are suitable for molecular follow-up. Our findings warrant future investigations into brain EV miRNA dysregulation in MDD.

Defining the activity of pro-reparative extracellular vesicles in wound healing based on miRNA payloads and cell type-specific lineage mapping

Small extracellular vesicles (EVs) are released by cells and deliver biologically active payloads to coordinate the response of multiple cell types in cutaneous wound healing. Here we used a cutaneous injury model as a donor of pro-reparative EVs to treat recipient diabetic obese mice, a model of impaired wound healing. We established a functional screen for microRNAs (miRNAs) that increased the pro-reparative activity of EVs and identified a down-regulation of miR-425-5p in EVs in vivo and in vitro associated with the regulation of adiponectin. We tested a cell type-specific reporter of a tetraspanin CD9 fusion with GFP to lineage map the release of EVs from macrophages in the wound bed, based on the expression of miR-425-5p in macrophage-derived EVs and the abundance of macrophages in EV donor sites. Analysis of different promoters demonstrated that EV release under the control of a macrophage-specific promoter was most abundant and that these EVs were internalized by dermal fibroblasts. These findings suggested that pro-reparative EVs deliver miRNAs, such as miR-425-5p, that stimulate the expression of adiponectin that has insulin-sensitizing properties. We propose that EVs promote intercellular signaling between cell layers in the skin to resolve inflammation, induce proliferation of basal keratinocytes, and accelerate wound closure.

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.

IsoSeek for unbiased and UMI-informed sequencing of miRNAs from low input samples at single-nucleotide resolution

Besides canonical microRNAs (miRNAs), sequence-based variations called isomiRs have biological relevance and diagnostic potential; however, accurate calling of these post-transcriptional modifications is challenging, especially for low input samples. Here, we present IsoSeek, a sequencing protocol that reduces ligation and PCR amplification bias and improves the accuracy of miRNA detection in low input samples. We describe steps for using randomized adapters combined with unique molecular identifiers (UMI), library quantification, and sequencing, followed by detailed procedures for data processing and analysis. For complete details on the use and execution of this protocol, please refer to C. Gómez-Martín et al. (2023)1 and Van Eijndhoven et al. (2021).2.

Construction of a molecular regulatory network related to fat deposition by multi-tissue transcriptome sequencing of Jiaxian red cattle

Intramuscular fat (IMF) refers to the fat that accumulates between muscle bundles or within muscle cells, whose content significantly impacts the taste, tenderness, and flavor of meat products, making it a crucial economic characteristic in livestock production. However, the intricate mechanisms governing IMF deposition, involving non-coding RNAs (ncRNAs), genes, and complex regulatory networks, remain largely enigmatic. Identifying adipose tissue-specific genes and ncRNAs is paramount to unravel these molecular mysteries. This study, conducted on Jiaxian red cattle, harnessed whole transcriptome sequencing to unearth the nuances of circRNAs and miRNAs across seven distinct tissues. The interplay of these ncRNAs was assessed through differential expression analysis and network analysis. These findings are not only pivotal in unveiling the intricacies of fat deposition mechanisms but also lay a robust foundation for future research, setting the stage for enhancing IMF content in Jiaxian red cattle breeding.

Engineering a tunable micropattern-array assay to sort single extracellular vesicles and particles to detect RNA and protein in situ

The molecular heterogeneity of extracellular vesicles (EVs) and the co-isolation of physically similar particles, such as lipoproteins (LPs), confounds and limits the sensitivity of EV bulk biomarker characterization. Herein, we present a single-EV and particle (siEVP) protein and RNA assay (siEVP PRA) to simultaneously detect mRNAs, miRNAs, and proteins in subpopulations of EVs and LPs. The siEVP PRA immobilizes and sorts particles via positive immunoselection onto micropatterns and focuses biomolecular signals in situ. By detecting EVPs at a single-particle resolution, the siEVP PRA outperformed the sensitivities of bulk-analysis benchmark assays for RNA and protein. To assess the specificity of RNA detection in complex biofluids, EVs from various glioma cell lines were processed with small RNA sequencing, whereby two mRNAs and two miRNAs associated with glioblastoma multiforme (GBM) were chosen for cross-validation. Despite the presence of single-EV-LP co-isolates in serum, the siEVP PRA detected GBM-associated vesicular RNA profiles in GBM patient siEVPs. The siEVP PRA effectively examines intravesicular, intervesicular, and interparticle heterogeneity with diagnostic promise.

Discovery of the major 15-30 nt mammalian small RNAs, their biogenesis and function

Small RNAs (sRNAs) within 15-30 nt such as miRNA, tsRNA, srRNA with 3'-OH have been identified. However, whether these sRNAs are the major 15-30 nt sRNAs is still unknown. Here we show about 90% mammalian sRNAs within 15-30 nt end with 2',3'-cyclic phosphate (3'-cP). TANT-seq was developed to simultaneously profile sRNAs with 3'-cP (sRNA-cPs) and sRNA-OHs, and huge amount of sRNA-cPs were detected. Surprisingly, sRNA-cPs and sRNA-OHs usually have distinct sequences. The data from TANT-seq were validated by a novel method termed TE-qPCR, and Northern blot. Furthermore, we found that Angiogenin and RNase 4 contribute to the biogenesis of sRNA-cPs. Moreover, much more sRNA-cPs than sRNA-OHs bind to Ago2, and can regulate gene expression. Particularly, snR-2-cP regulates Bcl2 by targeting to its 3'UTR dependent on Ago2, and subsequently regulates apoptosis. In addition, sRNA-cPs can guide the cleavage of target RNAs in Ago2 complex as miRNAs without the requirement of 3'-cP. Our discovery greatly expands the repertoire of mammalian sRNAs, and provides strategies and powerful tools towards further investigation of sRNA-cPs.

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer-Advances and Challenges

There is an urgent unmet need for robust and reliable biomarkers for early diagnosis, prognosis, and prediction of response to specific treatments of many aggressive and deadly cancers, such as pancreatic cancer, and liquid biopsy-based miRNA profiling has the potential for this. MiRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many cancers, functioning as either oncomes or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling of dysregulated miRNAs in pancreatic cancer has been shown to correlate with disease diagnosis, indicate optimal treatment options and predict response to a specific therapy. Specific miRNA signatures can track the stages of pancreatic cancer and hold potential as diagnostic, prognostic, and predictive markers, as well as therapeutics such as miRNA mimics and miRNA inhibitors (antagomirs). Furthermore, identified specific miRNAs and genes they regulate in pancreatic cancer along with downstream pathways can be used as potential therapeutic targets. However, a limited understanding and validation of the specific roles of miRNAs, lack of tissue specificity, methodological, technical, or analytical reproducibility, harmonization of miRNA isolation and quantification methods, the use of standard operating procedures, and the availability of automated and standardized assays to improve reproducibility between independent studies limit bench-to-bedside translation of the miRNA biomarkers for clinical applications. Here I review recent findings on miRNAs in pancreatic cancer pathogenesis and their potential as diagnostic, prognostic, and predictive markers.

Exosome-derived long noncoding RNAs: Mediators of host-Plasmodium parasite communication

Overcoming challenges associated with malaria eradication proves to be a formidable task due to the complicated life cycle exhibited by the malaria parasite and the lack of safe and enduring vaccines against malaria. Investigating the interplay between Plasmodium parasites and their mammalian hosts is crucial for the development of novel vaccines. Long noncoding RNAs (lncRNAs) derived from Plasmodium parasites or host cells have emerged as potential signaling molecules involved in the trafficking of proteins, RNA (mRNAs, miRNAs, and ncRNAs), and DNA. These lncRNAs facilitate the interaction between hosts and parasites, impacting normal physiology or pathology in malaria-infected individuals. Moreover, they possess the capacity to regulate immune responses and associated signaling pathways, thus potentially influencing chromatin organization, epigenetic modifications, mRNA processing, splicing, and translation. However, the functional role of exosomal lncRNAs in malaria remains poorly understood. This review offers a comprehensive analysis of lncRNA and exosomal lncRNA profiles during malaria infection. It presents an overview of recent progress in elucidating the involvement of exosomal lncRNAs in host-parasite interactions. Additionally, potential exosomal lncRNAs linked to the domains of innate and adaptive immunity in the context of malaria are proposed. These findings may contribute to the discovery of new diagnostic and therapeutic strategies for malaria. Furthermore, the need for additional research was highlighted that aimed to elucidate the mechanisms underlying lncRNA transportation into host cells and their targeting of specific genes to regulate the host's immune response. This knowledge gap presents an opportunity for future investigations, offering innovative approaches to enhance malarial control. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA in Disease and Development > RNA in Disease.

Efficient Metabolic Fingerprinting of Follicular Fluid Encodes Ovarian Reserve and Fertility

Ovarian reserve (OR) and fertility are critical in women's healthcare. Clinical methods for encoding OR and fertility rely on the combination of tests, which cannot serve as a multi-functional platform with limited information from specific biofluids. Herein, metabolic fingerprinting of follicular fluid (MFFF) from follicles is performed, using particle-assisted laser desorption/ionization mass spectrometry (PALDI-MS) to encode OR and fertility. PALDI-MS allows efficient MFFF, showing fast speed (≈30 s), high sensitivity (≈60 fmol), and desirable reproducibility (coefficients of variation <15%). Further, machine learning of MFFF is applied to diagnose diminished OR (area under the curve of 0.929) and identify high-quality oocytes/embryos (p < 0.05) by a single PALDI-MS test. Meanwhile, metabolic biomarkers from MFFF are identified, which also determine oocyte/embryo quality (p < 0.05) from the sampling follicles toward fertility prediction in clinics. This approach offers a powerful platform in women's healthcare, not limited to OR and fertility.

The translational landscape of human vascular smooth muscle cells identifies novel short open reading frame-encoded peptide regulators for phenotype alteration

AIMS

The plasticity of vascular smooth muscle cells (VSMCs) enables them to alter phenotypes under various physiological and pathological stimuli. The alteration of VSMC phenotype is a key step in vascular diseases, including atherosclerosis. Although the transcriptome shift during VSMC phenotype alteration has been intensively investigated, uncovering multiple key regulatory signalling pathways, the translatome dynamics in this cellular process, remain largely unknown. Here, we explored the genome-wide regulation at the translational level of human VSMCs during phenotype alteration.

METHODS AND RESULTS

We generated nucleotide-resolution translatome and transcriptome data from human VSMCs undergoing phenotype alteration. Deep sequencing of ribosome-protected fragments (Ribo-seq) revealed alterations in protein synthesis independent of changes in messenger ribonucleicacid levels. Increased translational efficiency of many translational machinery components, including ribosomal proteins, eukaryotic translation elongation factors and initiation factors were observed during the phenotype alteration of VSMCs. In addition, hundreds of candidates for short open reading frame-encoded polypeptides (SEPs), a class of peptides containing 200 amino acids or less, were identified in a combined analysis of translatome and transcriptome data with a high positive rate in validating their coding capability. Three evolutionarily conserved SEPs were further detected endogenously by customized antibodies and suggested to participate in the pathogenesis of atherosclerosis by analysing the transcriptome and single cell RNA-seq data from patient atherosclerotic artery samples. Gain- and loss-of-function studies in human VSMCs and genetically engineered mice showed that these SEPs modulate the alteration of VSMC phenotype through different signalling pathways, including the mitogen-activated protein kinase pathway and p53 pathway.

CONCLUSION

Our study indicates that an increase in the capacity of translation, which is attributable to an increased quantity of translational machinery components, mainly controls alterations of VSMC phenotype at the level of translational regulation. In addition, SEPs could function as important regulators in the phenotype alteration of human VSMCs.

Multisite assessment of reproducibility in high-content cell migration imaging data

High-content image-based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high-quality open-access data sharing and meta-analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy, have not been systematically investigated. Here, using high-content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image analysis of perturbation effects and meta-analysis depend on standardized procedures combined with batch correction.

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.

Reassessment of miRNA variant (isomiRs) composition by small RNA sequencing

IsomiRs, sequence variants of mature microRNAs, are usually detected and quantified using high-throughput sequencing. Many examples of their biological relevance have been reported, but sequencing artifacts identified as artificial variants might bias biological inference and therefore need to be ideally avoided. We conducted a comprehensive evaluation of 10 different small RNA sequencing protocols, exploring both a theoretically isomiR-free pool of synthetic miRNAs and HEK293T cells. We calculated that, with the exception of two protocols, less than 5% of miRNA reads can be attributed to library preparation artifacts. Randomized-end adapter protocols showed superior accuracy, with 40% of true biological isomiRs. Nevertheless, we demonstrate concordance across protocols for selected miRNAs in non-templated uridyl additions. Notably, NTA-U calling and isomiR target prediction can be inaccurate when using protocols with poor single-nucleotide resolution. Our results highlight the relevance of protocol choice for biological isomiRs detection and annotation, which has key potential implications for biomedical applications.

Dynamic transcriptomic responses to divergent acute exercise stimuli in young adults

Acute exercise elicits dynamic transcriptional changes that, when repeated, form the fundamental basis of health, resilience, and performance adaptations. While moderate-intensity endurance training combined with conventional resistance training (traditional, TRAD) is often prescribed and recommended by public health guidance, high-intensity training combining maximal-effort intervals with intensive, limited-rest resistance training is a time-efficient alternative that may be used tactically (HITT) to confer similar benefits. Mechanisms of action of these distinct stimuli are incompletely characterized and have not been directly compared. We assessed transcriptome-wide responses in skeletal muscle and circulating extracellular vesicles (EVs) to a single exercise bout in young adults randomized to TRAD (n = 21, 12 M/9 F, 22 ± 3 yr) or HITT (n = 19, 11 M/8 F, 22 ± 2 yr). Next-generation sequencing captured small, long, and circular RNA in muscle and EVs. Analysis identified differentially expressed transcripts (|log2FC|>1, FDR ≤ 0.05) immediately (h0, EVs only), h3, and h24 postexercise within and between exercise protocols. In aaddition, all apparently responsive transcripts (FDR < 0.2) underwent singular value decomposition to summarize data structures into latent variables (LVs) to deconvolve molecular expression circuits and interregulatory relationships. LVs were compared across time and exercise protocol. TRAD, a longer but less intense stimulus, generally elicited a stronger transcriptional response than HITT, but considerable overlap and key differences existed. Findings reveal shared and unique molecular responses to the exercise stimuli and lay groundwork toward establishing relationships between protein-coding genes and lesser-understood transcripts that serve regulatory roles following exercise. Future work should advance the understanding of these circuits and whether they repeat in other populations or following other types of exercise/stress.NEW & NOTEWORTHY We examined small and long transcriptomics in skeletal muscle and serum-derived extracellular vesicles before and after a single exposure to traditional combined exercise (TRAD) and high-intensity tactical training (HITT). Across 40 young adults, we found more consistent protein-coding gene responses to TRAD, whereas HITT elicited differential expression of microRNA enriched in brain regions. Follow-up analysis revealed relationships and temporal dynamics across transcript networks, highlighting potential avenues for research into mechanisms of exercise response and adaptation.

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.

An Introduction to Nanopore Sequencing: Past, Present, and Future Considerations

There has been significant progress made in the field of nanopore biosensor development and sequencing applications, which address previous limitations that restricted widespread nanopore use. These innovations, paired with the large-scale commercialization of biological nanopore sequencing by Oxford Nanopore Technologies, are making the platforms a mainstay in contemporary research laboratories. Equipped with the ability to provide long- and short read sequencing information, with quick turn-around times and simple sample preparation, nanopore sequencers are rapidly improving our understanding of unsolved genetic, transcriptomic, and epigenetic problems. However, there remain some key obstacles that have yet to be improved. In this review, we provide a general introduction to nanopore sequencing principles, discussing biological and solid-state nanopore developments, obstacles to single-base detection, and library preparation considerations. We present examples of important clinical applications to give perspective on the potential future of nanopore sequencing in the field of molecular diagnostics.

The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing

Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.

Single-base resolution mapping of 2′-O-methylation sites by an exoribonuclease-enriched chemical method

2'-O-methylation (Nm) is one of the most abundant RNA epigenetic modifications and plays a vital role in the post-transcriptional regulation of gene expression. Current Nm mapping approaches are normally limited to highly abundant RNAs and have significant technical hurdles in mRNAs or relatively rare non-coding RNAs (ncRNAs). Here, we developed a new method for enriching Nm sites by using RNA exoribonuclease and periodate oxidation reactivity to eliminate 2'-hydroxylated (2'-OH) nucleosides, coupled with sequencing (Nm-REP-seq). We revealed several novel classes of Nm-containing ncRNAs as well as mRNAs in humans, mice, and drosophila. We found that some novel Nm sites are present at fixed positions in different tRNAs and are potential substrates of fibrillarin (FBL) methyltransferase mediated by snoRNAs. Importantly, we discovered, for the first time, that Nm located at the 3'-end of various types of ncRNAs and fragments derived from them. Our approach precisely redefines the genome-wide distribution of Nm and provides new technologies for functional studies of Nm-mediated gene regulation.

Attomolar sensitivity microRNA detection using real-time digital microarrays

MicroRNAs (miRNAs) are a family of noncoding, functional RNAs. With recent developments in molecular biology, miRNA detection has attracted significant interest, as hundreds of miRNAs and their expression levels have shown to be linked to various diseases such as infections, cardiovascular disorders and cancers. A powerful and high throughput tool for nucleic acid detection is the DNA microarray technology. However, conventional methods do not meet the demands in sensitivity and specificity, presenting significant challenges for the adaptation of miRNA detection for diagnostic applications. In this study, we developed a highly sensitive and multiplexed digital microarray using plasmonic gold nanorods as labels. For proof of concept studies, we conducted experiments with two miRNAs, miRNA-451a (miR-451) and miRNA-223-3p (miR-223). We demonstrated improvements in sensitivity in comparison to traditional end-point assays that employ capture on solid phase support, by implementing real-time tracking of the target molecules on the sensor surface. Particle tracking overcomes the sensitivity limitations for detection of low-abundance biomarkers in the presence of low-affinity but high-abundance background molecules, where endpoint assays fall short. The absolute lowest measured concentration was 100 aM. The measured detection limit being well above the blank samples, we performed theoretical calculations for an extrapolated limit of detection (LOD). The dynamic tracking improved the extrapolated LODs from femtomolar range to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}∼ 10 attomolar (less than 1300 copies in 0.2 ml of sample) for both miRNAs and the total incubation time was decreased from 5 h to 35 min.

Small and long RNA transcriptome of whole human cerebrospinal fluid and serum as compared to their extracellular vesicle fractions reveal profound differences in expression patterns and impacts on biological processes

BACKGROUND

Next generation sequencing (NGS) of human specimen is expected to improve prognosis and diagnosis of human diseases, but its sensitivity urges for well-defined sampling and standardized protocols in order to avoid error-prone conclusions.

METHODS

In this study, large volumes of pooled human cerebrospinal fluid (CSF) were used to prepare RNA from human CSF-derived extracellular vesicles (EV) and from whole CSF, as well as from whole human serum and serum-derived EV. In all four fractions small and long coding and non-coding RNA expression was analyzed with NGS and transcriptome analyses.

RESULTS

We show, that the source of sampling has a large impact on the acquired NGS pattern, and differences between small RNA fractions are more distinct than differences between long RNA fractions. The highest percentual discrepancy between small RNA fractions and the second highest difference between long RNA fractions is seen in the comparison of CSF-derived EV and whole CSF. Differences between miR (microRNA) and mRNA fractions of EV and the respective whole body fluid have the potential to affect different cellular and biological processes. I.e. a comparison of miR in both CSF fractions reveals that miR from EV target four transcripts sets involved in neurobiological processes, whereas eight others, also involved in neurobiological processes are targeted by miR found in whole CSF only. Likewise, three mRNAs sets derived from CSF-derived EV are associated with neurobiological and six sets with mitochondrial metabolism, whereas no such mRNA transcript sets are found in the whole CSF fraction. We show that trace amounts of blood-derived contaminations of CSF can bias RNA-based CSF diagnostics.

CONCLUSIONS

This study shows that the composition of small and long RNA differ significantly between whole body fluid and its respective EV fraction and thus can affect different cellular and molecular functions. Trace amounts of blood-derived contaminations of CSF can bias CSF analysis. This has to be considered for a meaningful RNA-based diagnostics. Our data imply a transport of EV from serum to CSF across the blood-brain barrier.

A curated human cellular microRNAome based on 196 primary cell types

Background

An incomplete picture of the expression distribution of microRNAs (miRNAs) across human cell types has long hindered our understanding of this important regulatory class of RNA. With the continued increase in available public small RNA sequencing datasets, there is an opportunity to more fully understand the general distribution of miRNAs at the cell level.

Results

From the NCBI Sequence Read Archive, we obtained 6,054 human primary cell datasets and processed 4,184 of them through the miRge3.0 small RNA sequencing alignment software. This dataset was curated down, through shared miRNA expression patterns, to 2,077 samples from 196 unique cell types derived from 175 separate studies. Of 2,731 putative miRNAs listed in miRBase (v22.1), 2,452 (89.8%) were detected. Among reasonably expressed miRNAs, 108 were designated as cell specific/near specific, 59 as infrequent, 52 as frequent, 54 as near ubiquitous, and 50 as ubiquitous. The complexity of cellular microRNA expression estimates recapitulates tissue expression patterns and informs on the miRNA composition of plasma.

Conclusions

This study represents the most complete reference, to date, of miRNA expression patterns by primary cell type. The data are available through the human cellular microRNAome track at the UCSC Genome Browser (https://genome.ucsc.edu/cgi-bin/hgHubConnect) and an R/Bioconductor package (https://bioconductor.org/packages/microRNAome/).

Phase 2 of extracellular RNA communication consortium charts next-generation approaches for extracellular RNA research

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

Cloning and Sequencing Eukaryotic Small RNAs

Small RNAs are ubiquitous regulators of gene expression that participate in nearly all aspects of physiology in a wide range of organisms. There are many different classes of eukaryotic small RNAs that play regulatory roles at every level of gene expression, including transcription, RNA stability, and translation. While eukaryotic small RNAs display diverse functions across and within classes, they are generally grouped functionally based on the machinery required for their biogenesis, the effector proteins they associate with, and their molecular characteristics. The development of techniques to clone and sequence small RNAs has been critical for their identification, yet the ligation-dependent addition of RNA adapters and the use of reverse transcriptase to generate cDNA in traditional library preparation protocols can be unsuitable to detect certain small RNA subtypes. In particular, 3' or 5' chemical modifications that are characteristic of specific types of small RNAs can impede the ligation-dependent addition of RNA adapters, while internal RNA modifications can interfere with accurate reverse transcription. The inability to clone certain small RNA subtypes with traditional protocols results in an inaccurate assessment of small RNA abundance and diversity, where some RNAs appear over-represented and others are not detected. This overview aims to guide users on how to design small RNA cloning workflows in eukaryotes to more accurately capture specific small RNAs of interest. Hence, we discuss the molecular biology underlying the identification and quantitation of small RNAs, explore the limitations of commonly used protocols, and detail the alternative approaches that can be used to enrich specific small RNA classes. © 2022 Wiley Periodicals LLC.

Polyadenylation ligation-mediated sequencing (PALM-Seq) characterizes cell-free coding and non-coding RNAs in human biofluids

Background

Cell‐free messenger RNA (cf‐mRNA) and long non‐coding RNA (cf‐lncRNA) are becoming increasingly important in liquid biopsy by providing biomarkers for disease prediction, diagnosis and prognosis, but the simultaneous characterization of coding and non‐coding RNAs in human biofluids remains challenging.

Methods

Here, we developed polyadenylation ligation‐mediated sequencing (PALM‐Seq), an RNA sequencing strategy employing treatment of RNA with T4 polynucleotide kinase to generate cell‐free RNA (cfRNA) fragments with 5′ phosphate and 3′ hydroxyl and RNase H to deplete abundant RNAs, achieving simultaneous quantification and characterization of cfRNAs.

Results

Using PALM‐Seq, we successfully identified well‐known differentially abundant mRNA, lncRNA and microRNA in the blood plasma of pregnant women. We further characterized cfRNAs in blood plasma, saliva, urine, seminal plasma and amniotic fluid and found that the detected numbers of different RNA biotypes varied with body fluids. The profiles of cf‐mRNA reflected the function of originated tissues, and immune cells significantly contributed RNA to blood plasma and saliva. Short fragments (<50 nt) of mRNA and lncRNA were major in biofluids, whereas seminal plasma and amniotic fluid tended to retain long RNA. Body fluids showed distinct preferences of pyrimidine at the 3′ end and adenine at the 5′ end of cf‐mRNA and cf‐lncRNA, which were correlated with the proportions of short fragments.

Conclusion

Together, PALM‐Seq enables a simultaneous characterization of cf‐mRNA and cf‐lncRNA, contributing to elucidating the biology and promoting the application of cfRNAs.

Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis

Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients' plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids.

Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review

Traumatic brain injury (TBI) is not a single disease state but describes an array of conditions associated with insult or injury to the brain. While some individuals with TBI recover within a few days or months, others present with persistent symptoms that can cause disability, neuropsychological trauma, and even death. Understanding, diagnosing, and treating TBI is extremely complex for many reasons, including the variable biomechanics of head impact, differences in severity and location of injury, and individual patient characteristics. Because of these confounding factors, the development of reliable diagnostics and targeted treatments for brain injury remains elusive. We argue that the development of effective diagnostic and therapeutic strategies for TBI requires a deep understanding of human neurophysiology at the molecular level and that the framework of multiomics may provide some effective solutions for the diagnosis and treatment of this challenging condition. To this end, we present here a comprehensive review of TBI biomarker candidates from across the multiomic disciplines and compare them with known signatures associated with other neuropsychological conditions, including Alzheimer’s disease and Parkinson’s disease. We believe that this integrated view will facilitate a deeper understanding of the pathophysiology of TBI and its potential links to other neurological diseases.

Circular RNA circ_0047744 suppresses the metastasis of pancreatic ductal adenocarcinoma by regulating the miR-21/SOCS5 axis

There is increasing evidence that circular RNAs (circRNAs) can serve as microRNA (miRNA) sponges to regulate metastasis of multiple tumors, including pancreatic ductal adenocarcinoma (PDAC). However, the role of the circRNA/miRNA regulatory network in metastasis of PDAC has not been elucidated. The purpose of this study is to explore the role of circ_0047744/miR-21/SOCS5 in the metastasis of PDAC. We found that circRNA_0047744 was weakly expressed in PDAC tissues and cell lines. The expression of circ_0047744 was negatively correlated with lymph node metastasis and positively correlated with overall survival in PDAC patients. Functionally, the overexpression of circ_0047744 suppressed cell migration and invasion in vitro and in vivo. Mechanistically, circ_0047744 could regulate SOCS5 expression by acting as a sponge of miR-21 to inhibit migration and invasion of PDAC cells. Our study demonstrates that circ_0047744 acts as an anti-oncogene to inhibit PDAC metastasis by regulating the miR-21/SOCS5 axis, indicating that circ_0047744 may be a potential novel therapeutic target for PDAC patients.

miRNA/mRNA co-profiling identifies the miR-200 family as a central regulator of SMC quiescence

miRNAs are versatile regulators of smooth muscle cell (SMC) fate and behavior in vascular development and disease. Targeted loss-of-function studies have established the relevance of specific miRNAs in controlling SMC differentiation or mediating phenotypic modulation. Our goal was to characterize SMC miRNAome and its contribution to transcriptome changes during phenotypic modulation. Small RNA sequencing revealed that dedifferentiation led to the differential expression of over 50 miRNAs in cultured SMC. miRNA/mRNA comparison predicted that over a third of SMC transcript expression was regulated by differentially expressed miRNAs. Our screen identified the miR-200 cluster as highly downregulated during dedifferentiation. miR-200 maintains SMC quiescence and represses proliferation, migration, and neointima formation, in part by targeting Quaking, a central SMC phenotypic switching mediator. Our study unraveled the substantial contribution of miRNAs in regulating the SMC transcriptome and identified the miR-200 cluster as a pro-quiescence mechanism and a potential inhibitor of vascular restenosis.

An Expanded Landscape of Unusually Short RNAs in 11 Samples from Six Eukaryotic Organisms

Small RNA sequencing (sRNA-Seq) approaches unveiled sequences derived from longer non-coding RNAs, such as transfer RNA (tRNA) and ribosomal RNA (rRNA) fragments, known as tRFs and rRFs, respectively. However, rRNAs and RNAs shorter than 16 nt are often depleted from library preparations/sequencing analyses, although they may be functional. Here, we sought to obtain a complete repertoire of small RNAs by sequencing the total RNA from 11 samples of 6 different eukaryotic organisms, from yeasts to human, in an extended 8- to 30-nt window of RNA length. The 8- to 15-nt window essentially contained fragments of longer non-coding RNAs, such as microRNAs, PIWI-associated RNAs (piRNAs), small nucleolar RNAs (snoRNAs), tRNAs and rRNAs. Notably, unusually short RNAs < 16 nt were more abundant than those >16 nt in bilaterian organisms. A new RT-qPCR method confirmed that two unusually short rRFs of 12 and 13 nt were more overly abundant (~3-log difference) than two microRNAs. We propose to not deplete rRNA and to reduce the lower threshold of RNA length to include unusually short RNAs in sRNA-Seq analyses and datasets, as their abundance and diversity support their potential role and importance as biomarkers of disease and/or mediators of cellular function.

Extracellular Vesicles and Their Emerging Roles as Cellular Messengers in Endocrinology: An Endocrine Society Scientific Statement

During the last decade, there has been great interest in elucidating the biological role of extracellular vesicles (EVs), particularly, their hormone-like role in cell-to-cell communication. The field of endocrinology is uniquely placed to provide insight into the functions of EVs, which are secreted from all cells into biological fluids and carry endocrine signals to engage in paracellular and distal interactions. EVs are a heterogeneous population of membrane-bound vesicles of varying size, content, and bioactivity. EVs are specifically packaged with signaling molecules, including lipids, proteins, and nucleic acids, and are released via exocytosis into biofluid compartments. EVs regulate the activity of both proximal and distal target cells, including translational activity, metabolism, growth, and development. As such, EVs signaling represents an integral pathway mediating intercellular communication. Moreover, as the content of EVs is cell-type specific, it is a "fingerprint" of the releasing cell and its metabolic status. Recently, changes in the profile of EV and bioactivity have been described in several endocrine-related conditions including diabetes, obesity, cardiovascular diseases, and cancer. The goal of this statement is to highlight relevant aspects of EV research and their potential role in the field of endocrinology.

Advances in the development of new biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is a complex, heterogeneous, progressive disease and is the most common type of neurodegenerative dementia. The prevalence of AD is expected to increase as the population ages, placing an additional burden on national healthcare systems. There is a large need for new diagnostic tests that can detect AD at an early stage with high specificity at relatively low cost. The development of modern analytical diagnostic tools has made it possible to determine several biomarkers of AD with high specificity, including pathogenic proteins, markers of synaptic dysfunction, and markers of inflammation in the blood. There is a considerable potential in using microRNA (miRNA) as markers of AD, and diagnostic studies based on miRNA panels suggest that AD could potentially be determined with high accuracy for individual patients. Studies of the retina with improved methods of visualization of the fundus are also showing promising results for the potential diagnosis of the disease. This review focuses on the recent developments of blood, plasma, and ocular biomarkers for the diagnosis of AD.

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.

Nucleic acid liquid biopsies in Alzheimer's disease: current state, challenges, and opportunities

Alzheimer's disease (AD) is the most common neurodegenerative disease and affects persons of all races, ethnic groups, and sexes. The disease is characterized by neuronal loss leading to cognitive decline and memory loss. There is no cure and the effectiveness of existing treatments is limited and depends on the time of diagnosis. The long prodromal period, during which patients' ability to live a normal life is not affected despite neuronal loss, often leads to a delayed diagnosis because it can be mistaken for normal aging of the brain. In order to make a substantial impact on AD patient survival, early diagnosis may provide a greater therapeutic window for future therapies to slow AD-associated neurodegeneration. Current gold standards for disease detection include magnetic resonance imaging and positron emission tomography scans, which visualize amyloid β and phosphorylated tau depositions and aggregates. Liquid biopsies, already an active field of research in precision oncology, are hypothesized to provide early disease detection through minimally or non-invasive sample collection techniques. Liquid biopsies in AD have been studied in cerebrospinal fluid, blood, ocular, oral, and olfactory fluids. However, most of the focus has been on blood and cerebrospinal fluid due to biomarker specificity and sensitivity attributed to the effects of the blood-brain barrier and inter-laboratory variation during sample collection. Many studies have identified amyloid β and phosphorylated tau levels as putative biomarkers, however, advances in next-generation sequencing-based liquid biopsy methods have led to significant interest in identifying nucleic acid species associated with AD from liquid tissues. Differences in cell-free RNAs and DNAs have been described as potential biomarkers for AD and hold the potential to affect disease diagnosis, treatment, and future research avenues.

Prime-seq, efficient and powerful bulk RNA sequencing

Cost-efficient library generation by early barcoding has been central in propelling single-cell RNA sequencing. Here, we optimize and validate prime-seq, an early barcoding bulk RNA-seq method. We show that it performs equivalently to TruSeq, a standard bulk RNA-seq method, but is fourfold more cost-efficient due to almost 50-fold cheaper library costs. We also validate a direct RNA isolation step, show that intronic reads are derived from RNA, and compare cost-efficiencies of available protocols. We conclude that prime-seq is currently one of the best options to set up an early barcoding bulk RNA-seq protocol from which many labs would profit.

A Novel Tissue Atlas and Online Tool for the Interrogation of Small RNA Expression in Human Tissues and Biofluids

One promising goal for utilizing the molecular information circulating in biofluids is the discovery of clinically useful biomarkers. Extracellular RNAs (exRNAs) are one of the most diverse classes of molecular cargo, easily assayed by sequencing and with expressions that rapidly change in response to subject status. Despite diverse exRNA cargo, most evaluations from biofluids have focused on small RNA sequencing and analysis, specifically on microRNAs (miRNAs). Another goal of characterizing circulating molecular information, is to correlate expression to injuries associated with specific tissues of origin. Biomarker candidates are often described as being specific, enriched in a particular tissue or associated with a disease process. Likewise, miRNA data is often reported to be specific, enriched for a tissue, without rigorous testing to support the claim. Here we provide a tissue atlas of small RNAs from 30 different tissues and three different blood cell types. We analyzed the tissues for enrichment of small RNA sequences and assessed their expression in biofluids: plasma, cerebrospinal fluid, urine, and saliva. We employed published data sets representing physiological (resting vs. acute exercise) and pathologic states (early- vs. late-stage liver fibrosis, and differential subtypes of stroke) to determine differential tissue-enriched small RNAs. We also developed an online tool that provides information about exRNA sequences found in different biofluids and tissues. The data can be used to better understand the various types of small RNA sequences in different tissues as well as their potential release into biofluids, which should help in the validation or design of biomarker studies.

Global MicroRNA Profiling of Vascular Endothelial Cells

MicroRNA sequencing (miRNA-seq) enables the detection and characterization of the cell miRNome, including miRNA isoforms (isomiRs) and novel miRNA species. In roughly half of the cases, the most abundant isomiR in the cells is not the reference miRNA given in miRBase, which highlights the importance of isomiR-specific analysis. Here, we describe a gel-free protocol for global miRNA profiling in vascular endothelial cells and the main steps of the subsequent data analysis with two alternative analysis methods. In addition to endothelial cells, the protocol is suitable for other cell and tissue types and has been successfully used to obtain miRNA-seq data from human cardiac tissue, plasma, pericardial fluid, and biofluid exosomes.

Low-bias ncRNA libraries using ordered two-template relay: Serial template jumping by a modified retroelement reverse transcriptase

Retrotransposons are noninfectious, mobile genetic elements that proliferate in host genomes via an RNA intermediate that is copied into DNA by a reverse transcriptase (RT) enzyme. RTs are important for biotechnological applications involving information capture from RNA since RNA is first converted into complementary DNA for detection or sequencing. Here, we biochemically characterized RTs from two retroelements and uncovered several activities that allowed us to design a streamlined, efficient workflow for determining the inventory of RNA sequences in processed RNA pools. The unique properties of nonretroviral RT activities obviate many technical issues associated with current methods of RNA sequence analysis, with wide applications in research, biotechnology, and diagnostics.

Selfish, non-long terminal repeat (non-LTR) retroelements and mobile group II introns encode reverse transcriptases (RTs) that can initiate DNA synthesis without substantial base pairing of primer and template. Biochemical characterization of these enzymes has been limited by recombinant expression challenges, hampering understanding of their properties and the possible exploitation of their properties for research and biotechnology. We investigated the activities of representative RTs using a modified non-LTR RT from Bombyx mori and a group II intron RT from Eubacterium rectale. Only the non-LTR RT supported robust and serial template jumping, producing one complementary DNA (cDNA) from several templates each copied end to end. We also discovered an unexpected terminal deoxynucleotidyl transferase activity of the RTs that adds nucleotide(s) of choice to 3′ ends of single- and/or double-stranded RNA or DNA. Combining these two types of activity with additional insights about nontemplated nucleotide additions to duplexed cDNA product, we developed a streamlined protocol for fusion of next-generation sequencing adaptors to both cDNA ends in a single RT reaction. When benchmarked using a reference pool of microRNAs (miRNAs), library production by Ordered Two-Template Relay (OTTR) using recombinant non-LTR retroelement RT outperformed all commercially available kits and rivaled the low bias of technically demanding home-brew protocols. We applied OTTR to inventory RNAs purified from extracellular vesicles, identifying miRNAs as well as myriad other noncoding RNAs (ncRNAs) and ncRNA fragments. Our results establish the utility of OTTR for automation-friendly, low-bias, end-to-end RNA sequence inventories of complex ncRNA samples.

miRge3.0: a comprehensive microRNA and tRF sequencing analysis pipeline

MicroRNAs and tRFs are classes of small non-coding RNAs, known for their roles in translational regulation of genes. Advances in next-generation sequencing (NGS) have enabled high-throughput small RNA-seq studies, which require robust alignment pipelines. Our laboratory previously developed miRge and miRge2.0, as flexible tools to process sequencing data for annotation of miRNAs and other small-RNA species and further predict novel miRNAs using a support vector machine approach. Although miRge2.0 is a leading analysis tool in terms of speed with unique quantifying and annotation features, it has a few limitations. We present miRge3.0 that provides additional features along with compatibility to newer versions of Cutadapt and Python. The revisions of the tool include the ability to process Unique Molecular Identifiers (UMIs) to account for PCR duplicates while quantifying miRNAs in the datasets, correct erroneous single base substitutions in miRNAs with miREC and an accurate mirGFF3 formatted isomiR tool. miRge3.0 also has speed improvements benchmarked to miRge2.0, Chimira and sRNAbench. Finally, miRge3.0 output integrates into other packages for a streamlined analysis process and provides a cross-platform Graphical User Interface (GUI). In conclusion miRge3.0 is our third generation small RNA-seq aligner with improvements in speed, versatility and functionality over earlier iterations.

Biomarkers and Lung Cancer Early Detection: State of the Art

Simple Summary

Lung cancer is the leading cause of cancer death worldwide. Detecting lung malignancies promptly is essential for any anticancer treatment to reduce mortality and morbidity, especially in high-risk individuals. The use of liquid biopsy to detect circulating biomarkers such as RNA, microRNA, DNA, proteins, autoantibodies in the blood, as well as circulating tumor cells (CTCs), can substantially change the way we manage lung cancer patients by improving disease stratification using intrinsic molecular characteristics, identification of therapeutic targets and monitoring molecular residual disease. Here, we made an update on recent developments in liquid biopsy-based biomarkers for lung cancer early diagnosis, and we propose guidelines for an accurate study design, execution, and data interpretation for biomarker development.

Abstract

Lung cancer burden is increasing, with 2 million deaths/year worldwide. Current limitations in early detection impede lung cancer diagnosis when the disease is still localized and thus more curable by surgery or multimodality treatment. Liquid biopsy is emerging as an important tool for lung cancer early detection and for monitoring therapy response. Here, we reviewed recent advances in liquid biopsy for early diagnosis of lung cancer. We summarized DNA- or RNA-based biomarkers, proteins, autoantibodies circulating in the blood, as well as circulating tumor cells (CTCs), and compared the most promising studies in terms of biomarkers prediction performance. While we observed an overall good performance for the proposed biomarkers, we noticed some critical aspects which may complicate the successful translation of these biomarkers into the clinical setting. We, therefore, proposed a roadmap for successful development of lung cancer biomarkers during the discovery, prioritization, and clinical validation phase. The integration of innovative minimally invasive biomarkers in screening programs is highly demanded to augment lung cancer early detection.

MicroRNAs, damage levels, and DNA damage response control

DNA damage-inducible miRNAs are likely to be functional in the DNA damage response. This response can elicit damage resolution and cell survival or apoptosis. The current, albeit incomplete, picture suggests that miRNAs can affect cell fate via modulation of key response proteins, but the question is, who's in charge?

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.

A microRNA expression and regulatory element activity atlas of the mouse immune system

To better define the control of immune system regulation, we generated an atlas of microRNA (miRNA) expression from 63 mouse immune cell populations and connected these signatures with assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation followed by sequencing (ChIP-seq) and nascent RNA profiles to establish a map of miRNA promoter and enhancer usage in immune cells. miRNA complexity was relatively low, with >90% of the miRNA compartment of each population comprising <75 miRNAs; however, each cell type had a unique miRNA signature. Integration of miRNA expression with chromatin accessibility revealed putative regulatory elements for differentially expressed miRNAs, including miR-21a, miR-146a and miR-223. The integrated maps suggest that many miRNAs utilize multiple promoters to reach high abundance and identified dominant and divergent miRNA regulatory elements between lineages and during development that may be used by clustered miRNAs, such as miR-99a/let-7c/miR-125b, to achieve distinct expression. These studies, with web-accessible data, help delineate the cis-regulatory elements controlling miRNA signatures of the immune system.