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Background Next-Generation Sequencing (NGS) catalyzed breakthroughs across various scientific domains. Illumina’s sequencing by synthesis method has long been central to NGS, but new sequencing methods like Element Biosciences’ AVITI technology are emerging. AVITI is reported to offer improved signal-to-noise ratios and cost reductions. However, its reliance on rolling circle amplification, which can be affected by polymer size, raises questions about its effectiveness in sequencing small RNAs (sRNAs) such as microRNAs (miRNAs), small nucleolar RNAs (snoRNAs), and many others. These sRNAs are crucial regulators of gene expression and involved in various biological processes. Additionally, capturing capped small RNAs (csRNA-seq) is a powerful method for mapping active or “nascent” RNA polymerase II transcription initiation in tissues and clinical samples. Results Here, we report a new protocol for seamlessly sequencing short fragments on the AVITI and demonstrate that AVITI and Illumina sequencing technologies equivalently capture human, cattle ( Bos taurus ), and bison ( Bison bison ) sRNA or csRNA sequencing libraries, increasing confidence in both sequencing approaches. Additionally, analysis of generated nascent transcription start site (TSS) data for cattle and bison revealed inaccuracies in their current genome annotations, underscoring the potential and necessity to translate small and nascent RNA sequencing methodologies to livestock. Conclusions Our accelerated and optimized protocol bridges the advantages of AVITI sequencing with critical methods that rely on sequencing short fragments. This advance bolsters the utility of AVITI technology alongside traditional Illumina platforms, offering new opportunities for NGS applications.

Mentha haplocalyx (Lamiaceae) is a herbaceous perennial economic plant which is widely cultivated in China. Plants of M. haplocalyx with mosaic symptoms were collected from Zhaotong, Yunnan Province. Alfalfa mosaic virus (AMV) was detected from symptomatic leaf samples using small RNA sequencing and RT-PCR. The complete genome sequence of AMV-Mint was determined. AMV-Mint RNA1 was 3,644 nt, RNA2 was 2,594 nt and RNA3 was 2,040 nt, encoding P1 of 1,126 amino acids (aa), P2 of 794 aa, MP of 300 aa and CP of 218 aa. The genome structure of AMV-Mint was similar to those reported previously, except for an insertion of one adenine nucleotide at 2,389 nt of the RNA2, which results in reading frame shift mutation of the P2. Phylogenetic analysis based on RNA3 sequences grouped AMV-Mint into the Group I clade, with closest relationship to AMV-Lst. No recombination event was detected in the genome of AMV-Mint. This is the first report of the complete genome sequence of AMV from M. haplocalyx.

MicroRNAs (miRNAs) are endogenous non-coding ~21 nucleotide RNAs that regulate gene expression at the transcriptional and post-transcriptional levels in plants and animals. They play an important role in development, abiotic stress, and pathogen responses. miRNAs with their targets have been widely studied in model plants, but limited knowledge is available on the small RNA population of cotton (Gossypium hirsutum)—an important economic crop, and global identification of related targets through degradome sequencing has not been developed previously. In this study, small RNAs and their targets were identified during cotton somatic embryogenesis (SE) through high-throughput small RNA and degradome sequencing, comparing seedling hypocotyl and embryogenic callus (EC) of G. hirsutum YZ1. A total of 36 known miRNA families were found to be differentially expressed, of which 19 miRNA families were represented by 29 precursors. Twenty-five novel miRNAs were identified. A total of 234 transcripts in EC and 322 transcripts in control (CK) were found to be the targets of 23 and 30 known miRNA families, respectively, and 16 transcripts were targeted by eight novel miRNAs. Interestingly, four trans-acting small interfering RNAs (tas3-siRNAs) were also found in degradome libraries, three of which perfectly matched their precursors. Several targets were further validated via RNA ligase-mediated rapid amplification of 5’ cDNA ends (RLM 5’-RACE). The profiling of the miRNAs and their target genes provides new information on the miRNAs network during cotton SE.

The release and uptake of nano-sized extracellular vesicles (EV) is a highly conserved means of intercellular communication. The molecular composition of EV, and thereby their signaling function to target cells, is regulated by cellular activation and differentiation stimuli. EV are regarded as snapshots of cells and are, therefore, in the limelight as biomarkers for disease. Although research on EV-associated RNA has predominantly focused on microRNAs, the transcriptome of EV consists of multiple classes of small non-coding RNAs with potential gene-regulatory functions. It is not known whether environmental cues imposed on cells induce specific changes in a broad range of EV-associated RNA classes. Here, we investigated whether immune-activating or -suppressing stimuli imposed on primary dendritic cells affected the release of various small non-coding RNAs via EV. The small RNA transcriptomes of highly pure EV populations free from ribonucleoprotein particles were analyzed by RNA sequencing and RT-qPCR. Immune stimulus-specific changes were found in the miRNA, snoRNA, and Y-RNA content of EV from dendritic cells, whereas tRNA and snRNA levels were much less affected. Only part of the changes in EV-RNA content reflected changes in cellular RNA, which urges caution in interpreting EV as snapshots of cells. By comprehensive analysis of RNA obtained from highly purified EV, we demonstrate that multiple RNA classes contribute to genetic messages conveyed via EV. The identification of multiple RNA classes that display cell stimulation-dependent association with EV is the prelude to unraveling the function and biomarker potential of these EV-RNAs.

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.

Background RNA sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of these biases have focused on adapter ligation bias with limited evaluation of reverse transcription bias or amplification bias. Furthermore, evaluations of the quantification of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. No study had yet evaluated the quantification of isomiRs of altered length or compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases. Results All methods resulted in false isomiR detection; however, the adapter-free method tested was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency. Conclusions Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs across studies. We advocate for the use of UMIs to improve accuracy and reliability of miRNA quantifications.

Type 1 diabetes (T1D) is characterized by the immune-mediated destruction of insulin-producing islet β cells. Biomarkers capable of identifying T1D risk and dissecting disease-related heterogeneity represent an unmet clinical need. Toward the goal of informing T1D biomarker strategies, we profiled coding and noncoding RNAs in human islet-derived exosomes and identified RNAs that were differentially expressed under proinflammatory cytokine stress conditions. Human pancreatic islets were obtained from cadaveric donors and treated with/without IL-1β and IFN-γ. Total RNA and small RNA sequencing were performed from islet-derived exosomes to identify mRNAs, long noncoding RNAs, and small noncoding RNAs. RNAs with a fold change ≥1.3 and a p-value <0.05 were considered as differentially expressed. mRNAs and miRNAs represented the most abundant long and small RNA species, respectively. Each of the RNA species showed altered expression patterns with cytokine treatment, and differentially expressed RNAs were predicted to be involved in insulin secretion, calcium signaling, necrosis, and apoptosis. Taken together, our data identify RNAs that are dysregulated under cytokine stress in human islet-derived exosomes, providing a comprehensive catalog of protein coding and noncoding RNAs that may serve as potential circulating biomarkers in T1D.

The ability to accurately quantify all the microRNAs (miRNAs) in a sample is important for understanding miRNA biology and for development of new biomarkers and therapeutic targets. We develop a new method for preparing miRNA sequencing libraries, RealSeq®-AC, that involves ligating the miRNAs with a single adapter and circularizing the ligation products. When compared to other methods, RealSeq®-AC provides greatly reduced miRNA sequencing bias and allows the identification of the largest variety of miRNAs in biological samples. This reduced bias also allows robust quantification of miRNAs present in samples across a wide range of RNA input levels.

Extracellular vesicles (EVs) are intercellular communicators with key functions in physiological and pathological processes and have recently garnered interest because of their diagnostic and therapeutic potential. The past decade has brought about the development and commercialization of a wide array of methods to isolate EVs from serum. Which subpopulations of EVs are captured strongly depends on the isolation method, which in turn determines how suitable resulting samples are for various downstream applications. To help clinicians and scientists choose the most appropriate approach for their experiments, isolation methods need to be comparatively characterized. Few attempts have been made to comprehensively analyse vesicular microRNAs (miRNAs) in patient biofluids for biomarker studies. To address this discrepancy, we set out to benchmark the performance of several isolation principles for serum EVs in healthy individuals and critically ill patients. Here, we compared five different methods of EV isolation in combination with two RNA extraction methods regarding their suitability for biomarker discovery-focused miRNA sequencing as well as biological characteristics of captured vesicles. Our findings reveal striking method-specific differences in both the properties of isolated vesicles and the ability of associated miRNAs to serve in biomarker research. While isolation by precipitation and membrane affinity was highly suitable for miRNA-based biomarker discovery, methods based on size-exclusion chromatography failed to separate patients from healthy volunteers. Isolated vesicles differed in size, quantity, purity and composition, indicating that each method captured distinctive populations of EVs as well as additional contaminants. Even though the focus of this work was on transcriptomic profiling of EV-miRNAs, our insights also apply to additional areas of research. We provide guidance for navigating the multitude of EV isolation methods available today and help researchers and clinicians make an informed choice about which strategy to use for experiments involving critically ill patients.

Introduction Identification of molecular biomarkers in the saliva and serum of oral cavity cancer patients represents a first step in the development of essential and efficient clinical tools for early detection and post‐treatment monitoring. We hypothesized that molecular analyses of paired saliva and serum samples from an individual would likely yield better results than analyses of either serum or saliva alone. Materials and Methods We performed whole‐transcriptome and small non‐coding RNA sequencing analyses on 32 samples of saliva and serum collected from the same patients with oral squamous cell carcinoma (OSCC) and healthy controls (HC). Results We identified 12 novel saliva and serum miRNAs and a panel of unique miRNA and mRNA signatures, significantly differentially expressed in OSCC patients relative to HC (log2 fold change: 2.6–26.8; DE: 0.02–0.000001). We utilized a combined panel of the 10 top‐deregulated miRNAs and mRNAs and evaluated their putative diagnostic potential (>87% sensitivity; 100% specificity), recommending seven of them for further validation. We also identified unique saliva and serum miRNAs associated with OSCC and smoking history (OSCC smokers vs. never‐smokers or HC: log2 fold change: 22–23; DE: 0.00003–0.000000001). Functional and pathway analyses indicated interactions between the discovered OSCC‐related non‐invasive miRNAs and mRNAs and their targets, through PI3K/AKT/mTOR signaling. Conclusion Our data support our hypothesis that using paired saliva and serum from the same individuals and deep sequencing analyses can provide unique combined mRNA and miRNA signatures associated with canonical pathways that may have a diagnostic advantage relative to saliva or serum alone and may be useful for clinical testing. We believe this data will contribute to effective preventive care by post‐treatment monitoring of patients, as well as suggesting potential targets for therapeutic approaches.