Identification of protein-protected mRNA fragments and structured excised intron RNAs in human plasma by TGIRT-seq peak calling

Wide-spectrum profiling of plasma cell-free RNA and the potential for health-monitoring

Circulating cell-free RNA (cfRNA) has emerged as a promising analyte for disease detection. However, the comprehensive profiling of diverse cfRNA types remains under-characterized. Here, we applied a new wide-spectrum cfRNA sequencing method and simultaneously captured rRNA, tRNA, mRNA, miRNA, lncRNA and all mitochondrial RNA. The cfRNA compositions, size distributions and highly abundant cfRNA genes were analysed for each type of cfRNA. We depicted the cfRNA cell types of origin profiles of 66 generally healthy individuals and found that BMI showed a significant impact on the kidney-derived cfRNA proportion. Three individuals with some liver problems were identified because of relatively high levels of hepatocyte-specific cfRNA. The abundance levels of different genes and RNA types, including mRNA, miRNA and lncRNA, were significantly correlated with the liver function test results. The genes of individual cfRNA variances were enriched in pathways associated with common diseases such as liver diseases, virus infections, cancers and metabolic diseases. This study provided a profiling of cfRNA and displayed the potential of cfRNA as a biomarker in health monitoring.

Peak analysis of cell-free RNA finds recurrently protected narrow regions with clinical potential

BACKGROUND

Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understanding their biological functions and clinical value. However, many challenges still need to be addressed for their application, including developing specific analysis methods and translating cfRNA fragments with biological support into clinical applications.

RESULTS

We present cfPeak, a novel method combining statistics and machine learning models to detect the fragmented cfRNA signals effectively. When test in real and artificial cfRNA sequencing (cfRNA-seq) data, cfPeak shows an improved performance compared with other applicable methods. We reveal that narrow cfRNA peaks preferentially overlap with protein binding sites, vesicle-sorting sites, structural sites, and novel small non-coding RNAs (sncRNAs). When applied in clinical cohorts, cfPeak identified cfRNA peaks in patients' plasma that enable cancer detection and are informative of cancer types and metastasis.

CONCLUSIONS

Our study fills the gap in the current small cfRNA-seq analysis at fragment-scale and builds a bridge to the scientific discovery in cfRNA fragmentomics. We demonstrate the significance of finding low abundant tissue-derived signals in small cfRNA and prove the feasibility for application in liquid biopsy.

An intronic SNP in the Carotenoid Cleavage Dioxygenase 1 (CsCCD1) controls yellow flesh formation in cucumber fruit (Cucumis sativus L.)

Vitamin A is a crucial yet scarce vitamin essential for maintaining normal metabolism and bodily functions in humans and can only be obtained from food. Carotenoids represent a diverse group of functional pigments that act as precursors for vitamins, hormones, aroma volatiles and antioxidants. As a vital vegetable in the world, elevated carotenoid levels in cucumber fruit produce yellow flesh, enhancing both visual appeal and nutritional value. However, the genetic mechanisms and regulatory networks governing yellow flesh in cucumbers remain inadequately characterized. In this study, we employed map-based cloning to identify a Carotenoid Cleavage Dioxygenase 1 (CsCCD1) as a key genetic factor influencing yellow flesh in cucumbers. A causal single nucleotide polymorphism (SNP) in the eighth intron of CsCCD1 led to aberrant splicing, resulting in a truncated transcript. The truncated protein has significantly decreased enzyme activity and increased carotenoid accumulation in the fruit. CRISPR/Cas9-generated CsCCD1 knockout mutants exhibited yellow flesh and significantly higher carotenoid content compared to wild-type cucumbers. Metabolic profiling indicated a marked accumulation of β-cryptoxanthin in the flesh of these knockout mutants. The intronic SNP was shown to perfectly segregate with yellow flesh in 159 diverse cucumber germplasms, particularly within the semi-wild ecotype Xishuangbanna, known for its substantial carotenoid accumulation. Furthermore, transient overexpression of CsCCD1 in yellow-fleshed Xishuangbanna cucumbers restored a white flesh phenotype, underscoring the critical role of CsCCD1 in determining flesh colour in both cultivated and semi-wild cucumbers. These findings lay a theoretical foundation for breeding high-nutrient yellow-fleshed cucumber varieties.

Current Understandings and Open Hypotheses on Extracellular Circular RNAs

Circular RNAs (circRNAs) are closed RNA loops present in humans and other organisms. Various circRNAs have an essential role in diseases, including cancer. Cells can release circRNAs into the extracellular space of adjacent biofluids and can be present in extracellular vesicles. Due to their circular nature, extracellular circRNAs (excircRNAs) are more stable than their linear counterparts and are abundant in many biofluids, such as blood plasma and urine. circRNAs' link with disease suggests their extracellular counterparts have high biomarker potential. However, circRNAs and the extracellular space are challenging research domains, as they consist of complex biological systems plagued with nomenclature issues and a wide variety of protocols with different advantages and disadvantages. Here, we summarize what is known about excircRNAs, the current challenges in the field, and what is needed to improve extracellular circRNA research.

TGIRT-seq of Inflammatory Breast Cancer Tumor and Blood Samples Reveals Widespread Enhanced Transcription Impacting RNA Splicing and Intronic RNAs in Plasma

Inflammatory breast cancer (IBC) is the most aggressive and lethal breast cancer subtype but lacks unequivocal genomic differences or robust biomarkers that differentiate it from non-IBC. Here, Thermostable Group II intron Reverse Transcriptase RNA-sequencing (TGIRT-seq) revealed myriad differences in tumor samples, Peripheral Blood Mononuclear Cells (PBMCs), and plasma that distinguished IBC from non-IBC patients and healthy donors across all tested receptor-based subtypes. These included numerous differentially expressed protein-coding gene and non-coding RNAs in all three sample types, a granulocytic immune response in IBC PBMCs, and over-expression of antisense RNAs, suggesting wide-spread enhanced transcription in both IBC tumors and PBMCs. By using TGIRT-seq to quantitate Intron-exon Depth Ratios (IDRs) and mapping reads to both genome and transcriptome reference sequences, we developed methods for parallel analysis of transcriptional and post-transcriptional gene regulation. This analysis identified numerous differentially and non-differentially expressed protein-coding genes in IBC tumors and PBMCs with high IDRs, the latter reflecting rate-limiting RNA splicing that negatively impacts mRNA production. Mirroring gene expression differences in tumors and PBMCs, over-represented protein-coding gene RNAs in IBC patient plasma were largely intronic RNAs, while those in non-IBC patients and healthy donor plasma were largely mRNA fragments. Potential IBC biomarkers in plasma included T-cell receptor pre-mRNAs and intronic, LINE-1, and antisense RNAs. Our findings provide new insights into IBC and set the stage for monitoring disease progression and response to treatment by liquid biopsy. The methods developed for parallel transcriptional and post-transcriptional gene regulation analysis have potentially broad RNA-seq and clinical applications.

Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers

A previous study using Thermostable Group II Intron Reverse Transcriptase sequencing (TGIRT-seq) found human plasma contains short (≤300 nt) structured full-length excised linear intron (FLEXI) RNAs with potential to serve as blood-based biomarkers. Here, TGIRT-seq identified >9,000 different FLEXI RNAs in human cell lines, including relatively abundant FLEXIs with cell-type-specific expression patterns. Analysis of public CLIP-seq datasets identified 126 RNA-binding proteins (RBPs) that have binding sites within the region corresponding to the FLEXI or overlapping FLEXI splice sites in pre-mRNAs, including 53 RBPs with binding sites for ≥30 different FLEXIs. These included splicing factors, transcription factors, a chromatin remodeling protein, cellular growth regulators, and proteins with cytoplasmic functions. Analysis of ENCODE datasets identified subsets of these RBPs whose knockdown impacted FLEXI host gene mRNA levels or proximate alternative splicing, indicating functional interactions. Hierarchical clustering identified six subsets of RBPs whose FLEXI binding sites were co-enriched in six subsets of functionally related host genes: AGO1-4 and DICER, including but not limited to agotrons or mirtron pre-miRNAs; DKC1, NOLC1, SMNDC1, and AATF (Apoptosis Antagonizing Transcription Factor), including but not limited to snoRNA-encoding FLEXIs; two subsets of alternative splicing factors; and two subsets that included RBPs with cytoplasmic functions (e.g., LARP4, PABPC4, METAP2, and ZNF622) together with regulatory proteins. Cell fractionation experiments showed cytoplasmic enrichment of FLEXI RNAs with binding sites for RBPs with cytoplasmic functions. The subsets of host genes encoding FLEXIs with binding sites for different subsets of RBPs were co-enriched with non-FLEXI other short and long introns with binding sites for the same RBPs, suggesting overarching mechanisms for coordinately regulating expression of functionally related genes. Our findings identify FLEXIs as a previously unrecognized large class of cellular RNAs and provide a comprehensive roadmap for further analyzing their biological functions and the relationship of their RBPs to cellular regulatory mechanisms.

Senataxin deficiency disrupts proteostasis through nucleolar ncRNA-driven protein aggregation

Senataxin is an evolutionarily conserved RNA-DNA helicase involved in DNA repair and transcription termination that is associated with human neurodegenerative disorders. Here, we investigated whether Senataxin loss affects protein homeostasis based on previous work showing R-loop-driven accumulation of DNA damage and protein aggregates in human cells. We find that Senataxin loss results in the accumulation of insoluble proteins, including many factors known to be prone to aggregation in neurodegenerative disorders. These aggregates are located primarily in the nucleolus and are promoted by upregulation of non-coding RNAs expressed from the intergenic spacer region of ribosomal DNA. We also map sites of R-loop accumulation in human cells lacking Senataxin and find higher RNA-DNA hybrids within the ribosomal DNA, peri-centromeric regions, and other intergenic sites but not at annotated protein-coding genes. These findings indicate that Senataxin loss affects the solubility of the proteome through the regulation of transcription-dependent lesions in the nucleus and the nucleolus.

A Comprehensive Review on Circulating cfRNA in Plasma: Implications for Disease Diagnosis and Beyond

Circulating cfRNA in plasma has emerged as a fascinating area of research with potential applications in disease diagnosis, monitoring, and personalized medicine. Circulating RNA sequencing technology allows for the non-invasive collection of important information about the expression of target genes, eliminating the need for biopsies. This comprehensive review aims to provide a detailed overview of the current knowledge and advancements in the study of plasma cfRNA, focusing on its diverse landscape and biological functions, detection methods, its diagnostic and prognostic potential in various diseases, challenges, and future perspectives.

Profiling of repetitive RNA sequences in the blood plasma of patients with cancer

Liquid biopsies provide a means for the profiling of cell-free RNAs secreted by cells throughout the body. Although well-annotated coding and non-coding transcripts in blood are readily detectable and can serve as biomarkers of disease, the overall diagnostic utility of the cell-free transcriptome remains unclear. Here we show that RNAs derived from transposable elements and other repeat elements are enriched in the cell-free transcriptome of patients with cancer, and that they serve as signatures for the accurate classification of the disease. We used repeat-element-aware liquid-biopsy technology and single-molecule nanopore sequencing to profile the cell-free transcriptome in plasma from patients with cancer and to examine millions of genomic features comprising all annotated genes and repeat elements throughout the genome. By aggregating individual repeat elements to the subfamily level, we found that samples with pancreatic cancer are enriched with specific Alu subfamilies, whereas other cancers have their own characteristic cell-free RNA profile. Our findings show that repetitive RNA sequences are abundant in blood and can be used as disease-specific diagnostic biomarkers.

sRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.

sRNAfrag: A pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs hold biological relevance. However, they remain poorly understood, calling for more comprehensive methods for analysis. We developed sRNAfrag, a standardized workflow and set of scripts to quantify and analyze sRNA fragmentation of any biotype. In a benchmark, it is able to detect loci of mature microRNAs fragmented from precursors and, utilizing multi-mapping events, the conserved 5' seed sequence of miRNAs which we believe may extraoplate to other small RNA fragments. The tool detected 1411 snoRNA fragment conservation events between 2/4 eukaryotic species, providing the opportunity to explore motifs and fragmentation patterns not only within species, but between. Availability: https://github.com/kenminsoo/sRNAfrag.

A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection

BACKGROUND

Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA.

METHODS

We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance.

FINDINGS

We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928).

INTERPRETATION

This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP.

FUNDING

National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Integrated analysis of circulating cell free nucleic acids for cancer genotyping and immune phenotyping of tumor microenvironment

The circulating cell-free nucleic acids (ccfNAs) consist of a heterogenous cocktail of both single (ssNA) and double-stranded (dsNA) nucleic acids. These ccfNAs are secreted into the blood circulation by both healthy and malignant cells via various mechanisms including apoptosis, necrosis, and active secretion. The major source of ccfNAs are the cells of hematopoietic system under healthy conditions. These ccfNAs include fragmented circulating cell free DNA (ccfDNA), coding or messenger RNA (mRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and mitochondrial DNA/RNA (mtDNA and mtRNA), that serve as prospective biomarkers in assessment of various clinical conditions. For, e.g., free fetal DNA and RNA migrate into the maternal plasma, whereas circulating tumor DNA (ctDNA) has clinical relevance in diagnostic, prognostic, therapeutic targeting, and disease progression monitoring to improve precision medicine in cancer. The epigenetic modifications of ccfDNA as well as circulating cell-free RNA (ccfRNA) such as miRNA and lncRNA show disease-related variations and hold potential as epigenetic biomarkers. The messenger RNA present in the circulation or the circulating cell free mRNA (ccf-mRNA) and long non-coding RNA (ccf-lncRNA) have gradually become substantial in liquid biopsy by acting as effective biomarkers to assess various aspects of disease diagnosis and prognosis. Conversely, the simultaneous characterization of coding and non-coding RNAs in human biofluids still poses a significant hurdle. Moreover, a comprehensive assessment of ccfRNA that may reflect the tumor microenvironment is being explored. In this review, we focus on the novel approaches for exploring ccfDNA and ccfRNAs, specifically ccf-mRNA as biomarkers in clinical diagnosis and prognosis of cancer. Integrating the detection of circulating tumor DNA (ctDNA) for cancer genotyping in conjunction with ccfRNA both quantitatively and qualitatively, may potentially hold immense promise towards precision medicine. The current challenges and future directions in deciphering the complexity of cancer networks based on the dynamic state of ccfNAs will be discussed.

Detection of YAP1 and AR-V7 mRNA for Prostate Cancer Prognosis Using an ISFET Lab-On-Chip Platform

Prostate cancer (PCa) is the second most common cause of male cancer-related death worldwide. The gold standard of treatment for advanced PCa is androgen deprivation therapy (ADT). However, eventual failure of ADT is common and leads to lethal metastatic castration-resistant PCa. As such, the detection of relevant biomarkers in the blood for drug resistance in metastatic castration-resistant PCa patients could lead to personalized treatment options. mRNA detection is often limited by the low specificity of qPCR assays which are restricted to specialized laboratories. Here, we present a novel reverse-transcription loop-mediated isothermal amplification assay and have demonstrated its capability for sensitive detection of AR-V7 and YAP1 RNA (3 × 10¹ RNA copies per reaction). This work presents a foundation for the detection of circulating mRNA in PCa on a non-invasive lab-on-chip device for use at the point-of-care. This technique was implemented onto a lab-on-chip platform integrating an array of chemical sensors (ion-sensitive field-effect transistors) for real-time detection of RNA. Detection of RNA presence was achieved through the translation of chemical signals into electrical readouts. Validation of this technique was conducted with rapid detection (<15 min) of extracted RNA from prostate cancer cell lines 22Rv1s and DU145s.

Cancer type classification using plasma cell-free RNAs derived from human and microbes

The utility of cell-free nucleic acids in monitoring cancer has been recognized by both scientists and clinicians. In addition to human transcripts, a fraction of cell-free nucleic acids in human plasma were proven to be derived from microbes and reported to have relevance to cancer. To obtain a better understanding of plasma cell-free RNAs (cfRNAs) in cancer patients, we profiled cfRNAs in ~300 plasma samples of 5 cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer, and esophageal cancer) and healthy donors (HDs) with RNA-seq. Microbe-derived cfRNAs were consistently detected by different computational methods when potential contaminations were carefully filtered. Clinically relevant signals were identified from human and microbial reads, and enriched Kyoto Encyclopedia of Genes and Genomes pathways of downregulated human genes and higher prevalence torque teno viruses both suggest that a fraction of cancer patients were immunosuppressed. Our data support the diagnostic value of human and microbe-derived plasma cfRNAs for cancer detection, as an area under the ROC curve of approximately 0.9 for distinguishing cancer patients from HDs was achieved. Moreover, human and microbial cfRNAs both have cancer type specificity, and combining two types of features could distinguish tumors of five different primary locations with an average recall of 60.4%. Compared to using human features alone, adding microbial features improved the average recall by approximately 8%. In summary, this work provides evidence for the clinical relevance of human and microbe-derived plasma cfRNAs and their potential utilities in cancer detection as well as the determination of tumor sites.

A method for simultaneous detection of small and long RNA biotypes by ribodepleted RNA-Seq

RNA sequencing offers unprecedented access to the transcriptome. Key to this is the identification and quantification of many different species of RNA from the same sample at the same time. In this study we describe a novel protocol for simultaneous detection of coding and non-coding transcripts using modifications to the Ion Total RNA-Seq kit v2 protocol, with integration of QIASeq FastSelect rRNA removal kit. We report highly consistent sequencing libraries can be produced from both frozen high integrity mouse hippocampal tissue and the more challenging post-mortem human tissue. Removal of rRNA using FastSelect was extremely efficient, resulting in less than 1.5% rRNA content in the final library. We identified > 30,000 unique transcripts from all samples, including protein-coding genes and many species of non-coding RNA, in biologically-relevant proportions. Furthermore, the normalized sequencing read count for select genes significantly negatively correlated with Ct values from qRT-PCR analysis from the same samples. These results indicate that this protocol accurately and consistently identifies and quantifies a wide variety of transcripts simultaneously. The highly efficient rRNA depletion, coupled with minimized sample handling and without complicated and high-loss size selection protocols, makes this protocol useful to researchers wishing to investigate whole transcriptomes.

TGIRT-seq Protocol for the Comprehensive Profiling of Coding and Non-coding RNA Biotypes in Cellular, Extracellular Vesicle, and Plasma RNAs

High-throughput RNA sequencing (RNA-seq) has extraordinarily advanced our understanding of gene expression and disease etiology, and is a powerful tool for the identification of biomarkers in a wide range of organisms. However, most RNA-seq methods rely on retroviral reverse transcriptases (RTs), enzymes that have inherently low fidelity and processivity, to convert RNAs into cDNAs for sequencing. Here, we describe an RNA-seq protocol using Thermostable Group II Intron Reverse Transcriptases (TGIRTs), which have high fidelity, processivity, and strand-displacement activity, as well as a proficient template-switching activity that enables efficient and seamless RNA-seq adapter addition. By combining these activities, TGIRT-seq enables the simultaneous profiling of all RNA biotypes from small amounts of starting material, with superior RNA-seq metrics, and unprecedented ability to sequence structured RNAs. The TGIRT-seq protocol for Illumina sequencing consists of three steps: (i) addition of a 3' RNA-seq adapter, coupled to the initiation of cDNA synthesis at the 3' end of a target RNA, via template switching from a synthetic adapter RNA/DNA starter duplex; (ii) addition of a 5' RNA-seq adapter, by using thermostable 5' App DNA/RNA ligase to ligate an adapter oligonucleotide to the 3' end of the completed cDNA; (iii) minimal PCR amplification, to add capture sites and indices for Illumina sequencing. TGIRT-seq for the Illumina sequencing platform has been used for comprehensive profiling of coding and non-coding RNAs in ribodepleted, chemically fragmented cellular RNAs, and for the analysis of intact (non-chemically fragmented) cellular, extracellular vesicle (EV), and plasma RNAs, where it yields continuous full-length end-to-end sequences of structured small non-coding RNAs (sncRNAs), including tRNAs, snoRNAs, snRNAs, pre-miRNAs, and full-length excised linear intron (FLEXI) RNAs. Graphic abstract: Figure 1.Overview of the TGIRT-seq protocol for Illumina sequencing.Major steps are: (1) Template switching from a synthetic R2 RNA/R2R DNA starter duplex with a 1-nt 3' DNA overhang (a mixture of A, C, G, and T residues, denoted N) that base pairs to the 3' nucleotide of a target RNA, and upon initiating reverse transcription by adding dNTPs, seamlessly links an R2R adapter to the 5' end of the resulting cDNA; (2) Ligation of an R1R adapter to the 3' end of the completed cDNA; and (3) Minimal PCR amplification with primers that add Illumina capture sites (P5 and P7) and barcode sequences (indices 5 and 7). The index 7 barcode is required, while the index 5 barcode is optional, to provide unique dual indices (UDIs).

Single Cell and Plasma RNA Sequencing for RNA Liquid Biopsy for Hepatocellular Carcinoma

BACKGROUND

Human plasma contains RNA transcripts released by multiple cell types within the body. Single-cell transcriptomic analysis allows the cellular origin of circulating RNA molecules to be elucidated at high resolution and has been successfully utilized in the pregnancy context. We explored the application of a similar approach to develop plasma RNA markers for cancer detection.

METHODS

Single-cell RNA sequencing was performed to decipher transcriptomic profiles of single cells from hepatocellular carcinoma (HCC) samples. Cell-type-specific transcripts were identified and used for deducing the cell-type-specific gene signature (CELSIG) scores of plasma RNA from patients with and without HCC.

RESULTS

Six major cell clusters were identified, including hepatocyte-like, cholangiocyte-like, myofibroblast, endothelial, lymphoid, and myeloid cell clusters based on 4 HCC tumor tissues as well as their paired adjacent nontumoral tissues. The CELSIG score of hepatocyte-like cells was significantly increased in preoperative plasma RNA samples of patients with HCC (n = 14) compared with non-HCC participants (n = 49). The CELSIG score of hepatocyte-like cells declined in plasma RNA samples of patients with HCC within 3 days after tumor resection. Compared with the discriminating power between patients with and without HCC using the abundance of ALB transcript in plasma [area under curve (AUC) 0.72)], an improved performance (AUC: 0.84) was observed using the CELSIG score. The hepatocyte-specific transcript markers in plasma RNA were further validated by ddPCR assays. The CELSIG scores of hepatocyte-like cell and cholangiocyte trended with patients' survival.

CONCLUSIONS

The combination of single-cell transcriptomic analysis and plasma RNA sequencing represents an approach for the development of new noninvasive cancer markers.

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.

Structural basis for template switching by a group II intron-encoded non-LTR-retroelement reverse transcriptase

Reverse transcriptases (RTs) can switch template strands during complementary DNA synthesis, enabling them to join discontinuous nucleic acid sequences. Template switching (TS) plays crucial roles in retroviral replication and recombination, is used for adapter addition in RNA-Seq, and may contribute to retroelement fitness by increasing evolutionary diversity and enabling continuous complementary DNA synthesis on damaged templates. Here, we determined an X-ray crystal structure of a TS complex of a group II intron RT bound simultaneously to an acceptor RNA and donor RNA template–DNA primer heteroduplex with a 1-nt 3′-DNA overhang. The structure showed that the 3′ end of the acceptor RNA binds in a pocket formed by an N-terminal extension present in non–long terminal repeat–retroelement RTs and the RT fingertips loop, with the 3′ nucleotide of the acceptor base paired to the 1-nt 3′-DNA overhang and its penultimate nucleotide base paired to the incoming dNTP at the RT active site. Analysis of structure-guided mutations identified amino acids that contribute to acceptor RNA binding and a phenylalanine residue near the RT active site that mediates nontemplated nucleotide addition. Mutation of the latter residue decreased multiple sequential template switches in RNA-Seq. Our results provide new insights into the mechanisms of TS and nontemplated nucleotide addition by RTs, suggest how these reactions could be improved for RNA-Seq, and reveal common structural features for TS by non–long terminal repeat–retroelement RTs and viral RNA–dependent RNA polymerases.

Molecular evaluation of five different isolation methods for extracellular vesicles reveals different clinical applicability and subcellular origin

Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co-isolated entities, a combination of methods is needed. However, this is time-consuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 μl or 3 ml plasma, that is, precipitation (ExoQuick ULTRA), membrane affinity (exoEasy Maxi Kit), size-exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC-MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non-EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non-EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.

Circulating SNORD57 rather than piR-54265 is a promising biomarker for colorectal cancer: common pitfalls in the study of somatic piRNAs in cancer

There is increasing interest among cancer researchers in the study of Piwi-interacting RNAs (piRNAs), a group of small RNAs important for maintaining genome stability in the germline. Aberrant expression of piRNAs in cancer could imply an involvement of these regulatory RNAs in neoplastic transformation. On top of that, it could enable early cancer diagnosis based on RNA analysis in liquid biopsies, as piRNAs are not expected to widely circulate in the bloodstream of healthy individuals. Indeed, it has recently been shown that serum piR-54265 allows for excellent discrimination between colorectal cancer patients and healthy controls. However, we have also shown that most somatic piRNAs reported to date in mammals are actually fragments of other noncoding RNAs. Herein, we show that reports positioning piR-54265 as a noninvasive biomarker for colorectal cancer were actually measuring variations in the levels of a full-length (72 nt) small nucleolar RNA in serum. This should place a cautionary note for future research in somatic and cancer-specific piRNAs. We deeply encourage this line of research but discuss proper ways to identify somatic piRNAs without the interference of erroneous entries contained in piRNA databases. We also introduce the concept of miscellaneous-piRNAs (m-piRNAs) to distinguish between canonical piRNAs and other small RNAs circumstantially associated with PIWI proteins in somatic cells.

Identification of protein-protected mRNA fragments and structured excised intron RNAs in human plasma by TGIRT-seq peak calling

Human plasma contains > 40,000 different coding and non-coding RNAs that are potential biomarkers for human diseases. Here, we used thermostable group II intron reverse transcriptase sequencing (TGIRT-seq) combined with peak calling to simultaneously profile all RNA biotypes in apheresis-prepared human plasma pooled from healthy individuals. Extending previous TGIRT-seq analysis, we found that human plasma contains largely fragmented mRNAs from > 19,000 protein-coding genes, abundant full-length, mature tRNAs and other structured small non-coding RNAs, and less abundant tRNA fragments and mature and pre-miRNAs. Many of the mRNA fragments identified by peak calling correspond to annotated protein-binding sites and/or have stable predicted secondary structures that could afford protection from plasma nucleases. Peak calling also identified novel repeat RNAs, miRNA-sized RNAs, and putatively structured intron RNAs of potential biological, evolutionary, and biomarker significance, including a family of full-length excised intron RNAs, subsets of which correspond to mirtron pre-miRNAs or agotrons.