Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles
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PROVIDER: EGAC00001001591 | EGA |
REPOSITORIES: EGA
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Project description:RNA profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite enormous interest in extracellular nucleic acids, RNA sequencing methods to quantify the total RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. We found the method to be accurate, precise, compatible with low-input volumes and able to quantify a few thousand genes. We picked up distinct classes of RNA molecules, including mRNA, lncRNA, circRNA, miscRNA and pseudogenes. Notably, the read distribution and gene content drastically differ among biofluids. In conclusion, we are the first to show that the SMARTer method can be used for unbiased unraveling of the complete transcriptome of a wide range of biofluids and their extracellular vesicles.
| S-EPMC6879519 | biostudies-literature
Project description:RNA profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite enormous interest in extracellular nucleic acids, RNA sequencing methods to quantify the total RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. We found the method to be accurate, precise, compatible with low-input volumes and able to quantify a few thousand genes. We picked up distinct classes of RNA molecules, including mRNA, lncRNA, circRNA, miscRNA and pseudogenes. Notably, the read distribution and gene content drastically differ among biofluids. In conclusion, we are the first to show that the SMARTer method can be used for unbiased unraveling of the complete transcriptome of a wide range of biofluids and their extracellular vesicles.
| EGAS00001004428 | EGA
Project description:MotivationExtracellular vesicles (EVs) are produced and released by most cells and are now recognized to play a role in intercellular communication through the delivery of molecular cargo, including proteins, lipids, and RNA. Small RNA sequencing (small RNA-seq) has been widely used to characterize the small RNA content in EVs. However, there is a lack of a systematic assessment of the quality, technical biases, RNA composition, and RNA biotypes enrichment for small RNA profiling of EVs across cell types, biofluids, and conditions.MethodsWe collected and reanalyzed small RNA-seq datasets for 2756 samples from 83 studies involving 55 with EVs only and 28 with both EVs and matched donor cells. We assessed their quality by the total number of reads after adapter trimming, the overall alignment rate to the host and non-host genomes, and the proportional abundance of total small RNA and specific biotypes, such as miRNA, tRNA, rRNA, and Y RNA.ResultsWe found that EV extraction methods varied in their reproducibility in isolating small RNAs, with effects on small RNA composition. Comparing proportional abundances of RNA biotypes between EVs and matched donor cells, we discovered that rRNA and tRNA fragments were relatively enriched, but miRNAs and snoRNA were depleted in EVs. Except for the export of eight miRNAs being context-independent, the selective release of most miRNAs into EVs was study-specific.ConclusionThis work guides quality control and the selection of EV isolation methods and enhances the interpretation of small RNA contents and preferential loading in EVs.
| S-EPMC10340377 | biostudies-literature
Project description:Transcriptome profiling has emerged as a powerful tool to investigate the biomarker potential of human biofluids. However, despite an enormous interest in extracellular nucleic acids, total RNA sequencing methods to quantify RNA content outside cells are rare. Here, we evaluate the performance of the SMARTer Stranded Total RNA-Seq method in human platelet-rich plasma, platelet-poor plasma, urine, conditioned medium, and extracellular vesicles from these biofluids.
2019-09-01 | GSE131689 | GEO
Project description:BackgroundCircular RNAs (circRNAs) have emerged as a prominent class of covalently closed single-stranded RNA molecules that exhibit tissue-specific expression and potential as biomarkers in extracellular vesicles (EVs) derived from liquid biopsies. Still, their characteristics and applications in EVs remain to be unveiled.MethodsWe performed a comprehensive analysis of EV-derived circRNAs (EV-circRNAs) using transcriptomics data obtained from 1082 human body fluids, including plasma, urine, cerebrospinal fluid (CSF), and bile. Our validation strategy utilized RT-qPCR and RNA immunoprecipitation assays, complemented by computational techniques for analyzing EV-circRNA features and RNA-binding protein interactions.ResultsWe identified 136,327 EV-circRNAs from various human body fluids. Significantly, a considerable amount of circRNAs with a high back-splicing ratio are highly enriched in EVs compared to linear RNAs. Additionally, we discovered brain-specific circRNAs enriched in plasma EVs and cancer-associated EV-circRNAs linked to clinical outcomes. Moreover, we demonstrated that EV-circRNAs have the potential to serve as biomarkers for evaluating immunotherapy efficacy in non-small cell lung cancer (NSCLC). Importantly, we identified the involvement of RBPs, particularly YBX1, in the sorting mechanism of circRNAs into EVs.ConclusionsThis study unveils the extensive repertoire of EV-circRNAs across human biofluids, offering insights into their potential as disease biomarkers and their mechanistic roles within EVs. The identification of specific circRNAs and the elucidation of RBP-mediated sorting mechanisms open new avenues for the clinical application of EV-circRNAs in disease diagnostics and therapeutics.
| S-EPMC11526565 | biostudies-literature
Project description:BackgroundCell-free long RNAs in human plasma and extracellular vesicles (EVs) have shown promise as biomarkers in liquid biopsy, despite their fragmented nature.MethodsTo investigate these fragmented cell-free RNAs (cfRNAs), we developed a cost-effective cfRNA sequencing method called DETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing). DETECTOR-seq utilised a meticulously tailored set of customised guide RNAs to remove large amounts of unwanted RNAs (i.e., fragmented ribosomal and mitochondrial RNAs) in human plasma. Early barcoding strategy was implemented to reduce costs and minimise plasma requirements.ResultsUsing DETECTOR-seq, we conducted a comprehensive analysis of cell-free transcriptomes in both whole human plasma and EVs. Our analysis revealed discernible distributions of RNA types in plasma and EVs. Plasma exhibited pronounced enrichment in structured circular RNAs, tRNAs, Y RNAs and viral RNAs, while EVs showed enrichment in messenger RNAs (mRNAs) and signal recognition particle RNAs (srpRNAs). Functional pathway analysis highlighted RNA splicing-related ribonucleoproteins (RNPs) and antimicrobial humoral response genes in plasma, while EVs demonstrated enrichment in transcriptional activity, cell migration and antigen receptor-mediated immune signals. Our study indicates the comparable potential of cfRNAs from whole plasma and EVs in distinguishing cancer patients (i.e., colorectal and lung cancer) from healthy donors. And microbial cfRNAs in plasma showed potential in classifying specific cancer types.ConclusionsOur comprehensive analysis of total and EV cfRNAs in paired plasma samples provides valuable insights for determining the need for EV purification in cfRNA-based studies. We envision the cost effectiveness and efficiency of DETECTOR-seq will empower transcriptome-wide investigations in the fields of cfRNAs and liquid biopsy.KeypointsDETECTOR-seq (depletion-assisted multiplexed cell-free total RNA sequencing) enabled efficient and specific depletion of sequences derived from fragmented ribosomal and mitochondrial RNAs in plasma. Distinct human and microbial cell-free RNA (cfRNA) signatures in whole Plasma versus extracellular vesicles (EVs) were revealed. Both Plasma and EV cfRNAs were capable of distinguishing cancer patients from normal individuals, while microbial RNAs in Plasma cfRNAs enabled better classification of cancer types than EV cfRNAs.
| S-EPMC11259601 | biostudies-literature
Project description:Total RNA sequencing in human biofluids and extracellular vesicles using SMARTer technology
| PRJNA544444 | ENA
Project description:The recent discovery of extracellular RNAs in blood, including RNAs in extracellular vesicles (EVs), combined with low-input RNA-sequencing advances have enabled scientists to investigate their role in human disease. To date, most studies have been focusing on small RNAs, and methodologies to optimize long RNAs measurement are lacking. We used plasma RNA to assess the performance of six long RNA sequencing methods, at two different sites, and we report their differences in reads (%) mapped to the genome/transcriptome, number of genes detected, long RNA transcript diversity, and reproducibility. Using the best performing method, we further compare the profile of long RNAs in the EV- and no-EV-enriched RNA plasma compartments. These results provide insights on the performance and reproducibility of commercially available kits in assessing the landscape of long RNAs in human plasma and different extracellular RNA carriers that may be exploited for biomarker discovery.
| S-EPMC7283149 | biostudies-literature
Project description:The pathogenesis of breast cancer is still unclear. Small RNAs associated with extracellular vesicles (EVs) have been found to be involved in tumor development. It is important to explore the role of EVs small RNAs in breast cancer. In this study, we established a plasma EVS-associated small RNA dataset that included 120 women who were positive for breast cancer screening and 60 women who were negative. These small RNA included 2656 miRNAs, 728 piRNAs, and 154 tsRNAs. These data provide a reference for researchers to explore molecular diagnostic biomarkers for early breast lesions.
| S-EPMC11655662 | biostudies-literature
Project description:The presence and relative stability of extracellular RNAs (exRNAs) in biofluids has led to an emerging recognition of their promise as 'liquid biopsies' for diseases. Most prior studies on discovery of exRNAs as disease-specific biomarkers have focused on microRNAs (miRNAs) using technologies such as qRT-PCR and microarrays. The recent application of next-generation sequencing to discovery of exRNA biomarkers has revealed the presence of potential novel miRNAs as well as other RNA species such as tRNAs, snoRNAs, piRNAs and lncRNAs in biofluids. At the same time, the use of RNA sequencing for biofluids poses unique challenges, including low amounts of input RNAs, the presence of exRNAs in different compartments with varying degrees of vulnerability to isolation techniques, and the high abundance of specific RNA species (thereby limiting the sensitivity of detection of less abundant species). Moreover, discovery in human diseases often relies on archival biospecimens of varying age and limiting amounts of samples. In this study, we have tested RNA isolation methods to optimize profiling exRNAs by RNA sequencing in individuals without any known diseases. Our findings are consistent with other recent studies that detect microRNAs and ribosomal RNAs as the major exRNA species in plasma. Similar to other recent studies, we found that the landscape of biofluid microRNA transcriptome is dominated by several abundant microRNAs that appear to comprise conserved extracellular miRNAs. There is reasonable correlation of sets of conserved miRNAs across biological replicates, and even across other data sets obtained at different investigative sites. Conversely, the detection of less abundant miRNAs is far more dependent on the exact methodology of RNA isolation and profiling. This study highlights the challenges in detecting and quantifying less abundant plasma miRNAs in health and disease using RNA sequencing platforms.
| S-EPMC5218574 | biostudies-literature