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: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:Salivary biomarkers for disease detection, diagnostic and prognostic assessments have become increasingly well established in recent years. In this chapter we explain the current leading technology that has been used to characterize salivary non-coding RNAs (ncRNAs) from the extracellular RNA (exRNA) fraction: HiSeq from Illumina® platform for RNA sequencing. Therefore, the chapter is divided into two main sections regarding the type of the library constructed (small and long ncRNA libraries), from saliva collection, RNA extraction and quantification to cDNA library generation and corresponding QCs. Using these invaluable technical tools, one can identify thousands of ncRNA species in saliva. These methods indicate that salivary exRNA provides an efficient medium for biomarker discovery of oral and systemic diseases.
| S-EPMC5550740 | biostudies-other
Project description:BackgroundBreast cancer is the most common cancer affecting women across the world. Tumor endothelial cells (TECs) and malignant cells are the major constituents of the tumor microenvironment (TME), but their origin and role in shaping disease initiation, progression, and treatment responses remain unclear due to significant heterogeneity.MethodsTissue samples were collected from eight patients presenting with breast cancer. Single-cell RNA sequencing (scRNA-seq) analysis was employed to investigate the presence of distinct cell subsets in the tumor microenvironment. InferCNV was used to identify cancer cells. Pseudotime trajectory analysis revealed the dynamic process of breast cancer angiogenesis. We validated the function of small extracellular vesicles (sEVs)-derived protein phosphatase 1 regulatory inhibitor subunit 1B (PPP1R1B) in vitro experiments.ResultsWe performed single-cell transcriptomics analysis of the factors associated with breast cancer angiogenesis and identified twelve subclusters of endothelial cells involved in the tumor microenvironment. We also identified the role of TECs in tumor angiogenesis and confirmed their participation in different stages of angiogenesis, including communication with other cell types via sEVs. Overall, the research uncovered the TECs heterogeneity and the expression levels of genes at different stages of tumor angiogenesis.ConclusionsThis study showed sEVs derived from breast cancer malignant cells promote blood vessel formation by activating endothelial cells through the transfer of PPP1R1B. This provides a new direction for the development of anti-angiogenic therapies for human breast cancer.
| S-EPMC10463655 | 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
Project description:Extracellular vesicles (EVs) are reported to be involved in stem cell maintenance, self-renewal, and differentiation. Due to their bioactive cargoes influencing cell fate and function, interest in EVs in regenerative medicine has rapidly increased. EV-derived small non-coding RNA mimic the functions of the parent stem cells, regulating the maintenance and differentiation of stem cells, controlling the intercellular regulation of gene expression, and eventually affecting the cell fate. In this study, we used RNA sequencing to provide a comprehensive overview of the expression profiles of small non-coding transcripts carried by the EVs derived from human adipose tissue stromal/stem cells (AT-MSCs) and human pluripotent stem cells (hPSCs), both human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSC). Both hPSCs and AT-MSCs were characterized and their EVs were extracted using standard protocols. Small non-coding RNA sequencing from EVs showed that hPSCs and AT-MSCs showed distinct profiles, unique for each stem cell source. Interestingly, in hPSCs, most abundant miRNAs were from specific miRNA families regulating pluripotency, reprogramming and differentiation (miR-17-92, mir-200, miR-302/367, miR-371/373, CM19 microRNA cluster). For the AT-MSCs, the highly expressed miRNAs were found to be regulating osteogenesis (let-7/98, miR-10/100, miR-125, miR-196, miR-199, miR-615-3p, mir-22-3p, mir-24-3p, mir-27a-3p, mir-193b-5p, mir-195-3p). Additionally, abundant small nuclear and nucleolar RNA were detected in hPSCs, whereas Y- and tRNA were found in AT-MSCs. Identification of EV-miRNA and non-coding RNA signatures released by these stem cells will provide clues towards understanding their role in intracellular communication, and well as their roles in maintaining the stem cell niche.
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