scholarly journals RNA Sequencing by Direct Tagmentation of RNA/DNA Hybrids

2019 ◽  
Author(s):  
Lin Di ◽  
Yusi Fu ◽  
Yue Sun ◽  
Jie Li ◽  
Lu Liu ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Reverse Transcription ◽  
Single Cells ◽  
Pcr Amplification ◽  
Transcriptome Profiling ◽  
Rna Seq ◽  
New Approach ◽  
Double Stranded Dna ◽  
Wide Range ◽  
Tn5 Transposase

AbstractTranscriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status but it relies on second strand cDNA synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol, and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods.Significance StatementRNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides a new approach for simple and accurate RNA characterization and quantification.

scholarly journals RNA sequencing by direct tagmentation of RNA/DNA hybrids

2020 ◽  
Vol 117 (6) ◽  
pp. 2886-2893 ◽  
Author(s):  
Lin Di ◽  
Yusi Fu ◽  
Yue Sun ◽  
Jie Li ◽  
Lu Liu ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Initial Material ◽  
Library Preparation ◽  
Rna Seq ◽  
Cdna Synthesis ◽  
Complementary Dna ◽  
Dna Analyses ◽  
Wide Range

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status, but it relies on second-strand complementary DNA (cDNA) synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second-strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods.

scholarly journals 3′ MACE RNA-sequencing allows for transcriptome profiling in human tissue samples after long-term storage

2020 ◽  
Vol 100 (10) ◽  
pp. 1345-1355 ◽  
Author(s):  
Stefaniya Boneva ◽  
Anja Schlecht ◽  
Daniel Böhringer ◽  
Hans Mittelviefhaus ◽  
Thomas Reinhard ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Storage Time ◽  
Transcriptome Profiling ◽  
Rna Seq ◽  
Fresh Tissue ◽  
Long Term Storage ◽  
Ffpe Samples ◽  
The Impact ◽  
Term Storage

Abstract This study aims to compare the potential of standard RNA-sequencing (RNA-Seq) and 3′ massive analysis of c-DNA ends (MACE) RNA-sequencing for the analysis of fresh tissue and describes transcriptome profiling of formalin-fixed paraffin-embedded (FFPE) archival human samples by MACE. To compare MACE to standard RNA-Seq on fresh tissue, four healthy conjunctiva from four subjects were collected during vitreoretinal surgery, halved and immediately transferred to RNA lysis buffer without prior fixation and then processed for either standard RNA-Seq or MACE RNA-Seq analysis. To assess the impact of FFPE preparation on MACE, a third part was fixed in formalin and processed for paraffin embedding, and its transcriptional profile was compared with the unfixed specimens analyzed by MACE. To investigate the impact of FFPE storage time on MACE results, 24 FFPE-treated conjunctival samples from 24 patients were analyzed as well. Nineteen thousand six hundred fifty-nine transcribed genes were detected by both MACE and standard RNA-Seq on fresh tissue, while 3251 and 2213 transcripts were identified explicitly by MACE or RNA-Seq, respectively. Standard RNA-Seq tended to yield longer detected transcripts more often than MACE technology despite normalization, indicating that the MACE technology is less susceptible to a length bias. FFPE processing revealed negligible effects on MACE sequencing results. Several quality-control measurements showed that long-term storage in paraffin did not decrease the diversity of MACE libraries. We noted a nonlinear relation between storage time and the number of raw reads with an accelerated decrease within the first 1000 days in paraffin, while the numbers remained relatively stable in older samples. Interestingly, the number of transcribed genes detected was independent on FFPE storage time. RNA of sufficient quality and quantity can be extracted from FFPE samples to obtain comprehensive transcriptome profiling using MACE technology. We thus present MACE as a novel opportunity for utilizing FFPE samples stored in histological archives.

scholarly journals SHERRY2: A method for rapid and sensitive single cell RNA-seq

2021 ◽  
Author(s):  
Lin Di ◽  
Bo Liu ◽  
Yuzhu Lyu ◽  
Shihui Zhao ◽  
Yuhong Pang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Dynamic Range ◽  
Single Cells ◽  
Rna Seq ◽  
Wide Dynamic Range ◽  
Uniform Coverage ◽  
Optimized Protocol ◽  
Tn5 Transposase ◽  
Higher Sensitivity

Many single cell RNA-seq applications aim to probe a wide dynamic range of gene expression, but most of them are still challenging to accurately quantify low-aboundance transcripts. Based on our previous finding that Tn5 transposase can directly cut-and-tag DNA/RNA hetero-duplexes, we present SHERRY2, an optimized protocol for sequencing transcriptomes of single cells or single nuclei. SHERRY2 is robust and scalable, and it has higher sensitivity and more uniform coverage in comparison with prevalent scRNA-seq methods. With throughput of a few thousand cells per batch, SHERRY2 can reveal the subtle transcriptomic differences between cells and facilitate important biological discoveries.

scholarly journals Myeloid heterogeneity in kidney disease as revealed through single cell RNA sequencing

Kidney360 ◽  
2021 ◽  
pp. 10.34067/KID.0003682021
Author(s):  
Rachel M B Bell ◽  
Laura Denby
Keyword(s):  
Kidney Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Myeloid Cells ◽  
Rna Seq ◽  
Cellular Compartment ◽  
Single Cell Rna Sequencing ◽  
Health And Disease ◽  
Diseased Kidney

Kidney disease represents a global health burden of increasing prevalence and is an independent risk factor for cardiovascular disease. Myeloid cells are a major cellular compartment of the immune system; they are found in the healthy kidney and in increased numbers in the damaged and/or diseased kidney, where they act as key players in the progression of injury, inflammation and fibrosis. They possess enormous plasticity and heterogeneity, adopting different phenotypic and functional characteristics in response to stimuli in the local milieu. Though this inherent complexity remains to be fully understood in the kidney, advances in single-cell genomics promises to change this. Specifically, single-cell RNA sequencing (scRNA-seq) has had a transformative effect on kidney research, enabling the profiling and analysis of the transcriptomes of single cells at unprecedented resolution and throughput, and subsequent generation of cell atlases. Moving forward, combining scRNA- and single-nuclear RNA-seq with greater resolution spatial transcriptomics will allow spatial mapping of kidney disease of varying aetiology to further reveal the patterning of immune cells and non-immune renal cells. This review summarises the roles of myeloid cells in kidney health and disease, the experimental workflow in currently available scRNA-seq technologies and published findings using scRNA-seq in the context of myeloid cells and the kidney.

scholarly journals SPsimSeq: semi-parametric simulation of bulk and single cell RNA sequencing data

2019 ◽  
Author(s):  
Alemu Takele Assefa ◽  
Jo Vandesompele ◽  
Olivier Thas
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Empirical Distribution ◽  
Supplementary Information ◽  
Rna Seq ◽  
Sequencing Data ◽  
Actual Distribution ◽  
Wide Range ◽  
Single Cell Rna Sequencing

SummarySPsimSeq is a semi-parametric simulation method for bulk and single cell RNA sequencing data. It simulates data from a good estimate of the actual distribution of a given real RNA-seq dataset. In contrast to existing approaches that assume a particular data distribution, our method constructs an empirical distribution of gene expression data from a given source RNA-seq experiment to faithfully capture the data characteristics of real data. Importantly, our method can be used to simulate a wide range of scenarios, such as single or multiple biological groups, systematic variations (e.g. confounding batch effects), and different sample sizes. It can also be used to simulate different gene expression units resulting from different library preparation protocols, such as read counts or UMI counts.Availability and implementationThe R package and associated documentation is available from https://github.com/CenterForStatistics-UGent/SPsimSeq.Supplementary informationSupplementary data are available at bioRχiv online.

scholarly journals Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles

2019 ◽  
Author(s):  
Celine Everaert ◽  
Hetty Helsmoortel ◽  
Anneleen Decock ◽  
Eva Hulstaert ◽  
Ruben Van Paemel ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Extracellular Vesicles ◽  
Platelet Rich Plasma ◽  
Rna Seq ◽  
Total Rna ◽  
Rna Molecules ◽  
Rna Profiling ◽  
Wide Range ◽  
Read Distribution ◽  
Free Plasma

AbstractRNA 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.

scholarly journals GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Federico Marini ◽  
Annekathrin Ludt ◽  
Jan Linke ◽  
Konstantin Strauch
Keyword(s):  
Differential Expression ◽  
Differential Expression Analysis ◽  
Transcriptome Profiling ◽  
R Package ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Essential Information ◽  
Wide Range ◽  
Functional Patterns ◽  
Interactive Visualizations

Abstract Background The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats—normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently. Results We developed the software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility. Conclusion is distributed as an R package in the Bioconductor project (https://bioconductor.org/packages/GeneTonic/) under the MIT license. Offering both bird’s-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.

Comparative transcriptome profiling in human bicuspid aortic valve disease using RNA sequencing

2015 ◽  
Vol 47 (3) ◽  
pp. 75-87 ◽  
Author(s):  
Ratnasari Padang ◽  
Richard D. Bagnall ◽  
Tatiana Tsoutsman ◽  
Paul G. Bannon ◽  
Christopher Semsarian
Keyword(s):  
Aortic Valve ◽  
Rna Sequencing ◽  
Bicuspid Aortic Valve ◽  
Molecular Mechanisms ◽  
Transcriptome Profiling ◽  
Common Complication ◽  
Comparative Transcriptome ◽  
Rna Seq ◽  
Calcific Aortic Stenosis ◽  
Phenotype Heterogeneity

Intrinsic valvular degeneration and dysfunction is the most common complication of bicuspid aortic valve (BAV) disease. Phenotypically, it ranges from calcific aortic stenosis to redundant or prolapsing regurgitant leaflets. The underlying molecular mechanism underpinning phenotype heterogeneity of valvular degeneration in BAV is poorly understood. We used RNA sequencing (RNA-seq) to identify genes and pathways responsible for the development of valvular degeneration in BAV, compared with tricuspid aortic valve (TAV). Comparative transcriptome analysis was performed on total RNA of aortic valve tissues of patients with diseased BAV ( n = 5) and calcified TAV ( n = 3). RNA-seq findings were validated by RT-qPCR. A total of 59 and 177 genes were significantly up- and downregulated, respectively, in BAV compared with TAV. Hierarchical clustering indicated heterogeneity within the BAV group, separating those with heavy calcification (BAVc) from those with redundant leaflets and/or minimal calcification (BAVr). Interestingly, the gene expression profile of the BAVc group closely resembled the TAV, with shared up- and downregulation of inflammatory and NOTCH1 signaling pathways, respectively. Downregulation of matrix protease ADAMTS9 and protein aggrecan were observed in BAVr compared with TAV. Dysregulation of fetal gene programs were also present, with notable downregulation of SEMA6B and SEMA3F in BAVr and BAVc compared with TAV, respectively. Upregulation of TBX20 was observed exclusively in BAVr compared with BAVc. In conclusion, diverging molecular mechanisms underpin phenotype heterogeneity of valvular degeneration in BAV and data from the present study suggest that there may be shared mechanisms leading to calcification in BAV and TAV. Recognition of these pathways is fundamental to improve our understanding of the molecular basis of human BAV disease.

scholarly journals Highly parallel direct RNA sequencing on an array of nanopores

2016 ◽  
Author(s):  
Daniel R. Garalde ◽  
Elizabeth A. Snell ◽  
Daniel Jachimowicz ◽  
Andrew J. Heron ◽  
Mark Bruce ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Reverse Transcription ◽  
Biological Information ◽  
Rna Seq ◽  
Sequencing Technology ◽  
Rna Sequences ◽  
Oxford Nanopore ◽  
The Status ◽  
And Function ◽  
Oxford Nanopore Technologies

AbstractRibonucleic acid sequencing can allow us to monitor the RNAs present in a sample. This enables us to detect the presence and nucleotide sequence of viruses, or to build a picture of how active transcriptional processes are changing – information that is useful for understanding the status and function of a sample. Oxford Nanopore Technologies’ sequencing technology is capable of electronically analysing a sample’s DNA directly, and in real-time. In this manuscript we demonstrate the ability of an array of nanopores to sequence RNA directly, and we apply it to a range of biological situations. Nanopore technology is the only available sequencing technology that can sequence RNA directly, rather than depending on reverse transcription and PCR. There are several potential advantages of this approach over other RNA-seq strategies, including the absence of amplification and reverse transcription biases, the ability to detect nucleotide analogues and the ability to generate full-length, strand-specific RNA sequences. Direct RNA sequencing is a completely new way of analysing the sequence of RNA samples and it will improve the ease and speed of RNA analysis, while yielding richer biological information.

scholarly journals Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification

mSystems ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Taylor Reiter
Keyword(s):  
Rna Sequencing ◽  
Low Cost ◽  
Software Tool ◽  
Transcriptome Profiling ◽  
Tool Development ◽  
Rna Seq ◽  
Computational Tools ◽  
Biological Interpretation ◽  
Wet Lab ◽  
Polycistronic Transcripts

ABSTRACT RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely centered around the human transcriptome. While eukaryotic and prokaryotic transcriptomes are similar, key differences in transcribed units limit the transfer of wet-lab and computational tools between the two domains. The article by M. Chung, R. S. Adkins, J. S. A. Mattick, K. R. Bradwell, et al. (mSystems 6:e00917-20, 2021, https://doi.org/10.1128/mSystems.00917-20), demonstrates that integrating prokaryote-specific strategies into existing RNA-seq analyses improves read quantification. Unlike in eukaryotes, polycistronic transcripts derived from operons lead to sequencing reads that span multiple neighboring genes. Chung et al. introduce FADU, a software tool that performs a correction for such reads and thereby improves read quantification and biological interpretation of prokaryotic RNA sequencing.

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