Transcriptome Analysis at the Single‐Cell Level Using SMART Technology

Fish, Rachel N.; Bostick, Magnolia; Lehman, Alisa P.; Farmer, Andrew

doi:10.1002/cpmb.23

Cited by 3 publications

(3 citation statements)

References 33 publications

(42 reference statements)

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“…Although another group has already applied RNA-Seq using MinION to single-cell RNA-Seq, we also considered whether FL-cDNA-Seq is also applicable to this technique 13 . Some existing methods for single-cell RNA-Seq also uses cDNA templates prepared by the same SMART-Seq v4 25 , 26 . Full-length cDNA was synthesized and amplified using the Fluidigm C1 system.…”

Section: Resultsmentioning

confidence: 99%

Evaluation and application of RNA-Seq by MinION

et al. 2018

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The current RNA-Seq method analyses fragments of mRNAs, from which it is occasionally difficult to reconstruct the entire transcript structure. Here, we performed and evaluated the recent procedure for full-length cDNA sequencing using the Nanopore sequencer MinION. We applied MinION RNA-Seq for various applications, which would not always be easy using the usual RNA-Seq by Illumina. First, we examined and found that even though the sequencing accuracy was still limited to 92.3%, practically useful RNA-Seq analysis is possible. Particularly, taking advantage of the long-read nature of MinION, we demonstrate the identification of splicing patterns and their combinations as a form of full-length cDNAs without losing precise information concerning their expression levels. Transcripts of fusion genes in cancer cells can also be identified and characterized. Furthermore, the full-length cDNA information can be used for phasing of the SNPs detected by WES on the transcripts, providing essential information to identify allele-specific transcriptional events. We constructed a catalogue of full-length cDNAs in seven major organs for two particular individuals and identified allele-specific transcription and splicing. Finally, we demonstrate that single-cell sequencing is also possible. RNA-Seq on the MinION platform should provide a novel approach that is complementary to the current RNA-Seq.

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Section: Resultsmentioning

confidence: 99%

Evaluation and application of RNA-Seq by MinION

et al. 2018

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“…To demonstrate the performance of the method, we applied single cell total RNA-seq in four experiments on five different cancer cell lines, of which three undergoing a specific perturbation. In parallel, we also performed single cell polyA[+] RNA-seq on three cell lines using the well-established Smart-seq v4 method (6,40). As in any genomics study, the experimental set-up may suffer from confounding factors, such as variations in cell cycle states of the cells and batch effects of single cell capture and sequencing, masking real biological differences.…”

Section: Discussionmentioning

confidence: 99%

SMARTer single cell total RNA sequencing

Verboom

Everaert

Bolduc

et al. 2019

Nucleic Acids Research

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Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3′ end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.

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“…Besides proteins, nucleic acids are the major class of molecules used in EV-based biomarker studies. Especially, next generation sequencing (NGS) techniques have helped to overcome limitations of initial transcriptomic studies of EVs with expression microarrays, such as the necessity of a high sample input amount and the inability to detect undescribed RNA molecules [23]. Despite the rapid advances in NGS techniques [24], however, RNA sequencing of EVs is not yet a standard laboratory practice, and there are only a limited number of studies using this approach in PCa.…”

Section: Introductionmentioning

confidence: 99%

miR-10a-5p and miR-29b-3p as Extracellular Vesicle-Associated Prostate Cancer Detection Markers

Worst

Previti

Nitschke

et al. 2019

Cancers

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Extracellular vesicles (EVs) are shed by many different cell types. Their nucleic acids content offers new opportunities for biomarker research in different solid tumors. The role of EV RNA in prostate cancer (PCa) is still largely unknown. EVs were isolated from different benign and malignant prostate cell lines and blood plasma from patients with PCa (n = 18) and controls with benign prostatic hyperplasia (BPH) (n = 7). Nanoparticle tracking analysis (NTA), Western blot, electron microscopy, and flow cytometry analysis were used for the characterization of EVs. Non-coding RNA expression profiling of PC3 metastatic PCa cells and their EVs was performed by next generation sequencing (NGS). miRNAs differentially expressed in PC3 EVs were validated with qRT-PCR in EVs derived from additional cell lines and patient plasma and from matched tissue samples. 92 miRNAs were enriched and 48 miRNAs were depleted in PC3 EVs compared to PC3 cells, which could be confirmed by qRT-PCR. miR-99b-5p was significantly higher expressed in malignant compared to benign EVs. Furthermore, expression profiling showed miR-10a-5p (p = 0.018) and miR-29b-3p (p = 0.002), but not miR-99b-5p, to be overexpressed in plasma-derived EVs from patients with PCa compared with controls. In the corresponding tissue samples, no significant differences in the miRNA expression could be observed. We thus propose that EV-associated miR-10a-5p and miR-29b-3p could serve as potential new PCa detection markers.

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Transcriptome Analysis at the Single‐Cell Level Using SMART Technology

Cited by 3 publications

References 33 publications

Evaluation and application of RNA-Seq by MinION

Evaluation and application of RNA-Seq by MinION

SMARTer single cell total RNA sequencing

miR-10a-5p and miR-29b-3p as Extracellular Vesicle-Associated Prostate Cancer Detection Markers

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