scholarly journals SMARTer single cell total RNA sequencing

2019 ◽  
Vol 47 (16) ◽  
pp. e93-e93 ◽  
Author(s):  
Karen Verboom ◽  
Celine Everaert ◽  
Nathalie Bolduc ◽  
Kenneth J Livak ◽  
Nurten Yigit ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Expression Patterns ◽  
Cancer Cell Lines ◽  
Cellular Heterogeneity ◽  
Circular Rnas ◽  
Rna Seq ◽  
Total Rna

Abstract 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.

scholarly journals SMARTer single cell total RNA sequencing

2018 ◽  
Author(s):  
Verboom Karen ◽  
Everaert Celine ◽  
Bolduc Nathalie ◽  
Livak J. Kenneth ◽  
Yigit Nurten ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Transcript Level ◽  
Cellular Heterogeneity ◽  
Circular Rnas ◽  
Rna Seq ◽  
Sequencing Data ◽  
Total Rna ◽  
Sequencing Experiment

AbstractSingle 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. 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.

scholarly journals Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

2019 ◽  
Author(s):  
Gabriela S. Kinker ◽  
Alissa C. Greenwald ◽  
Rotem Tal ◽  
Zhanna Orlova ◽  
Michael S. Cuoco ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Human Tumors ◽  
Model Systems ◽  
Cellular Heterogeneity ◽  
Specific Cell ◽  
Rna Seq ◽  
Mesenchymal Transition

AbstractCultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

Expression patterns of miR-221 and its target Caspase-3 in different cancer cell lines

2014 ◽  
Vol 41 (9) ◽  
pp. 5877-5881 ◽  
Author(s):  
Sercan Ergun ◽  
Kaifee Arman ◽  
Ebru Temiz ◽  
İbrahim Bozgeyik ◽  
Önder Yumrutaş ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Caspase 3 ◽  
Expression Patterns ◽  
Cancer Cell Lines

scholarly journals Joint single cell DNA-seq and RNA-seq of gastric cancer cell lines reveals rules of in vitro evolution

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Noemi Andor ◽  
Billy T Lau ◽  
Claudia Catalanotti ◽  
Anuja Sathe ◽  
Matthew Kubit ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Phenotypic Diversity ◽  
Single Cells ◽  
Cancer Cell Lines ◽  
Gastric Cancer Cell Lines

Abstract Cancer cell lines are not homogeneous nor are they static in their genetic state and biological properties. Genetic, transcriptional and phenotypic diversity within cell lines contributes to the lack of experimental reproducibility frequently observed in tissue-culture-based studies. While cancer cell line heterogeneity has been generally recognized, there are no studies which quantify the number of clones that coexist within cell lines and their distinguishing characteristics. We used a single-cell DNA sequencing approach to characterize the cellular diversity within nine gastric cancer cell lines and integrated this information with single-cell RNA sequencing. Overall, we sequenced the genomes of 8824 cells, identifying between 2 and 12 clones per cell line. Using the transcriptomes of more than 28 000 single cells from the same cell lines, we independently corroborated 88% of the clonal structure determined from single cell DNA analysis. For one of these cell lines, we identified cell surface markers that distinguished two subpopulations and used flow cytometry to sort these two clones. We identified substantial proportions of replicating cells in each cell line, assigned these cells to subclones detected among the G0/G1 population and used the proportion of replicating cells per subclone as a surrogate of each subclone's growth rate.

scholarly journals Platform-integrated mRNA isoform quantification

2019 ◽  
Vol 36 (8) ◽  
pp. 2466-2473 ◽  
Author(s):  
Jiao Sun ◽  
Jae-Woong Chang ◽  
Teng Zhang ◽  
Jeongsik Yong ◽  
Rui Kuang ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Large Scale ◽  
Cancer Cell Lines ◽  
Supplementary Information ◽  
Rna Seq ◽  
Mrna Quantification ◽  
Transcript Quantification ◽  
Isoform Expression ◽  
Isoform Quantification

Abstract Motivation Accurate estimation of transcript isoform abundance is critical for downstream transcriptome analyses and can lead to precise molecular mechanisms for understanding complex human diseases, like cancer. Simplex mRNA Sequencing (RNA-Seq) based isoform quantification approaches are facing the challenges of inherent sampling bias and unidentifiable read origins. A large-scale experiment shows that the consistency between RNA-Seq and other mRNA quantification platforms is relatively low at the isoform level compared to the gene level. In this project, we developed a platform-integrated model for transcript quantification (IntMTQ) to improve the performance of RNA-Seq on isoform expression estimation. IntMTQ, which benefits from the mRNA expressions reported by the other platforms, provides more precise RNA-Seq-based isoform quantification and leads to more accurate molecular signatures for disease phenotype prediction. Results In the experiments to assess the quality of isoform expression estimated by IntMTQ, we designed three tasks for clustering and classification of 46 cancer cell lines with four different mRNA quantification platforms, including newly developed NanoString’s nCounter technology. The results demonstrate that the isoform expressions learned by IntMTQ consistently provide more and better molecular features for downstream analyses compared with five baseline algorithms which consider RNA-Seq data only. An independent RT-qPCR experiment on seven genes in twelve cancer cell lines showed that the IntMTQ improved overall transcript quantification. The platform-integrated algorithms could be applied to large-scale cancer studies, such as The Cancer Genome Atlas (TCGA), with both RNA-Seq and array-based platforms available. Availability and implementation Source code is available at: https://github.com/CompbioLabUcf/IntMTQ. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A combined computational pipeline to detect circular RNAs in human cancer cells under hypoxic stress

2019 ◽  
Vol 11 (10) ◽  
pp. 829-844 ◽  
Author(s):  
Antonella Di Liddo ◽  
Camila de Oliveira Freitas Machado ◽  
Sandra Fischer ◽  
Stefanie Ebersberger ◽  
Andreas W Heumüller ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Human Cancer ◽  
Cancer Cell Lines ◽  
Metabolic Adaptation ◽  
Circular Rnas ◽  
Hypoxic Stress ◽  
Computational Pipeline ◽  
Transcriptional Responses

Abstract Hypoxia is associated with several diseases, including cancer. Cells that are deprived of adequate oxygen supply trigger transcriptional and post-transcriptional responses, which control cellular pathways such as angiogenesis, proliferation, and metabolic adaptation. Circular RNAs (circRNAs) are a novel class of mainly non-coding RNAs, which have been implicated in multiple cancers and attract increasing attention as potential biomarkers. Here, we characterize the circRNA signatures of three different cancer cell lines from cervical (HeLa), breast (MCF-7), and lung (A549) cancer under hypoxia. In order to reliably detect circRNAs, we integrate available tools with custom approaches for quantification and statistical analysis. Using this consolidated computational pipeline, we identify ~12000 circRNAs in the three cancer cell lines. Their molecular characteristics point to an involvement of complementary RNA sequences as well as trans-acting factors in circRNA biogenesis, such as the RNA-binding protein HNRNPC. Notably, we detect a number of circRNAs that are more abundant than their linear counterparts. In addition, 64 circRNAs significantly change in abundance upon hypoxia, in most cases in a cell type-specific manner. In summary, we present a comparative circRNA profiling in human cancer cell lines, which promises novel insights into the biogenesis and function of circRNAs under hypoxic stress.

scholarly journals Expression of p120-Catenin Isoforms Correlates with Genomic and Transcriptional Phenotype of Breast Cancer Cell Lines

2007 ◽  
Vol 29 (6) ◽  
pp. 467-476
Author(s):  
Joana Paredes ◽  
Ana Luísa Correia ◽  
Ana Sofia Ribeiro ◽  
Fernando Schmitt
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Expression Patterns ◽  
Cell Signalling ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
P120 Catenin ◽  
Transcriptional Phenotype

Background: P120-catenin is a member of the Armadillo protein family, which is involved in intercellular adhesion and cell signalling. It directly interacts with the classical cadherins juxtamembrane domain and contributes for both junction formation and its disassembly. Accumulating evidences indicate that p120-catenin is important in tumour formation and progression, although the role of their multiple spliced isoforms in the regulation of cadherin-mediated adhesion of malignant cells is still not well understood. We investigated the expression of p120-catenin isoforms in a collection of breast cancer cell lines with distinct molecular profiles and expressing different cadherins. Methods: We assessed the expression by RT-PCR and Western-blotting analysis. Results: We observed that the expression of p120-catenin isoforms was associated with the genomic and transcriptional phenotype of breast cancer cells. Besides, the recruitment of p120-catenin isoforms was not apparently related with the particular expression of E-, P- or N-cadherin. Conclusion: We demonstrate that mammary tumour cells exhibit a characteristic p120-catenin isoform expression profile, depending from their specific genomic and transcriptional properties. These particular expression patterns, combined with other regulatory proteins and in a specific cellular context, may explain how p120-catenin can either contribute to strength intercellular adhesions or instead to promote cell motility.

Sign in / Sign up

Export Citation Format

Share Document