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TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing

ABSTRACT: TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing

PROVIDER: PRJNA415199 | ENA |

REPOSITORIES: ENA

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TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing [validation in cell lines; Figure 2 and Figure S3]

Project description:TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing [validation in cell lines; Figure 2 and Figure S3]

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TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing [validation in cell lines; Figure 2 and Figure S3]

Project description:We developed TARGET-seq, a single-cell genotyping and RNA-seq method, which allows accurate detection of multiple mutations within single-cells from genomic and coding DNA in parallel with whole transcriptome analysis, providing a powerful tool to link transcriptional and genetic tumor heterogeneity. Single cell whole transcriptome analysis of JURKAT, SET2 and HSPCs using SMART-seq+, mRNA targeting (tSMARTseq) or TARGET-seq reveals very good correlations between methods.

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Project description:We developed 3'-TARGET-seq, a single-cell genotyping and RNA-seq method, which allows accurate detection of multiple mutations within single-cells from genomic and coding DNA in parallel with high throughput 3'-biased whole transcriptome analysis, providing a powerful tool to link transcriptional and genetic tumor heterogeneity. Single cell whole transcriptome sequencing of 2798 Lineage-CD34+ HSPC (Hematopoietic Stem and Progenitor Cells) from patients with JAK2-V617F mutant myelofibrosis and normal controls using 3'-TARGET-seq reveals distinct molecular signatures associated with the presence of somatic mutations in single cells as well as distinct transcriptional profiles of WT cells from patient samples as compared with normal controls.

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TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing

Project description:This SuperSeries is composed of the SubSeries listed below.

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A Novel RNA Sequencing Data Analysis Method for Cell Line Authentication

Project description:We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.

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