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Concurrent Single-Cell RNA and Targeted DNA Sequencing on an Automated Platform for Comeasurement of Genomic and Transcriptomic Signatures.
Kong, Say Li; Li, Huipeng; Tai, Joyce A; Courtois, Elise T; Poh, Huay Mei; Lau, Dawn Pingxi; Haw, Yu Xuan; Iyer, Narayanan Gopalakrishna; Tan, Daniel Shao Weng; Prabhakar, Shyam; Ruff, Dave; Hillmer, Axel M.
Afiliação
  • Kong SL; Translational Research, Genome Institute of Singapore, Singapore; kongsl@gis.a-star.edu.sg ahillmer@uni-koeln.de.
  • Li H; Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
  • Tai JA; Computational and Systems Biology, Genome Institute of Singapore, Singapore.
  • Courtois ET; Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
  • Poh HM; Computational and Systems Biology, Genome Institute of Singapore, Singapore.
  • Lau DP; The Jackson Laboratory for Genomic Medicine, Farmington, CT.
  • Haw YX; Translational Research, Genome Institute of Singapore, Singapore.
  • Iyer NG; Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
  • Tan DSW; National Cancer Centre, Singapore.
  • Prabhakar S; Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore.
  • Ruff D; National Cancer Centre, Singapore.
  • Hillmer AM; National Cancer Centre, Singapore.
Clin Chem ; 65(2): 272-281, 2019 02.
Article em En | MEDLINE | ID: mdl-30523199
BACKGROUND: The comeasurement of both genomic and transcriptomic signatures in single cells is of fundamental importance to accurately assess how the genetic information correlates with the transcriptomic phenotype. However, existing technologies have low throughput and laborious work flows. METHODS: We developed a new method for concurrent sequencing of the transcriptome and targeted genomic regions (CORTAD-seq) within the same single cell on an automated microfluidic platform. The method was compatible with the downstream library preparation, allowing easy integration into existing next-generation sequencing work flows. We incorporated a single-cell bioinformatics pipeline for transcriptome and mutation analysis. RESULTS: As proof of principle, we applied CORTAD-seq to lung cancer cell lines to dissect the cellular consequences of mutations that result in resistance to targeted therapy. We obtained a mean detection of 6000 expressed genes and an exonic rate of 50%. The targeted DNA-sequencing data achieved a 97.8% detection rate for mutations and allowed for the identification of copy number variations and haplotype construction. We detected expression signatures of tyrosine kinase inhibitor (TKI) resistance, epidermal growth factor receptor (EGFR) amplification, and expansion of the T790M mutation among resistant cells. We also identified characteristics for TKI resistance that were independent of EGFR T790M, indicating that other alterations are required for resistance in this context. CONCLUSIONS: CORTAD-seq allows assessment of the interconnection between genetic and transcriptomic changes in single cells. It is operated on an automated, commercially available single-cell isolation platform, making its implementation straightforward.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA / Análise de Sequência de DNA / Genômica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA / Análise de Sequência de DNA / Genômica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article