Say Li Kong1,2, Huipeng Li3, Joyce A Tai2, Elise T Courtois3,4, Huay Mei Poh5,2, Dawn Pingxi Lau6, Yu Xuan Haw2, Narayanan Gopalakrishna Iyer6, Daniel Shao Weng Tan6, Shyam Prabhakar3, Dave Ruff7,8, Axel M Hillmer9,10. 1. Translational Research, Genome Institute of Singapore, Singapore; kongsl@gis.a-star.edu.sg ahillmer@uni-koeln.de. 2. Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore. 3. Computational and Systems Biology, Genome Institute of Singapore, Singapore. 4. The Jackson Laboratory for Genomic Medicine, Farmington, CT. 5. Translational Research, Genome Institute of Singapore, Singapore. 6. National Cancer Centre, Singapore. 7. Fluidigm Corporation, South San Francisco, CA. 8. Mission Bio, South San Francisco, CA. 9. Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore; kongsl@gis.a-star.edu.sg ahillmer@uni-koeln.de. 10. Institute for Pathology, University Hospital Cologne, Cologne, Germany.
Abstract
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.
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 EGFRT790M, 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.
Authors: Yalan Lei; Rong Tang; Jin Xu; Wei Wang; Bo Zhang; Jiang Liu; Xianjun Yu; Si Shi Journal: J Hematol Oncol Date: 2021-06-09 Impact factor: 17.388
Authors: Say Li Kong; Xingliang Liu; Swee Jin Tan; Joyce A Tai; Ler Yee Phua; Huay Mei Poh; Trifanny Yeo; Yong Wei Chua; Yu Xuan Haw; Wen Huan Ling; Raymond Chee Hui Ng; Tira J Tan; Kiley Wei Jen Loh; Daniel Shao-Weng Tan; Quan Sing Ng; Mei Kim Ang; Chee Keong Toh; Yi Fang Lee; Chwee Teck Lim; Tony Kiat Hon Lim; Axel M Hillmer; Yoon Sim Yap; Wan-Teck Lim Journal: Front Oncol Date: 2021-07-16 Impact factor: 6.244