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Abstract
Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural ‘barcodes’, we define the optimal targets for nanoranger, namely those loci close to the 5’ end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.
Single-cell transcriptomics excel in cell subset classification and can be augmented by suitable genotype information. Here the authors devise a long-read sequencing workflow, termed nanoranger, for detection of molecular barcodes from single-cell cDNA and apply this to clonal tracking of acute myeloid leukemia and identification of complex immune phenotypes.
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1 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Hematology, Berlin, Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662); Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Berlin, Germany (GRID:grid.484013.a) (ISNI:0000 0004 6879 971X)
2 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34); Dana-Farber Cancer Institute, Translational Immunogenomics Lab, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
3 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34)
4 Dana-Farber Cancer Institute, Translational Immunogenomics Lab, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
5 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X)
6 Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34)
7 Dana-Farber Cancer Institute, Department of Data Science, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
8 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Brigham and Women’s Hospital, Department of Medicine, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294)
9 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X)
10 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Dana-Farber Cancer Institute, Translational Immunogenomics Lab, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
11 Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910); Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, USA (GRID:grid.66859.34); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Brigham and Women’s Hospital, Department of Medicine, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294)