Somatic mutations and cell identity linked by Genotyping of Transcriptomes
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Abstract
Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.
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Cell hashing enabled multiplexing baseline and IFNa-treated samples into the same scRNA-seq reactions via time-point specifying barcoded antibodies, to obviate technical batch effects between serial samples.
“We further incorporated cell hashing 24 that enabled multiplexing baseline and IFNa-treated samples into the same scRNA-seq reactions via time-point specifying barcoded antibodies, to obviate technical batch effects between serial samples ( Fig. 1b ).”
From Type 1 interferon perturbates clonal competition by reshaping human blood development (2026) · cites this paper as [24]
The Methods section on Genotyping of Transcriptomes describes cell barcodes used to link genotypes with transcriptomes, not antibody-based cell hashing. Searches for cell hashing, time-point-specific barcoded antibodies, and baseline versus IFNa-treated sample multiplexing found no passage addressing the cited claim. (LLM, conf=0.76)
Experimental — accuracy not yet measuredTime-point specifying barcoded antibodies were incorporated to combine serial samples from the same individuals into a single experiment to remove technical batch effects.
“we incorporated time-point specifying barcoded antibodies 24 to combine serial samples from the same individuals into a single experiment to remove technical batch effects”
From Type 1 interferon perturbates clonal competition by reshaping human blood development (2026) · cites this paper as [24]
The Methods sections on GoT and Circularization GoT describe cell barcodes, sample indexes, and barcoded cDNA, but not time-point-specific barcoded antibodies. A search for antibody-based labeling of serial samples and removal of batch effects found no passage in our copy addressing that procedure. (LLM, conf=0.74)
Experimental — accuracy not yet measured
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MARIMO cells harbor a CALR mutation but are not dependent on JAK2/STAT5 signaling
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Cancer Evolution: No Room for Negative Selection
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Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional SpacesPreprint
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Clinical and therapeutic relevance of cancer-associated fibroblasts
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Self-citationSingle-Cell RNA Sequencing in Cancer: Lessons Learned and Emerging Challenges
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Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics
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The Glioma Stem Cell Model in the Era of Single-Cell Genomics
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Advancing Cancer Research and Medicine with Single-Cell Genomics
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Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling
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Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy
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Development and future of droplet microfluidics
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Leukemic stem cells and therapy resistance in acute myeloid leukemia
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Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states
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Self-citationDNA methylation disruption reshapes the hematopoietic differentiation landscape
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“Full transcript coverage unlocks the potential to detect mutations and allelic expression for specific isoforms in an unbiased way compared to methods such as GoT-seq [41].”
MethodVan Egeren, D., Escabi, J., Nguyen, M., Liu, S., Reilly, C. R., Patel, S., Kamaz, B., Kalyva, M., DeAngelo, D. J., Galinsky, I., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.02.001 · Cited by 206 · see citing works
Integration of whole transcriptome spatial profiling with protein markers
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Self-citationSingle-cell transcriptomics in cancer: computational challenges and opportunities
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“Molecular Cell 78, 477–49 This is an open access article und vides an unprecedented opportunity to identify cancer-cell-specific targets (Giustacchini et al., 2017; Nam et al., 2019; Rodriguez-Meira et al., 2019).”
BackgroundUnravelling cellular relationships during development and regeneration using genetic lineage tracing
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Genetic basis and molecular profiling in myeloproliferative neoplasms
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Clonal hematopoiesis is associated with protection from Alzheimer’s disease
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Unraveling Hematopoiesis through the Lens of Genomics
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High-throughput single-сell sequencing in cancer research
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“Genotyping of Transcriptomes based on the 10x Genomics platform could be an effective solution to this deficiency.(247) The existence of mature single-cell DNA sequencing technologies (such as Tapestri solution from Mission Bio) must also be mentioned; these may be the best way to accurately obtain genotypes (SNVs, CN…”
MethodDeciphering cell states and genealogies of human haematopoiesis
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Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors
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Landmarks of human embryonic development inscribed in somatic mutations
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De novo detection of somatic mutations in high-throughput single-cell profiling data sets
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RAS-mutant leukaemia stem cells drive clinical resistance to venetoclax
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“We next examined data obtained from a patient with AML with a subclonal NRAS G12D mutation with the Genotyping of Transcriptomes (GoT) method 31 (Fig.”
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Mutant calreticulin in myeloproliferative neoplasms
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Cancer Evolution: A Multifaceted Affair
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Self-citationER stress as a sentinel mechanism for ER Ca2+ homeostasis
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The evolutionary theory of cancer: challenges and potential solutions
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Nicheformer: a foundation model for single-cell and spatial omics
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Self-citationThe Somatic Mosaicism across Human Tissues Network
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Self-citationClonal hematopoiesis and inflammation – the perpetual cycle
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Age-associated differences in the cancer molecular landscape
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The functional and evolutionary impacts of human-specific deletions in conserved elements
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Ultraviolet radiation shapes dendritic cell leukaemia transformation in the skin
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Self-citationWhat is the Pathogenic CAG Expansion Length in Huntington’s Disease?
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The end of the genetic paradigm of cancer
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“When applied to human JAK2 V617 -mutated CH, PV and MF, GoT–ChA substantially increases the genotyping rate relative to RNA-based methods 19,22,23 .”
InfluentialSelf-citationMosca, M., Hermange, G., Tisserand, A., Noble, R., Marzac, C., Marty, C., Le Sueur, C., Campario, H., Vertenoeil, G., El-Khoury, M., et al. (2021) · Blood · doi:10.1182/blood.2021010986 · Cited by 57 · see citing works
Decoding Cancer Biology One Cell at a Time
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“, 2018 ( 119 ) Wilms tumor, clear cell renal carcinoma, papillary renal cell carcinoma 72,501 (23)”
BackgroundMethodActive learning framework leveraging transcriptomics identifies modulators of disease phenotypes
DeMeo, B., Nesbitt, C., Miller, S. A., Burkhardt, D. B., Lipchina, I., Fu, D., Holderrieth, P., Kim, D., Kolchenko, S., Szałata, A., et al. (2025) · Science · doi:10.1126/science.adi8577 · Cited by 58 · see citing works
“…strategies for signature identification, such as prioritizing genes on the basis of fate mapping ( 69 ), paired single-cell genotyping ( 70 ), transfer learning of signatures between contexts informed by epigenetic or spatial atlas priors, or by causal inference of regulatory…”
DENDRO: genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing
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Self-citationMastering the use of cellular barcoding to explore cancer heterogeneity
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“In comparison, MF shows no difference in gene enrichment between MkPs and HSCs. Additionally, mutant MkPs show upregulated TGFβ with the degree of upregulation correlating with the degree of fibrosis seen in MF and ET [60].”
BackgroundInfluentialApplications of Single-Cell Omics in Tumor Immunology
Liu, J., Qu, S., Zhang, T., Gao, Y., Shi, H., Song, K., Chen, W., & Yin, W. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.697412 · Cited by 52 · see citing works
“org 6 the IRE1-XBP1 pathway in HSPCs as a potential therapeutic target (77).”
BackgroundScalable co-sequencing of RNA and DNA from individual nuclei
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“For example, combining DEFND-seq with multiplexed targeted amplification either on-chip or following pooled library construction on either the mRNA or gDNA libraries could enhance our genotyping efficiency for specific targets 11,43 .”
Induced Human Regulatory T Cells Express the Glucagon-like Peptide-1 Receptor
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MethodSingle-cell genomics to understand disease pathogenesis
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Single‐Cell Multi‐Omics and Its Prospective Application in Cancer Biology
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Somatic Variants: New Kids on the Block in Human Immunogenetics
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“As the NfkB pathway is also upregulated in CALR-mutated HSPCs [44], it is also likely that BET inhibition would be beneficial in CALR-mediated MPNs. Early data using the BET inhibitor CPI-0610 in PMF patients, either as a monotherapy or with Ruxolitinib, reduced bone marrow fibrosis, spleen size and ameliorated cytope…”
BackgroundHigh-throughput microfluidic droplets in biomolecular analytical system: A review
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Mobilized peripheral blood: an updated perspective
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Nanopore Sequencing in Blood Diseases: A Wide Range of Opportunities
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“Changes in the promoter methylation of TAL1, ERHV-3, CDKN2A, CALCA, p15, IDH1/2, and TP53 genes have been associated with relapse in T-cell acute lymphoblastic leukemia (T-ALL) (Hogan et al., 2011; Nordlund et al., 2013).”
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Temporal recording of mammalian development and precancer
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Dissecting microbial communities with single-cell transcriptome analysis
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Functional analysis of structural variants in single cells using Strand-seq
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“3 | Haplotype-specific NO analysis shows local effects of a copy-neutral driver SV in AML. a , Balanced t(8;21) translocation in AML_1, discovered based on strand cosegregation ( P value = 0.00003 for translocation discovery using strand cosegregation 24 , FDR-adjusted Fisher’s exact test;…”
InfluentialThe Role of Megakaryocytes in Myelofibrosis
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Quantitative Single-Cell Proteomics as a Tool to Characterize Cellular HierarchiesPreprint
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LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data
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Genetic and Transcriptional Contributions to Relapse in Normal Karyotype Acute Myeloid Leukemia
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The Microenvironment in Myeloproliferative Neoplasms
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Genetic heterogeneity and clonal evolution in acute myeloid leukemia
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“Recent studies have improved the detection of low-level transcripts, longer read lengths to detect mutations distantly located from transcript ends, as well as increased throughput to sequence thousands of cells such as genotyping of transcriptomes and other single-cell method adaptations [13,14,21].”
BackgroundHuman embryonic genetic mosaicism and its effects on development and disease
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“Some groups have attempted to overcome the challenges of genotyping with scRNA-seq by first amplifying specific regions of interest in the scRNA-seq library 39 or by pairing it with bulk deep genome sequencing 40 .”
Calreticulin mutations affect its chaperone function and perturb the glycoproteome
Schürch, P. M., Malinovska, L., Hleihil, M., Losa, M., Hofstetter, M., Wildschut, M. H. E., Lysenko, V., Lakkaraju, A. K., Maat, C. A., Benke, D., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111689 · Cited by 31 · see citing works
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“Landau’s team performed the genotyping of transcriptomes of CALR-mutated cells, but also of cells carrying JAK2, SF3B1 and NFE2 mutations [52].”
BackgroundPrins, D., Park, H. J., Watcham, S., Li, J., Vacca, M., Bastos, H. P., Gerbaulet, A., Vidal‐Puig, A., Göttgens, B., & Green, A. R. (2020) · Science Advances · doi:10.1126/sciadv.abd3139 · Cited by 28 · see citing works
“In addition, mutant CALR cells showed an increase in cell cycle genes, again consistent with observations from human patient cells (34) and in agreement with our in vitro data, which showed that mutant CALR HSCs and MkPs were more proliferative.”
InfluentialApplication of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia
Zhang, Z., Huang, J., Zhang, Z., Shen, H., Tang, X., Wu, D., Bao, X., Xu, G., & Chen, S. (2024) · Biomarker Research · doi:10.1186/s40364-024-00600-1 · Cited by 30 · see citing works
“Metabolic information can also be integrated through measuring mitochondrial marker mutations (genotyping of transcriptomes, TARGET-seq, and MutaSeq) [283–285].”
BackgroundDeconvoluting clonal and cellular architecture in IDH-mutant acute myeloid leukemia
Sirenko, M., Lee, S., Sun, Z., Chaligne, R., Loghavi, S., Asimomitis, G., Brierley, C. K., Bernard, E., Cai, S. F., Myers, R. M., et al. (2025) · Cell Stem Cell · doi:10.1016/j.stem.2025.04.012 · Cited by 28 · see citing works
Self-citationStrickland, M., Quek, L. S., & Psaila, B. (2021) · British Journal of Haematology · doi:10.1111/bjh.17850 · Cited by 26 · see citing works
Jutzi, J. S., Marneth, A. E., Jiménez‐Santos, M. J., Hem, J. W., Guerra-Moreno, Á., Rolles, B., Bhatt, S., Myers, S. A., Carr, S. A., Hong, Y., et al. (2022) · Leukemia · doi:10.1038/s41375-022-01781-0 · Cited by 27 · see citing works
“Here, using mutant Calr knockin mice and primary CALR-mutant MPN samples, we find differential upregulation of the IRE1a-XBP1 axis of the UPR as well as the proteasome in CALR-mutated hematopoietic stem cells (HSCs) and megakaryocytes.”
BackgroundInfluentialSelf-citation
- Authors
- Nam, A. S., Kim, K.-T., Chaligne, R., Izzo, F., Ang, C., Taylor, J., Myers, R. M., Abu-Zeinah, G., Brand, R., Omans, N. D., Alonso, A., Sheridan, C., Mariani, M., Dai, X., Harrington, E., Pastore, A., Cubillos-Ruiz, J. R., Tam, W., Hoffman, R., Rabadan, R., Scandura, J. M., Abdel-Wahab, O., Smibert, P., & Landau, D. A.
- Affiliations
- New York Genome Center (US)
- Memorial Sloan Kettering Cancer Center (US)
- Weill Cornell Medicine (US)
- Oxford Nanopore Technologies (United Kingdom) (GB)
- Tisch Cancer Institute (US)
- Corresponding author
- Landau, Dan A.
- ORCID
- Venue
- Nature
- Published
- 2019-07-03
- Volume
- 571
- Issue
- 7765
- Pages
- 355-360
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6782071
- OpenAlex
- W2954384525
- Cited by
- 333
- References
- 92
- Citations by year
- 2026: 35 · 2025: 54 · 2024: 59 · 2023: 41 · 2022: 44 · 2021: 49 · 2020: 36 · 2019: 13 · 2018: 2
- FWCI
- 11.74
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Burroughs Wellcome Fund
- Brigham and Women's Hospital
- National Institutes of Health (1dp2ca239065-01, 5r01ca229902-05, UL1TR002384)
- Stand Up To Cancer
- National Heart, Lung, and Blood Institute (R01HL145283, P01HL053762)
- National Cancer Institute (DP2-CA239065, U54CA193313, R01-CA229902, P30CA008748, P01CA108671)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Genetics › Myeloproliferative Neoplasms: Diagnosis and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- somatic mutations, cell identity, CALR mutation, myeloproliferative neoplasms, hematopoiesis, unfolded protein response, NF-κB signaling, myeloid differentiation, clonal fitness, single-cell RNA sequencing, droplet-based sequencing
- MeSH terms
- Animals, Cell Line, Clone Cells, Endoribonucleases, Genotype, Hematopoiesis, Hematopoietic Stem Cells, Humans, Models, Molecular, Mutation, Myeloproliferative Disorders, Neoplasms, Neoplastic Stem Cells, NF-kappa B, Protein Serine-Threonine Kinases, Sequence Analysis, RNA, Antigens, CD34, Calreticulin, Cell Proliferation, Mice, Primary Myelofibrosis, Unfolded Protein Response, Single-Cell Analysis, High-Throughput Nucleotide Sequencing, Transcriptome
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