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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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“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]
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“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”
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Classification and Regression by randomForest
Liaw, A. I., & Wiener, M. C. (2007) · Cited by 18,594
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
Self-citationMinimap2: Pairwise alignment for nucleotide sequences
Li, H. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty191 · Cited by 14,807
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Self-citationGeneralized linear mixed models: a practical guide for ecology and evolution
Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2008.10.008 · Cited by 8,910
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055
Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
Tirosh, I., Izar, B., Prakadan, S. M., Wadsworth, M. H., Treacy, D., Trombetta, J. J., Rotem, A., Rodman, C., Lian, C., Murphy, G., et al. (2016) · Science · doi:10.1126/science.aad0501 · Cited by 4,944
Age-related clonal hematopoiesis associated with adverse outcomes
Jaiswal, S., Fontanillas, P., Flannick, J., Manning, A., Grauman, P. V., Mar, B. G., Lindsley, R. C., Mermel, C. H., Burtt, N., Chavez, A., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1408617 · Cited by 4,841
Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt
Durinck, S., Spellman, P. T., Birney, E., & Huber, W. K. (2009) · Nature Protocols · doi:10.1038/nprot.2009.97 · Cited by 4,156
Yoshida, H., Matsui, T., Yamamoto, A., Okada, T., & Mori, K. (2001) · Cell · doi:10.1016/s0092-8674(01)00611-0 · Cited by 4,054
Mutation of the mouse klotho gene leads to a syndrome resembling ageing
Kuro-o, M., Matsumura, Y., Aizawa, H., Kawaguchi, H., Suga, T., Utsugi, T., Ohyama, Y., Kurabayashi, M., Kaname, T., Kume, E., et al. (1997) · Nature · doi:10.1038/36285 · Cited by 3,837
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356
Simultaneous epitope and transcriptome measurement in single cells
Stoeckius, M., Hafemeister, C., Stephenson, W., Houck-Loomis, B., Chattopadhyay, P. K., Swerdlow, H., Satija, R., & Smibert, P. (2017) · Nature Methods · doi:10.1038/nmeth.4380 · Cited by 3,098
Self-citationDeep generative modeling for single-cell transcriptomics
Lopez, R., Regier, J., Cole, M. B., Jordan, M. I., & Yosef, N. (2018) · Nature Methods · doi:10.1038/s41592-018-0229-2 · Cited by 2,530
Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors
Villani, A.-C., Satija, R., Reynolds, G., Sarkizova, S., Shekhar, K., Fletcher, J., Griesbeck, M., Butler, A., Zheng, S., Lazo, S., et al. (2017) · Science · doi:10.1126/science.aah4573 · Cited by 2,413
Comprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.060 · Cited by 2,256
Lee, A., Iwakoshi, N. N., & Glimcher, L. H. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.23.21.7448-7459.2003 · Cited by 2,099
Somatic Mutations of Calreticulin in Myeloproliferative Neoplasms
Klampfl, T., Gisslinger, H., Harutyunyan, A. S., Nivarthi, H., Rumi, E., Milosevic, J. D., Them, N. C. C., Berg, T., Gisslinger, B., Pietra, D., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1311347 · Cited by 2,003
COSMIC: somatic cancer genetics at high-resolution
Forbes, S. A., Beare, D., Boutselakis, H., Bamford, S., Bindal, N., Tate, J., Cole, C. G., Ward, S., Dawson, E., Ponting, L., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1121 · Cited by 1,922
Age-related mutations associated with clonal hematopoietic expansion and malignancies
Xie, M., Lu, C., Wang, J., McLellan, M. D., Johnson, K. J., Wendl, M. C., McMichael, J. F., Schmidt, H. K., Yellapantula, V., Miller, C. A., et al. (2014) · Nature Medicine · doi:10.1038/nm.3733 · Cited by 1,874
Somatic CALR Mutations in Myeloproliferative Neoplasms with Nonmutated JAK2
Nangalia, J., Massie, C. E., Baxter, E. J., Nice, F. L., Gundem, G., Wedge, D. C., Avezov, E., Li, J., Kollmann, K., Kent, D. G., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1312542 · Cited by 1,756
The Unfolded Protein Response and Cell Fate Control
Hetz, C. A., & Papa, F. R. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.06.017 · Cited by 1,567
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia
Landau, D. A., Carter, S. L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M. S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.019 · Cited by 1,379
Self-citationg:Profiler—a web server for functional interpretation of gene lists (2016 update)
Reimand, J., Arak, T., Adler, P., Kolberg, L., Reisberg, S., Peterson, H., & Vilo, J. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw199 · Cited by 1,229
FUNDAMENTALS OF PLANARIAN REGENERATION
Reddien, P. W., & Alvarado, A. S. (2004) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev.cellbio.20.010403.095114 · Cited by 1,108
Multiplexed droplet single-cell RNA-sequencing using natural genetic variation
Kang, H. M., Subramaniam, M., Targ, S., Nguyen, M., Maliskova, L., McCarthy, E., Wan, E., Wong, S., Byrnes, L., Lanata, C. M., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4042 · Cited by 1,101
Mu, P., Zhang, Z., Benelli, M., Karthaus, W. R., Hoover, E., Chen, C.-C., Wongvipat, J., Ku, S., Gao, D., Cao, Z., et al. (2017) · Science · doi:10.1126/science.aah4307 · Cited by 1,089
Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors
Paul, F., Arkin, Y., Giladi, A., Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Winter, D., Lara-Astiaso, D., Gury, M., Weiner, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.013 · Cited by 1,082
Mutations driving CLL and their evolution in progression and relapse
Landau, D. A., Tausch, E., Taylor-Weiner, A. N., Stewart, C., Reiter, J. G., Bahlo, J., Kluth, S., Božić, I., Lawrence, M. S., Böttcher, S., et al. (2015) · Nature · doi:10.1038/nature15395 · Cited by 1,081
Self-citationStoeckius, M., Zheng, S., Houck-Loomis, B., Hao, S., Yeung, B. Z., Mauck, W. M., Smibert, P., & Satija, R. (2018) · Genome Biology · doi:10.1186/s13059-018-1603-1 · Cited by 1,046
Self-citationReconstructing and Reprogramming the Tumor-Propagating Potential of Glioblastoma Stem-like Cells
Suvà, M. L., Rheinbay, E., Gillespie, S. M., Patel, A. P., Wakimoto, H., Rabkin, S. D., Riggi, N., Chi, A. S., Cahill, D. P., Nahed, B. V., et al. (2014) · Cell · doi:10.1016/j.cell.2014.02.030 · Cited by 956
Densely Interconnected Transcriptional Circuits Control Cell States in Human Hematopoiesis
Novershtern, N., Subramanian, A., Lawton, L. N., Mak, R. H., Haining, W. N., McConkey, M. E., Habib, N., Yosef, N., Chang, C. Y., Shay, T., et al. (2011) · Cell · doi:10.1016/j.cell.2011.01.004 · Cited by 942
ER Stress Sensor XBP1 Controls Anti-tumor Immunity by Disrupting Dendritic Cell Homeostasis
Cubillos-Ruiz, J. R., Silberman, P. C., Rutkowski, M. R., Chopra, S., Perales-Puchalt, A., Song, M., Zhang, S., Bettigole, S. E., Gupta, D., Holcomb, K., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.025 · Cited by 933
Self-citationHuman haematopoietic stem cell lineage commitment is a continuous process
Velten, L., Haas, S. F., Raffel, S., Blaszkiewicz, S., Islam, S., Hennig, B. P., Hirche, C., Lutz, C., Buss, E. C., Nowak, D., et al. (2017) · Nature Cell Biology · doi:10.1038/ncb3493 · Cited by 925
IKK/NF- B signaling: balancing life and death - a new approach to cancer therapy
Luo, J. (2005) · Journal of Clinical Investigation · doi:10.1172/jci26322 · Cited by 898
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis
Farrell, J. A., Wang, Y., Riesenfeld, S. J., Shekhar, K., Regev, A., & Schier, A. F. (2018) · Science · doi:10.1126/science.aar3131 · Cited by 876
Recurrent somatic TET2 mutations in normal elderly individuals with clonal hematopoiesis
Busque, L., Patel, J. P., Figueroa, M. E., Vasanthakumar, A., Provost, S., Hamilou, Z., Mollica, L., Li, J., Viale, A., Heguy, A., et al. (2012) · Nature Genetics · doi:10.1038/ng.2413 · Cited by 830
Self-citationIndian Hedgehog: A Mechanotransduction Mediator in Condylar Cartilage
Tang, G. H., Rabie, A. B. M., & Hägg, U. (2004) · Journal of Dental Research · doi:10.1177/154405910408300516 · Cited by 819
Kowalczyk, M. S., Tirosh, I., Heckl, D., Rao, T. N., Dixit, A., Haas, B. J., Schneider, R. K., Wagers, A. J., Ebert, B. L., & Regev, A. (2015) · Genome Research · doi:10.1101/gr.192237.115 · Cited by 778
A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation
Nestorowa, S., Hamey, F. K., Pijuan Sala, B., Diamanti, E., Shepherd, M., Laurenti, E., Wilson, N. K., Kent, D. G., & Göttgens, B. (2016) · Blood · doi:10.1182/blood-2016-05-716480 · Cited by 768
The genetics of myelodysplastic syndrome: from clonal haematopoiesis to secondary leukaemia
Sperling, A. S., Gibson, C. J., & Ebert, B. L. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2016.112 · Cited by 695
ATF6α Optimizes Long-Term Endoplasmic Reticulum Function to Protect Cells from Chronic Stress
Wu, J., Rutkowski, D. T., Dubois, M., Swathirajan, J., Saunders, T. L., Wang, J., Song, B., Yau, G. D.-Y., & Kaufman, R. J. (2007) · Developmental Cell · doi:10.1016/j.devcel.2007.07.005 · Cited by 680
Buenrostro, J. D., Corces, M. R., Lareau, C. A., Wu, B., Schep, A. N., Aryee, M. J., Majeti, R., Chang, H. Y., & Greenleaf, W. J. (2018) · Cell · doi:10.1016/j.cell.2018.03.074 · Cited by 670
Clonal evolution and clinical correlates of somatic mutations in myeloproliferative neoplasms
Lundberg, P., Karow, A., Nienhold, R., Looser, R., Hao-Shen, H., Nissen, I., Girsberger, S., Lehmann, T., Passweg, J. R., Stern, M., et al. (2014) · Blood · doi:10.1182/blood-2013-11-537167 · Cited by 659
Effect of Mutation Order on Myeloproliferative Neoplasms
Ortmann, C. A., Kent, D. G., Nangalia, J., Silber, Y., Wedge, D. C., Grinfeld, J., Baxter, E. J., Massie, C. E., Papaemmanuil, E., Menon, S., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1412098 · Cited by 604
Comprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.034 · Cited by 552
Rampal, R. K., Al‐Shahrour, F., Abdel-Wahab, O. I., Patel, J. P., Brunel, J.-P., Mermel, C. H., Bass, A. J., Pretz, J. L., Ahn, J., Hricik, T., et al. (2014) · Blood · doi:10.1182/blood-2014-02-554634 · Cited by 442
Self-citationGiustacchini, A., Thongjuea, S., Barkas, N., Woll, P. S., Povinelli, B. J., Booth, C. A. G., Sopp, P., Norfo, R., Rodriguez-Meira, A., Ashley, N., et al. (2017) · Nature Medicine · doi:10.1038/nm.4336 · Cited by 403
Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity
Nguyen, Q., Pervolarakis, N., Blake, K., Ma, D., Davis, R. T., James, N., Phung, A. T., Willey, E., Kumar, R., Jabart, E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04334-1 · Cited by 388
Obeng, E. A., Chappell, R. J., Seiler, M., Chen, M. C., Campagna, D. R., Schmidt, P. J., Schneider, R. K., Lord, A. M., Wang, L., Gambe, R. G., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.08.006 · Cited by 380
Giladi, A., Paul, F., Herzog, Y., Lubling, Y., Weiner, A., Yofe, I., Jaitin, D., Cabezas-Wallscheid, N., Dress, R., Ginhoux, F., et al. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0121-4 · Cited by 366
The unfolded protein response governs integrity of the haematopoietic stem-cell pool during stress
van Galen, P., Kreso, A., Mbong, N., Kent, D. G., Fitzmaurice, T., Chambers, J. E., Xie, S., Laurenti, E., Hermans, K., Eppert, K., et al. (2014) · Nature · doi:10.1038/nature13228 · Cited by 363
Thrombopoietin receptor activation by myeloproliferative neoplasm associated calreticulin mutants
Chachoua, I., Pecquet, C., El-Khoury, M., Nivarthi, H., Albu, R.-I., Marty, C., Gryshkova, V., Defour, J., Vertenoeil, G., Ngo, A., et al. (2015) · Blood · doi:10.1182/blood-2015-11-681932 · Cited by 351
Burger, J. A., Landau, D. A., Taylor-Weiner, A., Bozic, I., Zhang, H., Sarosiek, K., Wang, L., Stewart, C., Fan, J., Hoellenriegel, J., et al. (2016) · Nature Communications · doi:10.1038/ncomms11589 · Cited by 345
Self-citationElf, S., Abdelfattah, N. S., Chen, E., Perales-Patón, J., Rosen, E. A., Ko, A., Peisker, F., Florescu, N., Giannini, S., Wolach, O., et al. (2016) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-1434 · Cited by 293
Human megakaryocyte stimulation of proliferation of bone marrow fibroblasts
Castro-Malaspina, H., Rabellino, E. M., Yen, A., Nachman, R. L., & Moore, M. (1981) · Blood · doi:10.1182/blood.v57.4.781.781 · Cited by 281
Kleppe, M., Koche, R., Zou, L., van Galen, P., Hill, C. E., Dong, L., De Groote, S., Papalexi, E., Hanasoge Somasundara, A. V., Cordner, K., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2017.11.009 · Cited by 279
Marty, C., Pecquet, C., Nivarthi, H., El-Khoury, M., Chachoua, I., Tulliez, M., Villeval, J., Raslová, H., Královics, R., Constantinescu, S. N., et al. (2015) · Blood · doi:10.1182/blood-2015-11-679571 · Cited by 274
On the design of CRISPR-based single-cell molecular screens
Hill, A. J., McFaline-Figueroa, J. L., Starita, L. M., Gasperini, M. J., Matreyek, K. A., Packer, J., Jackson, D., Shendure, J., & Trapnell, C. (2018) · Nature Methods · doi:10.1038/nmeth.4604 · Cited by 262
Pivotal contributions of megakaryocytes to the biology of idiopathic myelofibrosis
Ciurea, S. O., Merchant, D., Mahmud, N., Ishii, T., Zhao, Y., Hu, W., Bruno, E., Barosi, G., Xu, M., & Hoffman, R. (2007) · Blood · doi:10.1182/blood-2006-12-064626 · Cited by 213
Self-citationSingle-cell multimodal profiling reveals cellular epigenetic heterogeneity
Cheow, L. F., Courtois, E. T., Tan, Y., Viswanathan, R., Xing, Q. R., Tan, R. Z., Tan, D. S.-W., Robson, P., Loh, Y., Quake, S. R., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3961 · Cited by 193
Reinius, B., & Sandberg, R. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3888 · Cited by 192
Distinct Clinical Phenotypes Associated with JAK2V617F Reflect Differential STAT1 Signaling
Chen, E., Beer, P. A., Godfrey, A. L., Ortmann, C. A., Li, J., Costa‐Pereira, A. P., Ingle, C., Dermitzakis, E. T., Campbell, P. J., & Green, A. R. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.10.013 · Cited by 185
The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy
Landau, D. A., Sun, C., Rosebrock, D., Herman, S. E. M., Fein, J., Sivina, M., Underbayev, C., Liu, D., Hoellenriegel, J., Ravichandran, S., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-02329-y · Cited by 176
Self-citationTerui, T., Niitsu, Y., MAHARA, K., Fujisaki, Y., Urushizaki, Y., Yoshihiro, M. O. G. I., KOHGO, Y., Watanabe, N., Ogura, M., & Saito, H. (1990) · Blood · doi:10.1182/blood.v75.7.1540.1540 · Cited by 167
A discriminative learning approach to differential expression analysis for single-cell RNA-seq
Ntranos, V., Yi, L., Melsted, P., & Pachter, L. S. (2019) · Nature Methods · doi:10.1038/s41592-018-0303-9 · Cited by 152
Georgantas, R. W., Tanavde, V., Malehorn, M., Heimfeld, S., Chen, C., Carr, L., Martínez-Murillo, F., Riggins, G., Kowalski, J., & Civin, C. I. (2004) · Cancer Research · doi:10.1158/0008-5472.can-03-3247 · Cited by 129
Janus kinase deregulation in leukemia and lymphoma
Chen, E., Staudt, L. M., & Green, A. R. (2012) · Immunity · doi:10.1016/j.immuni.2012.03.017 · Cited by 123
Stein, S. J., & Baldwin, A. (2013) · Blood · doi:10.1182/blood-2013-02-486142 · Cited by 121
Kleppe, M., Koche, R. P., Zou, L., van Galen, P., Hill, C. E., Dong, L., Groote, S. D., Papalexi, E., Somasundara, A. V. H., Cordner, K. B., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.03.024 · Cited by 95
Geyer, J. T., Tam, W., Liu, Y.-C., Chen, Z., Wang, S. A., Bueso-Ramos, C., Oak, J. S., Arber, D. A., Hsi, E. D., Rogers, H. J., et al. (2017) · Modern Pathology · doi:10.1038/modpathol.2017.45 · Cited by 80
Self-citationThrombopoietin receptor is required for the oncogenic function of CALR mutants
Nivarthi, H., Chen, D., Cleary, C. M., Kubešová, B., Jäger, R., Bogner, E., Marty, C., Pecquet, C., Vainchenker, W., Constantinescu, S. N., et al. (2016) · Leukemia · doi:10.1038/leu.2016.32 · Cited by 80
MPN patients harbor recurrent truncating mutations in transcription factor NF-E2
Jutzi, J. S., Bogeska, R., Nikoloski, G., Schmid, C. A., Seeger, T. S., Stegelmann, F., Schwemmers, S., Gründer, A., Peeken, J. C., Gothwal, M., et al. (2013) · The Journal of Experimental Medicine · doi:10.1084/jem.20120521 · Cited by 77
Simultaneous multiplexed amplicon sequencing and transcriptome profiling in single cells
Saikia, M., Burnham, P., Keshavjee, S. H., Wang, M. F. Z., Heyang, M., Moral-Lopez, P., Hinchman, M. M., Danko, C. G., Parker, J. S. L., & De Vlaminck, I. (2019) · Nature Methods · doi:10.1038/s41592-018-0259-9 · Cited by 75
Defour, J., Chachoua, I., Pecquet, C., & Constantinescu, S. N. (2015) · Leukemia · doi:10.1038/leu.2015.271 · Cited by 73
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Metadata
- 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
- 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 › Hematology › 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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