C1 Publications

The world’s first automated solution for single-cell genomics research, C1 employs innovative microfluidic technology to rapidly and reliably isolate, process and prepare individual cells for genome and transcriptome analysis. Since its debut in 2012, C1 has helped pioneer the field of single-cell analysis in biology, enabling scientists and researchers around the world to ask ever more exciting and provocative questions about the nature and function of cell populations.

Browse our catalog of related publications to learn how C1 empowers researchers across single-cell genomics applications.

• Overview

  Number of papers per research area as of June, 2018

  Number of cumulative papers as of June, 2018

• Recent

  • Single cell transcriptomics suggest that human adipocyte progenitor cells constitute a homogeneous cell population
    Acosta, J.R., Joost, S., Karlsson, K. et al. Stem Cell Research and Therapy (2017): 250
  • Identification of genes expressed in a mesenchymal subset regulating prostate organogenesis using tissue and single cell transcriptomics
    Boufaied, N., Nash, C., Rochett, A. et al. Scientific Reports (2017): 16,385
  • Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis
    Zhao, D., Lin, M., Pedrosa, E. et al. BMC Genomics (2017): 860
  • Frontiers in toxicogenomics in the twenty-first century—the grand challenge: to understand how the genome and epigenome interact with the toxic environment at the single-cell, whole-organism, and multi-generational levels
    Ruden, D.M., Gurdziel, K., Aschner, M. Frontiers in Genetics (2017): 173
  • f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq
    Buettner, F., Pratanwanich, N., McCarthy, D.J. et al. Genome Biology (2017): 212

• Research Areas

  • Biomarker Screening

    • Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis
      Zhao, D., Lin, M., Pedrosa, E. et al. BMC Genomics (2017): 860
    • Identification of genes expressed in a mesenchymal subset regulating prostate organogenesis using tissue and single cell transcriptomics
      Boufaied, N., Nash, C., Rochett, A. et al. Scientific Reports (2017): 16,385
    • Single-cell protein-mRNA correlation analysis enabled by multiplexed dual-analyte co-detection
      Gong, H., Wang, X., Liu, B. et al. Scientific Reports (2017): 2,776
    • Single-Cell Resolution of Temporal Gene Expression during Heart Development
      DeLaughter, D.M., Bick, A.G., Wakimoto, H. et al. Developmental Cell (2016): 480–90
    • Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNA-Seq
      Gokce, O., Stanley, G., Treutlein, B. et al. Cell Reports (2016): 1,126–37
    • Lineage tracing of cells involved in atherosclerosis
      Albarrán-Juárez, J., Kaur, H., Grimm, M. et al. Atherosclerosis (2016): 445–53
    • Computational assignment of cell-cycle stage from single-cell transcriptome data
      Scialdone, A., Natarajan, K.N., Saraiva, L.R. et al. Methods (2015): 54–61
    • Systematic Reconstruction of Molecular Cascades Regulating GP Development Using Single-Cell RNA-Seq
      Li, J., Luo, H., Wang, R. et al. Cell Reports (2016): 1,467–80
    • A secretagogin locus of the mammalian hypothalamus controls stress hormone release
      Romanov, R.A., Alpár, A., Zhang, M.D. et al. The Embo Journal (2015): 36–54
    • Single cell transcriptomics of the human endocrine pancreas
      Wang, Y.J., Schug, J., Won, K.J. et al. Diabetes (2016): 3,028–38
    • Targeted ablation of periostin-expressing activated fibroblasts prevents adverse cardiac remodeling in mice
      Kaur, H., Takefuji, M., Ngai, C.Y. et al. Circulation Research (2016): 1,906–17
    • The primate-specific noncoding RNA HPAT5 regulates pluripotency during human preimplantation development and nuclear reprogramming
      Durruthy-Durruthy, J., Sebastiano, V., Wossidlo, M. et al. Nature Genetics (2015): 44–52
    • Single-cell RNA-Seq resolves cellular complexity in sensory organs from the neonatal inner ear
      Burns, J.C., Kelly, M.C., Hoa, M. et al. Nature Communications (2015): 8,557
    • A rare subset of skin-tropic regulatory T cells expressing Il10/Gzmb inhibits the cutaneous immune response
      Ikebuchi, R., Teraguchi, S., Vandenbon, A. et al. Scientific Reports (2016): 35,002
    • Micro-RNAs and next generation sequencing: new perspectives in heart failure
      Chini, V.P. Clinica Chimica Acta (2015): 114–9

  • I/O

    • Combating subclonal evolution of resistant cancer phenotypes
      Brady, S.W., McQuerry, J.A., Qiao, Y. et al. Nature Communications (2017): doi: 10.1038/s41467-017-01174-3

  • Immunology

    • Lytic gene expression is frequent in HSV-1 latent infection and correlates with the engagement of a cell-intrinsic transcriptional response
      Ma, J.Z., Russell, T.A., Spelman, T. et al. PLoS Pathogens (2014): e1004237
    • Population and single-cell genomics reveal the Aire dependency, relief from Polycomb silencing, and distribution of self-antigen expression in thymic epithelia
      Sansom, S.N., Shikama-Dorn, N., Zhanybekova, S. et al. Genome Research (2014): 1,918–31
    • Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
      Shalek, A.K., Satija, R., Shuga, J. et al. Nature (2014): 363–9
    • Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis
      Mahata, B., Zhang, X., Kolodziejczyk, A.A. et al. Cell Reports (2014): 1,130–42
    • Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation
      Prospero, V., Piccolo, A., Haim-Vilmovsky, L. et al. Genome Biology (2016): doi:10.1186/s13059-016-0957-5
    • Single-cell genomics unveils critical regulators of Th17 cell pathogenicity
      Gaublomme, J.T., Yosef, N., Lee, Y. et al. Cell (2015): 1,400–12
    • T cell fate and clonality inference from single-cell transcriptomes
      Stubbington, M.J.T., Lönnberg, T., Proserpio, V. et al. Nature Methods (2016): 329–32
    • Mapping the human DC lineage through the integration of high-dimensional techniques
      See, P., Dutertre, C.A., Chen, J. et al. Science (2017): doi: 10.1126/science.aag300
    • Tissue distribution and clonal diversity of the T and B cell repertoire in type 1 diabetes
      Seay, H.R., Yusko, E., Rothweiler, S.J. et al. JCI Insight (2016): e88242
    • Deformation-induced transitional myofibroblasts contribute to compensatory lung growth
      Bennett, R.D., Ysasi, A.B., Wagner, W.L. et al. American Journal of Physiology: Lung Cellular and Molecular Physiology (2017): L79–88
    • Origin, fate and dynamics of macrophages at CNS interfaces
      Goldmann, T., Costa Jordão, M.J.,. Wieghofer, P. et al. Nature Immunology (2016): 797–805
    • Tissue damage drives co-localization of NF-κB, Smad3, and Nrf2 to direct Rev-erb sensitive wound repair in mouse macrophages
      Eichenfield, D.Z., Troutman, T.D., Link, V.M. et al. eLife (2016): e13024
    • Mapping the human DC lineage through the integration of high-dimensional techniques
      See, P., Dutertre, C.A., Chen, J. et al. Science (2017): eaag3009
    • Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq
      Redmond, D., Poran, A., Elemento, O. Genome Medicine (2016): 80
    • Brain trauma elicits non-canonical macrophage activation states
      Kim, C.C., Nakamura, M.C., Hsieh, C.L. Journal of Neuroinflammation (2016): 117
    • Detecting Antigen-Specific T Cell Responses: From Bulk Populations to Single Cells
      Phetsouphanh, C., Zaunders, J.J., Kelleher, A.D. International Journal of Molecular Sciences (2015): 18,878–93
    • Novel Exons and Splice Variants in the Human Antibody Heavy Chain Identified by Single Cell and Single Molecule Sequencing
      Vollmers, C., Penland, L., Kanbar, J.N., Quake, S.R. PLoS One (2015): e0117050

  • Immunophenotyping

    • A multi-scale approach reveals that NF-κB cRel enforces a B-cell decision to divide
      Shokhirev, M.N., Almaden, J., Davis-Turak, J. et al. Molecular Systems Biology (2015): 783

  • Inherited Disease

    • Single-cell transcriptomics of East-Asian pancreatic islets cells
      Dorajoo, R., Ali, Y., Tay, V.S.Y. et al. Scientific Reports (2017): 5024
    • Single-cell RNA sequencing identifies diverse roles of epithelial cells in idiopathic pulmonary fibrosis
      Xu, Y., Mizuno, T., Sridharan, A. et al. JCI Insight (2016): e90558
    • Early somatic mosaicism is a rare cause of long-QT syndrome
      Priest, J.R., Gawad, C., Kahlig, K.M. et al. Proceedings of the National Academy of Sciences of the United States of America (2016): 11,555–60
    • Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis
      Der, E., Ranabothu, S., Suryawanshi, H. et al. JCI Insight (2017): e93009
    • Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes
      Lawlor, N., George, J., Bolisetty, M. et al. Genome Research (2017): 208–22
    • Genome-wide epigenomic profiling for biomarker discovery
      Dirks, R.A.M., Stunnenberg, H.G., Marks, H. Clinical Epigenetics (2016): 122
    • PARP9 and PARP14 cross-regulate macrophage activation via STAT1 ADP-ribosylation
      Iwata, H., Goettsch, C., Sharma, A. et al. Nature Communications (2016): 12,849

  • Method Development

    • The technology and biology of single-cell RNA sequencing
      Kolodziejczyk, A.A., Kim, J.K., Svensson, V. et al. Molecular Cell (2015): 610–20
    • A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA
      Lake, B.B., Codeluppi, S., Yung, Y.C. et al. Scientific Reports (2017): 6031
    • A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
      Haque, A., Engel, J., Teichmann, S.A. et al. Genome Medicine (2017): 75
    • f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq
      Buettner, F., Pratanwanich, N., McCarthy, D.J. et al. Genome Biology (2017): 212
    • A survey of best practices for RNA-seq data analysis
      Conesa, A., Madrigal, P., Tarazona, S. et al. Genome Biology (2016): 13
    • The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
      Trapnell, C., Cacchiarelli, D., Grimsby, J. et al. Nature Biotechnology (2014): 381–6
    • MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data
      Finak, G., McDavid, A., Yajima, M. et al. Genome Biology (2015): 278
    • The importance of study design for detecting differentially abundant features in high-throughput experiments
      Luo, H., Li, J., Chia, B.K.H. et al. Genome Biology (2014): 527
    • Classification of low quality cells from single-cell RNA-seq data
      Ilicic, T., Kim, J.K., Kolodziejczyk, A.A. et al. Genome Biology (2016): 29
    • CEL-Seq2: sensitive highly-multiplexed single-cell RNA-seq
      Hashimshony, T., Senderovich, N., Avital, G. et al. Genome Biology (2016): 77
    • High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin
      Achim, K., Pettit, J.B., Saraiva, L.R. et al. Nature Biotechnology (2015): 503–9
    • NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
      Ardeshirdavani, A., Souche, E., Dehaspe, L. et al. Genome Medicine (2014): 71
    • Single-cell genetic analysis using automated microfluidics to resolve somatic mosaicism
      Szulwach, K.E., Chen, P., Wang, X. et al. PLoS One (2015): e0135007
    • Single-cell chromatin accessibility reveals principles of regulatory variation
      Buenrostro, J.D., Wu, B., Litzenburger, U.M. et al. Nature (2015): 486–90
    • Live single-cell laser tag
      Binan, L., Mazzaferri, J., Choquet, K. et al. Nature Communications (2016): 11,636
    • Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
      Buettner, F., Natarajan, K.N., Casale, F.P. et al. Nature Biotechnology (2015): 155–60
    • The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data
      Tang, X., Baheti, S., Shameer, K. et al. Nucleic Acids Research (2014): e172
    • Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex
      Pollen, A.A., Nowakowski, T.J., Shuga, J. et al. Nature Biotechnology (2014): 1053–8
    • Strategies for profiling single mouse intestinal epithelial cells by targeted gene expression
      McDowell, W., Box, A., Staehling, K. et al. Journal of Biomolecular Techniques (2014): S26–7
    • Accounting for technical noise in single-cell RNA-seq experiments
      Brennecke, P., Anders, S., Kim, J.K.. et al. Nature Methods (2013): 1,093–5
    • Quantitative assessment of single-cell RNA-sequencing methods
      Wu, A.R., Neff, N.F., Kalisky, T. et al. Nature Methods (2014): 41–6
    • Simple method to prepare oligonucleotide-conjugated antibodies and its application in multiplex protein detection in single cells
      Gong, H., Holcomb, I., Ooi, A. Bioconjugate Chemistry (2016): 217–25
    • Microfluidics for single-cell genetic analysis
      Thompson, A.M., Paguirigan, A.L., Kreutz, J.E. et al. Lab on a Chip (2014): 3,135–42
    • Microfluidic single-cell whole-transcriptome sequencing
      Streets, A.M., Zhang, X., Cao, C. et al. Proceedings of the National Academy of Sciences of the United States of America (2014): 7,048–53
    • Microfluidic bioreactor for dynamic regulation of early mesodermal commitment in human pluripotent stem cells
      Cimetta, E., Sirabella, D., Yeager, K. et al. Lab on a Chip (2013): doi: 10.1039/c2lc40836h
    • OEFinder: a user interface to identify and visualize ordering effects in single-cell RNA-seq data
      Leng, N., Choi, J., Chu, L.F. et al. Bioinformatics (2016): 1,408–10
    • Miniaturization technologies for efficient single-cell library preparation for next-generation sequencing
      Mora-Castilla, S., To, C., Vaezeslami, S. et al. Journal of Laboratory Automation (2016): 557–67
    • New library construction method for single-cell genomes
      Xi, L., Belyaev, A., Spurgeon, S. et al. PLoS One (2017): doi: 10.1371/journal.pone.0181163
    • SC3: consensus clustering of single-cell RNA-seq data
      Kiselev, V.Y., Kirschner, K., Schaub, M.T. et al. Nature Methods (2017): 483–6
    • Validation of Synthetic CRISPR Reagents as a Tool for Arrayed Functional Genomic Screening
      Tan, J., Martin, S.E. PLoS One (2016): e0168968
    • A cost effective 5' selective single cell transcriptome profiling approach with improved UMI design
      Arguel, M.J., LeBrigand, K., Paquet, A. et al. Nucleic Acids Research (2016): e48
    • Advances and Applications of Single Cell Sequencing Technologies
      Wang, Y., Navin, N.E. Molecular Cell (2015): 598–609
    • Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations
      Oikonomopoulos, S., Wang, Y.C., Djambazian, H. et al. Scientific Reports (2016): 31,602
    • Synthetic evolutionary origin of a proofreading reverse transcriptase
      Ellefson, J.W., Gollihar, J., Shroff, R. et al. Science (2016): 1,590–3
    • Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction
      Genshaft, A.S., Li, S., Gallant, C.J. et al. Genome Biology (2016): 188
    • Gene length and detection bias in single cell RNA sequencing protocols
      Phipson, B., Zappia, L., Oshlack, A. F1000 Research (2017): 595
    • A Comparison Between Single Cell RNA Sequencing And Single Molecule RNA FISH For Rare Cell Analysis
      Torre, E.A., Dueck, H., Shaffer, S. et al. bioRxiv (2017): doi: 10.1101/138289
    • Power analysis of single-cell RNA-sequencing experiments
      Svensson, V., Natarajan, K.N., Ly, L.H. et al. Nature Methods (2017): 381–7
    • Chemically Defined and Small Molecule-Based Generation of Human Cardiomyocytes
      Burridge, P.W., Matsa, E., Shukla, P. et al. Nature Methods (2014): 855-60
    • Single-Cell Multiomics: Multiple Measurements from Single Cells
      Macaulay, I.C., Ponting, C.P., Voet, T. Trends in Genetics (2017): 155-68
    • Identification of a novel NAMPT inhibitor by CRISPR/Cas9 chemogenomic profiling in mammalian cells
      Estoppey, D., Hewett, J.W., Guy, C.T. et al. Scientific Reports (2017): 42,728
    • A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
      Lun, A.T.L., McCarthy, D.J., Marioni, J.C. F1000 Research (2016): 2,122
    • Assessing characteristics of RNA amplification methods for single cell RNA sequencing
      Dueck, H.R., Ai, R., Camarena, A. et al. BMC Genomics (2016): 966
    • Genetics and immunity in the era of single-cell genomics
      Vieira Braga, F.A., Teichmann, S.A., Chen, X. Human Molecular Genetics (2016): R141-8
    • Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments
      Leng, N., Chu, L.F., Barry, C., et al. Nature Methods (2015): 947–50
    • Single Cell Analysis: From Technology to Biology and Medicine
      Pan, X. Single Cell Biology (2014): 106
    • The future is now: single-cell genomics of bacteria and archaea
      Blainey, P.C. FEMS Microbiology Reviews (2013): 407–27
    • Three-Dimensional Computational Reconstruction of Tissues with Hollow Spherical Morphologies using Single-Cell Gene Expression Data
      Durruthy-Durruthy, R., Gottlieb, A., Heller, S. Nature Protocols (2015): 459–74
    • Single-cell RNA-seq: advances and future challenges
      Saliba, A.E., Westermann, A.J., Gorski, S.A., Vogel, J. Nucleic Acids Research (2014): 8845–60
    • Computational and analytical challenges in single-cell transcriptomics
      Stegle, O., Teichmann, S.A., Marioni, J.C. Nature Reviews - Genetics (2015): 133–45
    • New bandwidth selection criterion for Kernel PCA: Approach to dimensionality reduction and classification problems
      Thomas, M., De Brabanter, K., De Moor, B. BioMed Central Bioinformatics (2014): 137
    • Galahad: a web server for drug effect analysis from gene expression
      Laenen, G., Ardeshirdavani, A., Moreau, Y., Thorrez, L. Nucleic Acids Research (2015): gkv436
    • Design and computational analysis of single-cell RNA-sequencing experiments
      Bacher, R., Kendziorski, C. Genome Biology (2016): 63
    • Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
      Lun. A.T., Bach, K., Marioni, J.C. Genome Biology (2016): 75
    • The first five years of single-cell cancer genomics and beyond
      Navin, N.E. Genome Research (2015): 1499–507

  • Microbiology/Pathogen Detection (viral)

    • Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples
      Yu, F.B., Blainey, P.C., Schulz, F. et al. eLife (2017): e26580
    • Macrophage Colony Stimulating Factor Derived from CD4+ T Cells Contributes to Control of a Blood-Borne Infection
      Fontana, M.F., de Melo, G.L., Anidi, C. et al. PLoS One (2016): e1006046
    • RNA-guided endonuclease provides a therapeutic strategy to cure latent herpesviridae infection
      Wang, J., Quake, S.R. Proceedings of the National Academy of Sciences (2014): 13,157–62

  • Neurology

    • Hierarchical deconstruction of mouse olfactory sensory neurons: from whole mucosa to single-cell RNA-seq
      Saraiva, L.R., Ibarra-Soria, X., Khan, M. et al. Scientific Reports (2015): 18,178
    • Single-cell analysis of long non-coding RNAs in the developing human neocortex
      Liu, S.J., Nowakowski, T.J., Pollen, A.A. et al. Genome Biology (2016): 67
    • Subtype-selective small molecule inhibitors reveal a fundamental role for Na_V1.7 in nociceptor electrogenesis, axonal conduction and presynaptic release
      Alexandrou, A.J., Brown, A.R., Chapman, M.L. et al. PLoS One (2016): e0152405
    • Heterogeneity of astrocytes: from development to injury—single cell gene expression
      Rusnakova, V., Honsa, P., Dzamba, D. et al. PLoS One (2013): e69734
    • A survey of human brain transcriptome diversity at the single cell level
      Darmanis, S., Sloan, S.A., Zhang, Y. et al. Proceedings of the National Academy of Sciences of the United States of America (2015): 7,285–90
    • Direct conversion of normal and Alzheimer's disease human fibroblasts into neuronal cells by small molecules
      Hu, W., Qiu, B., Guan, W. et al. Cell Stem Cell (2015): 204–12
    • Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
      Zeisel, A., Munoz-Manchado, A.B., Codeluppi, S. et al. Science (2015): 1,138–42
    • Single-cell profiling reveals GPCR heterogeneity and functional patterning during neuroinflammation
      Tischner, D., Grimm, M., Kaur, H. et al. JCI Insight (2017): e95063
    • Nuclear RNA-seq of single neurons reveals molecular signatures of activation
      Lacar, B., Linker, S.B., Jaeger, B.N. et al. Nature Communications (2016): 11,022
    • Enhanced neuronal regeneration in the CAST/Ei mouse strain is linked to expression of differentiation markers after injury
      Lisi, V., Singh, B., Giroux, M. et al. Cell Reports (2017): 1,136-47
    • Single-cell RNA-sequencing of the brain
      Cuevas-Diaz Duran, R., Wei, H., Wu, J.Q. Clinical and Translational Medicine (2017): 20
    • Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
      Lake, B.B., Ai, R., Kaeser, G.E. et al. Science (2016): 1,586–90
    • Integrative single-cell transcriptomics reveals molecular networks defining neuronal maturation during postnatal neurogenesis
      Gao, Y., Wang, F., Eisinger, B.E. et al. Cerebral Cortex (2017): 2,064–77
    • Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types
      Chen, Y.J.J., Friedman, B.A., Ha, C. et al. Scientific Reports (2017): 45,656
    • Single-cell mRNA isoform diversity in the mouse brain
      Karlsson, K., Linnarsson, S. BMC Genomics (2017): 126
    • Transcriptomic and anatomic parcellation of 5-HT3AR expressing cortical interneuron subtypes revealed by single-cell RNA sequencing
      Frazer, S., Prados, J., Niquille, M. et al. Nature Communications (2017): 14,219
    • Olfactory sensory neurons transiently express multiple olfactory receptors during development
      Tan, L., Li, Q., Xie, X.S. Molecular Systems Biology (2015): 844

  • Oncology

    • The promise of single cell omics for onco-therapy
      Azizi, E., Clouthier, S.G., Wicha, M.S. Journal of Molecular and Genetic Medicine (2014): 121
    • Single-cell analysis of lung adenocarcinoma cell lines reveals diverse expression patterns of individual cells invoked by a molecular target drug treatment
      Suzuki, A., Matsushima, K., Makinoshima, H. et al. Genome Biology (2015): 66
    • "Stealth dissemination" of macrophage-tumor cell fusions cultured from blood of patients with pancreatic ductal adenocarcinoma
      Clawson, G.A., Matters, G.L., Xin, P. et al. PLoS One (2017): doi: 10.1371/journal.pone.0184451
    • Mutation allele burden remains unchanged in chronic myelomonocytic leukaemia responding to hypomethylating agents
      Merlevede, J., Droin, N., Qin, T. et al. Nature Communications (2016): 10767
    • Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma
      Kim, K.T., Lee, H.W., Lee, H.O. et al. Genome Biology (2016): 80
    • Identification of distinct tumor subpopulations in lung adenocarcinoma via single-cell RNA-seq
      Min, J.W., Kim, W.J., Han, J.A. et al. PLoS One (2015): e0135817
    • Impaired PRC2 activity promotes transcriptional instability and favors breast tumorigenesis
      Wassef, M., Rodilla, V., Teissandier, A. et al. Genes & Development (2015): 2,547–62
    • Granulocyte colony-stimulating factor prevents loss of spermatogenesis after sterilizing busulfan chemotherapy
      Benavides-Garcia, R., Joachim, R., Pina, N.A. et al. Fertility and Sterility (2015): 270–80
    • Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors
      Mitra, A.K., Mukherjee, U.K., Harding, T. et al. Leukemia (2016): 1,094–102
    • Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells
      Kim, K.T., Lee, H.W., Lee, H.O. et al. Genome Biology (2015): doi:10.1186/s13059-015-0692-3
    • Quantitative single-cell RNA-seq with unique molecular identifiers
      Islam, S., Zeisel, A., La Manno, G. et al. Nature Methods (2014): 163–6
    • Dynamic epigenetic regulation of glioblastoma tumorigenicity through LSD1 modulation of MYC expression
      Kozono, D., Li, J., Nitta, M., Sampetrean, O. et al. Proceedings of the National Academy of Sciences of the United States of America (2015): E4,055–64
    • Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia
      Landau, D.A., Clement, K., Ziller, M.J. et al. Cancer Cell (2014): 813–25
    • Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia
      Wang, L., Fan, J., Georghiou, G. et al. Genome Research (2017): 1,300–11
    • Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study
      Yan, B., Hu, Y., Ban, K.H.K. et al. Oncology Letters (2017): 1,625–30
    • RAD51 Is a Selective DNA Repair Target to Radiosensitize Glioma Stem Cells
      King, H.O., Brend, T., Payne, H.L. et al. Stem Cell Reports (2017): 125–39
    • p53 Regulates Progenitor Cell Quiescence and Differentiation in the Airway
      McConnell, A.M., Yao, C., Yeckes, A.R. et al. Cell Reports (2016): 2,173–82
    • Characterization of Rare, Dormant, and Therapy-Resistant Cells in Acute Lymphoblastic Leukemia
      Ebinger, S., Özdemir, E.Z., Ziegenhain, C. et al. Cancer Cell (2016): 849–62
    • Transcriptional Landscape of Human Tissue Lymphocytes Unveils Uniqueness of Tumor-Infiltrating T Regulatory Cells
      De Simone, M., Arrigoni, A., Rossetti, G. et al. Immunity (2016): 1,135–47
    • DNMT3A Haploinsufficiency Transforms FLT3ITD Myeloproliferative Disease into a Rapid, Spontaneous, and Fully Penetrant Acute Myeloid Leukemia
      Meyer, S.E., Qin, T., Muench, D.E. et al. Cancer Discovery (2016): 501–15
    • Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer
      Chung, W., Eum, H.H., Lee, H.O. et al. Nature Communications (2017): 15,081
    • Single-cell dissection of transcriptional heterogeneity in human colon tumors
      Dalerba, P., Kalisky, T., Sahoo, D. et al. Nature Biotechnology (2011): 1120–7
    • Inflammation Mediated Metastasis: Immune Induced Epithelial-To-Mesenchymal Transition in Inflammatory Breast Cancer Cells
      Cohen, E.N., Gao, H., Anfossi, S. et al. PLoS One (2015): e0132710
    • Efficient molecular subtype classification of high-grade serous ovarian cancer
      Leong, H.S., Galletta, L., Etemadmoghadam, D., et al. Journal of Pathology (2015): 272–7
    • Single‐cell sequencing maps gene expression to mutational phylogenies in PDGF‐ and EGF‐driven gliomas
      Müller, S., Liu, S.J., Di Lullo, E. et al. Molecular Systems Biology (2016): 889
    • High-Throughput Single-Cell Derived Sphere Formation for Cancer Stem-Like Cell Identification and Analysis
      Chen, Y.C., Ingram, P.N., Fouladdel, S. et al. Scientific Reports (2016): 27,301
    • Interferon-γ and Tumor Necrosis Factor-α Polarize Bone Marrow Stromal Cells Uniformly to a Th1 Phenotype
      Jin, P., Zhao, Y., Liu, H. et al. Scientific Reports (2016): 26,345
    • Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis
      Saadatpour, A., Guo, G., Orkin, S.H., Yuan, G.C. Genome Biology (2014): 525
    • Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics
      Gawad, C., Koh, W., Quake, S.R. Proceedings of the National Academy of Sciences (2014): 17947–52
    • Single-Cell Transcriptomics Identifies Intra-Tumor Heterogeneity in Human Myeloma Cell Lines
      Mitra, A.K., Stessman, H., Linden, M.A., Van Ness, B. Blood (2014): 3385

  • Population Screening

    • Single-cell profiling reveals heterogeneity and functional patterning of GPCR expression in the vascular system
      Kaur, H., Carvalho, J., Looso, M. et al. Nature Communications (2017): 15,700
    • Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity
      Joost, S., Zeisel, A., Jacob, T. et al. Cell Systems (2016): 221–37
    • Comprehensive alpha, beta and delta cell transcriptomes reveal that ghrelin selectively activates delta cells and promotes somatostatin release from pancreatic islets
      DiGruccio, M.R., Mawla, A.M., Donaldson, C.J., et al. Molecular Metabolism (2016): 449–58

  • Stem Cell

    • Bioconductor workflow for single-cell RNA sequencing: normalization, dimensionality reduction, clustering, and lineage inference
      Perraudeau, F., Risso, D., Street, K. et al. F1000 Research (2017): 1158
    • Single cell transcriptomics suggest that human adipocyte progenitor cells constitute a homogeneous cell population
      Acosta, J.R., Joost, S., Karlsson, K. et al. Stem Cell Research and Therapy (2017): 250
    • Adult human mesenchymal stem cell differentiation at the cell population and single-cell levels under alternating electric current
      Wechsler, M.E., Hermann, B.P., Bizios, R. Tissue Engineering Part C: Methods (2015): 155–64
    • Tbx3 controls Dppa3 levels and exit from pluripotency toward mesoderm
      Waghray, A., Saiz, N., Jayaprakash, A.D., et al. Stem Cell Reports (2015): 97–110
    • Single-cell genomics of post-pneumonectomy peripheral lung regeneration
      Bennett, R., Ysasi, A., Belle, J. et al. The FASEB Journal (2015): 876.12
    • Identification and specification of the mouse skeletal stem cell
      Chan, C.K., Seo, E.Y., Chen, J.Y. et al. Cell (2015): 285–98
    • Single cell dissection of early kidney development: multilineage priming
      Brunskill, E.W., Park, J.S., Chung, E. et al. Development (2014): 3,093–101
    • Sox7 is regulated by ETV2 during cardiovascular development
      Behrens, A.N., Zierold, C., Shi, X. et al. Stem Cells and Development (2014): 2004–13
    • Single-cell transcriptomic reconstruction reveals cell cycle and multi-lineage differentiation defects in Bcl11a-deficient hematopoietic stem cells
      Tsang, J.C., Yu, Y., Burke, S. et al.. Genome Biology (2015): 178
    • SINCERA: a pipeline for single-cell RNA-seq profiling analysis
      Guo, M., Wang, H., Potter, S.S. et al. PLoS Computational Biology (2015): e1004575
    • Sexual cell-fate reprogramming in the ovary by DMRT1
      Lindeman, R.E., Gearhart, M.D., Minkina, A. et al. Current Biology (2015): 764–71
    • Biased allelic expression in human primary fibroblast single cells
      Borel, C., Ferreira, P.G., Santoni, F. et al. American Journal of Human Genetics (2015): 70–80
    • Laser microdissection of the alveolar duct enables single-cell genomic analysis
      Bennett, R.D., Ysasi, A.B., Belle, J.M. et al. Frontiers in Oncology (2014): 260
    • Erythropoietin guides multipotent hematopoietic progenitor cells toward an erythroid fate
      Grover, A., Mancini, E., Moore, S. et al. Journal of Experimental Medicine (2014): 181–8
    • Pluripotent stem cells reveal erythroid-specific activities of the GATA1 N-terminus
      Byrska-Bishop, M., VanDorn, D., Campbell, A.E. et al. Journal of Clinical Investigation (2015): 993–1,005
    • Human germ cell formation in xenotransplants of induced pluripotent stem cells carrying X chromosome aneuploidies
      Dominguez, A.A., Chiang, H.R., Sukhwani, M. et al. Scientific Reports (2014): 6,432
    • Cross-platform single cell analysis of kidney development shows stromal cells express Gdnf
      Magella, B., Adam, M., Potter, A.S. et al. Developmental Biology (2017): doi: 10.1016/j.ydbio.2017.11.006
    • Single-cell RNA sequencing reveals molecular and functional platelet bias of aged haematopoietic stem cells
      Grover, A., Sanjuan-Pla, A., Thongjuea, S. et al. Nature Communications (2016): 11,075
    • Molecular identity of human outer radial glia during cortical development
      Pollen, A.A., Nowakowski, T.J., Chen, J. et al. Cell (2015): 55–67
    • Sex specification and heterogeneity of primordial germ cells in mice
      Sakashita, A., Kawabata, Y., Jincho, Y. et al. PLoS One (2015): e0144836
    • Direct reprogramming of human fibroblasts toward a cardiomyocyte-like state
      Fu, J.D., Stone, N.R., Liu, L. et al. Stem Cell Reports (2013): 235–47
    • The organoid-initiating cells in mouse pancreas and liver are phenotypically and functionally similar
      Dorrell, C., Tarlow, B., Wang, Y. et al. Stem Cell Reports (2014): 275–83
    • Reinforcement of STAT3 activity reprogrammes human embryonic stem cells to naive-like pluripotency
      Chen, H., Aksoy, I., Gonnot, F. et al. Nature Communications (2015): 7,095
    • Deconstructing transcriptional heterogeneity in pluripotent stem cells
      Kumar, R.M., Cahan, P., Shalek, A.K. et al. Nature (2014): 56–61
    • Clonal dynamics reveal two distinct populations of basal cells in slow-turnover airway epithelium
      Watson, J.K., Rulands, S., Wilkinson, A.C. et al. Cell Reports (2015): 90–101
    • Single cell RNA-sequencing of pluripotent states unlocks modular transcriptional variation
      Kolodziejczyk, A.A., Kim, J.K., Tsang, J.C.H. et al. Cell Stem Cell (2015): 471–85
    • Human cerebral organoids recapitulate gene expression programs of fetal neocortex development
      Camp, J.G., Badsha, F., Florio, M. et al. Proceedings of the National Academy of Sciences of the United States of America (2015): 15,672–7
    • Lineage-negative progenitors mobilize to regenerate lung epithelium after major injury
      Vaughan, A.E., Brumwell, A.N., Xi, Y. et al. Nature (2015): 621–5
    • A versatile strategy for isolating a highly enriched population of intestinal stem cells
      Nefzger, C.M., Jardé, T., Rossello, F.J. et al. Stem Cell Reports (2016): 321–9
    • Serum-based culture conditions provoke gene expression variability in mouse embryonic stem cells as revealed by single cell analysis
      Guo, G., Pinello, L., Han, X. et al. Cell Reports (2016): 956–65
    • Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling
      Pal, B., Chen, Y., Vaillant, F., et al. Nature Communications (2017): 1,627
    • The transcription factor Mesp1 interacts with cAMP-responsive element binding protein 1 (Creb1) and coactivates Ets variant 2 (Etv2) gene expression
      Shi, X., Zirbes, K.M., Rasmussen, T.L. et al. Journal of Biological Chemistry (2015): 9,614–25
    • Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes
      Bektik, E., Dennis, A., Prasanna, P. et al. PLoS One (2017): doi: 10.1371/journal.pone.0183000
    • Adaptive from Innate: Human IFN-γ+CD4+ T Cells Can Arise Directly from CXCL8-Producing Recent Thymic Emigrants in Babies and Adults
      Das, A., Rouault-Pierre, K., Kamdar, S. et al. Journal of Immunology (2017): 1,696-705
    • Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression
      Kar, G., Kim, J.K., Kolodziejczyk, A.A. et al. Nature Communications (2017): 36
    • Niche-mediated depletion of the normal hematopoietic stem cell reservoir by Flt3-ITD–induced myeloproliferation
      Mead, A.J., Neo, W.H., Barkas, N. et al. Journal of Experimental Medicine (2017): 2,005-11
    • Heterogeneity of Mesp1+ mesoderm revealed by single-cell RNA-seq
      Chan, S.S., Chan, H.H., Kyba, M. Biochemical and Biophysical Research Communications (2016): 469–75
    • Single-cell analysis reveals a nestin+ tendon stem/progenitor cell population with strong tenogenic potentiality
      Yin, Z., Hu, J.J., Yang, L. et al. Science Advances (2016): e1600874
    • Nat1 promotes translation of specific proteins that induce differentiation of mouse embryonic stem cells
      Sugiyama, H., Takahashi, K., Yamamoto, T. et al. Proceedings of the National Academy of Sciences of the United States of America (2017): 340–5
    • Single-Cell Transcriptomic Analysis Defines Heterogeneity and Transcriptional Dynamics in the Adult Neural Stem Cell Lineage
      Dulken, B.W., Leeman, D.S., Boutet, S.C. et al. Cell Reports (2017): 777–90
    • The Homeobox Transcription Factor RHOX10 Drives Mouse Spermatogonial Stem Cell Establishment
      Song, H.W., Bettegowda, A., Lake, B.B. et al. Cell Reports (2016): 149–64
    • Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells
      La Manno, G., Gyllborg, D., Codeluppi, S. et al. Cell (2016): 566–80.e19
    • Single epicardial cell transcriptome sequencing identifies Caveolin 1 as an essential factor in zebrafish heart regeneration
      Cao, J., Navis, A., Cox, B.D. et al. Development (2016): 232–43
    • Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm
      Chu, L.F., Leng, N., Zhang, J. et al. Genome Biology (2016): 173
    • A Panel of Embryonic Stem Cell Lines Reveals the Variety and Dynamic of Pluripotent States in Rabbits
      Osteil, P., Moulin, A., Santamaria, C. et al. Stem Cell Reports (2016): 383–98
    • SCALE: modeling allele-specific gene expression by single-cell RNA sequencing
      Jiang, Y., Zhang, N.R., Li, M. Genome Biology (2017): 74
    • A high-throughput platform for stem cell niche co-cultures and downstream gene expression analysis
      Gracz, A.D., Williamson, I.A., Roche, K.C. et al. Nature Cell Biology (2015): 340–9
    • Transcriptional and Translational Heterogeneity among Neonatal Mouse Spermatogonia
      Hermann, B.P., Mutoji, K.N., Velte, E.K. et al. Biology of Reproduction (2015): 54
    • Transcriptomic Profiling Maps Anatomically Patterned Subpopulations among Single Embryonic Cardiac Cells
      Li, G., Xu, A., Sims, S. et al. Developmental Cell (2016): 491-507
    • Dpath software reveals hierarchical haemato-endothelial lineages of Etv2 progenitors based on single-cell transcriptome analysis
      Gong, W., Rasmussen, T.L., Singh, B.N. et al. Nature Communications (2017): 14,362
    • The impact of microRNAs on transcriptional heterogeneity and gene co-expression across single embryonic stem cells
      Gambardella, G., Carissimo, A., Chen, A. et al. Nature Communications (2017): 14,126
    • Random X-chromosome inactivation dynamics in vivo by single-cell RNA sequencing
      Wang, M., Lin, F., Xing, K. et al. BMC Genomics (2017): 90
    • Derivation of Diverse Hormone-Releasing Pituitary Cells from Human Pluripotent Stem Cells
      Zimmer, B., Piao, J., Ramnarine, K., et al. Stem Cell Reports (2016): 858–72
    • An atlas of transcriptional, chromatin accessibility, and surface marker changes in human mesoderm development
      Koh, P.W., Sinha, R., Barkal, A.A. et al. Scientific Data (2016): 160,109
    • Single-Cell RNA-Seq of Bone Marrow-Derived Mesenchymal Stem Cells Reveals Unique Profiles of Lineage Priming
      Freeman, B.T., Jung, J.P., Ogle, B.M. PLoS One (2015): e0136199
    • Single-cell RNA-seq reveals activation of unique gene groups as a consequence of stem cell-parenchymal cell fusion
      Freeman, B.T., Jung, J.P., Ogle, B.M. Scientific Reports (2016): 23,270
    • Single-cell analysis reveals key roles for Bcl11a in regulating stem cell fate decisions
      Powers, A.N., Satija, R. Genome Biology (2015): 199

  • Other

    • Inhibition of DYRK1A and GSK3B induces human β-cell proliferation
      Shen, W., Taylor, B., Jin, Q. et al. Nature Communications (2015): 8,372
    • A subcutaneous adipose tissue-liver signalling axis controls hepatic gluconeogenesis
      Reilly, S.M., Ahmadian, M., Zamarron, B.F. et al. Nature Communications (2015): 6,047
    • Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression
      Kim, J.K., Kolodziejczyk, A.A., Illicic, T. et al. Nature Communications (2015): 8,687
    • Identification of cDC1- and cDC2-committed DC progenitors reveals early lineage priming at the common DC progenitor stage in the bone marrow
      Schlitzer, A., Sivakamasundari, V., Chen, J. et al. Nature Immunology (2015): 718–28
    • Single mammalian cells compensate for differences in cellular volume and DNA copy number through independent global transcriptional mechanisms
      Padovan-Merhar, O., Nair, G.P., Biaesch, A.G. et al. Molecular Cell (2015): 339–52
    • Mouse embryonic fibroblasts exhibit extensive developmental and phenotypic diversity
      Singhal, P.K., Sassi, S., Lan, L. et al. Proceedings of the National Academy of Sciences of the United States of America (2016): 122–7
    • Reconstructing lineage hierarchies of the distal lung epithelium using single cell RNA-seq
      Treutlein, B., Brownfield, D.G., Wu, A.R. et al. Nature (2014): 371–5
    • An X-ray transparent microfluidic platform for screening of the phase behavior of lipidic mesophases
      Khvostichenko, D.S., Kondrashkina, E., Perry, S.L. et al. Analyst (2013): 5,384–95
    • Naturally acquired microchimerism: Implications for transplantation outcome and novel methodologies for detection
      Eikmans, M., van Halteren, A.G.S., van Besien, K. et al. Chimerism (2014): 24–39
    • Single-cell RNA-sequence analysis of mouse glomerular mesangial cells uncovers mesangial cell essential genes
      Lu, Y., Ye, Y., Yang, Q., Shi, S. Kidney International (2017): 540–13
    • Frontiers in toxicogenomics in the twenty-first century—the grand challenge: to understand how the genome and epigenome interact with the toxic environment at the single-cell, whole-organism, and multi-generational levels
      Ruden, D.M., Gurdziel, K., Aschner, M. Frontiers in Genetics (2017): 173
    • Analysis of individual cells identifies cell‐to‐cell variability following induction of cellular senescence
      Wiley, C.D., Flynn, J.M., Morrissey, C. et al. Aging Cell (2017): 1,043-50
    • Single cardiomyocyte nuclear transcriptomes reveal a lincRNA-regulated de-differentiation and cell cycle stress-response in vivo
      See, K., Tan, W.L.W., Lim, E.H. et al. Nature Communications (2017): doi: 10.1038/s41467-017-00319-8
    • Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence
      Wiley, C.D., Flynn, J.M., Morrissey, C. et al. Aging Cell (2017): doi: 10.1111/acel.12632
    • Generation of Single-Cell Transcript Variability by Repression
      Antolović, V., Miermont, A., Corrigan, A.M. et al. Current Biology (2017): 1,811–17.e3
    • A Gene Regulatory Network Balances Neural and Mesoderm Specification during Vertebrate Trunk Development
      Gouti, M., Delile, J., Stamataki, D. et al. Developmental Cell (2017): 243–61
    • Aging increases cell-to-cell transcriptional variability upon immune stimulation
      Martinez-Jimenez, C.P, Eling, N., Chen, H.C. et al. Science (2017): 1,433–6
    • Dynamic ASXL1 Exon Skipping and Alternative Circular Splicing in Single Human Cells
      Koh, W., Gonzalez, V., Natarajan, S. et al. PLoS One (2016): e0164085
    • Specific Macrophage Subtypes Influence the Progression of Rhabdomyolysis-Induced Kidney Injury
      Belliere, J., Casemayou, A., Ducasse, L. et al. Journal of the American Society of Nephrology (2015): 1,363–77
    • Trimming of sequence reads alters RNA-Seq gene expression estimates
      Williams, C.R., Baccarella, A., Parrish, J.Z., Kim, C.C. BMC Bioinformatics (2016): 103
    • 3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data
      Durruthy-Durruthy, R., Gottlieb, A., Heller, S. Nature Protocols (2015): 459–74