The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation
Open accessAbstract
Key Points: An expression map of HSPC differentiation from single-cell RNA sequencing of HSPCs provides insights into blood stem cell differentiation. A user-friendly Web resource provides access to single-cell gene expression profiles for the wider research community.
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“But recent state maps from scSeq (9), as well as clonal studies using barcodes (10) and single cell culture (11), suggest that the traditional intermediate cell types are internally heterogeneous in state and fate potential, with HSPCs lying along a continuum of states rather than a stepwise hierarchy.”
From Lineage tracing on transcriptional landscapes links state to fate during differentiation (2020) · cites this paper as [9]
In the citing paper
“When computationally reconstructed, single-cell RNA sequencing (scRNA-seq) profiling of the mammalian hematopoietic system typically produces a largely continuous distribution of cells from the earliest HSCs through the characteristic hematopoietic lineages (Nestorowa et al., 2016; Olsson et al., 2016; Paul et al., 2015; Pellin et al., 2019; Tusi et al., 2018; Weinreb et al., 2020).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Nestorowa et al., 2016
In the citing paper
“As part of the genomics revolution, increasingly accurate deep sequencing and novel methods of cell tracking have revealed hematopoiesis to be more of a continuous and less of a discrete and punctuated process than originally envisioned.”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Nestorowa et al., 2016
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HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814
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
Full-length RNA-seq from single cells using Smart-seq2
Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137
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
Kiel, M. J., Yilmaz, Ö. H., Iwashita, T., Yilmaz, O. H., Terhorst, C., & Morrison, S. J. (2005) · Cell · doi:10.1016/j.cell.2005.05.026 · Cited by 3,168
A clonogenic common myeloid progenitor that gives rise to all myeloid lineages
Akashi, K., Traver, D., Miyamoto, T., & Weissman, I. L. (2000) · Nature · doi:10.1038/35004599 · Cited by 2,617
Wilson, A., Laurenti, E., Oser, G., van der Wath, R. C., Blanco-Bose, W., Jaworski, M., Offner, S., Dunant, C. F., Eshkind, L., Bockamp, E., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.048 · Cited by 1,908
Self-citationFast and SNP-tolerant detection of complex variants and splicing in short reads
Wu, T. D., & Nacu, S. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq057 · Cited by 1,894
Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Elefant, N., Paul, F., Zaretsky, I., Mildner, A., Cohen, N., Jung, S., Tanay, A., et al. (2014) · Science · doi:10.1126/science.1247651 · Cited by 1,795
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Linke, F., Johnson, J. E. C., Kern, S., Bennett, C., Lourdusamy, A., Lea, D., Clifford, S. C., Merry, C. L. R., Stolnik, S., Alexander, M. R., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22613450
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Bjeije, H., Han, W., Lin, S., Issa, N., Krishnan, A., Raj, I. X., Arand, J., Li, Y., Yang, W., Magee, J. A., et al. (2026) · Stem Cell Reports · doi:10.1016/j.stemcr.2026.102793
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Chen, L. (2026) · Research Square · doi:10.21203/rs.3.rs-10462037/v1
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Metadata
- Authors
- Nestorowa, S., Hamey, F. K., Pijuan Sala, B., Diamanti, E., Shepherd, M., Laurenti, E., Wilson, N. K., Kent, D. G., & Göttgens, B.
- Affiliations
- Wellcome/MRC Cambridge Stem Cell Institute (GB)
- Department of Haematology and Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
- ORCID
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2016-08-25
- Volume
- 128
- Issue
- 8
- Pages
- e20-e31
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- PMC
- PMC5305050
- OpenAlex
- W2465917013
- Cited by
- 768
- References
- 55
- Citations by year
- 2026: 46 · 2025: 87 · 2024: 81 · 2023: 89 · 2022: 99 · 2021: 102 · 2020: 104 · 2019: 64 · 2018: 60 · 2017: 31 · 2016: 3
- FWCI
- 27.36
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Blood (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (acceptedVersion, cc-by)
- Apollo
- Funders
- Wellcome Trust (107630/Z/15/Z, 097922/Z/11/Z)
- Cancer Research UK (12765)
- National Institute for Health and Care Research
- Directorate for Biological Sciences
- Medical Research Council (MR/M008975/1, MC_PC_12009)
- Biotechnology and Biological Sciences Research Council (BB/I00050X/1, 1800757)
- Cambridge Institute for Medical Research, University of Cambridge
- NIHR Cambridge Biomedical Research Centre
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- hematopoietic stem and progenitor cells, single-cell transcriptomics, differentiation trajectories, lymphoid differentiation, erythroid differentiation, cell cycle genes, oxidative phosphorylation, stem cell maintenance, mice
- MeSH terms
- Animals, Cell Cycle, Cell Differentiation, Female, Gene Expression Regulation, Hematopoietic Stem Cells, Mice, Inbred C57BL, Phenotype, RNA, Messenger, Transcription, Genetic, Biomarkers, Gene Expression Profiling, Single-Cell Analysis
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