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Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
Open accessAbstract
The mammalian lung is a highly branched network in which the distal regions of the bronchial tree transform during development into a densely packed honeycomb of alveolar air sacs that mediate gas exchange. Although this transformation has been studied by marker expression analysis and fate-mapping, the mechanisms that control the progression of lung progenitors along distinct lineages into mature alveolar cell types are still incompletely known, in part because of the limited number of lineage markers and the effects of ensemble averaging in conventional transcriptome analysis experiments on cell populations. Here we show that single-cell transcriptome analysis circumvents these problems and enables direct measurement of the various cell types and hierarchies in the developing lung. We used microfluidic single-cell RNA sequencing (RNA-seq) on 198 individual cells at four different stages encompassing alveolar differentiation to measure the transcriptional states which define the developmental and cellular hierarchy of the distal mouse lung epithelium. We empirically classified cells into distinct groups by using an unbiased genome-wide approach that did not require a priori knowledge of the underlying cell types or the previous purification of cell populations. The results confirmed the basic outlines of the classical model of epithelial cell-type diversity in the distal lung and led to the discovery of many previously unknown cell-type markers, including transcriptional regulators that discriminate between the different populations. We reconstructed the molecular steps during maturation of bipotential progenitors along both alveolar lineages and elucidated the full life cycle of the alveolar type 2 cell lineage. This single-cell genomics approach is applicable to any developing or mature tissue to robustly delineate molecularly distinct cell types, define progenitors and lineage hierarchies, and identify lineage-specific regulatory factors.
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Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
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
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682
Quality control and preprocessing of metagenomic datasets
Schmieder, R., & Edwards, R. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr026 · Cited by 5,119
mRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969
Flagged first, then by citations
Cited by
Sorted by citations
Items 601–700 of 1,001
Wang, R., Yang, X., Chen, J., Zhang, L., Griffiths, J. A., Cui, G., Chen, Y., Qian, Y., Peng, G., Li, J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41482-5 · Cited by 28
Mitchell, H. D., Markillie, L. M., Chrisler, W., Gaffrey, M. J., Hu, D., Szymanski, C. J., Xie, Y., Melby, E. S., Dohnalkova, A. C., Taylor, R. C., et al. (2016) · ACS Nano · doi:10.1021/acsnano.6b05452 · Cited by 28
Oligohydramnios compromises lung cells size and interferes with epithelial–endothelial development
Najrana, T., Ramos, L. M., Eid, R. A., & Sanchez‐Esteban, J. (2017) · Pediatric Pulmonology · doi:10.1002/ppul.23662 · Cited by 28
CD44highalveolar type II cells show stem cell properties during steady-state alveolar homeostasis
Chen, Q., Kumar, V. S., Finn, J., Jiang, D., Liang, J., Zhao, Y., & Liu, Y. (2017) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00564.2016 · Cited by 28
Spatial clustering and common regulatory elements correlate with coordinated gene expression
Zhang, J., Chen, H., Li, R., Taft, D. A., Yao, G., Bai, F., & Xing, J. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006786 · Cited by 30
Ren, L., Huang, D., Liu, H., Lin, N., Cai, P., Yu, X., Zhang, Y., Luo, N., Lin, H., Su, J., et al. (2024) · Oncology Letters · doi:10.3892/ol.2024.14285 · Cited by 28
He, Q., Qu, M., Xu, C., Wu, L., Xu, Y., Xu, Y., Bao, H., Shen, T., He, Y., Cai, J., et al. (2024) · Cancer Letters · doi:10.1016/j.canlet.2024.216922 · Cited by 27
Okawa, S., Angarica, V. E., Lemischka, I. R., Moore, K. A., & del Sol, A. (2015) · npj Systems Biology and Applications · doi:10.1038/npjsba.2015.12 · Cited by 28
scDoc: correcting drop-out events in single-cell RNA-seq data
Ran, D., Zhang, S., Lytal, N., & An, L. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa283 · Cited by 27
Tóth, A., Steinmeyer, S. H., Kannan, P. S., Gray, J. K., Jackson, C. M., Mukherjee, S., Demmert, M., Sheak, J. R., Benson, D., Kitzmiller, J. A., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abl8574 · Cited by 29
Cellular Deconstruction: Finding Meaning in Individual Cell Variation
Eberwine, J. H., & Kim, J. (2015) · Trends in Cell Biology · doi:10.1016/j.tcb.2015.07.004 · Cited by 30
Single-cell RNA-seq interpretations using evolutionary multiobjective ensemble pruning
Li, X., Zhang, S., & Wong, K. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty1056 · Cited by 27
Cell lineage inference from SNP and scRNA-Seq data
Ding, J., Lin, C. H., & Bar‐Joseph, Z. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz146 · Cited by 27
An Adaptive Sparse Subspace Clustering for Cell Type Identification
Zheng, R., Liang, Z., Chen, X., Tian, Y., Cao, C., & Li, M. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00407 · Cited by 27
A novel in vitro model of primary human pediatric lung epithelial cells
Wang, Q., Bhattacharya, S., Mereness, J. A., Anderson, C., Lillis, J. A., Misra, R. S., Romas, S., Huyck, H. L., Howell, A., Bandyopadhyay, G. K., et al. (2019) · Pediatric Research · doi:10.1038/s41390-019-0340-9 · Cited by 26
Single-cell RNA-seq data clustering: A survey with performance comparison study
Li, R., Guan, J., & Zhou, S. (2020) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720020400053 · Cited by 26
A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection
Zhang, D.-J., Gao, Y.-L., Zhao, J.-X., Zheng, C.-H., & Liu, J. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3190289 · Cited by 26
PRICAI 2019: Trends in Artificial Intelligence
Nayak, A., & Sharma, A. K. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29908-8 · Cited by 29
Dillon, M. M., Rouillard, N. P., van Dam, B., Gallet, R., & Cooper, V. S. (2016) · Evolution · doi:10.1111/evo.12868 · Cited by 26
Huang, X., Li, X., Qin, P., Zhu, Y., Xu, S., & Chen, J. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00582 · Cited by 27
Zhang, L., Zhu, J., Wang, H., Xia, J., Liu, P., Chen, F., Jiang, H., Miao, Q., Wu, W., Zhang, L., et al. (2021) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2021.03.012 · Cited by 27
Low-cost, low-input RNA-seq protocols perform nearly as well as high-input protocols
Combs, P. A., & Eisen, M. B. (2015) · PeerJ · doi:10.7717/peerj.869 · Cited by 25
Wang, H., Sham, P. C., Tong, T., & Pang, H. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2944865 · Cited by 25
Single-cell Sequencing in the Field of Stem Cells
Chen, T., Li, J., Jia, Y., Wang, J., Sang, R., Zhang, Y., & Rong, R. (2020) · Current Genomics · doi:10.2174/1389202921999200624154445 · Cited by 25
A single-cell regulatory map of postnatal lung alveologenesis in humans and mice
Duong, T. E., Wu, Y., Sos, B. C., Dong, W., Limaye, S., Rivier, L. H., Myers, G., Hagood, J. S., & Zhang, K. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100108 · Cited by 26
Zhu, Y., Pu, Q., Zhang, Q., Liu, Y., Ma, Y., Yuan, Y., Liu, L., & Zhu, W. (2023) · Cancer Medicine · doi:10.1002/cam4.6309 · Cited by 25
Selective single cell isolation for genomics using microraft arrays
Welch, J. D., Williams, L. A., DiSalvo, M., Brandt, A., Marayati, R., Sims, C. E., Allbritton, N. L., Prins, J. F., Yeh, J. J., & Jones, C. D. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw700 · Cited by 27
Kim, J., Stanescu, D. E., & Won, K. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky698 · Cited by 25
Single-cell RNA Sequencing in Immunology
Cao, Y., Qiu, Y., Tu, G.-W., & Yang, C. (2020) · Current Genomics · doi:10.2174/1389202921999201020203249 · Cited by 28
Carapito, C., Duek, P. D., Macron, C., Seffals, M., Rondel, K., Delalande, F., Lindskog, C., Fréour, T., Vandenbrouck, Y., Lane, L., et al. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00374 · Cited by 24
Zhang, L., Guo, X., Zhang, L., Yang, F., Qin, L., Zhang, D., & Qin, Y. A. (2017) · Molecular Carcinogenesis · doi:10.1002/mc.22768 · Cited by 24
Cell type- and replication stage-specific influenza virus responses in vivo
Fay, E. J., Aron, S. L., Macchietto, M. G., Markman, M. W., Esser‐Nobis, K., Gale, M., Shen, S., & Langlois, R. A. (2020) · PLoS Pathogens · doi:10.1371/journal.ppat.1008760 · Cited by 24
Wei, Y., Han, S., Wen, J., Liao, J., Liang, J., Yu, J., Chen, X., Xiang, S., Huang, Z., & Zhang, B. (2023) · Journal of Biomedical Science · doi:10.1186/s12929-023-00909-3 · Cited by 25
Transcriptomic signatures shaped by cell proportions shed light on comparative developmental biology
Pantalacci, S., Guéguen, L., Petit, C., Lambert, A., Peterková, R., & Sémon, M. (2017) · Genome biology · doi:10.1186/s13059-017-1157-7 · Cited by 26
Lung morphogenesis is orchestrated through Grainyhead-like 2 (Grhl2) transcriptional programs
Kersbergen, A. J., Best, S. A., Dworkin, S., Ah-Cann, C., de Vries, M. E., Asselin-Labat, M.-L., Ritchie, M. E., Jane, S. M., & Sutherland, K. D. (2018) · Developmental Biology · doi:10.1016/j.ydbio.2018.09.002 · Cited by 24
Transcriptomic profile of cystic fibrosis airway epithelial cells undergoing repair
Zoso, A., Sofoluwe, A., Bacchetta, M., & Chanson, M. (2019) · Scientific Data · doi:10.1038/s41597-019-0256-6 · Cited by 24
F-16 Class A mishaps in the U.S. Air Force, 1975-93.
Knapp, C.-L., & Johnson, W. R. (1996) · PubMed · Cited by 24
Wang, W., Penland, L., Gokce, O., Croote, D., & Quake, S. R. (2018) · BMC Genomics · doi:10.1186/s12864-018-4512-5 · Cited by 23
Self-citationImpact of recent innovations in the use of mass cytometry in support of drug development
Nassar, A. F., Ogura, H., & Wisnewski, A. V. (2015) · Drug Discovery Today · doi:10.1016/j.drudis.2015.06.001 · Cited by 23
Katsumiti, A., Ruenraroengsak, P., Cajaraville, M. P., Thorley, A. J., & Tetley, T. D. (2020) · Scientific Reports · doi:10.1038/s41598-020-77191-y · Cited by 23
Antounians, L., Figueira, R. L., Kukreja, B., Litvack, M. L., Zani‐Ruttenstock, E., Khalaj, K., Montalva, L., Doktor, F., Obed, M., Blundell, M., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn5405 · Cited by 23
Data acquisition approaches for single cell proteomics
Ghosh, G., Shannon, A. E., & Searle, B. C. (2024) · PROTEOMICS · doi:10.1002/pmic.202400022 · Cited by 25
Janes, K. A. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.03.015 · Cited by 23
Cellular identity at the single-cell level
Coskun, A. F., Eser, U., & Islam, S. (2016) · Molecular BioSystems · doi:10.1039/c6mb00388e · Cited by 24
Transcriptome profiling of human oocytes experiencing recurrent total fertilization failure
Suo, L., Zhou, Y., Jia, L. L., Wu, H. B., Zheng, J., Lyu, Q., Sun, L. H., Sun, H., & Kuang, Y. (2018) · Scientific Reports · doi:10.1038/s41598-018-36275-6 · Cited by 24
LAK: Lasso and K-Means Based Single-Cell RNA-Seq Data Clustering Analysis
Hua, J., Liu, H., Zhang, B., & Jin, S. (2020) · IEEE Access · doi:10.1109/access.2020.3008681 · Cited by 24
Horie, M., Castaldi, A., Sunohara, M., Wang, H., Ji, Y., Liu, Y., Li, F., Wilkinson, T. A., Hung, L. T., Shen, H. M., et al. (2020) · Cells · doi:10.3390/cells9112460 · Cited by 23
FEATS: feature selection-based clustering of single-cell RNA-seq data
Vans, E., Patil, A., & Sharma, A. K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa306 · Cited by 23
Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks
Atay, O., Doncic, A., & Skotheim, J. M. (2016) · Cell Systems · doi:10.1016/j.cels.2016.06.010 · Cited by 23
Gao, S., Dai, Y. D., & Rehman, J. (2021) · Genome Research · doi:10.1101/gr.265595.120 · Cited by 24
LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer
Murray, C. W., Brady, J. J., Han, M., Cai, H., Tsai, M. K., Pierce, S. E., Cheng, R., Demeter, J., Feldser, D. M., Jackson, P. K., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28619-8 · Cited by 22
Cell Therapy in Idiopathic Pulmonary Fibrosis†
Serrano‐Mollar, A. (2018) · Medical Sciences · doi:10.3390/medsci6030064 · Cited by 22
Kanter, I., Dalerba, P. D., & Tomer Kalisky, C. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty708 · Cited by 22
Clustering single-cell RNA-seq data by rank constrained similarity learning
Mei, Q., Li, G., & Su, Z. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab276 · Cited by 22
Lee, J., Møller, A. F., Chae, S., Bussek, A., Park, T. J., Kim, Y., Lee, H., Pers, T. H., Kwon, T., Sedzinski, J., et al. (2023) · Science Advances · doi:10.1126/sciadv.add5745 · Cited by 27
An enduring role for quiescent stem cells
Richmond, C. A., Shah, M. S., Carlone, D. L., & Breault, D. T. (2016) · Developmental Dynamics · doi:10.1002/dvdy.24416 · Cited by 23
Epithelial Sodium Channels in Pulmonary Epithelial Progenitor and Stem Cells
Liu, Y., Jiang, B.-J., Zhao, R., & Ji, H.-L. (2016) · International Journal of Biological Sciences · doi:10.7150/ijbs.15747 · Cited by 22
Applications of Single-Cell Sequencing for Multiomics
Xu, Y., & Zhou, X. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7717-8_19 · Cited by 22
Berglund, E., Saarenpää, S., Jemt, A., Gruselius, J., Larsson, L., Bergenstråhle, L., Lundeberg, J., & Giacomello, S. (2020) · BMC Genomics · doi:10.1186/s12864-020-6631-z · Cited by 23
A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data
Srinivasan, S., Leshchyk, A., Johnson, N. T., & Korkin, D. (2020) · RNA · doi:10.1261/rna.074427.119 · Cited by 24
Precision monitoring of immunotherapies in solid organ and hematopoietic stem cell transplantation
DiLoreto, R., Khush, K. K., & Vlaminck, I. D. (2017) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2017.06.009 · Cited by 21
He, H., Bell, S. M., Davis, A. K., Zhao, S., Sridharan, A., Na, C.-L., Guo, M., Xu, Y. J., Snowball, J. M., Swarr, D. T., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52154-3 · Cited by 21
Sukys, A., & Grima, R. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf295 · Cited by 22
ScGSLC: An unsupervised graph similarity learning framework for single-cell RNA-seq data clustering
Li, J., Jiang, W., Han, H., Liu, J., Liu, B., & Wang, Y. (2020) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2020.107415 · Cited by 21
Ahmadvand, N., Lingampally, A., Khosravi, F., Vazquez‐Armendariz, A. I., Rivetti, S., Jones, M. R., Wilhelm, J., Herold, S., Barreto, G., Koepke, J., et al. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04327-w · Cited by 21
Wang, Y., Lian, B., Zhang, H., Zhong, Y., He, J. Y., Wu, F., Reinert, K., Shang, X., Yang, H., & Hu, J. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad005 · Cited by 24
Stem cell heterogeneity, plasticity, and regulation
Cui, Z., Wei, H., Goding, C. R., & Cui, R. (2023) · Life Sciences · doi:10.1016/j.lfs.2023.122240 · Cited by 21
Shao, S., Zhang, N., Specht, G. P., You, S., Song, L., Fu, Q., Huang, D., You, H., Shu, J., Domissy, A., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2400077121 · Cited by 22
Specific Palmitoyltransferases Associate with and Activate the Epithelial Sodium Channel
Mukherjee, A., Wang, Z., Kinlough, C. L., Poland, P. A., Marciszyn, A. L., Montalbetti, N., Carattino, M. D., Butterworth, M. B., Kleyman, T. R., & Hughey, R. P. (2017) · Journal of Biological Chemistry · doi:10.1074/jbc.m117.776146 · Cited by 21
High-Throughput Single-Cell RNA Sequencing and Data Analysis
Sagar, Herman, J. S., Pospisilik, J. A., & Grün, D. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7768-0_15 · Cited by 21
van Veen, J. E., Scherzer, M. T., Boshuizen, J., Chu, M., Liu, A., Landman, A. S., Green, S., Trejo, C. L., & McMahon, M. (2019) · eLife · doi:10.7554/elife.43668 · Cited by 21
Noncontact Multiphysics Probe for Spatiotemporal Resolved Single‐Cell Manipulation and Analyses
Brimmo, A. T., Menachery, A., Sukumar, P., & Qasaimeh, M. A. (2021) · Small · doi:10.1002/smll.202100801 · Cited by 22
Delineating biological and technical variance in single cell expression data
Arzalluz-Luque, Á., Devailly, G., Mantsoki, A., & Joshi, A. (2017) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2017.07.006 · Cited by 21
Single-Cell Transcriptomics Enters the Age of Mass Production
Junker, J. P., & van Oudenaarden, A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.05.019 · Cited by 20
Fuentes‐Mateos, R., Jimeno, D., Gómez, C., Calzada, N., Fernández‐Medarde, A., & Santos, E. (2019) · Cell Death and Disease · doi:10.1038/s41419-019-2075-2 · Cited by 20
Endogenous lung stem cells for lung regeneration
McQualter, J. L. (2019) · Expert Opinion on Biological Therapy · doi:10.1080/14712598.2019.1596256 · Cited by 20
Single-Cell Multimodal Analytical Approach by Integrating Raman Optical Tweezers and RNA Sequencing
Fang, T., Shang, W., Liu, C. X., Liu, Y., & Ye, A. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c00912 · Cited by 20
Mucins and CFTR: Their Close Relationship
Okuda, K., Shaffer, K. M., & Ehré, C. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231810232 · Cited by 21
Borsi, G., Motheramgari, K., Dhiman, H., Baumann, M., Sinkala, E., Sauerland, M. B., Riba, J., & Borth, N. (2023) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2023.01.006 · Cited by 20
Emerging single-cell technologies in immunology
Herderschee, J., Fenwick, C. W., Pantaleo, G., Roger, T., & Calandra, T. (2015) · Journal of Leukocyte Biology · doi:10.1189/jlb.6ru0115-020r · Cited by 22
Yokota, M., Tamachi, T., Yokoyama, Y., Maezawa, Y., Takatori, H., Suto, A., Suzuki, K., Hirose, K., Takeda, K., & Nakajima, H. (2016) · Allergy · doi:10.1111/all.13079 · Cited by 20
Single Cell Gene Expression to Understand the Dynamic Architecture of the Heart
Massaia, A., Cháves, P., Samari, S., Miragaia, R. J., Meyer, K. B., Teichmann, S. A., & Noseda, M. (2018) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2018.00167 · Cited by 20
Lagerman, C. E., Acevedo, S. N. L., Fahad, A. S., Hailemariam, A. T., Madan, B., & DeKosky, B. J. (2019) · Journal of Bioscience and Bioengineering · doi:10.1016/j.jbiosc.2019.01.020 · Cited by 20
Dissecting the Niche for Alveolar Type II Cells With Alveolar Organoids
Liao, D., & Li, H. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.00419 · Cited by 21
Breathing fresh air into respiratory research with single-cell RNA sequencing
Alexander, M. J., Budinger, G. R. S., & Reyfman, P. A. (2020) · European Respiratory Review · doi:10.1183/16000617.0060-2020 · Cited by 23
Chawla, S., Samydurai, S., Kong, S. L., Wu, Z., Wang, Z., Tam, W. L., Sengupta, D., & Kumar, V. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkab018 · Cited by 20
Ou-Yang, L., Lü, F., Zhang, Z.-C., & Wu, M. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab479 · Cited by 20
Ming, J., Lin, Z., Zhao, J., Wan, X., Ezran, C., Liu, S., Yang, C., & Wu, A. R. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac167 · Cited by 21
Self-citationNoncommutative Biology: Sequential Regulation of Complex Networks
Letsou, W., & Cai, L. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005089 · Cited by 21
Cloned airway basal progenitor cells to repair fibrotic lung through re-epithelialization
Zhao, Y., Zhou, Y., Zhang, W., Liu, M., Duan, J., Zhang, X., Ma, Q., Wang, Y., Zhang, Y., Guo, Z., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56501-w · Cited by 19
Hoffman, E. T., Uriarte, J. J., Uhl, F. E., Eckstrom, K. M., Tanneberger, A. E., Becker, C., Moulin, C., Asarian, L., Ikonomou, L., Kotton, D. N., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-37685-x · Cited by 21
Witman, N., Zhou, C., Häneke, T., Xiao, Y., Huang, X., Rohner, E., Sohlmér, J., Beverborg, N. G., Lehtinen, M. L., Chien, K. R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41305-7 · Cited by 19
Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells
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Ma, J. Z.-I., Ng, W. C., Zappia, L., Gearing, L. J., Olshansky, M., Pham, K., Cheong, K., Hsu, A. L., Turner, S. J., Wijburg, O. L. C., et al. (2019) · Journal of Virology · doi:10.1128/jvi.01986-18 · Cited by 19
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O’Huallachain, M., Bava, F.-A., Shen, M., Dallett, C., Paladugu, S. R., Samusik, N., Yu, S., Hussein, R., Hillman, G. R., Higgins, S., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-0896-2 · Cited by 19
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Metadata
- Authors
- Treutlein, B., Brownfield, D. G., Wu, A. R., Neff, N. F., Mantalas, G. L., Espinoza, F. H., Desai, T. J., Krasnow, M. A., & Quake, S. R.
- Affiliations
- Howard Hughes Medical Institute (US)
- Stanford Medicine (US)
- Corresponding author
- Desai, Tushar J.
- Krasnow, Mark A.
- Quake, Stephen R.
- ORCID
- Venue
- Nature
- Published
- 2014-04-13
- Volume
- 509
- Issue
- 7500
- Pages
- 371-375
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4145853
- OpenAlex
- W2068881679
- Cited by
- 1,342
- References
- 41
- Citations by year
- 2026: 25 · 2025: 52 · 2024: 65 · 2023: 97 · 2022: 113 · 2021: 120 · 2020: 134 · 2019: 146 · 2018: 161 · 2017: 155 · 2016: 137 · 2015: 106 · 2014: 25
- FWCI
- 57.77
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Heart, Lung, and Blood Institute (K08HL084095, U01HL099995, U01HL099999)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32HD007249)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Neonatal Respiratory Health Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- distal lung epithelium, lung development, alveolar progenitor cells, alveolar type II cells, alveolar type I cells, cell type markers, lineage hierarchy, alveolar differentiation, transcription factors, mouse lung
- MeSH terms
- Animals, Bronchi, Cell Differentiation, Epithelial Cells, Female, Genetic Markers, Lung, Mice, Inbred C57BL, Pulmonary Alveoli, Pulmonary Gas Exchange, Stem Cells, Genome, Sequence Analysis, RNA, Cell Lineage, Genomics, Mice, Single-Cell Analysis, Transcriptome
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