<HashMap><database>biostudies-literature</database><scores/><additional><submitter>He P</submitter><funding>Medical Research Council</funding><funding>Rosetrees</funding><funding>Wellcome Trust</funding><pagination>4841-4860.e25</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7618435</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>185(25)</volume><pubmed_abstract>We present a multiomic cell atlas of human lung development that combines single-cell RNA and ATAC sequencing, high-throughput spatial transcriptomics, and single-cell imaging. Coupling single-cell methods with spatial analysis has allowed a comprehensive cellular survey of the epithelial, mesenchymal, endothelial, and erythrocyte/leukocyte compartments from 5-22 post-conception weeks. We identify previously uncharacterized cell states in all compartments. These include developmental-specific secretory progenitors and a subtype of neuroendocrine cell related to human small cell lung cancer. Our datasets are available through our web interface (https://lungcellatlas.org). To illustrate its general utility, we use our cell atlas to generate predictions about cell-cell signaling and transcrip</pubmed_abstract><journal>Cell</journal><pubmed_title>A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates.</pubmed_title><pmcid>PMC7618435</pmcid><funding_grant_id>MR/S035907/1</funding_grant_id><funding_grant_id>MR/P009581/1</funding_grant_id><funding_grant_id>M899</funding_grant_id><funding_grant_id>MC_PC_17230</funding_grant_id><funding_grant_id>222275/Z/20/Z</funding_grant_id><funding_grant_id>MR/R015635/1</funding_grant_id><funding_grant_id>G108/596</funding_grant_id><funding_grant_id>MR/W00111X/1</funding_grant_id><funding_grant_id>109146/Z/15/Z</funding_grant_id><funding_grant_id>MR/S036334/1</funding_grant_id><funding_grant_id>MR/R006237/1</funding_grant_id><funding_grant_id>203144/Z/16/Z</funding_grant_id><funding_grant_id>225221</funding_grant_id><funding_grant_id>MR/S005579/1</funding_grant_id><pubmed_authors>Meyer KB</pubmed_authors><pubmed_authors>Dong Z</pubmed_authors><pubmed_authors>Mamanova L</pubmed_authors><pubmed_authors>Tuong ZK</pubmed_authors><pubmed_authors>Jeng Q</pubmed_authors><pubmed_authors>Rawlins EL</pubmed_authors><pubmed_authors>Bolt L</pubmed_authors><pubmed_authors>Pett JP</pubmed_authors><pubmed_authors>Madissoon E</pubmed_authors><pubmed_authors>Goh I</pubmed_authors><pubmed_authors>Dann E</pubmed_authors><pubmed_authors>Sun D</pubmed_authors><pubmed_authors>Suo C</pubmed_authors><pubmed_authors>Yoshida M</pubmed_authors><pubmed_authors>Nikolic MZ</pubmed_authors><pubmed_authors>Richardson L</pubmed_authors><pubmed_authors>Wilbrey-Clark A</pubmed_authors><pubmed_authors>He P</pubmed_authors><pubmed_authors>Polanski K</pubmed_authors><pubmed_authors>Dabrowska M</pubmed_authors><pubmed_authors>He X</pubmed_authors><pubmed_authors>Janes SM</pubmed_authors><pubmed_authors>Lim K</pubmed_authors><pubmed_authors>Marioni JC</pubmed_authors><pubmed_authors>Barker RA</pubmed_authors><pubmed_authors>Teichmann SA</pubmed_authors></additional><is_claimable>false</is_claimable><name>A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates.</name><description>We present a multiomic cell atlas of human lung development that combines single-cell RNA and ATAC sequencing, high-throughput spatial transcriptomics, and single-cell imaging. Coupling single-cell methods with spatial analysis has allowed a comprehensive cellular survey of the epithelial, mesenchymal, endothelial, and erythrocyte/leukocyte compartments from 5-22 post-conception weeks. We identify previously uncharacterized cell states in all compartments. These include developmental-specific secretory progenitors and a subtype of neuroendocrine cell related to human small cell lung cancer. Our datasets are available through our web interface (https://lungcellatlas.org). To illustrate its general utility, we use our cell atlas to generate predictions about cell-cell signaling and transcrip</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Dec</publication><modification>2026-06-05T23:19:15.585Z</modification><creation>2026-05-23T03:13:51.8Z</creation></dates><accession>S-EPMC7618435</accession><cross_references><pubmed>36493756</pubmed><doi>10.1016/j.cell.2022.11.005</doi></cross_references></HashMap>