<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zhang H</submitter><funding>National Institute of Environmental Health Sciences</funding><funding>NIEHS NIH HHS</funding><funding>NIMH NIH HHS</funding><funding>NHLBI NIH HHS</funding><funding>National Heart, Lung, and Blood Institute</funding><funding>National Institute of Mental Health</funding><funding>National Institute of General Medical Sciences</funding><funding>NIGMS NIH HHS</funding><pagination>78</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10958877</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>25(1)</volume><pubmed_abstract>We develop a large-scale single-cell ATAC-seq method by combining Tn5-based pre-indexing with 10× Genomics barcoding, enabling the indexing of up to 200,000 nuclei across multiple samples in a single reaction. We profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16&lt;sup>-/-&lt;/sup>) model. Our study of CC16&lt;sup>-/-&lt;/sup> nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.</pubmed_abstract><journal>Genome biology</journal><pubmed_title>txci-ATAC-seq: a massive-scale single-cell technique to profile chromatin accessibility.</pubmed_title><pmcid>PMC10958877</pmcid><funding_grant_id>R35 GM137896</funding_grant_id><funding_grant_id>RF1 MH128842</funding_grant_id><funding_grant_id>R35 GM137910</funding_grant_id><funding_grant_id>T32 ES007091</funding_grant_id><funding_grant_id>T32ES007091</funding_grant_id><funding_grant_id>R35GM124704</funding_grant_id><funding_grant_id>RF1MH128842</funding_grant_id><funding_grant_id>R35 GM124704</funding_grant_id><funding_grant_id>R01 HL142769</funding_grant_id><funding_grant_id>R35GM137910</funding_grant_id><funding_grant_id>R01HL142769</funding_grant_id><funding_grant_id>R35GM137896</funding_grant_id><funding_grant_id>P30 ES006694</funding_grant_id><pubmed_authors>Cusanovich DA</pubmed_authors><pubmed_authors>Galligan JJ</pubmed_authors><pubmed_authors>Iannuzo N</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors><pubmed_authors>Mulqueen RM</pubmed_authors><pubmed_authors>Polverino F</pubmed_authors><pubmed_authors>Farrera DO</pubmed_authors><pubmed_authors>Ledford JG</pubmed_authors><pubmed_authors>Adey AC</pubmed_authors></additional><is_claimable>false</is_claimable><name>txci-ATAC-seq: a massive-scale single-cell technique to profile chromatin accessibility.</name><description>We develop a large-scale single-cell ATAC-seq method by combining Tn5-based pre-indexing with 10× Genomics barcoding, enabling the indexing of up to 200,000 nuclei across multiple samples in a single reaction. We profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16&lt;sup>-/-&lt;/sup>) model. Our study of CC16&lt;sup>-/-&lt;/sup> nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Mar</publication><modification>2026-06-02T10:38:00.702Z</modification><creation>2025-04-06T00:49:25.834Z</creation></dates><accession>S-EPMC10958877</accession><cross_references><pubmed>38519979</pubmed><doi>10.1186/s13059-023-03150-1</doi></cross_references></HashMap>