Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, genera...

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Veröffentlicht in:Science (American Association for the Advancement of Science) Jg. 376; H. 6594; S. eabl4290
Hauptverfasser: Eraslan, Gökcen, Drokhlyansky, Eugene, Anand, Shankara, Fiskin, Evgenij, Subramanian, Ayshwarya, Slyper, Michal, Wang, Jiali, Van Wittenberghe, Nicholas, Rouhana, John M, Waldman, Julia, Ashenberg, Orr, Lek, Monkol, Dionne, Danielle, Win, Thet Su, Cuoco, Michael S, Kuksenko, Olena, Tsankov, Alexander M, Branton, Philip A, Marshall, Jamie L, Greka, Anna, Getz, Gad, Segrè, Ayellet V, Aguet, François, Rozenblatt-Rosen, Orit, Ardlie, Kristin G, Regev, Aviv
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 13.05.2022
Schlagworte:
Biomarkers
Cell Nucleus - genetics
Disease - genetics
Genome-Wide Association Study
Humans
Organ Specificity
Phenotype
RNA-Seq - methods
ISSN:1095-9203, 1095-9203
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Zusammenfassung:Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.
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ISSN:1095-9203
1095-9203
DOI:10.1126/science.abl4290