File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Multiplexed bulk and single-cell RNA-seq hybrid enables cost-efficient disease modeling with chimeric organoids

TitleMultiplexed bulk and single-cell RNA-seq hybrid enables cost-efficient disease modeling with chimeric organoids
Authors
Issue Date1-Dec-2024
PublisherNature Portfolio
Citation
Nature Communications, 2024, v. 15, n. 1 How to Cite?
AbstractDisease modeling with isogenic Induced Pluripotent Stem Cell (iPSC)-differentiated organoids serves as a powerful technique for studying disease mechanisms. Multiplexed coculture is crucial to mitigate batch effects when studying the genetic effects of disease-causing variants in differentiated iPSCs or organoids, and demultiplexing at the single-cell level can be conveniently achieved by assessing natural genetic barcodes. Here, to enable cost-efficient time-series experimental designs via multiplexed bulk and single-cell RNA-seq of hybrids, we introduce a computational method in our Vireo Suite, Vireo-bulk, to effectively deconvolve pooled bulk RNA-seq data by genotype reference, and thereby quantify donor abundance over the course of differentiation and identify differentially expressed genes among donors. Furthermore, with multiplexed scRNA-seq and bulk RNA-seq, we demonstrate the usefulness and necessity of a pooled design to reveal donor iPSC line heterogeneity during macrophage cell differentiation and to model rare WT1 mutation-driven kidney disease with chimeric organoids. Our work provides an experimental and analytic pipeline for dissecting disease mechanisms with chimeric organoids.
Persistent Identifierhttp://hdl.handle.net/10722/350154

 

DC FieldValueLanguage
dc.contributor.authorCheng, Chen-
dc.contributor.authorWang, Gang-
dc.contributor.authorZhu, Yuqing-
dc.contributor.authorWu, Hangdi-
dc.contributor.authorZhang, Li-
dc.contributor.authorLiu, Zhihong-
dc.contributor.authorHuang, Yuanhua-
dc.contributor.authorZhang, Jin-
dc.date.accessioned2024-10-21T03:56:30Z-
dc.date.available2024-10-21T03:56:30Z-
dc.date.issued2024-12-01-
dc.identifier.citationNature Communications, 2024, v. 15, n. 1-
dc.identifier.urihttp://hdl.handle.net/10722/350154-
dc.description.abstractDisease modeling with isogenic Induced Pluripotent Stem Cell (iPSC)-differentiated organoids serves as a powerful technique for studying disease mechanisms. Multiplexed coculture is crucial to mitigate batch effects when studying the genetic effects of disease-causing variants in differentiated iPSCs or organoids, and demultiplexing at the single-cell level can be conveniently achieved by assessing natural genetic barcodes. Here, to enable cost-efficient time-series experimental designs via multiplexed bulk and single-cell RNA-seq of hybrids, we introduce a computational method in our Vireo Suite, Vireo-bulk, to effectively deconvolve pooled bulk RNA-seq data by genotype reference, and thereby quantify donor abundance over the course of differentiation and identify differentially expressed genes among donors. Furthermore, with multiplexed scRNA-seq and bulk RNA-seq, we demonstrate the usefulness and necessity of a pooled design to reveal donor iPSC line heterogeneity during macrophage cell differentiation and to model rare WT1 mutation-driven kidney disease with chimeric organoids. Our work provides an experimental and analytic pipeline for dissecting disease mechanisms with chimeric organoids.-
dc.languageeng-
dc.publisherNature Portfolio-
dc.relation.ispartofNature Communications-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleMultiplexed bulk and single-cell RNA-seq hybrid enables cost-efficient disease modeling with chimeric organoids-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/s41467-024-48282-5-
dc.identifier.pmid38729950-
dc.identifier.scopuseid_2-s2.0-85192846714-
dc.identifier.volume15-
dc.identifier.issue1-
dc.identifier.eissn2041-1723-
dc.identifier.issnl2041-1723-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats