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

Chen Cheng, Gang Wang, Yuqing Zhu, Hangdi Wu, Li Zhang, Zhihong Liu (), Yuanhua Huang () and Jin Zhang ()
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Chen Cheng: Hong Kong Science and Technology Park
Gang Wang: Zhejiang University School of Medicine
Yuqing Zhu: Zhejiang University
Hangdi Wu: Nanjing University School of Medicine
Li Zhang: Zhejiang University
Zhihong Liu: Zhejiang University School of Medicine
Yuanhua Huang: Hong Kong Science and Technology Park
Jin Zhang: Zhejiang University School of Medicine

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Disease 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.

Date: 2024
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DOI: 10.1038/s41467-024-48282-5

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