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多重批量和单细胞 RNA-seq 杂交使具有嵌合类器官的疾病建模具有成本效益。

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

机构信息

Center for Translational Stem Cell Biology, Hong Kong Science and Technology Park, Hong Kong SAR, China.

Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.

出版信息

Nat Commun. 2024 May 10;15(1):3946. doi: 10.1038/s41467-024-48282-5.

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.

摘要

利用同源诱导多能干细胞(iPSC)分化类器官进行疾病建模是研究疾病机制的一种强大技术。在研究分化的 iPSC 或类器官中致病变体的遗传效应时,多重共培养对于减轻批次效应至关重要,而通过评估天然遗传条码可以在单细胞水平上方便地进行去复用。在这里,为了通过混合的多重批量和单细胞 RNA-seq 实现具有成本效益的时间序列实验设计,我们在 Vireo 套件中引入了一种计算方法 Vireo-bulk,通过基因型参考有效地对汇集的批量 RNA-seq 数据进行反卷积,从而量化分化过程中的供体丰度并识别供体之间差异表达的基因。此外,通过多重 scRNA-seq 和批量 RNA-seq,我们展示了汇集设计在揭示巨噬细胞分化过程中供体 iPSC 系异质性以及使用嵌合类器官模拟罕见 WT1 突变驱动的肾脏疾病方面的有用性和必要性。我们的工作为使用嵌合类器官解析疾病机制提供了一个实验和分析管道。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c580/11087505/c85f3ebb6fe5/41467_2024_48282_Fig1_HTML.jpg

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