Computational approaches to minimize reproducibility problems in organoids

Abstract

Disease modeling with isogenic induced pluripotent Stem Cell (iPSC)-differentiated organoids serves as a powerful technique for modeling disease and study mechanisms. Despite the potential of this platform, its application has been limited due to poor reproducibility between organoid production batches. To address this, 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. Leveraging both single-cell and bulk RNA sequencing, a multiplexed batch free experimental design and a demultiplexing computational pipeline, Vireo-bulk, are introduced to uncover donor/clone dynamics during iPSC differentiation, identify differentially expressed genes/pathways in chimeric organoids, and establish genotype-phenotype relationships of modeled diseases, This thesis demonstrates 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 by Vireo-bulk, which effectively deconvolve pooled bulk RNA-seq data by genotype reference, and thereby quantify donor abundance over the course of differentiation. It also shows promise in other chimeric donor contexts, such as allogeneic transplantation, and could be utilized in emerging allogeneic immune cell therapies. offers a powerful tool for disease modeling and the study of donor dynamics.