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Mapping complex multimodal phenotypes in tissue with mosaic genetic screens

ABSTRACT: The function of organs in an animal requires the coordinated activity of thousands of genes in multiple, spatially organized cell types. Understanding the basis of this emergent tissue function will require new approaches to dissect how gene activity controls diverse cellular and tissue phenotypes in vivo. Here, we develop paired imaging and sequencing methods to construct large-scale spatial and transcriptional genotype-phenotypes maps in tissue infected in a mosaic with pooled genetic perturbations. Using imaging, we identify perturbed cells in fixed tissue sections while simultaneously measuring gene expression and subcellular morphology. Using single-cell sequencing, we then measure transcriptome-wide cellular states caused by the same genetic perturbations in dissociated fixed cells. We apply this multimodal approach to study hundreds of knockouts in a genetic mosaic mouse liver. We discover novel regulators of hepatocyte zonation, characterize a liver-specific component of the unfolded protein response, and identify distinct pathways that cause convergent hepatocyte steatosis. Our approach will enable new ways of interrogating the genetic basis of complex cellular and organismal physiology and will provide crucial training data for emerging machine learning models of cellular function.

ORGANISM(S): Mus musculus

PROVIDER: GSE275483 | GEO | 2025/06/12

REPOSITORIES: GEO

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Project description:Genetic screens in organoids hold tremendous promise for accelerating discoveries at the intersection of genomics and developmental biology. Embryoid bodies (EBs) are self-organizing multicellular structures that recapitulate aspects of early mammalian embryogenesis. We set out to perform a CRISPR screen perturbing all transcription factors (TFs) in murine EBs. Specifically, a library of TF-targeting guide RNAs (gRNAs) was used to generate mouse embryonic stem cells (mESCs) bearing single TF knockouts. Aggregates of these mESCs were induced to form mouse EBs, such that each resulting EB was “mosaic” with respect to the TF perturbations represented among its constituent cells. Upon performing single cell RNA-seq (scRNA-seq) on cells derived from mosaic EBs, we found many TF perturbations exhibiting large and seemingly significant effects on the likelihood that individual cells would adopt specific fates, suggesting roles for these TFs in lineage specification. However, to our surprise, these results were not reproducible across biological replicates. Upon further investigation, we discovered cellular bottlenecks during EB differentiation that dramatically reduce clonal complexity, curtailing statistical power and confounding interpretation of mosaic screens. Towards addressing this challenge, we developed a scalable protocol in which each individual EB is monoclonally derived from a single mESC. In a proof-of-concept experiment, we show how monoclonal, genetically barcoded EBs enable us to better quantify the consequences of TF perturbations as well as “inter-individual” heterogeneity across EBs harboring the same genetic perturbation. Looking forward, monoclonal EBs and EB-derived organoids may be powerful tools not only for genetic screens, but also for modeling Mendelian disorders, as their underlying genetic lesions are overwhelmingly constitutional (i.e. present in all somatic cells), yet give rise to phenotypes with incomplete penetrance and variable expressivity.

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Mapping complex multimodal phenotypes in tissue with mosaic genetic screens

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