Mouse lemur transcriptomic atlas informs primate genes, mutations, physiology, and disease

Ezran, Camille; Liu, Shixuan; Ming, Jingsi; Guethlein, Lisbeth A.; Wang, Michael F. Z.; Dehghannasiri, Roozbeh; Olivieri, Julia Eve; Frank, Hannah K.; Tarashansky, Alexander J.; Koh, Winston; Jing, Qiuyu; Botvinnik, Olga; Antony, Jane; Chang, Stephen; Pisco, Angela Oliveira; Karkanias, Jim; Yang, Can; Ferrell, James E.; Boyd, Scott D.; Parham, Peter; Long, Jonathan Z.; Wang, Bo; Salzman, Julia; Vlaminck, Iwijn De; Wu, Angela Ruohao; Quake, Stephen R.; Krasnow, Mark A.

doi:10.1101/2022.08.06.503035

Cited by 7 publications

(33 citation statements)

References 214 publications

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“…Although adipocytes were originally regarded only as nutrient storage cells, it is now clear that they also serve an endocrine role 34 . Surprisingly, leptin transcripts were almost undetectable in the adipocytes captured in the atlas (see discussion in the accompanying manuscript 16 ) ( Fig. S1 -leptin).…”

Section: Resultsmentioning

confidence: 93%

“…The atlas also contains diseased cells, including potential primary endometrial tumor cells in the uterus (MUC16+ non-ciliated uterus epithelial cells) and lung metastatic cells of endometrial cancer origin, as assessed by tumor gene signatures and histology (see accompanying manuscripts 15,16 ). Both tumor cell types clustered with the non- tumor epithelial cells of the uterus 16 and shared characteristic expression of the oxytocin receptor (OXTR) and the inhibin beta B subunit (INHBB) ( Fig. 3g , Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Because of its small size, rapid reproduction, and close genetic proximity to humans, the mouse lemur is an appealing model organism for studies of primate biology, behavior, aging, and disease [10][11][12][13][14] . As described in detail elsewhere 15,16 , we have recently created, using single-cell RNA-sequencing (scRNAseq), a molecular cell atlas of the mouse lemur by profiling mRNA sequences from ~225,000 cells from 27 mouse lemur organs and tissues from 4 individuals (https://tabula-microcebus.ds.czbiohub.org/). Given the ethical concerns of primate studies, tissue samples used in the study were collected opportunistically from aged lemurs.…”

Section: Introductionmentioning

confidence: 99%

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An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome

Liu

Ezran

Wang

et al. 2021

Preprint

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Hormones coordinate long-range cell-cell communication in multicellular organisms and play vital roles in normal physiology, metabolism, and health. Using the newly-completed organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), we have systematically identified hormone-producing and -target cells for 87 classes of hormones, and have created a browsable atlas for hormone signaling that reveals previously unreported sites of hormone regulation and species-specific rewiring. Hormone ligands and receptors exhibited cell-type-dependent, stereotypical expression patterns, and their transcriptional profiles faithfully classified the discrete cell types defined by the full transcriptome, despite their comprising less than 1% of the transcriptome. Although individual cell types generally exhibited the same characteristic patterns of hormonal gene expression, a number of examples of similar or seemingly-identical cell types (e.g., endothelial cells of the lung versus of other organs) displayed different hormonal gene expression patterns. By linking ligand-expressing cells to the cells expressing the corresponding receptor, we constructed an organism-wide map of the hormonal cell-cell communication network. The hormonal cell-cell network was remarkably densely and robustly connected, and included classical hierarchical circuits (e.g. pituitary → peripheral endocrine gland → diverse cell types) as well as examples of highly distributed control. The network also included both well-known examples of feedback loops and a long list of potential novel feedback circuits. This primate hormone atlas provides a powerful resource to facilitate discovery of regulation on an organism-wide scale and at single-cell resolution, complementing the single-site-focused strategy of classical endocrine studies. The network nature of hormone regulation and the principles discovered here further emphasize the importance of a systems approach to understanding hormone regulation.

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Section: Resultsmentioning

confidence: 93%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome

Liu

Ezran

Wang

et al. 2021

Preprint

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“…To extend our findings in mouse to primates, we next analyzed glial cells from Tabula Microcebus, a single cell whole organism transcriptomic cell atlases of the mouse lemur primate model [13]. We annotated glial cells from the mouse lemur as previously described [13] and identified gene expression profiles of myelinating (n= 47) and non-myelinating (n= 139) glial cells in mouse lemur across 8 different peripheral tissues: bladder, bone, fat, kidney, lung, pancreas, small intestine, and tongue (Fig. 5A-B, S5, Table S4).…”

Section: Cross-species Glial Cell Integration Identified Conserved Pe...mentioning

confidence: 99%

Cellular and molecular characterization of peripheral glia in the lung and other organs

Hall,

Liu,

Liang

et al. 2024

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Peripheral glia are important regulators of diverse physiologic functions yet their molecular distinctions and locations in almost all visceral organs are not well-understood. We performed a systematic analysis of peripheral glia, focusing on the lung and leveraging single cell RNA sequencing (scRNA-seq) analysis to characterize their cellular and molecular features. Using in vivo lineage studies, we characterized the anatomic, cellular, and molecular features of the Sox10+ glial lineage of the mouse lung. Using high-resolution imaging, we quantified the distribution and cellular morphologies of myelinating, non-myelinating, satellite, and terminal glial cells with their intricate extensions along peripheral nerves, including terminals at specialized neurosensory structures within the lung. Spatial analysis of selectively expressed myelinating (periaxin/Prx, claudin 19/Cldn) or non-myelinating (sodium channel/Scn7a) glial cell genes identified by scRNA-seq analysis revealed molecularly distinct populations surrounding myelinated nerve fibers in the lung. To extend this analysis to primates and other organs, we extracted rare peripheral glial cells in whole organism scRNA-seq atlases of mouse lemur and human. Our cross-species data analysis and integration of scRNA-seq data of ~700 peripheral glial cells from mouse, mouse lemur, and human glial cells identified conserved gene expression of molecularly distinct peripheral glial cell populations. This foundational knowledge facilitates subsequent functional studies targeting molecularly distinct subsets of peripheral glia and integrating them into organ-specific disorders of autonomic dysregulation. In addition, our cross-species analysis identifying conserved gene expression patterns and glial networks in extrapulmonary organs provides a valuable resource for studying the functional role of peripheral glia in multiorgan human diseases.

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“…Single-cell RNA sequencing (scRNA-seq) characterizes the whole transcriptome of individual cells within a given organ, providing remarkable opportunities for broad and deep biological investigations of diverse cellular behaviors [1, 2, 3]. However, scRNA-seq does not capture the spatial distribution of cells due to samples having to undergo tissue dissociation [4].…”

Section: Introductionmentioning

confidence: 99%

SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models

Wan

Xiao

Tam

et al. 2023

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The rapid emergence of spatial transcriptomics (ST) technologies is revolutionizing our understanding of tissue spatial architecture and their biology. Current ST technologies based on either next generation sequencing (seq-based approaches) or fluorescence in situ hybridization (image-based approaches), while providing hugely informative insights, remain unable to provide spatial characterization at transcriptome-wide single-cell resolution, limiting their usage in resolving detailed tissue structure and detecting cellular communications. To overcome these limitations, we developed SpatialScope, a unified approach to integrating scRNA-seq reference data and ST data that leverages deep generative models. With innovation in model and algorithm designs, SpatialScope not only enhances seq-based ST data to achieve single-cell resolution, but also accurately infers transcriptome-wide expression levels for image-based ST data. We demonstrate the utility of SpatialScope through comprehensive simulation studies and then apply it to real data from both seq-based and image-based ST approaches. SpatialScope provides a spatial characterization of tissue structures at transcriptome-wide single-cell resolution, greatly facilitating the downstream analysis of ST data, such as detection of cellular communication by identifying ligand-receptor interactions from seq-based ST data, localization of cellular subtypes, and detection of spatially differently expressed genes.

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Mouse lemur transcriptomic atlas informs primate genes, mutations, physiology, and disease

Cited by 7 publications

References 214 publications

An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome

An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome

Cellular and molecular characterization of peripheral glia in the lung and other organs

SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models

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