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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients

ABSTRACT: Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients

PROVIDER: PRJNA607949 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11139100_1.fastq.gz	Fastqsanger.gz
	SRR11139100_2.fastq.gz	Fastqsanger.gz
	SRR11139101_1.fastq.gz	Fastqsanger.gz
	SRR11139101_2.fastq.gz	Fastqsanger.gz
	SRR11139102_1.fastq.gz	Fastqsanger.gz

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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [Drop-seq]

Project description:Single-cell transcriptomics from dissociated organs lack information regarding the spatial origin of each cell, which limits their interpretation, particularly in complex and regionally heterogeneous tissues. This is relevant in the kidney, where cell types are exposed to a wide spectrum of cellular microenvironments along the corticomedullary axis, including steep gradients of extracellular osmolality and oxygen tension. Whether kidney single-cell transcriptomes can be exploited to predict spatial origins of cells and to provide physiological readouts of the cellular microenvironment is unknown. Here, we obtained single-cell transcriptomes of mouse kidney tissue from whole organs and from defined kidney zones (cortex, outer and inner medulla) and applied computational methods to reconstruct the spatial position of kidney tubule cells along the corticomedullary axis based on their transcriptomes. Our approach enabled a spatially resolved analysis of gene expression, showed a coordinated activation of osmolality-and hypoxia-associated genes towards the kidney medulla, and predicted that transcriptomes of a given cell type across different kidney zones change gradually rather than being clearly distinct in different anatomical zones. In genetically modified mice with a tubular concentration defect, spatial reconstruction of single-cell transcriptomics and osmogene expression quantitation accurately predicted reduced medullary osmolality. We conclude that our approach, which can be applied to any mouse whole kidney single-cell transcriptomic dataset, uncovers previously underappreciated information regarding spatial origin and microenvironment-dependent cellular states, adding improved readouts to existing and future datasets.

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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [single nuclei]

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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [single nuclei]

Project description:Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [single nuclei]

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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [Drop-seq]

Project description:Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [Drop-seq]

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Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [bulk RNA-seq]

Project description:Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients [bulk RNA-seq]

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Kidney Single-cell Transcriptomes Predict Spatial Corticomedullary Gene Expression and Tissue Osmolality Gradients.

Project description:BackgroundSingle-cell transcriptomes from dissociated tissues provide insights into cell types and their gene expression and may harbor additional information on spatial position and the local microenvironment. The kidney's cells are embedded into a gradient of increasing tissue osmolality from the cortex to the medulla, which may alter their transcriptomes and provide cues for spatial reconstruction.MethodsSingle-cell or single-nuclei mRNA sequencing of dissociated mouse kidneys and of dissected cortex, outer, and inner medulla, to represent the corticomedullary axis, was performed. Computational approaches predicted the spatial ordering of cells along the corticomedullary axis and quantitated expression levels of osmo-responsive genes. In situ hybridization validated computational predictions of spatial gene-expression patterns. The strategy was used to compare single-cell transcriptomes from wild-type mice to those of mice with a collecting duct-specific knockout of the transcription factor grainyhead-like 2 (Grhl2CD-/-), which display reduced renal medullary osmolality.ResultsSingle-cell transcriptomics from dissociated kidneys provided sufficient information to approximately reconstruct the spatial position of kidney tubule cells and to predict corticomedullary gene expression. Spatial gene expression in the kidney changes gradually and osmo-responsive genes follow the physiologic corticomedullary gradient of tissue osmolality. Single-nuclei transcriptomes from Grhl2CD-/- mice indicated a flattened expression gradient of osmo-responsive genes compared with control mice, consistent with their physiologic phenotype.ConclusionsSingle-cell transcriptomics from dissociated kidneys facilitated the prediction of spatial gene expression along the corticomedullary axis and quantitation of osmotically regulated genes, allowing the prediction of a physiologic phenotype.

| S-EPMC8054904 | biostudies-literature

Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients

Project description:This SuperSeries is composed of the SubSeries listed below.

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