DevelopmentDevelopmental BiologyPeer-reviewed journal article
Single-cell analysis of progenitor cell dynamics and lineage specification of the human fetal kidney
Rajasree MenoniD, Edgar A. OttoiD, Austin Kokoruda, Jian ZhouiD, Zidong ZhangiD, Euisik YooniD, Yu‐Chih CheniD, Olga G. TroyanskayaiD, Jason R. SpenceiD, Matthias KretzleriD, Cristina CebriániD
Abstract
The mammalian kidney develops through repetitive and reciprocal interactions between the ureteric bud and the metanephric mesenchyme to give rise to the entire collecting system and the nephrons, respectively. Most of our knowledge of the developmental regulators driving this process has been gained from the study of gene expression and functional genetics in mice and other animal models. In order to shed light on human kidney development, we have used singlecell transcriptomics to characterize gene expression in different cell population, and to study individual cell dynamics and lineage trajectories during development. Single cell transcriptome analyses of 3,865 cells identified 17 clusters of specific cell types as defined by their gene expression profile, including markers of ureteric bud tip- and metanephric mesenchyme-specific progenitors, as well as their intermediate and differentiated lineages including the mature collecting ducts, the renal vesicle and comma- and s-shaped bodies, immature and mature podocytes, proximal tubules, loops of Henle and distal tubules. Other lineages identified include mesangium and cortical and medullary interstitium, endothelial and immune cells as well as hematopoietic cells. Novel markers for these cell types were revealed in the analysis as well as components of key signaling pathways driving renal development in animal models. Altogether, we provide a comprehensive and dynamic gene expression array of the human developing kidney at the single-cell level.
- organism: human
- assay: scRNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- Citations
- 155
- FWCI
- 7.56
- Field percentile
- top 2%
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