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Representation and relative abundance of cell-type selective markers in whole-kidney RNA-Seq data

ABSTRACT: Purpose: We used RNA-seq to determine the mRNA species and cell types presented in the whole kidney tissue. Methods: We extracted RNA from the whole kidney tissue and microdissected proximal tubules. cDNA libraries were constructed for paired-end sequencing and sequenced on Illumina HiSeq3000 platform.Reads were mapped to mouse Ensembl Genome by STAR and transcript abundances were calculated in the units of transcripts per million (TPM) using RSEM (https://github.com/deweylab/RSEM). Results and conclusion: Based on a variety of data types we curated a list of 43 cell types that are thought to exist in the kidney. Our data indicated that, If mRNA levels parallel protein levels, the contribution of proximal tubules to total mRNA in the renal tubule is also likely to be in the vicinity of 66%.

ORGANISM(S): Mus musculus

PROVIDER: GSE111837 | GEO | 2019/01/17

REPOSITORIES: GEO

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Project description:Purpose: Transport processes in the renal collecting duct are responsible for precise regulation of blood pressure and body fluid composition. The collecting duct is composed of at least three cell types, type A intercalated cells (A-IC), type B intercalated cells (B-IC) and principal cells (PC). To identify the genes that are selectively expressed in each cell type, including cell-surface receptors, transcription factors, transporters and secreted proteins, we used cell surface markers necessary for isolation of each of the three cell types using fluorescence-activated cell sorting and carried out single-cell RNA-Seq to measure the mRNA species in each of these cell types. Methods: We enriched each of the three cell types using fluorescence-activated cell sorting. Subsequently, we carried out single-cell RNA-Seq of those cells using a microfluidic chip (Fluidigm C1 system). Single-cell cDNA libraries were constructed for paired-end sequencing and sequenced on Illumina HiSeq3000 platform. In addition, we also microdissected mouse CCDs and cTALs and carried out single-tubule RNA-Seq. Reads were mapped to mouse Ensembl Genome by STAR and transcript abundances were calculated in the units of transcripts per million (TPM) using RSEM (https://github.com/deweylab/RSEM). Single-cell RNA-Seq data anaysis were carried out using Seurat package in R. Results and conclusion: Single-cell cDNA libraries were constructed for paired-end sequencing and at least 10-million sequence reads per cell were mapped to the mouse genome (Ensembl, GRCm38.p5). On average, cells were sequenced to a depth of 3000 genes (TPM>1). Unsupervised clustering analysis revealed five different cell types, namely type A intercalated cells (n=87), type B intercalated cells (n=23), principal cells (74), proximal tubule cells (n=19), and non-epithelial cells (n=32). The identified patterns of gene expression among A-ICs, B-ICs and PCs provide a foundation for understanding physiological regulation and pathophysiology in the renal collecting duct.

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Representation and relative abundance of cell-type selective markers in whole-kidney RNA-Seq data

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