Unknown

Dataset Information

0

Molecular characterization of the human kidney interstitium in health and disease.


ABSTRACT: The gene expression signature of the human kidney interstitium is incompletely understood. The cortical interstitium (excluding tubules, glomeruli, and vessels) in reference nephrectomies (N = 9) and diabetic kidney biopsy specimens (N = 6) was laser microdissected (LMD) and sequenced. Samples underwent RNA sequencing. Gene signatures were deconvolved using single nuclear RNA sequencing (snRNAseq) data derived from overlapping specimens. Interstitial LMD transcriptomics uncovered previously unidentified markers including KISS1, validated with in situ hybridization. LMD transcriptomics and snRNAseq revealed strong correlation of gene expression within corresponding kidney regions. Relevant enriched interstitial pathways included G-protein coupled receptor. binding and collagen biosynthesis. The diabetic interstitium was enriched for extracellular matrix organization and small-molecule catabolism. Cell type markers with unchanged expression (NOTCH3, EGFR, and HEG1) and those down-regulated in diabetic nephropathy (MYH11, LUM, and CCDC3) were identified. LMD transcriptomics complements snRNAseq; together, they facilitate mapping of interstitial marker genes to aid interpretation of pathophysiology in precision medicine studies.

SUBMITTER: Barwinska D 

PROVIDER: S-EPMC7875540 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications


The gene expression signature of the human kidney interstitium is incompletely understood. The cortical interstitium (excluding tubules, glomeruli, and vessels) in reference nephrectomies (<i>N</i> = 9) and diabetic kidney biopsy specimens (<i>N</i> = 6) was laser microdissected (LMD) and sequenced. Samples underwent RNA sequencing. Gene signatures were deconvolved using single nuclear RNA sequencing (snRNAseq) data derived from overlapping specimens. Interstitial LMD transcriptomics uncovered p  ...[more]

Similar Datasets

| S-EPMC3094052 | biostudies-literature
| S-EPMC7438011 | biostudies-literature
| S-EPMC8849328 | biostudies-literature
2024-01-01 | GSE240640 | GEO
| S-EPMC3431649 | biostudies-literature
| S-EPMC5869738 | biostudies-literature
2024-12-17 | PXD045874 | Pride
| S-EPMC9732514 | biostudies-literature
2020-08-07 | GSE155794 | GEO
| S-EPMC4089448 | biostudies-literature