Single-Cell RNA Sequencing of the Adult Mouse Kidney: From Molecular Cataloging of Cell Types to Disease-Associated Predictions

Lindström, Nils O.; Brandine, Guilherme de Sena; Ransick, Andrew; McMahon, Andrew P.

doi:10.1053/j.ajkd.2018.07.002

Cited by 10 publications

(9 citation statements)

References 22 publications

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“…Many of these cell populations are distinguished by specific differentially expressed genes (DEGs), which include transporters, secreted proteins, and transcription factors. Single-cell approaches have also identified insights into disease and identified novel cell populations in the murine kidney (10,11). Such methods, however, rely on protease digestion of tissues, resulting in underrepresentation of specific cell An incomplete understanding of the biology of the human kidney, including the relative abundances of and interactions between intrinsic and immune cells, has long constrained the development of therapies for kidney disease.…”

Section: Introductionmentioning

confidence: 99%

Development of a 2-dimensional atlas of the human kidney with imaging mass cytometry

Singh¹,

Avigan²,

Kliegel³

et al. 2019

JCI Insight

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Section: Introductionmentioning

confidence: 99%

Development of a 2-dimensional atlas of the human kidney with imaging mass cytometry

Singh¹,

Avigan²,

Kliegel³

et al. 2019

JCI Insight

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“…In nephrology, few studies have addressed reference genes for qPCR normalization (13), exposing a lack of information regarding which gene must be used for gene expression studies for kidney samples and cell lines. Kidney itself is an organ specifically characterized by numerous cell types, justifying the need for reference genes regarding each different cell line (35,36).…”

Section: Discussionmentioning

confidence: 99%

“…CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted January 19, 2021. ; https://doi.org/10.1101/2021.01.19.427251 doi: bioRxiv preprint by numerous cell types, justifying the need for reference genes regarding each different cell line (35,36).…”

Section: Discussionmentioning

confidence: 99%

Reference genes for mesangial cell and podocyte qPCR gene expression studies under high-glucose and renin-angiotensin-system blocker conditions

Hosni

Anauate

Boim

2021

Preprint

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BackgroundReal-time PCR remains currently the gold standard method for gene expression studies. Identification of the best reference gene is a key point in performing high quality qPCR, providing strong support for results, as well as performing as a source of bias when inappropriately chosen. Mesangial cells and podocytes, as essential cell lines to study diabetic kidney disease (DKD) physiopathology, demand accurate analysis of the reference genes used so far to enhance validity of gene expression studies, especially regarding high glucose (HG) and DKD treatments, with angiotensin II receptor blockers (e.g. Losartan) being the most commonly used. This study aimed to evaluate the suitability and define the most stable reference gene for mesangial cells and podocytes studies of an in vitro DKD model of disease and its treatment.MethodsFive software packages (RefFinder, NormFinder, GeNorm, Bestkeeper, and DataAssist) and the comparative ΔCt method were selected to analyze six different candidate genes: HPRT, ACTB, PGAM-1, GAPDH, PPIA, and B2M. RNA was extracted and cDNA was synthesized from immortalized mouse mesangial cells and podocytes cultured in 4 groups: control (n=5; 5mM glucose), mannitol (n=5; 30mM, as osmotic control), HG (n=5; 30mM glucose), and HG + losartan (n=5; 30mM glucose and 10-4 mM of losartan). Real-time PCR was performed according to MIQE guidelines.ResultsWe identified that the use of 2 genes is the best combination for qPCR normalization for both mesangial cell and podocytes. For mesangial cells, the combination of HPRT and ACTB presented higher stability values. For podocytes, HPRT and GAPDH showed the best results.ConclusionThis analysis provides support for the use of HPRT and ACTB as reference genes in mouse mesangial cell studies of gene expression via real-time PCR technique, while for podocytes, HPRT and GAPDH should be chosen.

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“…We designed HyPR-seq probes to distinguish 11 cell populations using 25 canonical marker genes. Some of these marker genes were lowly expressed in their corresponding cell types (<2 TPM) and are not robustly detected in existing scRNA-seq datasets ( Table S7) [33][34][35][36][37] . Accordingly, we included up to 20 probe sets per gene to enable sensitive detection (see Methods).…”

Section: Measuring Cell Type Frequencies and Low-abundance Genes In Tmentioning

confidence: 99%

HyPR-seq: Single-cell quantification of chosen RNAs via hybridization and sequencing of DNA probes

Marshall

Doughty

Subramanian

et al. 2020

Preprint

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Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of up to 100 chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome scRNA-seq, making HyPR-seq a powerful method for targeted RNA profiling in single cells.

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Single-Cell RNA Sequencing of the Adult Mouse Kidney: From Molecular Cataloging of Cell Types to Disease-Associated Predictions

Cited by 10 publications

References 22 publications

Development of a 2-dimensional atlas of the human kidney with imaging mass cytometry

Development of a 2-dimensional atlas of the human kidney with imaging mass cytometry

Reference genes for mesangial cell and podocyte qPCR gene expression studies under high-glucose and renin-angiotensin-system blocker conditions

HyPR-seq: Single-cell quantification of chosen RNAs via hybridization and sequencing of DNA probes

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