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Advantages of single nucleus over single cell RNA-seq in adult kidney

ABSTRACT: Advantages of single nucleus over single cell RNA-seq in adult kidney

PROVIDER: PRJNA489475 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7789670_1.fastq.gz	Fastqsanger.gz
	SRR7789670_2.fastq.gz	Fastqsanger.gz
	SRR7789671_1.fastq.gz	Fastqsanger.gz
	SRR7789671_2.fastq.gz	Fastqsanger.gz
	SRR7789672_1.fastq.gz	Fastqsanger.gz

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Advantages of single nucleus over single cell RNA-seq in adult kidney

Project description:A key limitation in single cell genomics is generating a high-quality single cell suspension that contains rare or difficult to dissociate cell types and is free of RNA degradation or transcriptional stress responses. Samples with unpredictable availability or that must be collected at several timepoints present additional challenges. Using adult mouse kidney, we compared single-cell RNA sequencing (scRNA-seq) data generated using DropSeq with snRNA-seq data generated from nuclei using sNuc-DropSeq, DroNc-seq and 10X Chromium. We validated snRNA-seq on fibrotic kidney from day 14 unilateral ureteral obstruction (UUO).

2018-10-13 | GSE119531 | GEO

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Project description:Single nucleus inDrops to profile adult human kidney

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Single nucleus inDrops to profile adult human kidney

Project description:Single nucleus inDrops to profile adult human kidney

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Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis.

Project description:BackgroundA challenge for single-cell genomic studies in kidney and other solid tissues is generating a high-quality single-cell suspension that contains rare or difficult-to-dissociate cell types and is free of both RNA degradation and artifactual transcriptional stress responses.MethodsWe compared single-cell RNA sequencing (scRNA-seq) using the DropSeq platform with single-nucleus RNA sequencing (snRNA-seq) using sNuc-DropSeq, DroNc-seq, and 10X Chromium platforms on adult mouse kidney. We validated snRNA-seq on fibrotic kidney from mice 14 days after unilateral ureteral obstruction (UUO) surgery.ResultsA total of 11,391 transcriptomes were generated in the comparison phase. We identified ten clusters in the scRNA-seq dataset, but glomerular cell types were absent, and one cluster consisted primarily of artifactual dissociation-induced stress response genes. By contrast, snRNA-seq from all three platforms captured a diversity of kidney cell types that were not represented in the scRNA-seq dataset, including glomerular podocytes, mesangial cells, and endothelial cells. No stress response genes were detected. Our snRNA-seq protocol yielded 20-fold more podocytes compared with published scRNA-seq datasets (2.4% versus 0.12%, respectively). Unexpectedly, single-cell and single-nucleus platforms had equivalent gene detection sensitivity. For validation, analysis of frozen day 14 UUO kidney revealed rare juxtaglomerular cells, novel activated proximal tubule and fibroblast cell states, and previously unidentified tubulointerstitial signaling pathways.ConclusionssnRNA-seq achieves comparable gene detection to scRNA-seq in adult kidney, and it also has substantial advantages, including reduced dissociation bias, compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and successful performance on inflamed fibrotic kidney.

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Comparative analysis of kidney organoid and adult human kidney single cell and single nucleus transcriptomes

Project description:Comparative analysis of kidney organoid and adult human kidney single cell and single nucleus transcriptomes

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Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

Project description:Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

2018-12-06 | GSE123454 | GEO

Single-nucleus RNA-Seq

Project description:Single-nucleus RNA-Seq

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Single nucleus RNA-seq, ATAC-seq, and multiomic sequencing of adult human kidney

Project description:In this study, we generated a single nucleus multiomic (snRNA-seq and snATAC-seq) dataset of adult human kidney. We developed a bioinformatic tool to analyze this dataset by identifying key cis-regulatory elements and transcription factors associated with specific cell types and states. We applied this tool to identify transcription factors implicated in proximal tubule cell injury and failed repair states. We demonstrate this tool can be applied to single cell multiomic datasets to derive insight into cell type- and state-specific gene regulatory networks.

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Project description:We analyzed single cell transcriptomes over 80,000 cells isolated from 65 organoids differentiated from iPSCs and ESCs using two different protocols. We find that both protocols generate kidney organoids that contain a diverse range of kidney cells at differing ratios as well as non-renal cell types. We reconstructed lineage relationships during organoid differentiation through pseudotemporal ordering, and identified transcription factor networks associated with fate decisions. When comparing to adult human kidney, we reveal immaturity of all kidney organoid cell types. These results define impressive kidney organoid cell diversity, identify incomplete differentiation as a major roadblock for current directed differentiation protocols and provide a human adult kidney snRNA-seq dataset against which to benchmark future progress.

2018-10-13 | GSE118184 | GEO

Single-nucleus RNA-seq on undifferentiated human KD3 myoblasts and differentiated myotubes and mononucleated cells.

Project description:We report the application of single-nucleus-based sequencing technology for high-throughput profiling of transcriptome in immortazalized human myoblast KD3. By obtaining over sixty billion bases of sequence from mRNA, we generated comprehensive transcriptome profiles from KD3 undifferentiated myoblast and differentiated multi-nucleated myotube and mono-nucleated cells. We find that the data from single-nucleus RNA-seq is consistent with the transcriptome from single-cell RNA-seq. The pri-mRNA expression characterized by single-nucleus RNA-seq can reflect the actual miRNA level in the whole cell. Examination of transcriptome in 1 cell type in 3 differential stages.

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