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An optimized protocol for retina single-cell RNA sequencing [scRNA-Seq]

ABSTRACT: An optimized protocol for retina single-cell RNA sequencing [scRNA-Seq]

PROVIDER: PRJNA643589 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR12130647.fastq.gz	Fastqsanger.gz
	SRR12130648.fastq.gz	Fastqsanger.gz
	SRR12130649.fastq.gz	Fastqsanger.gz
	SRR12130650.fastq.gz	Fastqsanger.gz
	SRR12130651.fastq.gz	Fastqsanger.gz

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An optimized protocol for retina single-cell RNA sequencing [scRNA-Seq]

Project description:In this work, we compared different protocols to prepare single-cell suspensions used for scRNAseq and suggest an optimized dissociation protocol for mouse retina, which preserves cell morphology to a higher level leading to an overall increase of gene number per cell. We compared scRNAseq libraries generated with our optimized protocol to publicly available scRNAseq data of mouse retina. We further demonstrate a pipeline to reduce noise in scRNAseq caused by multiplets and ambient RNA.

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Project description:Single cell RNA sequencing (scRNA-seq) has advanced the assessment of cellular heterogeneity at the single-cell resolution by identifying transcriptional similarities and differences. Data resources of scRNA-seq have been largely produced and extensively studied for the mouse retina. They serve as a powerful tool to study cellular components, transcriptome relationships, and regulatory mechanisms underlying various retinal diseases and biological processes. The large volume of mouse retinal scRNA-seq data has been released in separate repositories, limiting their widespread use in mouse retina communities. In this work, we are presenting a unified single-cell atlas for adult wild-type mouse retina using our in-house generated single-cell RNA-seq data complementing public datasets. The collected data account for over 323,000 single cells. After data integration, cell clustering, and cell type annotation, we have annotated 11 major classes and over 120 retinal cell types to form a unified single-cell reference for the mouse retina. To facilitate the public use of the reference, we have deposited it on CELLxGENE, UCSC Cell Browser, and Single Cell Portal for visualization and gene expression exploration. The unified atlas is also released to annotate new mouse retinal cells using scArches utilities. This unified reference serves an easy-to-use data resource of mouse retina communities.

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An optimized protocol for retina single-cell RNA sequencing

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-10-23 | GSE153674 | GEO

An optimized protocol for retina single-cell RNA sequencing.

Project description:Purpose:Single-cell RNA sequencing (scRNA-seq) is a powerful technique used to explore gene expression at the single cell level. However, appropriate preparation of samples is essential to obtain the most information out of this transformative technology. Generating high-quality single-cell suspensions from the retina is critical to preserve the native expression profile that will ensure meaningful transcriptome data analysis. Methods:We modified the conditions for rapid and optimal dissociation of retina sample preparation. We also included additional filtering steps in data analysis for retinal scRNA-seq. Results:We report a gentle method for dissociation of the mouse retina that minimizes cell death and preserves cell morphology. This protocol also results in detection of higher transcriptional complexity. In addition, the modified computational pipeline leads to better-quality single-cell RNA-sequencing data in retina samples. We also demonstrate the advantages and limitations of using fresh versus frozen retinas to prepare cell or nuclei suspensions for scRNA-seq. Conclusions:We provide a simple yet robust and reproducible protocol for retinal scRNA-seq analysis, especially for comparative studies.

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