Quality control in scRNA-Seq can discriminate pacemaker cells: the mtRNA bias.

Abstract:

Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to "low quality" potentially leading to data misinterpretation. Common standard quality control parameters involve the number of detected genes, transcripts per cell, and the fraction of transcripts from mitochondrial genes. While cutoffs for transcripts and genes per cell are usually user-defined for each experiment or individually calculated, a fixed threshold of 5% mitochondrial transcripts is standard and often set as default in scRNA-seq software. However, this parameter is highly dependent on the tissue type. In the heart, mitochondrial transcripts comprise almost 30% of total mRNA due to high energy demands. Here, we demonstrate that a 5%-threshold not only causes an unacceptable exclusion of cardiomyocytes but also introduces a bias that particularly discriminates pacemaker cells. This effect is apparent for our in vitro generated induced-sinoatrial-bodies (iSABs; highly enriched physiologically functional pacemaker cells), and also evident in a public data set of cells isolated from embryonal murine sinoatrial node tissue (Goodyer William et al. in Circ Res 125:379-397, 2019). Taken together, we recommend omitting this filtering parameter for scRNA-seq in cardiovascular applications whenever possible.

SEEK ID: https://fairdomhub.org/publications/621

PubMed ID: 34427691

Projects: iRhythmics

Publication type: Manual

Journal: Cell Mol Life Sci

Citation: Cell Mol Life Sci. 2021 Aug 24. pii: 10.1007/s00018-021-03916-5. doi: 10.1007/s00018-021-03916-5.

Date Published: 24th Aug 2021

Registered Mode: by PubMed ID

Authors: A. M. Galow, S. Kussauer, M. Wolfien, R. M. Brunner, T. Goldammer, R. David, A. Hoeflich

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Created: 3rd Sep 2021 at 09:53

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