Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Hong, Rui; Koga, Yusuke; Bandyadka, Shruthi; Leshchyk, Anastasia; Wang, Zhe; Alabdullatif, Salam; Wang, Yichen; Akavoor, Vidya; Cao, Xinyun; Sarfraz, Irzam; Jansen, Frederick; Johnson, William; Yajima, Masanao; Campbell, Joshua D.

doi:10.1101/2020.11.16.385328

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…2A-D; Fig. S2A-K; Table S1) (Hong et al, 2022). Cultured cells maintain very high viability after minimal or no dissociation, leading to high data quality.…”

Section: Resultsmentioning

confidence: 99%

A contamination focused approach for optimizing the single-cell RNA-seq experiment

Arceneaux

Chen

Simmons

et al. 2022

Preprint

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Achieving high data quality in single-cell RNA-seq (scRNA seq) experiments has always been a significant challenge stemming from minute signal that can be detected in individual cells. Droplet-based scRNA-seq additionally suffers from ambient contamination, comprising nucleic acid materials released by dead cells into the loading buffer and co-encapsulated with real cells, which further washes out real biological signals. Here, we developed quantitative, ambient contamination-based metrics and an associated software package that can both evaluate current datasets and guide new experimental optimizations. We performed a series of experimental optimizations using the inDrops platform to address the mechanical and microfluidic cell encapsulation aspect of an scRNA-seq experiment, with a focus on minimizing ambient contamination. We report improvements that can be achieved via cell fixation, microfluidic loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide insights into previously obscured factors that can affect scRNA-seq data quality and suggest mitigation strategies that can guide future experiments.

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“…2A-D; Fig. S2A-K; Table S1) (Hong et al, 2022). Cultured cells maintain very high viability after minimal or no dissociation, leading to high data quality.…”

Section: Resultsmentioning

confidence: 99%

A contamination focused approach for optimizing the single-cell RNA-seq experiment

Arceneaux

Chen

Simmons

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Preprocessed count matrices of the nasal and bronchial samples were pre-processed using the Scruff package 27 and analyzed using the Seurat 3.0 28 with standard settings. Quality Control of the nasal and bronchial count matrices was performed using SCTK-QC pipeline 29,30,31 . Uniform Manifold Approximation and Projection (UMAP) was used for dimension reduction and visualizing relationships amongst cells.…”

Section: Methodsmentioning

confidence: 99%

Smoking Modulates Different Secretory Subpopulations Expressing SARS-CoV-2 Entry Genes in the Nasal and Bronchial Airways

Shi

Husted

et al. 2021

Preprint

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Background: SARS-CoV-2 infection and disease severity are influenced by viral entry (VE) gene expression patterns in airway epithelium. The similarities and differences of VE gene expression (ACE2, TMPRSS2, and CTSL) across nasal and bronchial compartments has not been fully characterized using matched samples from large cohorts. Results: Gene expression data from 793 nasal and 1,673 bronchial brushes obtained from individuals participating in lung cancer screening or diagnostic workup revealed that smoking was the only clinical factor significantly and reproducibly associated with VE gene expression. ACE2 and TMPRSS2 expression were higher in smokers in the bronchus but not in the nose. scRNA-seq of nasal brushings indicated that ACE2 co-expressed genes were highly expressed in club and C15orf48+ secretory cells while TMPRSS2 co-expressed genes were highly expressed in keratinizing epithelial cells. In contrast, these ACE2 and TMPRSS2 modules were highly expressed in goblet cells in scRNA-seq from bronchial brushings. Cell-type deconvolution of the RNA-seq confirmed that smoking increased the abundance of several secretory cell populations in the bronchus, but only goblet cells in the nose. Conclusions: The association of ACE2 and TMPRSS2 with smoking in the bronchus is due to their high expression in goblet cells which increase in abundance in current smoker airways. In contrast, in the nose these genes are not predominantly expressed in cell populations modulated by smoking. Smoking-induced VE gene expression changes in the nose likely has minimal impact on SARS-CoV-2 infection, but in the bronchus, smoking may lead to higher viral loads and more severe disease.

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Multi-modal profiling of human fetal liver hematopoietic stem cells reveals the molecular signature of engraftment

et al. 2022

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The human hematopoietic stem cell harbors remarkable regenerative potential that can be harnessed therapeutically. During early development, hematopoietic stem cells in the fetal liver undergo active expansion while simultaneously retaining robust engraftment capacity, yet the underlying molecular program responsible for their efficient engraftment remains unclear. Here, we profile 26,407 fetal liver cells at both the transcriptional and protein level including ~7,000 highly enriched and functional fetal liver hematopoietic stem cells to establish a detailed molecular signature of engraftment potential. Integration of transcript and linked cell surface marker expression reveals a generalizable signature defining functional fetal liver hematopoietic stem cells and allows for the stratification of enrichment strategies with high translational potential. More precisely, our integrated analysis identifies CD201 (endothelial protein C receptor (EPCR), encoded by PROCR) as a marker that can specifically enrich for engraftment potential. This comprehensive, multi-modal profiling of engraftment capacity connects a critical biological function at a key developmental timepoint with its underlying molecular drivers. As such, it serves as a useful resource for the field and forms the basis for further biological exploration of strategies to retain the engraftment potential of hematopoietic stem cells ex vivo or induce this potential during in vitro hematopoietic stem cell generation.

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Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Cited by 4 publications

References 32 publications

A contamination focused approach for optimizing the single-cell RNA-seq experiment

A contamination focused approach for optimizing the single-cell RNA-seq experiment

Smoking Modulates Different Secretory Subpopulations Expressing SARS-CoV-2 Entry Genes in the Nasal and Bronchial Airways

Multi-modal profiling of human fetal liver hematopoietic stem cells reveals the molecular signature of engraftment

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