The Transcriptome of SH-SY5Y at Single-Cell Resolution: A CITE-Seq Data Analysis Workflow.

Area of Science:

• Single-cell biology
• Molecular biology
• Genomics

Background:

• Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) integrates immunophenotyping with single-cell RNA sequencing (scRNA-seq).
• CITE-seq utilizes nucleotide barcodes on antibodies (cell hashing) for simultaneous sequencing of antibody tags and cellular mRNA.
• This method reduces scRNA-seq costs by enabling multiplexing of barcoded samples in a single run.

Purpose of the Study:

• To illustrate an ideal CITE-seq data analysis workflow.
• To characterize the transcriptome of the SH-SY5Y neuroblastoma cell line.
• To identify stable genes for potential use as reference housekeeping genes.

Main Methods:

• Application of CITE-seq to analyze the transcriptome of 2879 single cells from the SH-SY5Y cell line.
• Standard scRNA-seq data handling, including quality checks and cell filtering.
• Exploratory analyses using R packages (Seurat, Monocle, slalom) to investigate cell heterogeneity and identify stable genes.

Main Results:

• Characterization of the transcriptome from 2879 single cells, with an average of 1600 genes measured per cell.
• Identification of potential reference housekeeping genes within the SH-SY5Y cell line transcriptome.
• Demonstration of cell heterogeneity analysis using popular R packages.

Conclusions:

• The presented CITE-seq workflow provides a robust method for multimodal single-cell analysis.
• The study offers valuable insights into the transcriptome of SH-SY5Y cells and identifies potential housekeeping genes.
• Freely shared dataset and analysis code promote reproducibility and future research in single-cell genomics.