Single-cell RNA-seq analysis hearts in patients with fetal tetralogy of Fallot.

Abstract

Introduction: To explore the cytological characteristics of tetralogy of Fallot (TOF), we collected samples and studied the differences in cytological classification between normal fetal hearts and fetuses with TOF, and then we searched for possible differential genes of disease markers through single-cell sequencing analysis.

Methods: In this study, we analyzed the right ventricle of a TOF and a healthy human fetal heart sample by single-cell sequencing. Utilizing Cellranger to perform data quality control filtering, comparison, quantification, and identification of recovered cells on the raw data, ultimately obtaining gene expression matrices for each cell. Subsequently, Seurat was used for further cell filtration, standardization, cell subgroup classification, differential expression gene analysis of each subgroup, and Marker gene screening.

Results: Bioinformatic analysis identified 9979 and 15224 cells derived from the healthy and disease samples, respectively, with an average read depth of 25000/cell. The cardiomyocyte cell populations derived from the abnormal samples identified by the first-level graph-based analysis were separated into six distinct cell clusters.

Conclusions: Our study reveals some information on TOF in a fetus, which can provide a new reference for early detection and treatment of TOF by comparing it with normal heart cells.