Accurate profiling of single-cell alternative transcript start sites by correcting RNA degradation

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Alternative transcription start site (TSS) usage is a key regulatory mechanism in biological processes and disease.
• Single-cell RNA sequencing (scRNA-seq) allows for TSS analysis at the individual cell level.
• RNA degradation in scRNA-seq data complicates accurate TSS quantification.

Purpose of the Study:

• To develop a computational tool, scATS, to accurately quantify TSSs from scRNA-seq data.
• To address and correct for RNA degradation artifacts in TSS quantification.
• To investigate the role of TSS regulation in hematopoiesis, disease, and lung cancer.

Main Methods:

• Developed scATS (single-cell alternative transcription start site) tool for TSS quantification.
• Implemented methods to estimate and correct for RNA degradation at isoform and sample levels.
• Utilized a machine-learning pipeline (lung cancer relevance score, LRS) to identify cancer-associated TSSs.

Main Results:

• scATS accurately quantifies TSSs by correcting for RNA degradation.
• Demonstrated dynamic and context-dependent TSS regulation in hematopoiesis and disease.
• Identified specific TSS isoforms of CCR6, CCR2, and RTKN2 that promote lung cancer cell proliferation and migration.

Conclusions:

• scATS provides a robust solution for accurate TSS quantification in scRNA-seq data, mitigating RNA degradation challenges.
• TSS isoform analysis offers finer resolution for cell clustering and biological insights.
• TSS-mediated gene regulation plays a significant role in tumorogenesis, with implications for cancer therapy.