Short Tandem Repeat Profiling via Next Generation Sequencing for Cell Line Authentication

Abstract

Cell lines are indispensable models for modern biomedical research. In the era of CRISPR gene editing, they serve as versatile tools for preclinical studies, allowing patient specific mutations to be modeled or corrected and the resulting phenotypic outcomes studied. A large part of their usefulness derives from the ability of a cell line to proliferate over multiple passages (often indefinitely) allowing multiple experiments to be performed. However, over time, the cell line identity and purity can be compromised by human errors. Both cross contamination from other cell lines and even complete misidentification are possible. Routine cell line authentication is a necessary preventive measure and has become a requirement for many funding applications and publications. Short tandem repeat (STR) profiling is the most common method for cell line authentication and is usually carried out using standard polymerase chain reaction (PCR)-capillary electrophoresis (CE) analysis (STR-CE). Here we evaluated next generation sequencing (NGS)-based STR profiling of human and mouse cell lines at 18 and 15 loci, respectively, in a high-throughput format. Using the program STRight written in Python, we demonstrate that NGS-based analysis (STR-NGS) is superior to standard STR-CE in terms of the ability to report the sequence context of repeat motifs, sensitivity, and flexible multiplexing capability. STR-NGS is a valuable alternative for cell line authentication.