Short tandem repeat profiling via next-generation sequencing for cell line authentication

Abstract

ABSTRACT Cell lines are indispensable models for modern biomedical research. 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, cell line identity and purity can be compromised by human errors. Cross-contamination from other cell lines and complete misidentification are both 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-capillary electrophoresis 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 Python program STRight, 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 thus a valuable alternative for cell line authentication.