Clinically pertinent electrocardiogram (ECG) data from model systems, such as zebrafish, are crucial for illuminating factors contributing to human cardiac electrophysiology abnormalities and disease. Current zebrafish ECG collection strategies have not adequately addressed the consistent acquisition of high-quality traces or sources of phenotypic variation that could obscure data interpretation. Thus, we developed a novel platform to ensure high-quality recording of in vivo subdermal adult zebrafish ECGs and zERG (Zebrafish ECG Reading GUI), a program to acquire measurements from traces commercial software cannot examine due to erroneous peak calling. We evaluate normal ECG trait variation, revealing the intervals are highly reproducible while wave amplitude variation appears largely driven by recording artifacts, and identify sex and body size as potential confounders to PR, QRS, and QT intervals. With this framework, we characterize the effect of the class I anti-arrhythmic drug flecainide acetate on adults, provide support for the impact of a Long QT syndrome model, and establish power calculations for this and other studies. These results highlight our pipeline as a robust approach to evaluate zebrafish models of human cardiac electrophysiologic phenotypes.

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