The good, the bad, and the stable: Reference genes for preclinical biodistribution studies

Digital PCR (dPCR) enables absolute, precise nucleic acid quantification without the need for standard curves. Still, technical variability across the sample life cycle remains a challenge in complex multi-organ preclinical studies. This study evaluated the necessity of internal reference genes (i.e., housekeeping genes; HKGs) for normalizing reverse transcription (RT)-dPCR data from recombinant adeno-associated virus (rAAV) studies in mice and non-human primates (NHPs). HKGs were ranked using statistical analysis and further evaluated with the BestKeeper and geNorm algorithms. In mice, Eef2, Eif3, and Rpl27 were identified as the most stable HKGs. Normalization to a single HKG (Rpl27) consistently and markedly reduced transgene-expression variability across tissues. In NHPs, ARL1 and SAR1 demonstrated the highest stability. Importantly, multiplexing HKGs allowed to differentiate technical from biological variation, thereby mitigating common assay pitfalls. Collectively, these findings underscore that normalization is essential for reliable inter- and intra-group comparability in RT-dPCR. We strongly recommend multiplexing at least two medium-expression, validated HKGs to derive a robust normalization factor, thereby significantly improving accuracy in complex preclinical settings.