Evaluation of Sample Pooling for Gene Sequencing of SARS-CoV-2: A Simulation Study

Abstract COVID-19 continues to pose a significant public health threat, requiring ongoing epidemiological and genomic surveillance. Next-generation sequencing (NGS) is commonly utilized for monitoring viral evolution at high-cost. Real-time reverse transcription polymerase chain reaction(RT-qPCR) pooling test have been have been demonstrated to increase molecular testing throughput effectively during the pandemic, while pooling sequencing shows promise as a cost-effective tool for monitoring virus variants. A simulation study was conducted to evaluate the efficacy of sample pooling for viral gene sequencing of SARS-CoV-2. In this study, 72 original raw data of gene sequencing results with different lineages were collected and combined to create simulated samples based on five pooling strategies. A bioinformatics tool based on Freyja was utilized to analyze the variant composition of these 70 simulated pooled samples. The genetic composition of the pooled samples mostly recovered the variant compositions of the original samples, with discrepancies between the top X results (where X is the number of original samples included in the mixture)and the complete results (P < 0.05).Variations were observed in the calculation method for the top X results (P < 0.05) but not in the complete calculation approach (P > 0.05) across the five pooling strategy groups. Some original samples of suboptimal quality were not accurately identified. The present results indicated that sample pooling coupled with streamlined genotyping offers a promising approach for cost-effective gene sequencing of SARS-CoV-2, which will aid in genomic surveillance efforts against COVID-19.