Evaluation of sample pooling for gene sequencing of SARS-CoV-2: a simulation study
DOI:
https://doi.org/10.3855/jidc.20348Keywords:
SARS-CoV-2, sample pooling, gene sequencing, simulation studyAbstract
Introduction: Coronavirus disease 2019 (COVID-19) continues to pose a significant public health threat, requiring epidemiological and genomic surveillance. Next generation sequencing (NGS) is commonly utilized for monitoring viral evolution at a high cost. This study evaluated pooled sequencing as a cost-effective tool for monitoring virus variants.
Methodology: A simulation study was conducted to evaluate the efficacy of sample pooling for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing. In total, 72 original sets of raw data of gene sequencing with different genotypes were collected and combined to create 70 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 efficiency of recovering the correct genotypes of the original samples among different pooling strategies, result reports, and genotypes was evaluated with R software.
Results: The genetic composition of the pooled samples mostly recovered the genotype compositions of the original samples, with discrepancies between the top X results (where X is the number of original samples in the pool) and the complete results (p < 0.05). Variability in identification efficiency of genotypes were observed in the reports for the top X results (p < 0.05) across the five pooling strategies, but not in the reports of complete results (p > 0.05). Some original samples of low quality were not accurately identified.
Conclusions: Sample pooling coupled with streamlined genotyping offers a promising approach for cost-effective gene sequencing of SARS-CoV-2, which will aid in COVID-19genomic surveillance.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Dr. Heng Chen, Ms. Yue Cheng; Miss. Xun He; Ms. Yuzhen Zhou, Ms. Wenjun Xie, Ms. Danyun Shen, Miss. Zhiqun He, Miss. Ruidan Li, Miss. Weixuan Liu, Mr. Liang Wang, Mr. Xuejun Zhang

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).