A benchmark study of deconvolution methods and target enrichment kits to estimate the proportions of COVID 19 lineages in wastewater samples sequenced with ONT

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VACUS, Benjamin | Délépine, Marc | Gerber, Zuzana | Sandron, Florian | Daviaud, Christian | Delafoy, Damien | Meyer, Vincent | Le Floch, Edith | Olaso, Robert | Deleuze, Jean-François | Gloaguen, Arnaud

Edité par CCSD -

International audience. Wastewater surveillance is a relevant tool for monitoring the evolution of SARS-CoV-2. After target enrichment for SARS-CoV-2 by Polymerase Chain Reaction (PCR) amplification followed by next-generation sequencing, previous studies were able to identify and quantify COVID-19 lineages present in wastewater samples.Our goal is to investigate if the generation of longer reads allows to better discriminate among lineages present in such complex mixtures.Our contribution is twofold. First, we generated three distinct data-sets on the same set of synthetic samples including positive/negative controls (single lineage/water only) and several known mixtures of lineages (amongst Alpha, Delta, Omicron, …). Data-sets differ in the primer design used for target enrichment, generating amplicons of either 400, 1200 or 2400 base pairs long.Second, three deconvolution methods, Freyja (Karthikeyan & al. 2021), LCS (Valieris & al. 2021) and VirPool (Gafurov & al. 2022) were compared for the estimation of the proportion of COVID-19 lineages. Only VirPool can take advantage of the co-occurrence of Single Nucleotide Polymorphisms (SNPs) on a single read, an event better captured by longer reads. This benchmark was built with Snakemake.Relying on this benchmark, new methods able to exploit the co-occurrence of SNPs will be developed and extended to other viruses.

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