TY - JOUR T1 - Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences. JF - Gigascience Y1 - 2021 A1 - Ortuno, Francisco M A1 - Loucera, Carlos A1 - Casimiro-Soriguer, Carlos S A1 - Lepe, Jose A A1 - Camacho Martinez, Pedro A1 - Merino Diaz, Laura A1 - de Salazar, Adolfo A1 - Chueca, Natalia A1 - GarcĂ­a, Federico A1 - Perez-Florido, Javier A1 - Dopazo, Joaquin KW - Genome, Viral KW - Phylogeny KW - SARS-CoV-2 KW - Whole Genome Sequencing AB -

BACKGROUND: The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data.

RESULTS: We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239,301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (<20%).

CONCLUSIONS: Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole-genome sequencing.

VL - 10 IS - 12 U1 - https://www.ncbi.nlm.nih.gov/pubmed/34865008?dopt=Abstract ER -