Your browser doesn't support javascript.
loading
Olivar: automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens.
Wang, Michael X; Lou, Esther G; Sapoval, Nicolae; Kim, Eddie; Kalvapalle, Prashant; Kille, Bryce; Elworth, R A Leo; Liu, Yunxi; Fu, Yilei; Stadler, Lauren B; Treangen, Todd J.
Affiliation
  • Wang MX; Department of Bioengineering, Rice University, Houston, 77030, USA.
  • Lou EG; Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA.
  • Sapoval N; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Kim E; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Kalvapalle P; Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA.
  • Kille B; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Elworth RAL; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Liu Y; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Fu Y; Department of Computer Science, Rice University, Houston, 77005, USA.
  • Stadler LB; Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA.
  • Treangen TJ; Department of Computer Science, Rice University, Houston, 77005, USA.
bioRxiv ; 2023 Sep 30.
Article de En | MEDLINE | ID: mdl-36824759
ABSTRACT
Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 2 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluated Olivar on real wastewater samples and found that Olivar had up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available as a web application at https//olivar.rice.edu. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https//github.com/treangenlab/Olivar.

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Guideline / Prognostic_studies Langue: En Journal: BioRxiv Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Guideline / Prognostic_studies Langue: En Journal: BioRxiv Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique