Determining the Relative Fitness Score of Mutant Viruses in a Population Using Illumina Paired-end Sequencing and Regression Analysis

Abstract

Recent advances in DNA sequencing capacity to accurately quantify the copy number of individual variants in a large and diverse population allows in parallel determination of the phenotypic effects caused by each genetic modification. This systematic profiling approach is a combination of forward and reverse genetics, which we refer to as quantitative high-resolution genetics (qHRG). This protocol describes how to determine the relative fitness score of each variant compared to wild type (WT) virus based on its frequency determined by Illumina sequencing. Random mutagenesis techniques will be used to introduce randomization at each codon position of the targeted region, thereby generating a comprehensive input mutant library with substitutions at each position of interest (Qi et al., 2014; Wu et al., 2014a; Wu et al., 2014b). After selection, each selected library will be sequenced by Illumina paired-end sequencing and the frequency of each mutation will be determined. Based on the change in frequency, the relative fitness score of each mutant can be calculated with regression analysis.