Abstract
Understanding evolutionary dynamics within microbial populations requires the ability to accurately follow allele frequencies through time. Here we present a rapid, cost-effective method (FREQ-Seq) that leverages Illumina next-generation sequencing for localized, quantitative allele frequency detection. Analogous to RNA-Seq, FREQ-Seq relies upon counts from the >105 reads generated per locus per time-point to determine allele frequencies. Loci of interest are directly amplified from a mixed population via two rounds of PCR using inexpensive, user-designed oligonucleotides and a bar-coded bridging primer system that can be regenerated in-house. The resulting bar-coded PCR products contain the adapters needed for Illumina sequencing, eliminating further library preparation. We demonstrate the utility of FREQ-Seq by determining the order and dynamics of beneficial alleles that arose as a microbial population, founded with an engineered strain of Methylobacterium, evolved to grow on methanol. Quantifying allele frequencies with minimal bias down to 1% abundance allowed effective analysis of SNPs, small in-dels and insertions of transposable elements. Our data reveal large-scale clonal interference during the early stages of adaptation and illustrate the utility of FREQ-Seq as a cost-effective tool for tracking allele frequencies in populations.
Highlights
The textbook definition of evolution is the change in frequency of alleles in a population over time [1]
A key aspect of FREQ-Seq is its capacity for multiplexing a large number of samples
For academic laboratories engaged in experimental evolution or environmental microbiology, FREQ-Seq provides a low-cost, highly extendable method for investigating genetic variation over large temporal and spatial scales
Summary
The textbook definition of evolution is the change in frequency of alleles in a population over time [1]. Identifying evolved alleles by applying next-generation sequencing technologies either to isolates [3,4,5] or mixed-population samples [6] has revolutionized the discovery of polymorphisms that occur during adaptation This information does not often yield quantitative allele frequency information. Several methods exist that allow accurate determination of allelic frequencies directly from population samples, but these either require substantial material and personnel cost and/or have limited sensitivity and accuracy [10,11,12] For these reasons, a reliable, high-throughput pipeline for allele frequency detection in natural and laboratory populations will allow a more extensive understanding of evolutionary processes
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