Characterization of Viral Populations by Using Circular Sequencing

Abstract

With the enormous sizes viral populations reach, many variants are at too low a frequency to be detected by conventional next-generation sequencing (NGS) methods. Circular sequencing (CirSeq) is a method by which the error rate of next-generation sequencing is decreased so that even low-frequency viral variants can be accurately detected. The ability to visualize almost the entire genetic makeup of a viral swarm has implications for epidemiology, viral evolution, and vaccine design. Here we discuss experimental planning, analysis, and recent insights using CirSeq.

FIG 1

Illustration of variant fitness categories. Variants detected using CirSeq will be assigned a fitness based on the trajectory of their frequency during the course of the experiment. Here, a hypothetical C→A mutation can fall into one of four categories. The Δ symbol represents the inherent mutation rate for this type of variant (i.e., the overall mutation rate for C→A). Neutral mutations rise but only due to newly generated variants due to Δ. Detrimental variant frequencies may fall within the population, or could even rise, but at a level less than Δ. Beneficial mutations will increase in frequency within a population at a rate greater than Δ. Lethal mutations will be present in a population only at or below Δ.