High-frequency mutation in viral RNA is a primary evolutionary mechanism driving viral adaptation. Such mutation is necessary for adaptation to biological challenges such as survival in both vector and main host and between tissues, as well as for evasion of immune responses and attachment to cell-specific receptors. CirSeq is an RNA circular replication-based technique that can significantly reduce error rate, improve next generation sequencing sensitivity, and reveal key mutations for viral evolutionary adaptations and subpopulations.
CirSeq enables prediction of mutation frequency and mutation fitness in areas that are vital for viral replication and adaptation. Mutation types can be mapped on the protein structure along with information on whether each mutation is beneficial, detrimental, or lethal. This fitness information can be obtained through the CirSeq protocol with computational tools in the T-BioInfo platform.
Fitness prediction can be used to characterize populations, and this information can be applied to epidemiological aspects of the disease. Predictive models of population-defining mutations can be highly accurate. In the case of polio, such models can account for roughly 50% of the historical mutation data associated with this virus. Precision CirSeq data coupled with advanced mathematical modeling tools can improve the quality of predictive pandemic analytics.
Greater sequencing depth provides new insight into the genetic composition of viruses
A high level of resolution is needed to identify mutations leading to differentiated subpopulations of a virus that may be biologically and clinically important in terms of virus survival and adaptation. Next generation sequencing methods by themselves are not sufficient to provide this level of resolution.
CirSeq is an improved sequencing method that allows for the identification of individual viral strains with highly accurate and precise sequence data within a population.