Speaker
Description
The Human immunodeficiency virus type I (HIV-1) is characterised by its exceptionally high genetic variability, a trait that challenges the effectiveness of therapeutic interventions and vaccine development. Therefore, a better understanding of the evolutionary dynamics of the virus remains crucial. While existing research has predominantly focused on substitutions, the exploration of insertion or deletion (indel) events has been notably limited. Indels, with the capacity to extend across multiple characters, can introduce substantial shifts in the virus's fitness landscape, influencing its adaptability and ability to navigate the host environment.
To bridge that gap, and given that phylogenetic inference methods often represent indels simplistically as gaps or missing data, we propose a novel method, long indel-aware parsimony, that treats insertions and deletions as distinct events. The multiple sequence alignment and ancestral sequence reconstruction methods perform well on densely sampled data sets and are inherently fast, making them the perfect choice for datasets of epidemiological size.
We thoroughly investigated the HIV-1 genome's indel patterns using our methods for indel pattern analysis. These methods were integrated into an adaptable pipeline for indel metric visualisation. Estimated metrics include indel rates, distribution of indel lengths, and indel hotspots within the genome and across branches. Furthermore, we explored the effect of indel events on glycosylation sites and epitopes.
This pipeline is an essential resource for researchers and clinicians, allowing them to examine indel patterns between and within-patient data highlighting potential areas of interest for further investigation. The pipeline is user-friendly and can be accessed via a command-line interface, which makes it easy for users with varying levels of expertise to conduct comprehensive analyses of indel dynamics.
