Read Length Dominates Phylogenetic Placement Accuracy of Ancient DNA Reads

A common problem when analyzing ancient DNA data is to identify the species that corresponds to the recovered analyzing ancient DNA sequence(s). The standard approach is to deploy sequence similarity-based tools, such as BLAST. However, as analyzing ancient DNA reads may frequently stem from unsampled taxa due to extinction, it is likely that there is no exact match in any database. As a consequence, these tools may not be able to accurately place such reads in a phylogenetic context. Phylogenetic placement is a technique where a read is placed onto a specific branch of a phylogenetic reference tree, which allows for a substantially finer resolution when identifying reads. Prior applications of phylogenetic placement have deployed only on data from extant sources. Therefore, it is unclear how the analyzing ancient DNA damage affects phylogenetic placement's applicability to analyzing ancient DNA data. To investigate how analyzing ancient DNA damage affects placement accuracy, we re-implemented a statistical model of analyzing ancient DNA damage. We deploy this model, along with a modified version of the existing assessment pipeline PEWO, to 7 empirical datasets with 4 leading tools: APPLES, EPA-Ng, pplacer, and RAPPAS. We explore the analyzing ancient DNA damage parameter space via a grid search in order to identify the analyzing ancient DNA damage factors that exhibit the largest impact on placement accuracy. We find that the frequency of DNA backbone nicks (and consequently read length) has the, by far, largest impact on analyzing ancient DNA read placement accuracy, and that other factors, such as misincorporations, have a negligible effect on overall placement accuracy.