Dates allow evolutionary events to be compared not only with other evolutionary events (like the expansion of grasslands) but with geological and historical events. The addition of divergence time data allowed for exploration of correlations between these evolutionary events. It is therefore possible to hypothesize an expansion in habitat fostering an expansion in ground dwelling mammals like the Marmotini. It is also known that there was a large increase in savannas and grasslands worldwide during the same period. It is apparent that there was a significant increase in the species of ground squirrels during the late Miocene to early Pliocene eras. These times closely approximate the most recent published divergence time data for the family. The divergence times computed are shown in units of Millions of Years. Adding dates to historical events allows us to temporally connect events and thereby draw additional conclusions from the data.Ĭonsider the ground squirrels as represented by the tribe Marmotini (Fig. In addition to knowing how species are related to each other (as shown by the tree topology), we would also like to know when these species diverged from their ancestors. While projects such as the Open Tree of Life ( ) seek to develop an all-encompassing tree, the vast majority of phylogenetic analysis focus on a particular branch of the tree. A recent estimate places the number of living species at 8.8 million ☑.3 million.
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Through the use of these new algorithms we open up the ability to perform divergence time inference on large phylogenetic studies.ĭarwin envisioned the relationship between all the various species as a great tree with living species as the leaves and branches leading downward to extinct ancestors. Additionally, we show that our new method for the computation of the Bayesian prior on node ages reduces the running time for this computation on the 349 taxa dataset by 99%. ResultsĪs part of AncestralAge, we demonstrate a new method for the computation of phylogenetic likelihood and our experiments show a 90% improvement in likelihood computation time on the aforementioned dataset of 349 primates taxa with over 60,000 DNA base pairs. In this work, we present a new algorithm, AncestralAge, that significantly improves the performance of the divergence time process. For example a study of 349 primate taxa was estimated to require over 9 months of processing time. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. The inference of species divergence time is a key step in most phylogenetic studies.