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Predicting the ancestral sequences of a group of homologous sequences relatedby a phylogenetic tree has been the subject of many studies, and numerousmethods have been proposed to this purpose. Theoretical results are availablethat show that when the mutation rate become too large, reconstructing theancestral state at the tree root is no longer feasible. Here, we also study thereconstruction of the ancestral changes that occurred along the tree edges. Weshow that, depending on the tree and branch length distribution, reconstructingthese changes (i.e. reconstructing the ancestral state of all internal nodes inthe tree) may be easier or harder than reconstructing the ancestral root state.However, results from information theory indicate that for the standard Yuletree, the task of reconstructing internal node states remains feasible, evenfor very high substitution rates. Moreover, computer simulations demonstratethat for more complex trees and scenarios, this result still holds. For a largevariety of counting, parsimony-based and likelihood-based methods, thepredictive accuracy of a randomly selected internal node in the tree is indeedmuch higher than the accuracy of the same method when applied to the tree root.Moreover, parsimony- and likelihood-based methods appear to be remarkablyrobust to sampling bias and model mis-specification.

Predicting the ancestral character changes in a tree is typically easier than predicting the root state