Abstract
New species arise from pre-existing species and inherit similar genomes and environments. This predicts greater similarity of mutation rates and the tempo of molecular evolution between direct ancestors and descendants, resulting in correlation of evolutionary rates within lineages in the tree of life. Surprisingly, molecular sequence data have not confirmed this expectation, possibly because available methods lack power to detect correlated rates. Here we present an accurate machine learning method used to detect correlation of rates in large phylogenies. By applying this method to multigene and genome-scale sequence alignments from mammals, birds, insects, metazoans, plants, fungi, and prokaryotes, we discover extensive correlation in molecular evolutionary rates throughout the tree of life in both DNA and protein sequences. These findings suggest concordance between molecular and non-molecular evolutionary patterns and will foster unbiased and precise dating of the tree of life.