TimeTree 5: An Expanded Resource for Species Divergence Times.

We present the fifth edition of the TimeTree of Life resource (TToL5), a product of the timetree of life project that aims to synthesize published molecular timetrees and make evolutionary knowledge easily accessible to all. Using the TToL5 web portal, users can retrieve published studies and divergence times between species, the timeline of a species' evolution beginning with the origin of life, and the timetree for a given evolutionary group at the desired taxonomic rank. TToL5 contains divergence time information on 137,306 species, 41% more than the previous edition. The TToL5 web interface is now ADA-compliant and mobile-friendly, a result of comprehensive source code refactoring. TToL5 also offers programmatic access to species divergence times and timelines through an application programming interface, which is accessible at timetree.temple.edu/api. TToL5 is publicly available at timetree.org.

TimeTree: A Resource for Timelines, Timetrees, and Divergence Times.

Evolutionary information on species divergence times is fundamental to studies of biodiversity, development, and disease. Molecular dating has enhanced our understanding of the temporal patterns of species divergences over the last five decades, and the number of studies is increasing quickly due to an exponential growth in the available collection of molecular sequences from diverse species and large number of genes. Our TimeTree resource is a public knowledge-base with the primary focus to make available all species divergence times derived using molecular sequence data to scientists, educators, and the general public in a consistent and accessible format. Here, we report a major expansion of the TimeTree resource, which more than triples the number of species (>97,000) and more than triples the number of studies assembled (>3,000). Furthermore, scientists can access not only the divergence time between two species or higher taxa, but also a timetree of a group of species and a timeline that traces a species' evolution through time. The new timetree and timeline visualizations are integrated with display of events on earth and environmental history over geological time, which will lead to broader and better understanding of the interplay of the change in the biosphere with the diversity of species on Earth. The next generation TimeTree resource is publicly available online at http://www.timetree.org.

Tree of life reveals clock-like speciation and diversification.

Genomic data are rapidly resolving the tree of living species calibrated to time, the timetree of life, which will provide a framework for research in diverse fields of science. Previous analyses of taxonomically restricted timetrees have found a decline in the rate of diversification in many groups of organisms, often attributed to ecological interactions among species. Here, we have synthesized a global timetree of life from 2,274 studies representing 50,632 species and examined the pattern and rate of diversification as well as the timing of speciation. We found that species diversity has been mostly expanding overall and in many smaller groups of species, and that the rate of diversification in eukaryotes has been mostly constant. We also identified, and avoided, potential biases that may have influenced previous analyses of diversification including low levels of taxon sampling, small clade size, and the inclusion of stem branches in clade analyses. We found consistency in time-to-speciation among plants and animals, ∼2 My, as measured by intervals of crown and stem species times. Together, this clock-like change at different levels suggests that speciation and diversification are processes dominated by random events and that adaptive change is largely a separate process.

Positional conservation and amino acids shape the correct diagnosis and population frequencies of benign and damaging personal amino acid mutations.

As the cost of DNA sequencing drops, we are moving beyond one genome per species to one genome per individual to improve prevention, diagnosis, and treatment of disease by using personal genotypes. Computational methods are frequently applied to predict impairment of gene function by nonsynonymous mutations in individual genomes and single nucleotide polymorphisms (nSNPs) in populations. These computational tools are, however, known to fail 15%-40% of the time. We find that accurate discrimination between benign and deleterious mutations is strongly influenced by the long-term (among species) history of positions that harbor those mutations. Successful prediction of known disease-associated mutations (DAMs) is much higher for evolutionarily conserved positions and for original-mutant amino acid pairs that are rarely seen among species. Prediction accuracies for nSNPs show opposite patterns, forecasting impediments to building diagnostic tools aiming to simultaneously reduce both false-positive and false-negative errors. The relative allele frequencies of mutations diagnosed as benign and damaging are predicted by positional evolutionary rates. These allele frequencies are modulated by the relative preponderance of the mutant allele in the set of amino acids found at homologous sites in other species (evolutionarily permissible alleles [EPAs]). The nSNPs found in EPAs are biochemically less severe than those missing from EPAs across all allele frequency categories. Therefore, it is important to consider position evolutionary rates and EPAs when interpreting the consequences and population frequencies of human mutations. The impending sequencing of thousands of human and many more vertebrate genomes will lead to more accurate classifiers needed in real-world applications.