Fast-Evolving Alignment Sites Are Highly Informative for Reconstructions of Deep Tree of Life Phylogenies.

The trimming of fast-evolving sites, often known as "slow-fast" analysis, is broadly used in microbial phylogenetic reconstruction under the assumption that fast-evolving sites do not retain an accurate phylogenetic signal due to substitution saturation. Therefore, removing sites that have experienced multiple substitutions would improve the signal-to-noise ratio in phylogenetic analyses, with the remaining slower-evolving sites preserving a more reliable record of evolutionary relationships. Here, we show that, contrary to this assumption, even the fastest-evolving sites present in the conserved proteins often used in Tree of Life studies contain reliable and valuable phylogenetic information, and that the trimming of such sites can negatively impact the accuracy of phylogenetic reconstruction. Simulated alignments modeled after ribosomal protein datasets used in Tree of Life studies consistently show that slow-evolving sites are less likely to recover true bipartitions than even the fastest-evolving sites. Furthermore, site-specific substitution rates are positively correlated with the frequency of accurately recovered short-branched bipartitions, as slowly evolving sites are less likely to have experienced substitutions along these intervals. Using published Tree of Life sequence alignment datasets, we also show that both slow- and fast-evolving sites contain similarly inconsistent phylogenetic signals, and that, for fast-evolving sites, this inconsistency can be attributed to poor alignment quality. Furthermore, trimming fast sites, slow sites, or both is shown to have a substantial impact on phylogenetic reconstruction across multiple evolutionary models. This is perhaps most evident in the resulting placements of the Eukarya and Asgardarchaeota groups, which are especially sensitive to the implementation of different trimming schemes.

A Proterozoic microbial origin of extant cyanide-hydrolyzing enzyme diversity.

In addition to its role as a toxic environmental contaminant, cyanide has been hypothesized to play a key role in prebiotic chemistry and early biogeochemical evolution. While cyanide-hydrolyzing enzymes have been studied and engineered for bioremediation, the extant diversity of these enzymes remains underexplored. Additionally, the age and evolution of microbial cyanide metabolisms is poorly constrained. Here we provide comprehensive phylogenetic and molecular clock analyses of the distribution and evolution of the Class I nitrilases, thiocyanate hydrolases, and nitrile hydratases. Molecular clock analyses indicate that bacterial cyanide-reducing nitrilases were present by the Paleo- to Mesoproterozoic, and were subsequently horizontally transferred into eukaryotes. These results present a broad diversity of microbial enzymes that could be optimized for cyanide bioremediation.

DaTeR: error-correcting phylogenetic chronograms using relative time constraints.

MOTIVATION: A chronogram is a dated phylogenetic tree whose branch lengths have been scaled to represent time. Such chronograms are computed based on available date estimates (e.g. from dated fossils), which provide absolute time constraints for one or more nodes of an input undated phylogeny, coupled with an appropriate underlying model for evolutionary rates variation along the branches of the phylogeny. However, traditional methods for phylogenetic dating cannot take into account relative time constraints, such as those provided by inferred horizontal transfer events. In many cases, chronograms computed using only absolute time constraints are inconsistent with known relative time constraints. RESULTS: In this work, we introduce a new approach, Dating Trees using Relative constraints (DaTeR), for phylogenetic dating that can take into account both absolute and relative time constraints. The key idea is to use existing Bayesian approaches for phylogenetic dating to sample posterior chronograms satisfying desired absolute time constraints, minimally adjust or 'error-correct' these sampled chronograms to satisfy all given relative time constraints, and aggregate across all error-corrected chronograms. DaTeR uses a constrained optimization framework for the error-correction step, finding minimal deviations from previously assigned dates or branch lengths. We applied DaTeR to a biological dataset of 170 Cyanobacterial taxa and a reliable set of 24 transfer-based relative constraints, under six different molecular dating models. Our extensive analysis of this dataset demonstrates that DaTeR is both highly effective and scalable and that its application can significantly improve estimated chronograms. AVAILABILITY AND IMPLEMENTATION: Freely available from https://compbio.engr.uconn.edu/software/dater/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessing the accuracy of phylogenetic rooting methods on prokaryotic gene families.

Almost all standard phylogenetic methods for reconstructing gene trees result in unrooted trees; yet, many of the most useful applications of gene trees require that the gene trees be correctly rooted. As a result, several computational methods have been developed for inferring the root of unrooted gene trees. However, the accuracy of such methods has never been systematically evaluated on prokaryotic gene families, where horizontal gene transfer is often one of the dominant evolutionary events driving gene family evolution. In this work, we address this gap by conducting a thorough comparative evaluation of five different rooting methods using large collections of both simulated and empirical prokaryotic gene trees. Our simulation study is based on 6000 true and reconstructed gene trees on 100 species and characterizes the rooting accuracy of the four methods under 36 different evolutionary conditions and 3 levels of gene tree reconstruction error. The empirical study is based on a large, carefully designed data set of 3098 gene trees from 504 bacterial species (406 Alphaproteobacteria and 98 Cyanobacteria) and reveals insights that supplement those gleaned from the simulation study. Overall, this work provides several valuable insights into the accuracy of the considered methods that will help inform the choice of rooting methods to use when studying microbial gene family evolution. Among other findings, this study identifies parsimonious Duplication-Transfer-Loss (DTL) rooting and Minimal Ancestor Deviation (MAD) rooting as two of the most accurate gene tree rooting methods for prokaryotes and specifies the evolutionary conditions under which these methods are most accurate, demonstrates that DTL rooting is highly sensitive to high evolutionary rates and gene tree error, and that rooting methods based on branch-lengths are generally robust to gene tree reconstruction error.