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Abstract Microorganisms have the unique ability to survive extended periods of time in environments with extremely low levels of exploitable energy. To determine the extent that energy limitation affects microbial evolution, we examined the molecular evolutionary dynamics of a phylogenetically diverse set of taxa over the course of 1,000 days. We found that periodic exposure to energy limitation affected the rate of molecular evolution, the accumulation of genetic diversity, and the rate of extinction. We then determined the degree that energy limitation affected the spectrum of mutations as well as the direction of evolution at the gene level. Our results suggest that the initial depletion of energy altered the direction and rate of molecular evolution within each taxon, though after the initial depletion the rate and direction did not substantially change. However, this consistent pattern became diminished when comparisons were performed across phylogenetically distant taxa, suggesting that although the dynamics of molecular evolution under energy limitation are highly generalizable across the microbial tree of life, the targets of adaptation are specific to a given taxon. 

Abstract The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net. 

Abstract The relationships among the four major embryophyte lineages (mosses, liverworts, hornworts, vascular plants) and the timing of the origin of land plants are enigmatic problems in plant evolution. Here, we resolve the monophyly of bryophytes by improving taxon sampling of hornworts and eliminating the effect of synonymous substitutions. We then estimate the divergence time of crown embryophytes based on three fossil calibration strategies, and reveal that maximum calibration constraints have a major effect on estimating the time of origin of land plants. Moreover, comparison of priors and posteriors provides a guide for evaluating the optimal calibration strategy. By considering the reliability of fossil calibrations and the influences of molecular data, we estimate that land plants originated in the Precambrian (980–682 Ma), much older than widely recognized. Our study highlights the important contribution of molecular data when faced with contentious fossil evidence, and that fossil calibrations used in estimating the timescale of plant evolution require critical scrutiny.