Complex Models of Sequence Evolution Require Accurate Estimators as Exemplified with the Invariable Site Plus Gamma Model

An evolutionary epigenetic clock in plants

Molecular clocks are the basis for dating the divergence between lineages over macroevolutionary timescales (~105 to 108 years). However, classical DNA-based clocks tick too slowly to inform us about the recent past. Here, we demonstrate that stochastic DNA methylation changes at a subset of cytosines in plant genomes display a clocklike behavior. This "epimutation clock" is orders of magnitude faster than DNA-based clocks and enables phylogenetic explorations on a scale of years to centuries. We show experimentally that epimutation clocks recapitulate known topologies and branching times of intraspecies phylogenetic trees in the self-fertilizing plant Arabidopsis thaliana and the clonal seagrass Zostera marina, which represent two major modes of plant reproduction. This discovery will open new possibilities for high-resolution temporal studies of plant biodiversity.

Characterizing conflict and congruence of molecular evolution across organellar genome sequences for phylogenetics in land plants

Chloroplasts and mitochondria each contain their own genomes, which have historically been and continue to be important sources of information for inferring the phylogenetic relationships among land plants. The organelles are predominantly inherited from the same parent, and therefore should exhibit phylogenetic concordance. In this study, we examine the mitochondrion and chloroplast genomes of 226 land plants to infer the degree of similarity between the organelles' evolutionary histories. Our results show largely concordant topologies are inferred between the organelles, aside from four well-supported conflicting relationships that warrant further investigation. Despite broad patterns of topological concordance, our findings suggest that the chloroplast and mitochondrial genomes evolved with significant differences in molecular evolution. The differences result in the genes from the chloroplast and the mitochondrion preferentially clustering with other genes from their respective organelles by a program that automates selection of evolutionary model partitions for sequence alignments. Further investigation showed that changes in compositional heterogeneity are not always uniform across divergences in the land plant tree of life. These results indicate that although the chloroplast and mitochondrial genomes have coexisted for over 1 billion years, phylogenetically, they are still evolving sufficiently independently to warrant separate models of evolution. As genome sequencing becomes more accessible, research into these organelles' evolution will continue revealing insight into the ancient cellular events that shaped not only their history, but the history of plants as a whole.

Everglades virus evolution: Genome sequence analysis of the envelope 1 protein reveals recent mutation and divergence in South Florida wetlands

Everglades virus (EVEV) is a subtype (II) of Venezuelan equine encephalitis virus (VEEV), endemic in southern Florida, USA. EVEV has caused clinical encephalitis in humans, and antibodies have been found in a variety of wild and domesticated mammals. Over 29,000 Culex cedecei females, the main vector of EVEV, were collected in 2017 from Big Cypress and Fakahatchee Strand Preserves in Florida and pool-screened for the presence of EVEV using reverse transcription real-time polymerase chain reaction. The entire 1 E1 protein gene was successfully sequenced from fifteen positive pools. Phylogenetic analysis showed that isolates clustered, based on the location of sampling, into two monophyletic clades that diverged in 2009. Structural analyses revealed two mutations of interest, A116V and H441R, which were shared among all isolates obtained after its first isolation of EVEV in 1963, possibly reflecting adaptation to a new host. Alterations of the Everglades ecosystem may have contributed to the evolution of EVEV and its geographic compartmentalization. This is the first report that shows in detail the evolution of EVEV in South Florida. This zoonotic pathogen warrants inclusion into routine surveillance given the high natural infection rate in the vectors. Invasive species, increasing urbanization, the Everglades restoration, and modifications to the ecosystem due to climate change and habitat fragmentation in South Florida may increase rates of EVEV spillover to the human population.

Genetic variation in aneuploidy prevalence and tolerance across Saccharomyces cerevisiae lineages

Individuals carrying an aberrant number of chromosomes can vary widely in their expression of aneuploidy phenotypes. A major unanswered question is the degree to which an individual's genetic makeup influences its tolerance of karyotypic imbalance. Here we investigated within-species variation in aneuploidy prevalence and tolerance, using Saccharomyces cerevisiae as a model for eukaryotic biology. We analyzed genotypic and phenotypic variation recently published for over 1,000 S. cerevisiae strains spanning dozens of genetically defined clades and ecological associations. Our results show that the prevalence of chromosome gain and loss varies by clade and can be better explained by differences in genetic background than ecology. The relationships between lineages with high aneuploidy frequencies suggest that increased aneuploidy prevalence emerged multiple times in S. cerevisiae evolution. Separate from aneuploidy prevalence, analyzing growth phenotypes revealed that some genetic backgrounds-such as the European Wine lineage-show fitness costs in aneuploids compared to euploids, whereas other clades with high aneuploidy frequencies show little evidence of major deleterious effects. Our analysis confirms that chromosome gain can produce phenotypic benefits, which could influence evolutionary trajectories. These results have important implications for understanding genetic variation in aneuploidy prevalence in health, disease, and evolution.

A phylogeny for the Drosophila montium species group: A model clade for comparative analyses

The Drosophila montium species group is a clade of 94 named species, closely related to the model species D. melanogaster. The montium species group is distributed over a broad geographic range throughout Asia, Africa, and Australasia. Species of this group possess a wide range of morphologies, mating behaviors, and endosymbiont associations, making this clade useful for comparative analyses. We use genomic data from 42 available species to estimate the phylogeny and relative divergence times within the montium species group, and its relative divergence time from D. melanogaster. To assess the robustness of our phylogenetic inferences, we use 3 non-overlapping sets of 20 single-copy coding sequences and analyze all 60 genes with both Bayesian and maximum likelihood methods. Our analyses support monophyly of the group. Apart from the uncertain placement of a single species, D. baimaii, our analyses also support the monophyly of all seven subgroups proposed within the montium group. Our phylograms and relative chronograms provide a highly resolved species tree, with discordance restricted to estimates of relatively short branches deep in the tree. In contrast, age estimates for the montium crown group, relative to its divergence from D. melanogaster, depend critically on prior assumptions concerning variation in rates of molecular evolution across branches, and hence have not been reliably determined. We discuss methodological issues that limit phylogenetic resolution - even when complete genome sequences are available - as well as the utility of the current phylogeny for understanding the evolutionary and biogeographic history of this clade.

The Relative Importance of Modeling Site Pattern Heterogeneity Versus Partition-Wise Heterotachy in Phylogenomic Inference

Large taxa-rich genome-scale data sets are often necessary for resolving ancient phylogenetic relationships. But accurate phylogenetic inference requires that they are analyzed with realistic models that account for the heterogeneity in substitution patterns amongst the sites, genes and lineages. Two kinds of adjustments are frequently used: models that account for heterogeneity in amino acid frequencies at sites in proteins, and partitioned models that accommodate the heterogeneity in rates (branch lengths) among different proteins in different lineages (protein-wise heterotachy). Although partitioned and site-heterogeneous models are both widely used in isolation, their relative importance to the inference of correct phylogenies has not been carefully evaluated. We conducted several empirical analyses and a large set of simulations to compare the relative performances of partitioned models, site-heterogeneous models, and combined partitioned site heterogeneous models. In general, site-homogeneous models (partitioned or not) performed worse than site heterogeneous, except in simulations with extreme protein-wise heterotachy. Furthermore, simulations using empirically-derived realistic parameter settings showed a marked long-branch attraction (LBA) problem for analyses employing protein-wise partitioning even when the generating model included partitioning. This LBA problem results from a small sample bias compounded over many single protein alignments. In some cases, this problem was ameliorated by clustering similarly-evolving proteins together into larger partitions using the PartitionFinder method. Similar results were obtained under simulations with larger numbers of taxa or heterogeneity in simulating topologies over genes. For an empirical Microsporidia test data set, all but one tested site-heterogeneous models (with or without partitioning) obtain the correct Microsporidia+Fungi grouping, whereas site-homogenous models (with or without partitioning) did not. The single exception was the fully partitioned site-heterogeneous analysis that succumbed to the compounded small sample LBA bias. In general unless protein-wise heterotachy effects are extreme, it is more important to model site-heterogeneity than protein-wise heterotachy in phylogenomic analyses. Complete protein-wise partitioning should be avoided as it can lead to a serious LBA bias. In cases of extreme protein-wise heterotachy, approaches that cluster similarly-evolving proteins together and coupled with site-heterogeneous models work well for phylogenetic estimation.

Morphological Data Sets Fit a Common Mechanism Much More Poorly than DNA Sequences and Call Into Question the Mkv Model

The Mkv evolutionary model, based on minor modifications to models of molecular evolution, is being increasingly used to infer phylogenies from discrete morphological data, often producing different results from parsimony. The critical difference between Mkv and parsimony is the assumption of a "common mechanism" in the Mkv model, with branch lengths determining that probability of change for all characters increases or decreases at the same tree branches by the same exponential factor. We evaluate whether the assumption of a common mechanism applies to morphology, by testing the implicit prediction that branch lengths calculated from different subsets of characters will be significantly correlated. Our analysis shows that DNA (38 data sets tested) is often compatible with a common mechanism, but morphology (86 data sets tested) generally is not, showing very disparate branch lengths for different character partitions. The low levels of branch length correlation demonstrated for morphology (fitting models without a common mechanism) suggest that the Mkv model is too unrealistic and inadequate for the analysis of most morphological data sets. [Bayesian analysis; Mkv model; morphological data; phylogenetics.].