Incomplete lineage sorting and phenotypic evolution in marsupials.

Incomplete lineage sorting (ILS) makes ancestral genetic polymorphisms persist during rapid speciation events, inducing incongruences between gene trees and species trees. ILS has complicated phylogenetic inference in many lineages, including hominids. However, we lack empirical evidence that ILS leads to incongruent phenotypic variation. Here, we performed phylogenomic analyses to show that the South American monito del monte is the sister lineage of all Australian marsupials, although over 31% of its genome is closer to the Diprotodontia than to other Australian groups due to ILS during ancient radiation. Pervasive conflicting phylogenetic signals across the whole genome are consistent with some of the morphological variation among extant marsupials. We detected hundreds of genes that experienced stochastic fixation during ILS, encoding the same amino acids in non-sister species. Using functional experiments, we confirm how ILS may have directly contributed to hemiplasy in morphological traits that were established during rapid marsupial speciation ca. 60 mya.

Emergence of immune escape at dominant SARS-CoV-2 killer T cell epitope.

We studied the prevalent cytotoxic CD8 T cell response mounted against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike glycoprotein269-277 epitope (sequence YLQPRTFLL) via the most frequent human leukocyte antigen (HLA) class I worldwide, HLA A∗02. The Spike P272L mutation that has arisen in at least 112 different SARS-CoV-2 lineages to date, including in lineages classified as "variants of concern," was not recognized by the large CD8 T cell response seen across cohorts of HLA A∗02+ convalescent patients and individuals vaccinated against SARS-CoV-2, despite these responses comprising of over 175 different individual T cell receptors. Viral escape at prevalent T cell epitopes restricted by high frequency HLAs may be particularly problematic when vaccine immunity is focused on a single protein such as SARS-CoV-2 Spike, providing a strong argument for inclusion of multiple viral proteins in next generation vaccines and highlighting the need for monitoring T cell escape in new SARS-CoV-2 variants.

Quantitative fate mapping: A general framework for analyzing progenitor state dynamics via retrospective lineage barcoding.

Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; whether these lineage barcodes capture the complex dynamics of progenitor states remains unclear. We introduce quantitative fate mapping, an approach to reconstruct the hierarchy, commitment times, population sizes, and commitment biases of intermediate progenitor states during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a general barcoding mutagenesis model. We validate these approaches using realistic in silico and in vitro barcoding experiments. We further establish criteria for the number of cells that must be analyzed for robust quantitative fate mapping and a progenitor state coverage statistic to assess the robustness. This work demonstrates how lineage barcodes, natural or synthetic, enable analyzing progenitor fate and dynamics long after embryonic development in any organism.

Multiple evolutionary pressures shape identical consonant avoidance in the world's languages.

Languages disfavor word forms containing sequences of similar or identical consonants, due to the biomechanical and cognitive difficulties posed by patterns of this sort. However, the specific evolutionary processes responsible for this phenomenon are not fully understood. Words containing sequences of identical consonants may be more likely to arise than those without; processes of word form mutation may be more likely to remove than create sequences of identical consonants in word forms; finally, words containing identical consonants may die out more frequently than those without. Phylogenetic analyses of the evolution of homologous word forms indicate that words with identical consonants arise less frequently than those without. However, words with identical consonants do not die out more frequently than those without. Further analyses reveal that forms with identical consonants are replaced in basic meaning functions more frequently than words without. Taken together, results suggest that the underrepresentation of sequences of identical consonants is overwhelmingly a by-product of constraints on word form coinage, though processes related to word usage also serve to ensure that such patterns are infrequent in more salient vocabulary items. These findings clarify aspects of processes of lexical evolution and competition that take place during language change, optimizing communicative systems.

Bacterial lifestyle shapes pangenomes.

Pangenomes vary across bacteria. Some species have fluid pangenomes, with a high proportion of genes varying between individual genomes. Other species have less fluid pangenomes, with different genomes tending to contain the same genes. Two main hypotheses have been suggested to explain this variation: differences in species' bacterial lifestyle and effective population size. However, previous studies have not been able to test between these hypotheses because the different features of lifestyle and effective population size are highly correlated with each other, and phylogenetically conserved, making it hard to disentangle their relative importance. We used phylogeny-based analyses, across 126 bacterial species, to tease apart the causal role of different factors. We found that pangenome fluidity was lower in i) host-associated compared with free-living species and ii) host-associated species that are obligately dependent on a host, live inside cells, and are more pathogenic and less motile. In contrast, we found no support for the competing hypothesis that larger effective population sizes lead to more fluid pangenomes. Effective population size appears to correlate with pangenome variation because it is also driven by bacterial lifestyle, rather than because of a causal relationship.

The metabolic domestication syndrome of budding yeast.

Cellular metabolism evolves through changes in the structure and quantitative states of metabolic networks. Here, we explore the evolutionary dynamics of metabolic states by focusing on the collection of metabolite levels, the metabolome, which captures key aspects of cellular physiology. Using a phylogenetic framework, we profiled metabolites in 27 populations of nine budding yeast species, providing a graduated view of metabolic variation across multiple evolutionary time scales. Metabolite levels evolve more rapidly and independently of changes in the metabolic network's structure, providing complementary information to enzyme repertoire. Although metabolome variation accumulates mainly gradually over time, it is profoundly affected by domestication. We found pervasive signatures of convergent evolution in the metabolomes of independently domesticated clades of Saccharomyces cerevisiae. Such recurring metabolite differences between wild and domesticated populations affect a substantial part of the metabolome, including rewiring of the TCA cycle and several amino acids that influence aroma production, likely reflecting adaptation to human niches. Overall, our work reveals previously unrecognized diversity in central metabolism and the pervasive influence of human-driven selection on metabolite levels in yeasts.

A region of suppressed recombination misleads neoavian phylogenomics.

Genomes are typically mosaics of regions with different evolutionary histories. When speciation events are closely spaced in time, recombination makes the regions sharing the same history small, and the evolutionary history changes rapidly as we move along the genome. When examining rapid radiations such as the early diversification of Neoaves 66 Mya, typically no consistent history is observed across segments exceeding kilobases of the genome. Here, we report an exception. We found that a 21-Mb region in avian genomes, mapped to chicken chromosome 4, shows an extremely strong and discordance-free signal for a history different from that of the inferred species tree. Such a strong discordance-free signal, indicative of suppressed recombination across many millions of base pairs, is not observed elsewhere in the genome for any deep avian relationships. Although long regions with suppressed recombination have been documented in recently diverged species, our results pertain to relationships dating circa 65 Mya. We provide evidence that this strong signal may be due to an ancient rearrangement that blocked recombination and remained polymorphic for several million years prior to fixation. We show that the presence of this region has misled previous phylogenomic efforts with lower taxon sampling, showing the interplay between taxon and locus sampling. We predict that similar ancient rearrangements may confound phylogenetic analyses in other clades, pointing to a need for new analytical models that incorporate the possibility of such events.

Epigenetics and transcription regulation during eukaryotic diversification: the saga of TFIID.

The basal transcription factor TFIID is central for RNA polymerase II-dependent transcription. Human TFIID is endowed with chromatin reader and DNA-binding domains and protein interaction surfaces. Fourteen TFIID TATA-binding protein (TBP)-associated factor (TAF) subunits assemble into the holocomplex, which shares subunits with the Spt-Ada-Gcn5-acetyltransferase (SAGA) coactivator. Here, we discuss the structural and functional evolution of TFIID and its divergence from SAGA. Our orthologous tree and domain analyses reveal dynamic gains and losses of epigenetic readers, plant-specific functions of TAF1 and TAF4, the HEAT2-like repeat in TAF2, and, importantly, the pre-LECA origin of TFIID and SAGA. TFIID evolution exemplifies the dynamic plasticity in transcription complexes in the eukaryotic lineage.

Phylogenetic inference of inter-population transmission rates for infectious diseases.

Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. Various methods exist for estimating transmission rates, each with distinct assumptions, data needs, and constraints. This study introduces a novel phylogenetic approach called transRate, which integrates genetic information with traditional epidemiological approaches to estimate inter-population transmission rates. The phylogenetic method is statistically consistent as the sample size (i.e. the number of pathogen genomes) approaches infinity under the multi-population susceptible-infected-recovered model. Simulation analyses indicate that transRate can accurately estimate the transmission rate with a sample size of 200 ~ 400 pathogen genomes. Using transRate, we analyzed 40,028 high-quality sequences of SARS-CoV-2 in human hosts during the early pandemic. Our analysis uncovered significant transmission between populations even before widespread travel restrictions were implemented. The development of transRate provides valuable insights for scientists and public health officials to enhance their understanding of the pandemic's progression and aiding in preparedness for future viral outbreaks. As public databases for genomic sequences continue to expand, transRate is increasingly vital for tracking and mitigating the spread of infectious diseases.

Phylogenomic comparative methods: Accurate evolutionary inferences in the presence of gene tree discordance.

Phylogenetic comparative methods have long been a mainstay of evolutionary biology, allowing for the study of trait evolution across species while accounting for their common ancestry. These analyses typically assume a single, bifurcating phylogenetic tree describing the shared history among species. However, modern phylogenomic analyses have shown that genomes are often composed of mosaic histories that can disagree both with the species tree and with each other-so-called discordant gene trees. These gene trees describe shared histories that are not captured by the species tree, and therefore that are unaccounted for in classic comparative approaches. The application of standard comparative methods to species histories containing discordance leads to incorrect inferences about the timing, direction, and rate of evolution. Here, we develop two approaches for incorporating gene tree histories into comparative methods: one that constructs an updated phylogenetic variance-covariance matrix from gene trees, and another that applies Felsenstein's pruning algorithm over a set of gene trees to calculate trait histories and likelihoods. Using simulation, we demonstrate that our approaches generate much more accurate estimates of tree-wide rates of trait evolution than standard methods. We apply our methods to two clades of the wild tomato genus Solanum with varying rates of discordance, demonstrating the contribution of gene tree discordance to variation in a set of floral traits. Our approaches have the potential to be applied to a broad range of classic inference problems in phylogenetics, including ancestral state reconstruction and the inference of lineage-specific rate shifts.

Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale.

Adaptation in protein-coding sequences can be detected from multiple sequence alignments across species or alternatively by leveraging polymorphism data within a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of nonsynonymous over synonymous substitution rates. Evidence of an accelerated nonsynonymous substitution rate is considered a signature of pervasive adaptation. However, because of the background of purifying selection, these models are potentially limited in their sensitivity. Recent developments have led to more sophisticated mutation-selection codon models aimed at making a more detailed quantitative assessment of the interplay between mutation, purifying, and positive selection. In this study, we conducted a large-scale exome-wide analysis of placental mammals with mutation-selection models, assessing their performance at detecting proteins and sites under adaptation. Importantly, mutation-selection codon models are based on a population-genetic formalism and thus are directly comparable to the McDonald and Kreitman test at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics analyses, we integrated divergence and polymorphism data across the entire exome for 29 populations across 7 genera and showed that proteins and sites detected to be under adaptation at the phylogenetic scale are also under adaptation at the population-genetic scale. Altogether, our exome-wide analysis shows that phylogenetic mutation-selection codon models and the population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.

Climatic stability and geological history shape global centers of neo- and paleoendemism in seed plants.

Assessing the distribution of geographically restricted and evolutionarily unique species and their underlying drivers is key to understanding biogeographical processes and critical for global conservation prioritization. Here, we quantified the geographic distribution and drivers of phylogenetic endemism for ~320,000 seed plants worldwide and identified centers and drivers of evolutionarily young (neoendemism) and evolutionarily old endemism (paleoendemism). Tropical and subtropical islands as well as tropical mountain regions displayed the world's highest phylogenetic endemism. Most tropical rainforest regions emerged as centers of paleoendemism, while most Mediterranean-climate regions showed high neoendemism. Centers where high neo- and paleoendemism coincide emerged on some oceanic and continental fragment islands, in Mediterranean-climate regions and parts of the Irano-Turanian floristic region. Global variation in phylogenetic endemism was well explained by a combination of past and present environmental factors (79.8 to 87.7% of variance explained) and most strongly related to environmental heterogeneity. Also, warm and wet climates, geographic isolation, and long-term climatic stability emerged as key drivers of phylogenetic endemism. Neo- and paleoendemism were jointly explained by climatic and geological history. Long-term climatic stability promoted the persistence of paleoendemics, while the isolation of oceanic islands and their unique geological histories promoted neoendemism. Mountainous regions promoted both neo- and paleoendemism, reflecting both diversification and persistence over time. Our study provides insights into the evolutionary underpinnings of biogeographical patterns in seed plants and identifies the areas on Earth with the highest evolutionary and biogeographical uniqueness-key information for setting global conservation priorities.

Landscape dynamics and diversification of the megadiverse South American freshwater fish fauna.

Landscape dynamics are widely thought to govern the tempo and mode of continental radiations, yet the effects of river network rearrangements on dispersal and lineage diversification remain poorly understood. We integrated an unprecedented occurrence dataset of 4,967 species with a newly compiled, time-calibrated phylogeny of South American freshwater fishes-the most species-rich continental vertebrate fauna on Earth-to track the evolutionary processes associated with hydrogeographic events over 100 Ma. Net lineage diversification was heterogeneous through time, across space, and among clades. Five abrupt shifts in net diversification rates occurred during the Paleogene and Miocene (between 30 and 7 Ma) in association with major landscape evolution events. Net diversification accelerated from the Miocene to the Recent (c. 20 to 0 Ma), with Western Amazonia having the highest rates of in situ diversification, which led to it being an important source of species dispersing to other regions. All regional biotic interchanges were associated with documented hydrogeographic events and the formation of biogeographic corridors, including the Early Miocene (c. 23 to 16 Ma) uplift of the Serra do Mar and Serra da Mantiqueira and the Late Miocene (c. 10 Ma) uplift of the Northern Andes and associated formation of the modern transcontinental Amazon River. The combination of high diversification rates and extensive biotic interchange associated with Western Amazonia yielded its extraordinary contemporary richness and phylogenetic endemism. Our results support the hypothesis that landscape dynamics, which shaped the history of drainage basin connections, strongly affected the assembly and diversification of basin-wide fish faunas.

Elucidating the origins of phycocyanobilin biosynthesis and phycobiliproteins.

Terrestrial ecosystems and human societies depend on oxygenic photosynthesis, which began to reshape our atmosphere approximately 2.5 billion years ago. The earliest known organisms carrying out oxygenic photosynthesis are the cyanobacteria, which use large complexes of phycobiliproteins as light-harvesting antennae. Phycobiliproteins rely on phycocyanobilin (PCB), a linear tetrapyrrole (bilin) chromophore, as the light-harvesting pigment that transfers absorbed light energy from phycobilisomes to the chlorophyll-based photosynthetic apparatus. Cyanobacteria synthesize PCB from heme in two steps: A heme oxygenase converts heme into biliverdin IXα (BV), and the ferredoxin-dependent bilin reductase (FDBR) PcyA then converts BV into PCB. In the current work, we examine the origins of this pathway. We demonstrate that PcyA evolved from pre-PcyA proteins found in nonphotosynthetic bacteria and that pre-PcyA enzymes are active FDBRs that do not yield PCB. Pre-PcyA genes are associated with two gene clusters. Both clusters encode bilin-binding globin proteins, phycobiliprotein paralogs that we designate as BBAGs (bilin biosynthesis-associated globins). Some cyanobacteria also contain one such gene cluster, including a BBAG, two V4R proteins, and an iron-sulfur protein. Phylogenetic analysis shows that this cluster is descended from those associated with pre-PcyA proteins and that light-harvesting phycobiliproteins are also descended from BBAGs found in other bacteria. We propose that PcyA and phycobiliproteins originated in heterotrophic, nonphotosynthetic bacteria and were subsequently acquired by cyanobacteria.

Principles of metabolome conservation in animals.

Metabolite levels shape cellular physiology and disease susceptibility, yet the general principles governing metabolome evolution are largely unknown. Here, we introduce a measure of conservation of individual metabolite levels among related species. By analyzing multispecies tissue metabolome datasets in phylogenetically diverse mammals and fruit flies, we show that conservation varies extensively across metabolites. Three major functional properties, metabolite abundance, essentiality, and association with human diseases predict conservation, highlighting a striking parallel between the evolutionary forces driving metabolome and protein sequence conservation. Metabolic network simulations recapitulated these general patterns and revealed that abundant metabolites are highly conserved due to their strong coupling to key metabolic fluxes in the network. Finally, we show that biomarkers of metabolic diseases can be distinguished from other metabolites simply based on evolutionary conservation, without requiring any prior clinical knowledge. Overall, this study uncovers simple rules that govern metabolic evolution in animals and implies that most tissue metabolome differences between species are permitted, rather than favored by natural selection. More broadly, our work paves the way toward using evolutionary information to identify biomarkers, as well as to detect pathogenic metabolome alterations in individual patients.

Homoplastic versus xenoplastic evolution: exploring the emergence of key intrinsic and extrinsic traits in the montane genus Soldanella (Primulaceae).

Specific ecological conditions in the high mountain environment exert a selective pressure that often leads to convergent trait evolution. Reticulations induced by incomplete lineage sorting and introgression can lead to discordant trait patterns among gene and species trees (hemiplasy/xenoplasy), providing a false illusion that the traits under study are homoplastic. Using phylogenetic species networks, we explored the effect of gene exchange on trait evolution in Soldanella, a genus profoundly influenced by historical introgression. At least three features evolved independently multiple times: the single-flowered dwarf phenotype, dysploid cytotype, and ecological generalism. The present analyses also indicated that the recurring occurrence of stoloniferous growth might have been prompted by an introgression event between an ancestral lineage and a still extant species, although its emergence via convergent evolution cannot be completely ruled out. Phylogenetic regression suggested that the independent evolution of larger genomes in snowbells is most likely a result of the interplay between hybridization events of dysploid and euploid taxa and hostile environments at the range margins of the genus. The emergence of key intrinsic and extrinsic traits in snowbells has been significantly impacted not only by convergent evolution but also by historical and recent introgression events.

PhyloBench: A Benchmark for Evaluating Phylogenetic Programs.

Phylogenetic inference based on protein sequence alignment is a widely used procedure. Numerous phylogenetic algorithms have been developed, most of which have many parameters and options. Choosing a program, options, and parameters can be a nontrivial task. No benchmark for comparison of phylogenetic programs on real protein sequences was publicly available. We have developed PhyloBench, a benchmark for evaluating the quality of phylogenetic inference, and used it to test a number of popular phylogenetic programs. PhyloBench is based on natural, not simulated, protein sequences of orthologous evolutionary domains. The measure of accuracy of an inferred tree is its distance to the corresponding species tree. A number of tree-to-tree distance measures were tested. The most reliable results were obtained using the Robinson-Foulds distance. Our results confirmed recent findings that distance methods are more accurate than maximum likelihood (ML) and maximum parsimony. We tested the bayesian program MrBayes on natural protein sequences and found that, on our datasets, it performs better than ML, but worse than distance methods. Of the methods we tested, the Balanced Minimum Evolution method implemented in FastME yielded the best results on our material. Alignments and reference species trees are available at https://mouse.belozersky.msu.ru/tools/phylobench/ together with a web-interface that allows for a semi-automatic comparison of a user's method with a number of popular programs.

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs.

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Connecting Species-Specific Extents of Genome Reduction in Mitochondria and Plastids.

Mitochondria and plastids have both dramatically reduced their genomes since the endosymbiotic events that created them. The similarities and differences in the evolution of the two organelle genome types have been the target of discussion and investigation for decades. Ongoing work has suggested that similar mechanisms may modulate the reductive evolution of the two organelles in a given species, but quantitative data and statistical analyses exploring this picture remain limited outside of some specific cases like parasitism. Here, we use cross-eukaryote organelle genome data to explore evidence for coevolution of mitochondrial and plastid genome reduction. Controlling for differences between clades and pseudoreplication due to relatedness, we find that extents of mtDNA and ptDNA gene retention are related to each other across taxa, in a generally positive correlation that appears to differ quantitatively across eukaryotes, for example, between algal and nonalgal species. We find limited evidence for coevolution of specific mtDNA and ptDNA gene pairs, suggesting that the similarities between the two organelle types may be due mainly to independent responses to consistent evolutionary drivers.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes.

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.