The Evolutionary Dynamics of the Lion Panthera leo Revealed by Host and Viral Population Genomics

Abstract Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

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Molecular Phylogenesis and Spatiotemporal Spread of SARS-CoV-2 in Southeast Asia

Frontiers in Public Health ◽

10.3389/fpubh.2021.685315 ◽

2021 ◽

Vol 9 ◽

Author(s):

Mingjian Zhu ◽

Jian Shen ◽

Qianli Zeng ◽

Joanna Weihui Tan ◽

Jirapat Kleepbua ◽

...

Keyword(s):

Southeast Asia ◽

Evolutionary Dynamics ◽

Phylogenetic Analyses ◽

Population Expansion ◽

Principal Component ◽

Viral Population ◽

Recent Common Ancestor ◽

Tropical Region ◽

Effective Population ◽

Most Recent Common Ancestor

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed an unprecedented challenge to public health in Southeast Asia, a tropical region with limited resources. This study aimed to investigate the evolutionary dynamics and spatiotemporal patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the region.Materials and Methods: A total of 1491 complete SARS-CoV-2 genome sequences from 10 Southeast Asian countries were downloaded from the Global Initiative on Sharing Avian Influenza Data (GISAID) database on November 17, 2020. The evolutionary relationships were assessed using maximum likelihood (ML) and time-scaled Bayesian phylogenetic analyses, and the phylogenetic clustering was tested using principal component analysis (PCA). The spatial patterns of SARS-CoV-2 spread within Southeast Asia were inferred using the Bayesian stochastic search variable selection (BSSVS) model. The effective population size (Ne) trajectory was inferred using the Bayesian Skygrid model.Results: Four major clades (including one potentially endemic) were identified based on the maximum clade credibility (MCC) tree. Similar clustering was yielded by PCA; the first three PCs explained 46.9% of the total genomic variations among the samples. The time to the most recent common ancestor (tMRCA) and the evolutionary rate of SARS-CoV-2 circulating in Southeast Asia were estimated to be November 28, 2019 (September 7, 2019 to January 4, 2020) and 1.446 × 10−3 (1.292 × 10−3 to 1.613 × 10−3) substitutions per site per year, respectively. Singapore and Thailand were the two most probable root positions, with posterior probabilities of 0.549 and 0.413, respectively. There were high-support transmission links (Bayes factors exceeding 1,000) in Singapore, Malaysia, and Indonesia; Malaysia involved the highest number (7) of inferred transmission links within the region. A twice-accelerated viral population expansion, followed by a temporary setback, was inferred during the early stages of the pandemic in Southeast Asia.Conclusions: With available genomic data, we illustrate the phylogeography and phylodynamics of SARS-CoV-2 circulating in Southeast Asia. Continuous genomic surveillance and enhanced strategic collaboration should be listed as priorities to curb the pandemic, especially for regional communities dominated by developing countries.

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Explaining the geographical origins of seasonal influenza A (H3N2)

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2016.1312 ◽

2016 ◽

Vol 283 (1838) ◽

pp. 20161312 ◽

Cited By ~ 9

Author(s):

Frank Wen ◽

Trevor Bedford ◽

Sarah Cobey

Keyword(s):

Influenza A ◽

Seasonal Influenza ◽

Evolutionary Dynamics ◽

Spatial Dynamics ◽

Basic Reproductive Number ◽

Viral Population ◽

Reproductive Number ◽

Antigenic Evolution ◽

Migratory Patterns ◽

Seasonal Population

Most antigenically novel and evolutionarily successful strains of seasonal influenza A (H3N2) originate in East, South and Southeast Asia. To understand this pattern, we simulated the ecological and evolutionary dynamics of influenza in a host metapopulation representing the temperate north, tropics and temperate south. Although seasonality and air traffic are frequently used to explain global migratory patterns of influenza, we find that other factors may have a comparable or greater impact. Notably, a region's basic reproductive number ( R 0 ) strongly affects the antigenic evolution of its viral population and the probability that its strains will spread and fix globally: a 17–28% higher R 0 in one region can explain the observed patterns. Seasonality, in contrast, increases the probability that a tropical (less seasonal) population will export evolutionarily successful strains but alone does not predict that these strains will be antigenically advanced. The relative sizes of different host populations, their birth and death rates, and the region in which H3N2 first appears affect influenza's phylogeography in different but relatively minor ways. These results suggest general principles that dictate the spatial dynamics of antigenically evolving pathogens and offer predictions for how changes in human ecology might affect influenza evolution.

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The Genomic Landscape of Divergence Across the Speciation Continuum in Island-Colonising Silvereyes (Zosterops lateralis)

G3 Genes|Genome|Genetics ◽

10.1534/g3.120.401352 ◽

2020 ◽

Vol 10 (9) ◽

pp. 3147-3163

Author(s):

Ashley T Sendell-Price ◽

Kristen C Ruegg ◽

Eric C Anderson ◽

Claudio S Quilodrán ◽

Benjamin M Van Doren ◽

...

Keyword(s):

Gene Flow ◽

Evolutionary Dynamics ◽

Population Genomics ◽

A Priori ◽

Genomic Islands ◽

Zosterops Lateralis ◽

Genome Wide ◽

Genomic Landscape ◽

Speciation Continuum ◽

Genomic Patterns

Abstract Inferring the evolutionary dynamics at play during the process of speciation by analyzing the genomic landscape of divergence is a major pursuit in population genomics. However, empirical assessments of genomic landscapes under varying evolutionary scenarios that are known a priori are few, thereby limiting our ability to achieve this goal. Here we combine RAD-sequencing and individual-based simulations to evaluate the genomic landscape of divergence in the silvereye (Zosterops lateralis). Using pairwise comparisons that differ in divergence timeframe and the presence or absence of gene flow, we document how genomic patterns accumulate along the speciation continuum. In contrast to previous predictions, our results provide limited support for the idea that divergence accumulates around loci under divergent selection or that genomic islands widen with time. While a small number of genomic islands were found in populations diverging with and without gene flow, in few cases were SNPs putatively under selection tightly associated with genomic islands. The transition from localized to genome-wide levels of divergence was captured using individual-based simulations that considered only neutral processes. Our results challenge the ubiquity of existing verbal models that explain the accumulation of genomic differences across the speciation continuum and instead support the idea that divergence both within and outside of genomic islands is important during the speciation process.

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The population genomics of adaptive loss of function

Heredity ◽

10.1038/s41437-021-00403-2 ◽

2021 ◽

Author(s):

J. Grey Monroe ◽

John K. McKay ◽

Detlef Weigel ◽

Pádraic J. Flood

Keyword(s):

Population Genetics ◽

Evolutionary Dynamics ◽

Population Genomics ◽

Genomic Variation ◽

Genomic Diversity ◽

Loss Of Function ◽

Population Genomic ◽

Genomic Tools ◽

Challenges And Opportunities ◽

Early View

AbstractDiscoveries of adaptive gene knockouts and widespread losses of complete genes have in recent years led to a major rethink of the early view that loss-of-function alleles are almost always deleterious. Today, surveys of population genomic diversity are revealing extensive loss-of-function and gene content variation, yet the adaptive significance of much of this variation remains unknown. Here we examine the evolutionary dynamics of adaptive loss of function through the lens of population genomics and consider the challenges and opportunities of studying adaptive loss-of-function alleles using population genetics models. We discuss how the theoretically expected existence of allelic heterogeneity, defined as multiple functionally analogous mutations at the same locus, has proven consistent with empirical evidence and why this impedes both the detection of selection and causal relationships with phenotypes. We then review technical progress towards new functionally explicit population genomic tools and genotype-phenotype methods to overcome these limitations. More broadly, we discuss how the challenges of studying adaptive loss of function highlight the value of classifying genomic variation in a way consistent with the functional concept of an allele from classical population genetics.

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Comparative Population Genetics in the Human Gut Microbiome

10.1101/2021.03.02.433642 ◽

2021 ◽

Author(s):

William R. Shoemaker ◽

Daisy Chen ◽

Nandita R. Garud

Keyword(s):

Population Genetics ◽

Gut Microbiome ◽

Evolutionary Dynamics ◽

Population Genomics ◽

Purifying Selection ◽

Human Gut ◽

Human Gut Microbiome ◽

New Genes ◽

Compare And Contrast ◽

Comparative Population

AbstractThe genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of co-existing species in this microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we re-analyzed patterns of purifying selection across ~40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

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Linking influenza virus evolution within and between human hosts

10.1101/812016 ◽

2019 ◽

Cited By ~ 1

Author(s):

Katherine S. Xue ◽

Jesse D. Bloom

Keyword(s):

Evolutionary Dynamics ◽

Global Scale ◽

Influenza Viruses ◽

Viral Population ◽

Global Evolution ◽

Synonymous Sites ◽

Host Genetic ◽

Selection For ◽

Human Infections ◽

Individual Human

AbstractInfluenza viruses rapidly diversify within individual human infections. Several recent studies have deep-sequenced clinical influenza infections to identify viral variation within hosts, but it remains unclear how within-host mutations fare in the global viral population. Here, we compare viral variation within and between hosts to link influenza’s evolutionary dynamics across scales. Synonymous sites evolve at similar rates at both scales, indicating that global evolution at these putatively neutral sites results from the accumulation of within-host variation. However, nonsynonymous mutations are depleted in global viral populations compared to within hosts, suggesting that selection purges many of the protein-altering changes that arise within hosts. The exception is at antigenic sites, where selection detectably favors nonsynonymous mutations at the global scale, but not within hosts. These results suggest that selection against deleterious mutations and selection for antigenic change are the main forces that transform influenza’s within-host genetic variation into global evolution.

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Rapid evolution and horizontal gene transfer in the genome of a male-killing Wolbachia

10.1101/2020.11.16.385294 ◽

2020 ◽

Author(s):

Tom Hill ◽

Robert L. Unckless ◽

Jessamyn I. Perlmutter

Keyword(s):

Gene Transfer ◽

Horizontal Gene Transfer ◽

Host Species ◽

Evolutionary Dynamics ◽

Population Genomics ◽

Rapid Evolution ◽

Male Killing ◽

Show Evidence ◽

Bacterial Endosymbionts ◽

Unique Genes

AbstractWolbachia are widespread bacterial endosymbionts that infect a large proportion of insect species. While some strains of this bacteria do not cause observable host phenotypes, many strains of Wolbachia have some striking effects on their hosts. In some cases, these symbionts manipulate host reproduction to increase the fitness of infected, transmitting females. Here we examine the genome and population genomics of a male-killing Wolbachia strain, wInn, that infects Drosophila innubila mushroom-feeding flies. We compared wInn to other closely-related Wolbachia genomes to understand the evolutionary dynamics of specific genes. The wInn genome is similar in overall gene content to wMel, but also contains many unique genes and repetitive elements that indicate distinct gene transfers between wInn and non-Drosophila hosts. We also find that genes in the Wolbachia prophage and Octomom regions are particularly rapidly evolving, including those putatively or empirically confirmed to be involved in host pathogenicity. Of the genes that rapidly evolve, many also show evidence of recent horizontal transfer among Wolbachia symbiont genomes, suggesting frequent movement of rapidly evolving regions among individuals. These dynamics of rapid evolution and horizontal gene transfer across the genomes of several Wolbachia strains and divergent host species may be important underlying factors in Wolbachia’s global success as a symbiont.

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Viral population genomics reveals host and infectivity impact on SARS-CoV-2 adaptive landscape

10.1101/2021.12.30.474516 ◽

2021 ◽

Author(s):

Kaitlyn Gayvert ◽

Richard Copin ◽

Sheldon McKay ◽

Ian Setliff ◽

Wei Keat Lim ◽

...

Keyword(s):

T Cell ◽

Population Genomics ◽

Cell Epitope ◽

Purifying Selection ◽

Spike Protein ◽

Viral Population ◽

Adaptive Landscape ◽

T Cell Epitopes ◽

Treatment Development ◽

The Impact

Public health surveillance, drug treatment development, and optimization of immunological interventions all depend on understanding pathogen adaptation, which differ for specific pathogens. SARS-CoV-2 is an exceptionally successful human pathogen, yet complete understanding of the forces driving its evolution is lacking. Here, we leveraged almost four million SARS-CoV-2 sequences originating mostly from non-vaccinated naive patients to investigate the impact of functional constraints and natural immune pressures on the sequence diversity of the SARS-CoV-2 genome. Overall, we showed that the SARS-CoV-2 genome is under strong and intensifying levels of purifying selection with a minority of sites under diversifying pressure. With a particular focus on the spike protein, we showed that sites under selection were critical for protein stability and virus fitness related to increased infectivity and/or reduced neutralization by convalescent sera. We investigated the genetic diversity of SARS-CoV-2 B and T cell epitopes and determined that the currently known T cell epitope sequences were highly conserved. Outside of the spike protein, we observed that mutations under selection in variants of concern can be associated to beneficial outcomes for the virus. Altogether, the results yielded a comprehensive map of all sites under selection across the entirety of SARS-CoV-2 genome, highlighting targets for future studies to better understand the virus spread, evolution and success.

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Antigenic waves of virus–immune coevolution

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2103398118 ◽

2021 ◽

Vol 118 (27) ◽

pp. e2103398118

Author(s):

Jacopo Marchi ◽

Michael Lässig ◽

Aleksandra M. Walczak ◽

Thierry Mora

Keyword(s):

Mathematical Theory ◽

Seasonal Influenza ◽

Evolutionary Dynamics ◽

Cross Reactivity ◽

Host Population ◽

Viral Population ◽

Immune Systems ◽

Persistence Time ◽

Immune Pressure ◽

Finite Dimensional

The evolution of many microbes and pathogens, including circulating viruses such as seasonal influenza, is driven by immune pressure from the host population. In turn, the immune systems of infected populations get updated, chasing viruses even farther away. Quantitatively understanding how these dynamics result in observed patterns of rapid pathogen and immune adaptation is instrumental to epidemiological and evolutionary forecasting. Here we present a mathematical theory of coevolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections. We show the emergence of an antigenic wave that is pushed forward and canalized by cross-reactivity. We obtain analytical results for shape, speed, and angular diffusion of the wave. In particular, we show that viral–immune coevolution generates an emergent timescale, the persistence time of the wave’s direction in antigenic space, which can be much longer than the coalescence time of the viral population. We compare these dynamics to the observed antigenic turnover of influenza strains, and we discuss how the dimensionality of antigenic space impacts the predictability of the evolutionary dynamics. Our results provide a concrete and tractable framework to describe pathogen–host coevolution.

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