scholarly journals Modeling the growth and decline of pathogen effective population size provides insight into epidemic dynamics and drivers of antimicrobial resistance

2017 ◽  
Author(s):  
Erik M. Volz ◽  
Xavier Didelot
Keyword(s):  
Growth Rate ◽  
Population Size ◽  
Effective Population Size ◽  
Growth Rates ◽  
Sequence Data ◽  
Demographic History ◽  
Parametric Models ◽  
Effective Population ◽  
Epidemic Dynamics ◽  
Non Parametric

AbstractNon-parametric population genetic modeling provides a simple and flexible approach for studying demographic history and epidemic dynamics using pathogen sequence data. Existing Bayesian approaches are premised on stationary stochastic processes which may provide an unrealistic prior for epidemic histories which feature extended period of exponential growth or decline. We show that non-parametric models defined in terms of the growth rate of the effective population size can provide a more realistic prior for epidemic history. We propose a non-parametric autoregressive model on the growth rate as a prior for effective population size, which corresponds to the dynamics expected under many epidemic situations. We demonstrate the use of this model within a Bayesian phylodynamic inference framework. Our method correctly reconstructs trends of epidemic growth and decline from pathogen genealogies even when genealogical data is sparse and conventional skyline estimators erroneously predict stable population size. We also propose a regression approach for relating growth rates of pathogen effective population size and time-varying variables that may impact the replicative fitness of a pathogen. The model is applied to real data from rabies virus and Staphylococcus aureus epidemics. We find a close correspondence between the estimated growth rates of a lineage of methicillin-resistant S. aureus and population-level prescription rates of β-lactam antibiotics. The new models are implemented in an open source R package called skygrowth which is available at https://mrc-ide.github.io/skygrowth/.

scholarly journals Maximum likelihood inference of pathogen population size history from a phylogeny

2021 ◽  
Author(s):  
Xavier Didelot ◽  
Erik M Volz
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Sequence Data ◽  
Demographic History ◽  
Genetic Data ◽  
Parametric Models ◽  
Process Models ◽  
Effective Population ◽  
Latent Process ◽  
Non Parametric

ABSTRACTInference of effective population size from genomic data can provide unique information about demographic history, and when applied to pathogen genetic data can also provide insights into epidemiological dynamics. Non-parametric models for population dynamics combined with molecular clock models which relate genetic data to time have enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The theory for non-parametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on non-parametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the models to genetic data from several pathogen data sets.

scholarly journals Inferring pandemic growth rates from sequence data

2012 ◽  
Vol 9 (73) ◽  
pp. 1797-1808 ◽  
Author(s):  
Eric de Silva ◽  
Neil M. Ferguson ◽  
Christophe Fraser
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Sequence Data ◽  
Simulated Data ◽  
Parametric Methods ◽  
Sampling Strategies ◽  
Size Estimation ◽  
Effective Population ◽  
Population Size Estimates ◽  
Non Parametric

Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic.

Elusive does not always equal rare: genetic assessment of a protected Gila monster (Heloderma suspectum) population in Saguaro National Park, Arizona

2017 ◽  
Vol 38 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Victoria Sophia Farrar ◽  
Taylor Edwards ◽  
Kevin Edward Bonine
Keyword(s):  
Genetic Diversity ◽  
Population Size ◽  
Effective Population Size ◽  
National Parks ◽  
Sonoran Desert ◽  
National Park ◽  
Sequence Data ◽  
Demographic History ◽  
Effective Population ◽  
Heloderma Suspectum

Population genetic baselines for species perceived to be at-risk are crucial for monitoring population trends and making well-informed management decisions. We characterized the genetic status of a population of Gila monsters (Heloderma suspectum), a large venomous lizard native to deserts of the southwestern United States and northern Mexico, by sampling 100 individuals in Sonoran Desert upland habitat at Saguaro National Park, Arizona, USA. We used 18 microsatellite markers, along with 1195 bp of sequence data from the mitochondrial DNA 12S locus, to examine genetic diversity, estimate effective population size, and assess demographic history. Despite suburban development adjacent to the study area, we observed high genetic diversity with uninhibited gene flow within this protected population. We estimated effective population size (Ne) for the total sample area (80 km2) using the linkage disequilibrium method in NeEstimator to be 94 individuals (95% confidence interval: 80.7-111.2). In 2011, we used capture-recapture methods to estimate that 80 adult Gila monsters (95% CI = 37-225) inhabited the area along the 14-km transect that we surveyed most frequently; probability of detecting resident Gila monsters during surveys was <0.01, highlighting the challenges of studying the species. Despite being considered an elusive and thus potentially rare species, these data reveal that in this protected environment the population appears healthy and robust. The results provide an important genetic baseline for future studies and monitoring, and exemplify the success of protective population measures in National Parks and under Arizona state laws.

scholarly journals Low effective population size and high spatial genetic structure of black poplar populations from the Oder valley in Poland

2021 ◽  
Vol 78 (2) ◽  
Author(s):  
Błażej Wójkiewicz ◽  
Andrzewj Lewandowski ◽  
Weronika B. Żukowska ◽  
Monika Litkowiec ◽  
Witold Wachowiak
Keyword(s):  
Genetic Structure ◽  
Genetic Resources ◽  
Population Size ◽  
Effective Population Size ◽  
Spatial Genetic Structure ◽  
Demographic History ◽  
River Valley ◽  
Ex Situ ◽  
Effective Population ◽  
Black Poplar

Abstract Context Black poplar (Populus nigra L.) is a keystone species of European riparian ecosystems that has been negatively impacted by riverside urbanization for centuries. Consequently, it has become an endangered tree species in many European countries. The establishment of a suitable rescue plan of the remaining black poplar forest stands requires a preliminary knowledge about the distribution of genetic variation among species populations. However, for some parts of the P. nigra distribution in Europe, the genetic resources and demographic history remain poorly recognized. Aims Here, we present the first study on identifying and characterizing the genetic resources of black poplar from the Oder valley in Poland. This study (1) assessed the genetic variability and effective population size of populations and (2) examined whether gene flow is limited by distance or there is a single migrant pool along the studied river system. Methods A total of 582 poplar trees derived from nine black poplar populations were investigated with nuclear microsatellite markers. Results (1) The allelic richness and heterozygosity level were high and comparable between populations. (2) The genetic structure of the studied poplar stands was not homogenous. (3) The signatures of past bottlenecks were detected. Conclusion Our study (1) provides evidence for genetic substructuring of natural black poplar populations from the studied river catchment, which is not a frequent phenomenon reported for this species in Europe, and (2) indicates which poplar stands may serve as new genetic conservation units (GCUs) of this species in Europe. Key message The genetic resources of black poplar in the Oder River valley are still substantial compared to those reported for rivers in Western Europe. On the other hand, clear signals of isolation by distance and genetic erosion reflected in small effective population sizes and high spatial genetic structure of the analyzed populations were detected. Based on these findings, we recommend the in situ and ex situ conservation strategies for conserving and restoring the genetic resources of black poplar populations in this strongly transformed by human river valley ecosystem.

scholarly journals Demographic history and divergence of sibling grouse species inferred from whole genome sequencing reveal past effects of climate change

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Song ◽  
Bin Gao ◽  
Peter Halvarsson ◽  
Yun Fang ◽  
Siegfried Klaus ◽  
...  
Keyword(s):  
Climate Change ◽  
Boreal Forest ◽  
Population Size ◽  
Effective Population Size ◽  
Demographic History ◽  
Bird Species ◽  
Future Climate Change ◽  
Effective Population ◽  
Hazel Grouse ◽  
Chinese Grouse

Abstract Background The boreal forest is one of the largest biomes on earth, supporting thousands of species. The global climate fluctuations in the Quaternary, especially the ice ages, had a significant influence on the distribution of boreal forest, as well as the divergence and evolution of species inhabiting this biome. To understand the possible effects of on-going and future climate change it would be useful to reconstruct past population size changes and relate such to climatic events in the past. We sequenced the genomes of 32 individuals from two forest inhabiting bird species, Hazel Grouse (Tetrastes bonasia) and Chinese Grouse (T. sewerzowi) and three representatives of two outgroup species from Europe and China. Results We estimated the divergence time of Chinese Grouse and Hazel Grouse to 1.76 (0.46–3.37) MYA. The demographic history of different populations in these two sibling species was reconstructed, and showed that peaks and bottlenecks of effective population size occurred at different times for the two species. The northern Qilian population of Chinese Grouse became separated from the rest of the species residing in the south approximately 250,000 years ago and have since then showed consistently lower effective population size than the southern population. The Chinese Hazel Grouse population had a higher effective population size at the peak of the Last Glacial Period (approx. 300,000 years ago) than the European population. Both species have decreased recently and now have low effective population sizes. Conclusions Combined with the uplift history and reconstructed climate change during the Quaternary, our results support that cold-adapted grouse species diverged in response to changes in the distribution of palaeo-boreal forest and the formation of the Loess Plateau. The combined effects of climate change and an increased human pressure impose major threats to the survival and conservation of both species.

Global changes explain the long-term demographic trend of the Eurasian common lizard (Squamata: Lacertidae)

2021 ◽  
Author(s):  
Jose L Horreo ◽  
Patrick S Fitze
Keyword(s):  
Growth Rate ◽  
Population Size ◽  
Effective Population Size ◽  
Climatic Changes ◽  
Vegetation Changes ◽  
Effective Population ◽  
Short Term ◽  
Demographic Trend ◽  
Common Lizard

Abstract The demographic trend of a species depends on the dynamics of its local populations, which can be compromised by local or by global phenomena. However, the relevance of local and global phenomena has rarely been investigated simultaneously. Here we tested whether local phenomena compromised a species’ demographic trend using the Eurasian common lizard Zootoca vivipara, the terrestrial reptile exhibiting the widest geographic distribution, as a model species. We analysed the species’ ancient demographic trend using genetic data from its six allopatric genetic clades and tested whether its demographic trend mainly depended on single clades or on global phenomena. Zootoca vivipara’s effective population size increased since 2.3 million years ago and started to increase steeply and continuously from 0.531 Mya. Population growth rate exhibited two maxima, both occurring during global climatic changes and important vegetation changes on the northern hemisphere. Effective population size and growth rate were negatively correlated with global surface temperatures, in line with global parameters driving long-term demographic trends. Zootoca vivipara’s ancient demography was not driven by a single clade, nor by the two clades that colonized huge geographic areas after the last glaciation. The low importance of local phenomena, suggests that the experimentally demonstrated high sensitivity of this species to short-term ecological changes is a response in order to cope with short-term and local changes. This suggests that what affected its long-term demographic trend the most, were not these local changes/responses, but rather the important and prolonged global climatic changes and important vegetation changes on the northern hemisphere, including the opening up of the forest by humans.

Estimating Ancestral Population Sizes and Divergence Times

Genetics ◽  
2003 ◽  
Vol 163 (1) ◽  
pp. 395-404 ◽  
Author(s):  
Jeffrey D Wall
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Sequence Data ◽  
Ancestral Population ◽  
Divergence Times ◽  
Intragenic Recombination ◽  
Intergenic Sequence ◽  
Effective Population ◽  
Recombination Rates ◽  
Population Sizes

Abstract This article presents a new method for jointly estimating species divergence times and ancestral population sizes. The method improves on previous ones by explicitly incorporating intragenic recombination, by utilizing orthologous sequence data from closely related species, and by using a maximum-likelihood framework. The latter allows for efficient use of the available information and provides a way of assessing how much confidence we should place in the estimates. I apply the method to recently collected intergenic sequence data from humans and the great apes. The results suggest that the human-chimpanzee ancestral population size was four to seven times larger than the current human effective population size and that the current human effective population size is slightly &gt;10,000. These estimates are similar to previous ones, and they appear relatively insensitive to assumptions about the recombination rates or mutation rates across loci.

scholarly journals Robust estimation of recent effective population size from number of independent origins in soft sweeps

2018 ◽  
Author(s):  
Bhavin S. Khatri ◽  
Austin Burt
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Demographic History ◽  
Population Sample ◽  
Natural Populations ◽  
Population History ◽  
Effective Population ◽  
Current Frequency ◽  
Population Size Estimate ◽  
Recurrent Mutations

Estimating recent effective population size is of great importance in characterising and predicting the evolution of natural populations. Methods based on nucleotide diversity may underestimate current day effective population sizes due to historical bottlenecks, whilst methods that reconstruct demographic history typically only detect long-term variations. However, soft selective sweeps, which leave a fingerprint of mutational history by recurrent mutations on independent haplotype backgrounds, holds promise of an estimate more representative of recent population history. Here we present a simple and robust method of estimation based only on knowledge of the number of independent recurrent origins and the current frequency of the beneficial allele in a population sample, independent of the strength of selection and age of the mutation. Using a forward time theoretical framework, we show the mean number of origins is a function of θ = 2Nμ and current allele frequency, through a simple equation, and the distribution is approximately Poisson. This estimate is robust to whether mutants pre-existed before selection arose, and is equally accurate for diploid populations with incomplete dominance. For fast (e.g., seasonal) demographic changes compared to time scale for fixation of the mutant allele, and for moderate peak-to-trough ratios, we show our constant population size estimate can be used to bound the maximum and minimum population size. Applied to the Vgsc gene of Anopheles gambiae, we estimate an effective population size of roughly 6 × 107, and including seasonal demographic oscillations, a minimum effective population size greater than 6 × 106 and a maximum less than 3 × 109.

scholarly journals Recent evolution in Rattus norvegicus is shaped by declining effective population size

2015 ◽  
Author(s):  
Eva E Deinum ◽  
Daniel L Halligan ◽  
Rob W Ness ◽  
Yao-Hua Zhang ◽  
Lin Cong ◽  
...  
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Rattus Norvegicus ◽  
Demographic History ◽  
Physical Distance ◽  
House Mice ◽  
Effective Population ◽  
Genome Sequences ◽  
Wild House Mice ◽  
Wild Rats

The brown rat, Rattus norvegicus, is both a notorious pest and a frequently used model in biomedical research. By analysing genome sequences of 12 wild-caught brown rats from their ancestral range in NE China, along with the sequence of a black rat, R. rattus, we investigate the selective and demographic forces shaping variation in the genome. We estimate that the recent effective population size (N_e) of this species = 1.24 x 10^5, based on silent site diversity. We compare patterns of diversity in these genomes with patterns in multiple genome sequences of the house mouse Mus musculus castaneus), which has a much larger N_e. This reveals an important role for variation in the strength of genetic drift in mammalian genome evolution. By a Pairwise Sequentially Markovian Coalescent (PSMC) analysis of demographic history, we infer that there has been a recent population size bottleneck in wild rats, which we date to approximately 20,000 years ago. Consistent with this, wild rat populations have experienced an increased flux of mildly deleterious mutations, which segregate at higher frequencies in protein-coding genes and conserved noncoding elements (CNEs). This leads to negative estimates of the rate of adaptive evolution (alpha) in proteins and CNEs, a result which we discuss in relation to the strongly positive estimates observed in wild house mice. As a consequence of the population bottleneck, wild rats also show a markedly slower decay of linkage disequilibrium with physical distance than wild house mice.

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