Population dynamics can be inferred from genetic sequence data by using phylodynamic methods. These methods typically quantify the dynamics in unstructured populations or assume migration rates and effective population sizes to be constant through time in structured populations. When considering rates to vary through time in structured populations, the number of parameters to infer increases rapidly and the available data might not be sufficient to inform these. Additionally, it is often of interest to know what predicts these parameters rather than knowing the parameters themselves. Here, we introduce a method to infer the predictors for time-varying migration rates and effective population sizes by using a generalized linear model (GLM) approach under the marginal approximation of the structured coalescent. Using simulations, we show that our approach is able to reliably infer the model parameters and its predictors from phylogenetic trees. Furthermore, when simulating trees under the structured coalescent, we show that our new approach outperforms the discrete trait GLM model. We then apply our framework to a previously described Ebola virus dataset, where we infer the parameters and its predictors from genome sequences while accounting for phylogenetic uncertainty. We infer weekly cases to be the strongest predictor for effective population size and geographic distance the strongest predictor for migration. This approach is implemented as part of the BEAST2 package MASCOT, which allows us to jointly infer population dynamics, i.e. the parameters and predictors, within structured populations, the phylogenetic tree, and evolutionary parameters.
The emergence of the early COVID-19 epidemic in the United States (U.S.) went largely undetected, due to a lack of adequate testing and mitigation efforts. The city of New Orleans, Louisiana experienced one of the earliest and fastest accelerating outbreaks, coinciding with the annual Mardi Gras festival, which went ahead without precautions. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large, crowded events may have accelerated early transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana initially had limited sequence diversity compared to other U.S. states, and that one successful introduction of SARS-CoV-2 led to almost all of the early SARS-CoV-2 transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras and that the festival dramatically accelerated transmission, eventually leading to secondary localized COVID-19 epidemics throughout the Southern U.S.. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate COVID-19 epidemics on a local and regional scale.
Studies were carried out to determine whether the in vitro capacity of adherent peritoneal cells to replicate herpes simplex virus type 1 (HSV-1) might correlate with the in vivo susceptibility of mice genetically resistant, moderately susceptible, or very susceptible to HSV-1 infection. Unstimulated and proteose peptonestimulated monolayers restricted viral replication when infected immediately, but replicated HSV-1 when infected after 3 to 7 days of culture. Macrophages from resistant C57B1/6 mice restricted HSV-1 replication significantly better than cells from susceptible mice. This function did not segregate with resistance, since macrophages from resistant F1 mice failed to restrict HSV-1 replication. Induction of peritoneal exudate cells with thioglycolate yielded cells capable of replicating HSV-1 when infected immediately after plating and after 4 days of culture.Using inbred strains of adult mice, we have demonstrated mice genetically resistant, moderately susceptible, and very susceptible to an intraperitoneal inoculation with a virulent strain of herpes simplex virus type 1 (HSV-1) (13). Although all seven HSV-1 strains tested to date have yielded the same pattern of resistance in the three prototype mouse strains (C57BI/6 = resistant; BALB/c = moderately susceptible; and A/J = very susceptible), the various strains of virus were shown to demonstrate weak to high virulence (13). When inoculated intracerebrally, all three strains of mice were found to be very susceptible, indicating that if virus gets to the target cells it is capable of replicating and killing in all three strains. Earlier observations (C. Lopez, in Oncogenesis and Herpesviruses, in press) as well as more recent findings indicate that resistance is immunological in nature. Thus resistance in mice can be abrogated by treatment of resistant mice by agents which impair either macrophage or lymphocyte (probably T-cell) function. In addition, reconstitution of lethally irradiated susceptible mice with bone marrow cells from resistant F1 mice yielded mice resistant to HSV-1 infection (Lopez, in press).The early experiments of Johnson (12) demonstrated that the in vitro replication of HSV in peritoneal macrophages from suckling mice could be correlated with their susceptibility to intracerebral inoculation of the virus. Macrophages from adult mice restricted the replication of the virus in vitro, and that was associated with in vivo resistance to HSV. These observations were followed by studies of Zisman et al.(23), who demonstrated that impairing macro-phage function in adult mice resulted in an increased susceptibility to an intraperitoneal inoculation with HSV. Hirsch et al. (11) additionally demonstrated the protective effect of adult macrophages in suckling mice. These studies and the more recent in vitro studies of Stevens and Cook (21) indicate an important role for the macrophage, and in particular its capacity to restrict the replication of HSV, in resistance to the virus infection.
The latitudinal diversity gradient (LDG) is arguably one of the most striking patterns in nature. The global increase in species richness toward the tropics across continents and taxonomic groups stimulated the formulation of many hypotheses to explain the underlying mechanisms of this pattern. We evaluated several of these hypotheses to explain spatial diversity patterns in the butterfly family, Nymphalidae, by assessing the contributions of speciation, extinction, and dispersal to the LDG, and also the extent to which these processes differ among regions at the same latitude. We generated a new, time-calibrated phylogeny of Nymphalidae based on 10 gene fragments and containing ca. 2,800 species (∼45% of extant diversity). Neither speciation nor extinction rate variations consistently explain the LDG among regions because temporal diversification dynamics differ greatly across longitude. For example, we found that Neotropical nymphalid diversity results from low extinction rates, not high speciation rates, and that biotic interchanges with other regions were rare. Southeast Asia was also characterized by a low speciation rate but, unlike the Neotropics, was the main source of dispersal events through time. Our results suggest that global climate change throughout the Cenozoic, particularly during the Eocene-Oligocene transition, combined with the conserved ancestral tropical niches, played a major role in generating the modern LDG of butterflies.
Recombination is a process that unlinks neighbouring loci allowing for independent evolutionary trajectories within genomes of many organisms. If not properly accounted for, recombination can compromise many evolutionary analyses. In addition, when dealing with organisms that are not obligately sexually reproducing, recombination gives insight into the rate at which distinct genetic lineages come into contact. Since June, 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) has caused 1106 laboratory-confirmed infections, with 421 MERS-CoV associated deaths as of April 16, 2015. Although bats are considered as the likely ultimate source of zoonotic betacoronaviruses, dromedary camels have been consistently implicated as the source of current human infections in the Middle East. In this paper we use phylogenetic methods and simulations to show that MERS-CoV genome has likely undergone numerous recombinations recently. Recombination in MERS-CoV implies frequent co-infection with distinct lineages of MERS-CoV, probably in camels given the current understanding of MERS-CoV epidemiology.
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