We propose a novel, non-discriminatory classification of monkeypox virus diversity. Together with the World Health Organization, we named three clades (I, IIa and IIb) in order of detection. Within ...IIb, the cause of the current global outbreak, we identified multiple lineages (A.1, A.2, A.1.1 and B.1) to support real-time genomic surveillance.
Abstract
Horizontal transfer, gene loss, and duplication result in dynamic bacterial genomes shaped by a complex mixture of different modes of evolution. Closely related strains can differ in the ...presence or absence of many genes, and the total number of distinct genes found in a set of related isolates-the pan-genome-is often many times larger than the genome of individual isolates. We have developed a pipeline that efficiently identifies orthologous gene clusters in the pan-genome. This pipeline is coupled to a powerful yet easy-to-use web-based visualization for interactive exploration of the pan-genome. The visualization consists of connected components that allow rapid filtering and searching of genes and inspection of their evolutionary history. For each gene cluster, panX displays an alignment, a phylogenetic tree, maps mutations within that cluster to the branches of the tree and infers gain and loss of genes on the core-genome phylogeny. PanX is available at pangenome.de. Custom pan-genomes can be visualized either using a web server or by serving panX locally as a browser-based application.
A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The ...outbreak has been declared a pandemic by the WHO on Mar 11, 2020. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterise our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.
Many new variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been termed variants of concern/interest (VOC/I) because of the greater risk they pose due to possible ...enhanced transmissibility and/or severity, immune escape, diagnostic and/or treatment failure, and reduced vaccine efficacy.
We sought to review the current knowledge of emerging SARS-CoV-2 variants, particularly those deemed VOC/Is: B.1.351, B.1.1.7, and P.1.
MEDLINE and BioRxiv databases, as well as the grey literature, were searched for reports of SARS-CoV-2 variants since November 2020. Relevant articles and their references were screened.
Mutations on the spike protein in particular may affect both affinity for the SARS-CoV-2 cell receptor ACEII and antibody binding. These VOC/Is often share similar mutation sets. The N501Y mutation is shared by the three main VOCs: B.1.1.7, first identified in the United Kingdom, P.1, originating from Brazil, and B.1.351, first described in South Africa. This mutation likely increases transmissibility by increasing affinity for ACEII. The B.1.351 and P.1 variants also display the E484K mutation which decreases binding of neutralizing antibodies, leading to partial immune escape; this favours reinfections, and decreases the in vitro efficacy of some antibody therapies or vaccines. Those mutations may also have phenotypical repercussions of greater severity. Furthermore, the accumulation of mutations poses a diagnostic risk (lowered when using multiplex assays), as seen for some assays targeting the S gene. With ongoing surveillance, many new VOC/Is have been identified. The emergence of the E484K mutation independently in different parts of the globe may reflect the adaptation of SARS-CoV-2 to humans against a background of increasing immunity.
These VOC/Is are increasing in frequency globally and pose challenges to any herd immunity approach to managing the pandemic. While vaccination is ongoing, vaccine updates may be prudent. The virus continues to adapt to transmission in humans, and further divergence from the initial Wuhan sequences is expected.
Seasonal influenza viruses evolve rapidly, allowing them to evade immunity in their human hosts and reinfect previously infected individuals. Similarly, vaccines against seasonal influenza need to be ...updated frequently to protect against an evolving virus population. We have thus developed a processing pipeline and browser-based visualization that allows convenient exploration and analysis of the most recent influenza virus sequence data. This web-application displays a phylogenetic tree that can be decorated with additional information such as the viral genotype at specific sites, sampling location and derived statistics that have been shown to be predictive of future virus dynamics. In addition, mutation, genotype and clade frequency trajectories are calculated and displayed.
Python and Javascript source code is freely available from https://github.com/blab/nextflu, while the web-application is live at http://nextflu.org.
tbedford@fredhutch.org.
Abstract
Mutations that accumulate in the genome of cells or viruses can be used to infer their evolutionary history. In the case of rapidly evolving organisms, genomes can reveal their detailed ...spatiotemporal spread. Such phylodynamic analyses are particularly useful to understand the epidemiology of rapidly evolving viral pathogens. As the number of genome sequences available for different pathogens has increased dramatically over the last years, phylodynamic analysis with traditional methods becomes challenging as these methods scale poorly with growing datasets. Here, we present TreeTime, a Python-based framework for phylodynamic analysis using an approximate Maximum Likelihood approach. TreeTime can estimate ancestral states, infer evolution models, reroot trees to maximize temporal signals, estimate molecular clock phylogenies and population size histories. The runtime of TreeTime scales linearly with dataset size.
Abstract
Summary
Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a ...bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike.
Availability and implementation
All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.
Genealogies of rapidly adapting populations Neher, Richard A.; Hallatschek, Oskar
Proceedings of the National Academy of Sciences - PNAS,
01/2013, Letnik:
110, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The genetic diversity of a species is shaped by its recent evolutionary history and can be used to infer demographic events or selective sweeps. Most inference methods are based on the null ...hypothesis that natural selection is a weak or infrequent evolutionary force. However, many species, particularly pathogens, are under continuous pressure to adapt in response to changing environments. A statistical framework for inference from diversity data of such populations is currently lacking. Towards this goal, we explore the properties of genealogies in a model of continual adaptation in asexual populations. We show that lineages trace back to a small pool of highly fit ancestors, in which almost simultaneous coalescence of more than two lineages frequently occurs. Whereas such multiple mergers are unlikely under the neutral coalescent, they create a unique genetic footprint in adapting populations. The site frequency spectrum of derived neutral alleles, for example, is nonmonotonic and has a peak at high frequencies, whereas Tajima’s D becomes more and more negative with increasing sample size. Because multiple merger coalescents emerge in many models of rapid adaptation, we argue that they should be considered as a null model for adapting populations.
To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetics inferences are based on frameworks ...assuming that adaptive evolution is rare. But if positive selection operates on many loci simultaneously, as has recently been suggested for many species, including animals such as flies, then a different approach is necessary. In this review, I discuss recent progress in characterizing and understanding evolution in rapidly adapting populations, in which random associations of mutations with genetic backgrounds of different fitness, i.e., genetic draft, dominate over genetic drift. As a result, neutral genetic diversity depends weakly on population size but strongly on the rate of adaptation or more generally the variance in fitness. Coalescent processes with multiple mergers, rather than Kingman's coalescent, are appropriate genealogical models for rapidly adapting populations, with important implications for population genetics inference.
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