Nextclade: clade assignment, mutation calling and quality control for viral genomes

The variants of concern (VoCs) of SARS-CoV-2 have highlighted the need for a global molecular surveillance of pathogens via whole genome sequencing. Such sequencing, for SARS-CoV-2 and other pathogens, is performed by an ever increasing number of labs across the globe, resulting in an increased need for an easy, fast, and decentralized analysis of initial data. Nextclade aligns viral genomes to a reference sequence, calculates several quality control (QC) metrics, assigns sequences to a clade or variant, and identifies changes in the viral proteins relative to the reference sequence. Nextclade is available as a command-line tool and as a web application with completely client based processing, meaning that sequence data doesn't leave the user's browser

Urgent need for a non-discriminatory and non-stigmatizing nomenclature for monkeypox virus

Free PMC article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451062/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.info:eu-repo/semantics/publishedVersio

Emergence of SARS-CoV-2 Omicron lineages BA.4 and BA.5 in South Africa

Three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern predominantly drove South Africa's fourth COVID-19 wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild type amino acid at Q493.The two lineages only differ outside of the spike region. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature . BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.08 - 0.09) and 0.10 (95% CI: 0.09 - 0.11) per day respectively over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus

Viral genetic clustering and transmission dynamics of the 2022 mpox outbreak in Portugal

Pathogen genome sequencing during epidemics enhances our ability to identify and understand suspected clusters and investigate their relationships. Here, we combine genomic and epidemiological data of the 2022 mpox outbreak to better understand early viral spread, diversification and transmission dynamics. By sequencing 52% of the confirmed cases in Portugal, we identified the mpox virus sublineages with the highest impact on case numbers and fitted them into a global context, finding evidence that several international sublineages probably emerged or spread early in Portugal. We estimated a 62% infection reporting rate and that 1.3% of the population of men who have sex with men in Portugal were infected. We infer the critical role played by sexual networks and superspreader gatherings, such as sauna attendance, in the dissemination of mpox virus. Overall, our findings highlight genomic epidemiology as a tool for the real-time monitoring and control of mpox epidemics, and can guide future vaccine policy in a highly susceptible population.info:eu-repo/semantics/publishedVersio

Documenting the Unauthorized: Political Responses to Unauthorized Immigration

Cultural prejudice rather than self interest is the conventional wisdom for why voters respond negatively to immigration. Using a new measure of unauthorized immigrants based on self-reported invalid social security numbers, we show that voters' responses are more nuanced than mere prejudice against minorities. Using county level data from the U.S. state of Georgia, we find that voters in counties with above median levels of unauthorized workers are more likely to support the Republican party. We also find that wealthier counties and wealthier voters are most likely to respond negatively to the unauthorized. Our evidence warns against arguments that depict opposition to immigration as motivated solely by xenophobia and cultural fears among lower income whites

States Of Discontent

Latin America’s recent inclusionary turn centers on changing relationships between the popular sectors and the state. Yet the new inclusion unfolds in a region in which most states are weak and prone to severe pathologies, such as corruption, inefficiency, and particularism. The first part of the chapter outlines an argument, developed at more length elsewhere, regarding how “state crises” helped drive the consolidation of three distinct party system trajectories among the eight South American countries where the Left would eventually win power. The second part of the chapter argues that these trajectories differed in three ways that likely conditioned how the concomitant inclusionary Left turn unfolded in each case: the institutionalization of left-wing parties, the occurrence of state transformation via constitutional reform, and the level of state capacity. The discussion helps highlight the central role of the state and its pathologies in both driving alternative paths of political development and in conditioning the politics of inclusion. By putting the emphasis on the state and its pathologies, we can better consider not just the sources of sociopolitical exclusion but also the limits of sociopolitical inclusion

LAPIS is a fast web API for massive open virus sequencing data

Background Recent epidemic outbreaks such as the SARS-CoV-2 pandemic and the mpox outbreak in 2022 have demonstrated the value of genomic sequencing data for tracking the origin and spread of pathogens. Laboratories around the globe generated new sequences at unprecedented speed and volume and bioinformaticians developed new tools and dashboards to analyze this wealth of data. However, a major challenge that remains is the lack of simple and efficient approaches for accessing and processing sequencing data. Results The Lightweight API for Sequences (LAPIS) facilitates rapid retrieval and analysis of genomic sequencing data through a REST API. It supports complex mutation- and metadata-based queries and can perform aggregation operations on massive datasets. LAPIS is optimized for typical questions relevant to genomic epidemiology. Using a newly-developed in-memory database engine, it has a high speed and throughput: between 25 January and 4 February 2023, the SARS-CoV-2 instance of LAPIS, which contains 14.5 million sequences, processed over 20 million requests with a mean response time of 411 ms and a median response time of 1 ms. LAPIS is the core engine behind our dashboards on genspectrum.org and we currently maintain public LAPIS instances for SARS-CoV-2 and mpox. Conclusions Powered by an optimized database engine and available through a web API, LAPIS enhances the accessibility of genomic sequencing data. It is designed to serve as a common backend for dashboards and analyses with the potential to be integrated into common database platforms such as GenBank.ISSN:1471-210

CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants

The CoV-Spectrum website supports the identification of new SARS-CoV-2 variants of concern and the tracking of known variants. Its flexible amino acid and nucleotide mutation search allows querying of variants before they are designated by a lineage nomenclature system. The platform brings together SARS-CoV-2 data from different sources and applies analyses. Results include the proportion of different variants over time, their demographic and geographic distributions, common mutations, hospitalization and mortality probabilities, estimates for transmission fitness advantage and insights obtained from wastewater samples.ISSN:1367-4803ISSN:1460-205

A framework for automated scalable designation of viral pathogen lineages from genomic data.

Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets

A framework for automated scalable designation of viral pathogen lineages from genomic data.

Acknowledgements: This study was funded in part by the Austrian Science Fund (FWF) project I 6440-N to M.T.W. This study was funded in part by CDC award BAA 200-2021-11554 to R.C.-D. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper. We gratefully acknowledge O. Pybus and S. Bell for contributing to early discussions on the topic. We also thank all the volunteers who have worked on finding new Pango lineages.Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets