Treenome Browser: co-visualization of enormous phylogenies and millions of genomes

Variant mutation G215C in SARS-CoV-2 nucleocapsid enhances viral infection via altered genomic encapsidation

The evolution of SARS-CoV-2 variants and their respective phenotypes represents an important set of tools to understand basic coronavirus biology as well as the public health implications of individual mutations in variants of concern. While mutations outside of spike are not well studied, the entire viral genome is undergoing evolutionary selection, with several variants containing mutations in the central disordered linker region of the nucleocapsid (N) protein. Here, we identify a mutation (G215C), characteristic of the Delta variant, that introduces a novel cysteine into this linker domain, which results in the formation of a more stable N-N dimer. Using reverse genetics, we determined that this cysteine residue is necessary and sufficient for stable dimer formation in a WA1 SARS-CoV-2 background, where it results in significantly increased viral growth both in vitro and in vivo. Mechanistically, we show that the N:G215C mutant has more encapsidation as measured by increased RNA binding to N, N incorporation into virions, and electron microscopy showing that individual virions are larger, with elongated morphologies.

A Phylogenetic Method Identifies Candidate Drivers of the Evolution of the SARS-CoV-2 Mutation Spectrum

The molecular processes that generate new mutations evolve, but the causal mechanisms are largely unknown. In particular, the relative rates of mutation types (e.g. C > T), the mutation spectrum, sometimes vary among closely related species and populations. I present an algorithm for subdividing a phylogeny into distinct mutation spectra. By applying this approach to a SARS-CoV-2 phylogeny comprising approximately 8 million genome sequences, I identify ten shifts in the mutation spectrum. I find strong enrichment consistent with candidate causal amino-acid substitutions in the SARS-CoV-2 polymerase, and strikingly three appearances of the same homoplasious substitution are each associated with decreased C > T relative mutation rates. With rapidly growing genomic datasets, this approach and future extensions promise new insights into the mechanisms of the evolution of mutational processes. Keywords: Mutation Spectrum; Phylogenetic Analysis; SARS-CoV-2 Evolution.

mapPat: tracking pathogens evolution in space and time

Motivation

The COVID-19 pandemic highlighted the importance of genomic surveillance for monitoring pathogens evolution, mitigating the spread of infectious disorders, and informing decision-making by public health authorities. Since the need for the summarization and interpretation of large bodies of data, computational methods are critical for the implementation of effective genomic surveillance strategies.

Results

Here, we introduce mapPat, an R Shiny application for the interactive visualization of pathogens genomic data in space and time. mapPat is designed as a user-friendly dashboard and allows the dynamic monitoring of the evolution of variants, lineages, and mutations in the genome of a pathogen at glance through informative geographic maps and elegant data visuals. mapPat provides a fine-grained map of pathogens evolution and circulation and represents a useful addition to the catalogue of bioinformatics methods for the genomic surveillance of pathogens.

Availability and implementation

mapPat is available at GitHub (https://github.com/F3rika/mapPat.git).

A phylogenetic method identifies candidate drivers of the evolution of the SARS-CoV-2 mutation spectrum

The molecular processes that generate new mutations evolve, but the causal mechanisms are largely unknown. In particular, the relative rates of mutation types (e.g., C>T), the mutation spectrum, sometimes vary among closely related species and populations. I present an algorithm for subdividing a phylogeny into distinct mutation spectra. By applying this approach to a SARS-CoV-2 phylogeny comprising approximately eight million genome sequences, I identify 10 shifts in the mutation spectrum. I find strong enrichment consistent with candidate causal amino-acid substitutions in the SARS-CoV-2 polymerase, and strikingly three appearances of the same homoplasious substitution are each associated with decreased C>T relative mutation rates. With rapidly growing genomic datasets, this approach and future extensions promises new insights into the mechanisms of evolution of mutational processes.

Variant mutation in SARS-CoV-2 nucleocapsid enhances viral infection via altered genomic encapsidation

The evolution of SARS-CoV-2 variants and their respective phenotypes represents an important set of tools to understand basic coronavirus biology as well as the public health implications of individual mutations in variants of concern. While mutations outside of Spike are not well studied, the entire viral genome is undergoing evolutionary selection, particularly the central disordered linker region of the nucleocapsid (N) protein. Here, we identify a mutation (G215C), characteristic of the Delta variant, that introduces a novel cysteine into this linker domain, which results in the formation of a disulfide bond and a stable N-N dimer. Using reverse genetics, we determined that this cysteine residue is necessary and sufficient for stable dimer formation in a WA1 SARS-CoV-2 background, where it results in significantly increased viral growth both in vitro and in vivo. Finally, we demonstrate that the N:G215C virus packages more nucleocapsid per virion and that individual virions are larger, with elongated morphologies.

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.

Tracking and curating putative SARS-CoV-2 recombinants with RIVET

MOTIVATION

Identifying and tracking recombinant strains of SARS-CoV-2 is critical to understanding the evolution of the virus and controlling its spread. But confidently identifying SARS-CoV-2 recombinants from thousands of new genome sequences that are being shared online every day is quite challenging, causing many recombinants to be missed or suffer from weeks of delay in being formally identified while undergoing expert curation.

RESULTS

We present RIVET-a software pipeline and visual platform that takes advantage of recent algorithmic advances in recombination inference to comprehensively and sensitively search for potential SARS-CoV-2 recombinants and organize the relevant information in a web interface that would help greatly accelerate the process of identifying and tracking recombinants.

AVAILABILITY AND IMPLEMENTATION

RIVET-based web interface displaying the most updated analysis of potential SARS-CoV-2 recombinants is available at https://rivet.ucsd.edu/. RIVET's frontend and backend code is freely available under the MIT license at https://github.com/TurakhiaLab/rivet and the documentation for RIVET is available at https://turakhialab.github.io/rivet/. The inputs necessary for running RIVET's backend workflow for SARS-CoV-2 are available through a public database maintained and updated daily by UCSC (https://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/).