Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness

Obermeyer, Fritz; Jankowiak, Martin; Barkas, Nikolaos; Schaffner, Stephen F.; Pyle, Jesse D.; Yurkovetskiy, Leonid; Bosso, Matteo; Park, Danny; Babadi, Mehrtash; MacInnis, Bronwyn; Wang, Yetao; Sabeti, Pardis C.; Lemieux, Jacob E.

doi:10.1126/science.abm1208

Cited by 242 publications

(312 citation statements)

References 49 publications

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“…6D). Many nonsynonymous epitope mutations were also found in the C.36.3 linage, which is thought to be highly transmissible ( 41 ). However, the most nonsynonymous epitope mutations were observed in Omicron (B.1.1.529, Fig.…”

Section: Resultsmentioning

confidence: 99%

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Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping combined with genome sequence analysis

N'Guessan

Kailasam

Mostefai

et al. 2022

Preprint

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A deeper understanding of the molecular determinants that drive humoral responses to coronaviruses, and in particular severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is critical for improving and developing diagnostics, therapies and vaccines. Moreover, viral mutations can change key antigens in a manner that alters the ability of the immune system to detect and clear infections. In this study, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses of asymptomatic or recovered COVID-19-positive patients relative to COVID-19- negative patients. We made use of a novel high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses to rapidly identify B cell epitopes recognized by distinct antibody isotypes in patients' blood sera. Using our integrated computational pipeline, we then evaluated the fine immunological properties of detected SARS-CoV-2 epitopes and relate them to their evolutionary and structural properties. While some epitopes are common across all CoVs, others are private to specific hCoVs. We also highlight the existence of hotspots of pre-existing immunity and identify a subset of cross-reactive epitopes that contributes to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves and SARS-CoV-2 variants, which have important implications for genomic surveillance and vaccine design. Lastly, we show that mutations in Spike and Nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

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Section: Resultsmentioning

confidence: 99%

“…6D). Many nonsynonymous epitope mutations were also found in the C.36.3 linage, which is thought to be highly transmissible (41).…”

Section: Assessing the Immune Evasion Potential Of Sars-cov-2 Variantsmentioning

confidence: 99%

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping combined with genome sequence analysis

N'Guessan

Kailasam

Mostefai

et al. 2022

Preprint

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“…The elevated contribution of S-gene mutations (notably in the RBD) over non-S-gene mutations starting around November 2021 is conspicuous. Compare to Figure 2CDE in Obermeyer et al (2022).…”

Section: Sars-cov-2 Analysismentioning

confidence: 89%

“…Our raw data consist of 8.6 million samples downloaded from GISAID (Elbe and Buckland-Merrett, 2017) on April 18 th , 2022. In initial pre-processing we follow the procedure in Obermeyer et al (2022), which relies on a phylogenetic tree constructed by UShER (Turakhia et al, 2021; McBroome et al, 2021), and results in L = 3000 SARS-CoV-2 clusters that are finer than the 1662 PANGO lineages in the data (Rambaut et al, 2020). In our main analysis we consider A = 2975 non-synonymous amino acid substitutions, excluding both insertions and deletions due to limitations of UShER, and taking Wuhan A as the reference genotype, i.e.…”

Section: Sars-cov-2 Analysismentioning

confidence: 99%

“…An open-source implementation of our analysis code is available at https://github.com/broadinstitute/bvas. The initial portion of our data pre-processing pipeline relies on open source code described by Obermeyer et al (2022): https://github.com/broadinstitute/pyro-cov. Allele-level and lineage-level inference results from our main BVAS analysis are publicly available: https://github.com/broadinstitute/bvas/raw/main/paper/allele_summary.csv https://github.com/broadinstitute/bvas/raw/main/paper/growth_rates_summary.csv…”

Section: Data Availability Statementmentioning

confidence: 99%

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Inferring selection effects in SARS-CoV-2 with Bayesian Viral Allele Selection

Jankowiak

Obermeyer

Lemieux

2022

Preprint

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The global effort to sequence millions of SARS-CoV-2 genomes has provided an unprecedented view of viral evolution. Characterizing how selection acts on SARS-CoV-2 is critical to developing effective, long-lasting vaccines and other treatments, but the scale and complexity of genomic surveillance data make rigorous analysis distinctly challenging. To meet this challenge, we develop Bayesian Viral Allele Selection (BVAS), a principled and scalable probabilistic method for inferring the genetic determinants of differential viral fitness and the relative growth rates of viral lineages, including newly emergent lineages. After demonstrating the accuracy and efficacy of our method through simulation, we apply BVAS to 6.9 million SARS-CoV-2 genomes. We identify numerous mutations that increase fitness, including previously identified mutations in the SARS-CoV-2 Spike and Nucleocapsid proteins, as well as mutations in non-structural proteins whose contribution to fitness is less well characterized. In addition, we extend our baseline model to identify mutations whose fitness exhibits strong dependence on vaccination status. Our method, which couples Bayesian variable selection with a diffusion approximation in allele frequency space, lays a foundation for identifying fitness-associated mutations under the assumption that most alleles are neutral.

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SARS‐CoV‐2 Evolution: Immune Dynamics, Omicron Specificity, and Predictive Modeling in Vaccinated Populations

Zhang,

Li,

Zhang

et al. 2024

Advanced Science

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Host immunity is central to the virus's spread dynamics, which is significantly influenced by vaccination and prior infection experiences. In this work, we analyzed the co‐evolution of SARS‐CoV‐2 mutation, angiotensin‐converting enzyme 2 (ACE2) receptor binding, and neutralizing antibody (NAb) responses across various variants in 822 human and mice vaccinated with different non‐Omicron and Omicron vaccines is analyzed. The link between vaccine efficacy and vaccine type, dosing, and post‐vaccination duration is revealed. The classification of immune protection against non‐Omicron and Omicron variants is co‐evolved with genetic mutations and vaccination. Additionally, a model, the Prevalence Score (P‐Score) is introduced, which surpasses previous algorithm‐based models in predicting the potential prevalence of new variants in vaccinated populations. The hybrid vaccination combining the wild‐type (WT) inactivated vaccine with the Omicron BA.4/5 mRNA vaccine may provide broad protection against both non‐Omicron variants and Omicron variants, albeit with EG.5.1 still posing a risk. In conclusion, these findings enhance understanding of population immunity variations and provide valuable insights for future vaccine development and public health strategies.

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Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness

Cited by 242 publications

References 49 publications

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping combined with genome sequence analysis

Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping combined with genome sequence analysis

Inferring selection effects in SARS-CoV-2 with Bayesian Viral Allele Selection

SARS‐CoV‐2 Evolution: Immune Dynamics, Omicron Specificity, and Predictive Modeling in Vaccinated Populations

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