Dynamically evolving novel overlapping gene as a factor in the SARS-CoV-2 pandemic
Abstract
Understanding the emergence of novel viruses requires an accurate and comprehensive annotation of their genomes. Overlapping genes (OLGs) are common in viruses and have been associated with pandemics, but are still widely overlooked. We identify and characterize ORF3d, a novel OLG in SARS-CoV-2 that is also present in Guangxi pangolin-CoVs but not other closely related pangolin-CoVs or bat-CoVs. We then document evidence of ORF3d translation, characterize its protein sequence, and conduct an evolutionary analysis at three levels: between taxa (21 members of Severe acute respiratory syndrome-related coronavirus), between human hosts (3978 SARS-CoV-2 consensus sequences), and within human hosts (401 deeply sequenced SARS-CoV-2 samples). ORF3d has been independently identified and shown to elicit a strong antibody response in COVID-19 patients. However, it has been misclassified as the unrelated gene ORF3b, leading to confusion. Our results liken ORF3d to other accessory genes in emerging viruses and highlight the importance of OLGs.
Data availability
All data generated or analyzed during this study are included in the manuscript and supplement. Scripts and source data for all analyses and figures are provided on GitHub at https://github.com/chasewnelson/SARS-CoV-2-ORF3d and Zenodo at https://zenodo.org/record/4052729.
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Proteome and Translatome of SARS-CoV-2 infected cellsPRIDE database, PXD017710.
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Vero cells infected with SARS CoV 2 no quantitation slices 1-10 of 20; vero cells infected with SARS CoV2 slices 11-20 of 20 slicesZenodo, 10.5281/zenodo.3722590, 10.5281/zenodo.3722596.
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Proteomics of SARS-CoV and SARS-CoV-2 infected cellsPRIDE database, PXD018581.
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Decoding SARS-CoV-2 coding capacityGEO database, sample IDs: SRR11713366, SRR11713367, SRR11713368, SRR11713369 from GSE149973.
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Assays and Merits of Proteomics for SARS-CoV-2 Research and TestingPRIDE database, PXD019645.
Article and author information
Author details
Funding
Academia Sinica (Postdoctoral Research Fellowship)
- Chase W Nelson
National Philanthropic Trust (Grant)
- Zachary Ardern
University of Wisconsin-Madison (John D. MacArthur Professorship Chair)
- Tony L Goldberg
National Science Foundation (IOS grants #1755370 and #1758800)
- Sergios-Orestis Kolokotronis
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Nelson et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Evolutionary Biology
The majority of highly polymorphic genes are related to immune functions and with over 100 alleles within a population, genes of the major histocompatibility complex (MHC) are the most polymorphic loci in vertebrates. How such extraordinary polymorphism arose and is maintained is controversial. One possibility is heterozygote advantage (HA), which can in principle maintain any number of alleles, but biologically explicit models based on this mechanism have so far failed to reliably predict the coexistence of significantly more than 10 alleles. We here present an eco-evolutionary model showing that evolution can result in the emergence and maintenance of more than 100 alleles under HA if the following two assumptions are fulfilled: first, pathogens are lethal in the absence of an appropriate immune defence; second, the effect of pathogens depends on host condition, with hosts in poorer condition being affected more strongly. Thus, our results show that HA can be a more potent force in explaining the extraordinary polymorphism found at MHC loci than currently recognised.
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