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Nelson, C. W.

Publications and source records attributed to Nelson, C. W..

3 recordsLinked to original sources

A previously uncharacterized gene in SARS-CoV-2 illuminates the functional dynamics and evolutionary origins of the COVID-19 pandemic

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.

evolutionary biology

OLGenie: Estimating Natural Selection to Predict Functional Overlapping Genes

Purifying (negative) natural selection is a hallmark of functional biological sequences, and can be detected in protein-coding genes using the ratio of nonsynonymous to synonymous substitutions per site (dN/dS). However, when two genes overlap the same nucleotide sites in different frames, synonymous changes in one gene may be nonsynonymous in the other, perturbing dN/dS. Thus, scalable methods are needed to estimate functional constraint specifically for overlapping genes (OLGs). We propose OLGenie, which implements a modification of the Wei-Zhang method. Assessment with simulations and controls from viral genomes (58 OLGs and 176 non-OLGs) demonstrates low false positive rates and good discriminatory ability in differentiating true OLGs from non-OLGs. We also apply OLGenie to the unresolved case of HIV-1s putative antisense protein gene, showing significant purifying selection. OLGenie can be used to study known OLGs and to predict new OLGs in genome annotation. Software and example data are freely available at https://github.com/chasewnelson/OLGenie.

evolutionary biology

Trevolver: simulating non-reversible DNA sequence evolution in trinucleotide context on a bifurcating tree

SummaryRecent de novo mutation data allow the estimation of non-reversible mutation rates for trinucleotide sequence contexts. However, existing tools for simulating DNA sequence evolution are limited to time-reversible models or do not consider trinucleotide context-dependent rates. As this ability is critical to testing evolutionary scenarios under neutrality, we created Trevolver. Sequence evolution is simulated on a bifurcating tree using a 64 x 4 trinucleotide mutation model. Runtime is fast and results match theoretical expectation for CpG sites. Simulations with Trevolver will enable neutral hypotheses to be tested at within-species (polymorphism), between-species (divergence), within-host (e.g., viral evolution), and somatic (e.g., cancer) levels of evolutionary change.\n\nAvailability and ImplementationTrevolver is implemented in Perl and available on GitHub under GNU General Public License (GPL) version 3 at https://github.com/chasewnelson/trevolver.\n\nContactcnelson@amnh.org\n\nSupplementary informationFurther details and example data are available on GitHub.

evolutionary biology