Mysterious new “hidden” gene discovered in COVID-19 Virus

Researchers have discovered a new “hidden” gene in EARS-CoV-2 – the virus that causes COVID-19 – which may have contributed to its unique biology and pandemic potential. In a virus that has only about 15 genes in total, more about these and other overlapping genes – or “genes within genes” – can have a significant impact on how we fight the virus. The new gene is described in the journal today eLife.

“Overlapping genes can be one of an arsenal of ways coronaviruses have evolved to replicate efficiently, prevent host immunity, or transmit themselves,” said lead author Chase Nelson, a postdoctoral researcher at Academia Sinica in Taiwan. and visiting scientist at the American Museum of Nature. “Knowing that there are overlapping genes and how they function may reveal new possibilities for coronavirus control, for example through antiviral drugs.”

The research team identified ORF3d, a new overlapping gene in SARS-CoV-2 that has the potential to encode a protein that is longer than expected by chance. They found that this gene was also present in a previously discovered pangolin coronavirus, possibly reflecting repeated loss or increase of this gene during the development of SARS-CoV-2 and related viruses. In addition, ORF3d has been independently identified and shown to elicit a strong antibody response in COVID-19 patients, proving that the protein of the new gene is produced during human infection.

“We do not yet know what the function is or whether there is clinical significance,” Nelson said. ‘But we predict that it is relatively unlikely that it can be detected by a T-cell response, as opposed to the antibody response. And maybe it has something to do with the way the gene could have originated. ”

At first glance, genes may look like written language in that they consist of strings of letters (in RNA viruses, the nucleotides A, U, G and C) that transmit information. But while the units of languages ​​(words) are discrete and non-overlapping, genes can be overlapping and multifunctional, with information being cryptically encoded depending on where you start “reading”. Overlapping genes are hard to spot, and most scientific computer programs are not designed to detect them. However, it is common in viruses. This is partly because RNA viruses have a high mutation rate, and therefore they tend to keep their gene count low to prevent a large number of mutations. Consequently, viruses have developed a kind of data compression system in which one letter in its genome can contribute to two or even three different genes.

“Missing overlapping genes put us at risk of looking out for important aspects of viral biology,” Nelson said. “In terms of genome size, SARS-CoV-2 and its relatives are one of the longest-lived RNA viruses in existence. Thus, they are perhaps more prone to ‘genomic trickery’ than other RNA viruses. ‘

Prior to the pandemic, while working as a Gerstner scholar in bioinformatics and computer biology, Nelson developed a computer program that examined genomics for patterns of genetic change unique to overlapping genes. For this study, Nelson collaborated with colleagues from institutions, including the Technical University of Munich and the University of California, Berkeley, to apply this software and other methods to the myriad new sequence data available for SARS-CoV-2. The group is hopeful that other scientists will investigate the gene they discovered in the laboratory to determine its function and possibly determine what role it played in the rise of the pandemic virus.

Reference: “Dynamically evolving novel overlapping genes as a factor in the SARS-CoV-2 pandemic” by Chase W Nelson, Zachary Ardern, Tony L Goldberg, Chen Meng, Chen-Hao Kuo, Christina Ludwig, Sergios-Orestis Kolokotronis and Xinzhu Wei , 1 October 2020, eLife.
DOI: 10.7554 / eLife.59633

Funding for this work was provided in part by Academia Sinica, the Bavarian State Government and 12 National Philanthropic Trust, the American National Science Foundation (grant numbers 1755370 and 1758800, and the University of Wisconsin-Madison.

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