Abstract
We propose an efficient framework for genetic subtyping of a pandemic virus, with application to the novel coronavirus SARS-CoV-2. Efficient identification of subtypes is particularly important for tracking the geographic distribution and temporal dynamics of infectious spread in real-time. In this paper, we utilize an entropy analysis to identify nucleotide sites within SARS-CoV-2 genome sequences that are highly informative of genetic variation, and thereby define an Informative Subtype Marker (ISM) for each sequence. We further apply an error correction technique to the ISMs, for more robust subtype definition given ambiguity and noise in sequence data. We show that, by analyzing the ISMs of global SARS-CoV-2 sequence data, we can distinguish interregional differences in viral subtype distribution, and track the emergence of subtypes in different regions over time. Based on publicly available data up to April 5, 2020, we show, for example: (1) distinct genetic subtypes of infections in Europe, with earlier transmission linked to subtypes prevalent in Italy with later development of subtypes specific to other countries over time; (2) within the United States, the emergence of an endogenous U.S. subtype that is distinct from the outbreak in New York, which is linked instead to subtypes found in Europe; and (3) dynamic emergence of SARS-CoV-2 from localization in China to a pattern of distinct regional subtypes in different countries around the world over time. Our results demonstrate that utilizing ISMs for genetic subtyping can be an important complement to conventional phylogenetic tree-based analyses of the COVID-19 pandemic. Particularly, because ISMs are efficient and compact subtype identifiers, they will be useful for modeling, data-mining, and machine learning tools to help enhance containment, therapeutic, and vaccine targeting strategies for fighting the COVID-19 pandemic. We have made the subtype identification pipeline described in this paper publicly available at https://github.com/EESI/ISM.
Author Summary The novel coronavirus responsible for COVID-19, SARS-CoV-2, expanded to reportedly 1.3 million confirmed cases worldwide by April 7, 2020. The global SARS-CoV-2 pandemic highlights the importance of tracking dynamics of viral pandemics in real-time. Through the beginning of April 2020, researchers obtained genetic sequences of SARS-CoV-2 from nearly 4,000 infected individuals worldwide. Since the virus readily mutates, each sequence of an infected individual contains useful information linked to the individual’s exposure location and sample date. But, there are over 30,000 bases in the full SARS-CoV-2 genome — so tracking genetic variants on a whole-sequence basis becomes unwieldy. We describe a method to instead efficiently identify and label genetic variants, or “subtypes” of SARS-CoV-2. Applying this method results in a compact, 17 base-long label, called an Informative Subtype Marker or “ISM.” We define viral subtypes for each ISM, and show how regional distribution of subtypes track the progress of the pandemic. Major findings include (1) showing distinct viral subtypes of infections in Europe emanating from Italy to other countries over time, and (2) tracking emergence of a local subtype across the United States connected to Asia and distinct from the outbreak in New York, which is connected to Europe.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵† bahrad{at}molhealtheng.com
↵+ glr26{at}drexel.edu
We added an error correction algorithm to correct ambiguous base calls to improve the robustness of ISMs.
6 The cumulative reported Worldwide cases were obtained from the Our World In Data Project, which reported them from the European Center for Disease Prevention and Control, made available at https://ourworldindata.org/coronavirus-source-data.
