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Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable

Mavian, Carla; Pond, Sergei Kosakovsky; Marini, Simone; Magalis, Brittany Rife; Vandamme, Anne-Mieke; Dellicour, Simon; Scarpino, Samuel V.; Houldcroft, Charlotte; Villabona-Arenas, Julian; Paisie, Taylor K.; Trovão, Nídia S.; Boucher, Christina; Zhang, Yun; Scheuermann, Richard H.; Gascuel, Olivier; Lam, Tommy Tsan-Yuk; Suchard, Marc A.; Abecasis, Ana; Wilkinson, Eduan; de Oliveira, Tulio; ... mehr

There is obvious interest in gaining insights into the epidemiology and evolution of the virus that has recently emerged in humans as the cause of the coronavirus disease 2019 (COVID-19) pandemic. The recent paper by Forster et al. analyzed 160 severe acute respiratory syndrome coronavirus (SARS-CoV-2) full genomes available ( in early March 2020. The central claim is the identification of three main SARS-CoV-2 types, named A, B, and C, circulating in different proportions among Europeans and Americans (types A and C) and East Asians (type B). According to a median-joining network analysis, variant A is proposed to be the ancestral type because it links to the sequence of a coronavirus from bats, used as an outgroup to trace the ancestral origin of the human strains. The authors further suggest that the “ancestral Wuhan B-type virus is immunologically or environmentally adapted to a large section of the East Asian population, and may need to mutate to overcome resistance outside East Asia.” There are several serious flaws with their findings and interpretation. First, and most obviously, the sequence identity between SARS-CoV-2 and the bat virus is only 96.2%, implying that these viral genomes (which are nearly 30,000 nucleotides long) differ by more than 1,000 mutations. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000124863
Veröffentlicht am 20.10.2020
DOI: 10.1073/pnas.2007295117
Zitationen: 12
Web of Science
Zitationen: 9
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 06.2020
Sprache Englisch
Identifikator ISSN: 0027-8424, 1091-6490
KITopen-ID: 1000124863
Erschienen in Proceedings of the National Academy of Sciences of the United States of America
Band 117
Heft 23
Seiten 12522–12523
Vorab online veröffentlicht am 07.05.2020
Nachgewiesen in Web of Science
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