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Cited by 1,006SARS-CoV-2 and COVID-19 ResearchEvolution and Genetic DynamicsCOVID-19 epidemiological studies

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Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

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Volz, Erik, Hill, Verity, McCrone, John T., Price, Anna, Jorgensen, David, O’Toole, Áine, Southgate, Joel, Johnson, Robert, Jackson, Ben, Nascimento, Fabricia F., Rey, Sara M., Nicholls, Samuel M., Colquhoun, Rachel M., da Silva Filipe, Ana, Shepherd, James, Pascall, David J., Shah, Rajiv, Jesudason, Natasha, Li, Kathy, Jarrett, Ruth, Pacchiarini, Nicole, Bull, Matthew, Geidelberg, Lily, Siveroni, Igor, Koshy, Cherian, Wise, Emma, Cortes, Nick, Lynch, Jessica, Kidd, Stephen, Mori, Matilde, Fairley, Derek J., Curran, Tanya, McKenna, James P., Adams, Helen, Fraser, Christophe, Golubchik, Tanya, Bonsall, David, Moore, Catrin, Caddy, Sarah L., Khokhar, Fahad A., Wantoch, Michelle, Reynolds, Nicola, Warne, Ben, Maksimovic, Joshua, Spellman, Karla, McCluggage, Kathryn, John, Michaela, Beer, Robert, Afifi, Safiah, Morgan, Sian, Marchbank, Angela, Price, Anna, Kitchen, Christine, Gulliver, Huw, Merrick, Ian, Southgate, Joel, Guest, Martyn, Munn, Robert, Workman, Trudy, Connor, Thomas R., Fuller, William, Bresner, Catherine, Snell, Luke B., Charalampous, Themoula, Nebbia, Gaia, Batra, Rahul, Edgeworth, Jonathan, Robson, Samuel C., Beckett, Angela, Loveson, Katie F., Aanensen, David M., Underwood, Anthony P., Yeats, Corin A., Abudahab, Khalil, Taylor, Ben E.W., Menegazzo, Mirko, Clark, Gemma, Smith, Wendy, Khakh, Manjinder, Fleming, Vicki M., Lister, Michelle M., Howson-Wells, Hannah C., Berry, Louise, Boswell, Tim, Joseph, Amelia, Willingham, Iona, Bird, Paul, Helmer, Thomas, Fallon, Karlie, Holmes, Christopher, Tang, Julian, Raviprakash, Veena, Campbell, Sharon, Sheriff, Nicola, Loose, Matthew W., Holmes, Nadine, Moore, Christopher, Carlile, Matthew, Wright, Victoria, Sang, Fei, Debebe, Johnny, Coll, Francesc, Signell, Adrian W., Betancor, Gilberto, Wilson, Harry D., Feltwell, Theresa, Houldcroft, Charlotte J., Eldirdiri, Sahar, Kenyon, Anita, Davis, Thomas, Pybus, Oliver, du Plessis, Louis, Zarebski, Alex, Raghwani, Jayna, Kraemer, Moritz, Francois, Sarah, Attwood, Stephen, Vasylyeva, Tetyana, Torok, M. Estee, Hamilton, William L., Goodfellow, Ian G., Hall, Grant, Jahun, Aminu S., Chaudhry, Yasmin, Hosmillo, Myra, Pinckert, Malte L., Georgana, Iliana, Yakovleva, Anna, Meredith, Luke W., Moses, Samuel, Lowe, Hannah, Ryan, Felicity, Fisher, Chloe L., Awan, Ali R., Boyes, John, Breuer, Judith, Harris, Kathryn Ann, Brown, Julianne Rose, Shah, Divya, Atkinson, Laura, Lee, Jack C.D., Alcolea-Medina, Adela, Moore, Nathan, Cortes, Nicholas, Williams, Rebecca, Chapman, Michael R., Levett, Lisa J., Heaney, Judith, Smith, Darren L., Bashton, Matthew, Young, Gregory R., Allan, John, Loh, Joshua, Randell, Paul A., Cox, Alison, Madona, Pinglawathee, Holmes, Alison, Bolt, Frances, Price, James, Mookerjee, Siddharth, Rowan, Aileen, Taylor, Graham P., Ragonnet-Cronin, Manon, Nascimento, Fabricia F., Jorgensen, David, Siveroni, Igor, Johnson, Rob, Boyd, Olivia, Geidelberg, Lily, Volz, Erik M., Brunker, Kirstyn, Smollett, Katherine L., Loman, Nicholas J., Quick, Joshua, McMurray, Claire, Stockton, 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Dervisevic, Samir, Stanley, Rachael, Prakash, Reenesh, Stuart, Claire, Elumogo, Ngozi, Sethi, Dheeraj K., Meader, Emma J., Coupland, Lindsay J., Potter, Will, Graham, Clive, Barton, Edward, Padgett, Debra, Scott, Garren, Swindells, Emma, Greenaway, Jane, Nelson, Andrew, Yew, Wen C., Resende Silva, Paola C., Andersson, Monique, Shaw, Robert, Peto, Timothy, Justice, Anita, Eyre, David, Crooke, Derrick, Hoosdally, Sarah, Sloan, Tim J., Duckworth, Nichola, Walsh, Sarah, Chauhan, Anoop J., Glaysher, Sharon, Bicknell, Kelly, Wyllie, Sarah, Butcher, Ethan, Elliott, Scott, Lloyd, Allyson, Impey, Robert, Levene, Nick, Monaghan, Lynn, Bradley, Declan T., Allara, Elias, Pearson, Clare, Muir, Peter, Vipond, Ian B., Hopes, Richard, Pymont, Hannah M., Hutchings, Stephanie, Curran, Martin D., Parmar, Surendra, Lackenby, Angie, Mbisa, Tamyo, Platt, Steven, Miah, Shahjahan, Bibby, David, Manso, Carmen, Hubb, Jonathan, Chand, Meera, Dabrera, Gavin, Ramsay, Mary, Bradshaw, Daniel, Thornton, Alicia, Myers, Richard, Schaefer, Ulf, Groves, Natalie, Gallagher, Eileen, Lee, David, Williams, David, Ellaby, Nicholas, Harrison, Ian, Hartman, Hassan, Manesis, Nikos, Patel, Vineet, Bishop, Chloe, Chalker, Vicki, Osman, Husam, Bosworth, Andrew, Robinson, Esther, Holden, Matthew T.G., Shaaban, Sharif, Birchley, Alec, Adams, Alexander, Davies, Alisha, Gaskin, Amy, Plimmer, Amy, Gatica-Wilcox, Bree, McKerr, Caoimhe, Moore, Catherine, Williams, Chris, Heyburn, David, De Lacy, Elen, Hilvers, Ember, Downing, Fatima, Shankar, Giri, Jones, Hannah, Asad, Hibo, Coombes, Jason, Watkins, Joanne, Evans, Johnathan M., Fina, Laia, Gifford, Laura, Gilbert, Lauren, Graham, Lee, Perry, Malorie, Morgan, Mari, Bull, Matthew, Cronin, Michelle, Pacchiarini, Nicole, Craine, Noel, Jones, Rachel, Howe, Robin, Corden, Sally, Rey, Sara, Kumziene-Summerhayes, Sara, Taylor, Sarah, Cottrell, Simon, Jones, Sophie, Edwards, Sue, O’Grady, Justin, Page, Andrew J., Wain, John, Webber, Mark A., Mather, Alison E., Baker, David J., Rudder, Steven, Yasir, Muhammad, Thomson, Nicholas M., Aydin, Alp, Tedim, Ana P., Kay, Gemma L., Trotter, Alexander J., Gilroy, Rachel A.J., Alikhan, Nabil-Fareed, de Oliveira Martins, Leonardo, Le-Viet, Thanh, Meadows, Lizzie, Kolyva, Anastasia, Diaz, Maria, Bell, Andrew, Gutierrez, Ana Victoria, Charles, Ian G., Adriaenssens, Evelien M., Kingsley, Robert A., Casey, Anna, Simpson, David A., Molnar, Zoltan, Thompson, Thomas, Acheson, Erwan, Masoli, Jane A.H., Knight, Bridget A., Hattersley, Andrew, Ellard, Sian, Auckland, Cressida, Mahungu, Tabitha W., Irish-Tavares, Dianne, Haque, Tanzina, Bourgeois, Yann, Scarlett, Garry P., Partridge, David G., Raza, Mohammad, Evans, Cariad, Johnson, Kate, Liggett, Steven, Baker, Paul, Essex, Sarah, Lyons, Ronan A., Caller, Laura G., Castellano, Sergi, Williams, Rachel J., Kristiansen, Mark, Roy, Sunando, Williams, Charlotte A., Dyal, Patricia L., Tutill, Helena J., Panchbhaya, Yasmin N., Forrest, Leysa M., Niola, Paola, Findlay, Jacqueline, Brooks, Tony T., Gavriil, Artemis, Mestek-Boukhibar, Lamia, Weeks, Sam, Pandey, Sarojini, Berry, Lisa, Jones, Katie, Richter, Alex, Beggs, Andrew, Smith, Colin P., Bucca, Giselda, Hesketh, Andrew R., Harrison, Ewan M., Peacock, Sharon J., Palmer, Sophie, Churcher, Carol M., Bellis, Katherine L., Girgis, Sophia T., Naydenova, Plamena, Blane, Beth, Sridhar, Sushmita, Ruis, Chris, Forrest, Sally, Cormie, Claire, Gill, Harmeet K., Dias, Joana, Higginson, Ellen E., Maes, Mailis, Young, Jamie, Kermack, Leanne M., Hadjirin, Nazreen F., Aggarwal, Dinesh, Griffith, Luke, Swingler, Tracey, Davidson, Rose K., Rambaut, Andrew, Williams, Thomas, Balcazar, Carlos E., Gallagher, Michael D., O'Toole, Áine, Rooke, Stefan, Jackson, Ben, Colquhoun, Rachel, Ashworth, Jordan, Hill, Verity, McCrone, J.T., Scher, Emily, Yu, Xiaoyu, Williamson, Kathleen A., Stanton, Thomas D., Michell, Stephen L., Bewshea, Claire M., Temperton, Ben, Michelsen, Michelle L., Warwick-Dugdale, Joanna, Manley, Robin, Farbos, Audrey, Harrison, James W., Sambles, Christine M., Studholme, David J., Jeffries, Aaron R., Darby, Alistair C., Hiscox, Julian A., Paterson, Steve, Iturriza-Gomara, Miren, Jackson, Kathryn A., Lucaci, Anita O., Vamos, Edith E., Hughes, Margaret, Rainbow, Lucille, Eccles, Richard, Nelson, Charlotte, Whitehead, Mark, Turtle, Lance, Haldenby, Sam T., Gregory, Richard, Gemmell, Matthew, Kwiatkowski, Dominic, de Silva, Thushan I., Smith, Nikki, Angyal, Adrienn, Lindsey, Benjamin B., Groves, Danielle C., Green, Luke R., Wang, Dennis, Freeman, Timothy M., Parker, Matthew D., Keeley, Alexander J., Parsons, Paul J., Tucker, Rachel M., Brown, Rebecca, Wyles, Matthew, Constantinidou, Chrystala, Unnikrishnan, Meera, Ott, Sascha, Cheng, Jeffrey K.J., Bridgewater, Hannah E., Frost, Lucy R., Taylor-Joyce, Grace, Stark, Richard, Baxter, Laura, Alam, Mohammad T., Brown, Paul E., McClure, Patrick C., Chappell, Joseph G., Tsoleridis, Theocharis, Ball, Jonathan, Grammatopoulos, Dimitris, Buck, David, Todd, John A., Green, Angie, Trebes, Amy, MacIntyre-Cockett, George, de Cesare, Mariateresa, Langford, Cordelia, Alderton, Alex, Amato, Roberto, Goncalves, Sonia, Jackson, David K., Johnston, Ian, Sillitoe, John, Palmer, Steve, Lawniczak, Mara, Berriman, Matt, Danesh, John, Livett, Rich, Shirley, Lesley, Farr, Ben, Quail, Mike, Thurston, Scott, Park, Naomi, Betteridge, Emma, Weldon, Danni, Goodwin, Scott, Nelson, Rachel, Beaver, Charlotte, Letchford, Laura, Jackson, David A., Foulser, Luke, McMinn, Liz, Prestwood, Liam, Kay, Sally, Kane, Leanne, Dorman, Matthew J., Martincorena, Inigo, Puethe, Christoph, Keatley, Jon-Paul, Tonkin-Hill, Gerry, Smith, Christen, Jamrozy, Dorota, Beale, Mathew A., Patel, Minal, Ariani, Cristina, Spencer-Chapman, Michael, Drury, Eleanor, Lo, Stephanie, Rajatileka, Shavanthi, Scott, Carol, James, Keith, Buddenborg, Sarah K., Berger, Duncan J., Patel, Gaurang, Garcia-Casado, Maria V., Dibling, Thomas, McGuigan, Samantha, Rogers, Hazel A., Hunter, Adam D., Souster, Emily, Neaverson, Alexandra S., Goodfellow, Ian, Loman, Nicholas J., Pybus, Oliver G., Robertson, David L., Thomson, Emma C., Rambaut, Andrew, Connor, Thomas R.·2021·Cell
DOI 10.1016/j.cell.2020.11.020PMC PMC7674007

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Abstract

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.

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Graphical abstract CC BY · PubMed Central
Figure 1 Maximum Likelihood Phylogeny Estimated from a Representative Set of 900 SARS-CoV-2 Genome Sequences, Showing global Lineage Assignments and the Origins of the Spike Protein D614G Mutation, which Seeded Many Introductions in the United Kingdom Putative reversions to 614D and independently arising D614G mutations are shown as large circles. The D614N genomes shown as red circles indicated two independent clusters in the United Kingdom.
Figure 1 Maximum Likelihood Phylogeny Estimated from a Representative Set of 900 SARS-CoV-2 Genome Sequences, Showing global Lineage Assignments and the Origins of the Spike Protein D614G Mutation, which Seeded Many Introductions in the United Kingdom Putative reversions to 614D and independently arising D614G mutations are shown as large circles. The D614N genomes shown as red circles indicated two independent clusters in the United Kingdom.CC BY · PubMed Central
Figure S1 Expanded Phylogenetic Tree, Related to Figure 1 This shows the early stages of emergence of D614G into Europe from China. Acknowledgments and details for highlighted genome sequences are given in Table S3.
Figure S1 Expanded Phylogenetic Tree, Related to Figure 1 This shows the early stages of emergence of D614G into Europe from China. Acknowledgments and details for highlighted genome sequences are given in Table S3.CC BY · PubMed Central
Figure 2 Geographic and Temporal Distribution of UK Phylogenetic Clusters, Classified as 614D or 614G According to the Residue They Carry at Spike Protein Position 614D (A) Shaded regions show the predominant residue in each region on the 15th of each month for March, April, May, and June 2020, with orange indicating that 614G was more frequently sampled and green indicating that 614D was more (or equally) frequent. Light gray indicates that no sequences had been sampled by that point in time. Dark gray indicates the Republic of Ireland. (B) The date when each cluster was first detected in the United Kingdom for variants 614D and 614G. Each cluster contains two or more sampled genomes. Solid lines show the total number of sequences collected by day of each 614 variant. (C) The log odds of sampling a 614G variant over time. (D) The size of cluster versus time of first sample collected within a cluster.
Figure 2 Geographic and Temporal Distribution of UK Phylogenetic Clusters, Classified as 614D or 614G According to the Residue They Carry at Spike Protein Position 614D (A) Shaded regions show the predominant residue in each region on the 15th of each month for March, April, May, and June 2020, with orange indicating that 614G was more frequently sampled and green indicating that 614D was more (or equally) frequent. Light gray indicates that no sequences had been sampled by that point in time. Dark gray indicates the Republic of Ireland. (B) The date when each cluster was first detected in the United Kingdom for variants 614D and 614G. Each cluster contains two or more sampled genomes. Solid lines show the total number of sequences collected by day of each 614 variant. (C) The log odds of sampling a 614G variant over time. (D) The size of cluster versus time of first sample collected within a cluster.CC BY · PubMed Central
Figure 3 Relative Frequency of Spike 614D and G over Time, Phylodynamic Growth Rates and Comparison of Clinical Severity Metrics Relative frequency of spike 614D and G over time (A and B), phylodynamic growth rates (C and D), and comparison of clinical severity metrics (E–G). (A) Frequency of sampling spike 614G over time for clusters sampled during exponential growth phase. The size of points represents the number of samples collected on each day. The line and shaded region showed the maximum likelihood estimate (MLE) and confidence interval fit of the logistic growth model. (B) As in (A) but including samples during a period after April 15 during a period of epidemic decline. (C) Distribution of exponential growth rate for spike 614G (brown) and 614D (gray) in units of 1/year. Solid areas span the 95% credible interval. Points indicate the rates estimated for specific clusters and are sized by the number of sequences in that cluster. (D) Log odds of sampling spike 614G in London comparing empirical values (black line) and estimates based on the phylodynamic susceptible-exposed-infectious-recovered (SEIR) model (shaded regions). The green shaded region shows estimates making use of both genetic data and sample frequency data. (E) The probability over time of fatal outcome within 28 days of diagnosis among UK patients with sequence data that can be matched to clinical records. Shaded regions show 95% confidence region of a 7-day moving average. Points with fewer than 20 observations are omitted. (F) Moving average of age among samples included in (E). (G) Viral load (real-time qPCR mean genome copies) estimated using SARS-CoV-2 RNA strands from 31 614D (614D) and 290 614G samples.
Figure 3 Relative Frequency of Spike 614D and G over Time, Phylodynamic Growth Rates and Comparison of Clinical Severity Metrics Relative frequency of spike 614D and G over time (A and B), phylodynamic growth rates (C and D), and comparison of clinical severity metrics (E–G). (A) Frequency of sampling spike 614G over time for clusters sampled during exponential growth phase. The size of points represents the number of samples collected on each day. The line and shaded region showed the maximum likelihood estimate (MLE) and confidence interval fit of the logistic growth model. (B) As in (A) but including samples during a period after April 15 during a period of epidemic decline. (C) Distribution of exponential growth rate for spike 614G (brown) and 614D (gray) in units of 1/year. Solid areas span the 95% credible interval. Points indicate the rates estimated for specific clusters and are sized by the number of sequences in that cluster. (D) Log odds of sampling spike 614G in London comparing empirical values (black line) and estimates based on the phylodynamic susceptible-exposed-infectious-recovered (SEIR) model (shaded regions). The green shaded region shows estimates making use of both genetic data and sample frequency data. (E) The probability over time of fatal outcome within 28 days of diagnosis among UK patients with sequence data that can be matched to clinical records. Shaded regions show 95% confidence region of a 7-day moving average. Points with fewer than 20 observations are omitted. (F) Moving average of age among samples included in (E). (G) Viral load (real-time qPCR mean genome copies) estimated using SARS-CoV-2 RNA strands from 31 614D (614D) and 290 614G samples.CC BY · PubMed Central
Figure S2 Frequency of Sampling Spike 614G over Time, Related to Figure 3 This shows frequency and numbers of Spike 614G and Spike 614D samples over time. The size of points represents the number of samples collected on each day. The line and shaded region showed the MLE and confidence interval fit of the logistic growth model.
Figure S2 Frequency of Sampling Spike 614G over Time, Related to Figure 3 This shows frequency and numbers of Spike 614G and Spike 614D samples over time. The size of points represents the number of samples collected on each day. The line and shaded region showed the MLE and confidence interval fit of the logistic growth model.CC BY · PubMed Central
Figure S3 Frequency of Sampling Spike 614G after April 15, Related to Figure 3 This shows frequency and numbers of Spike 614G and Spike 614D samples over time using 37 DT clusters detected before March 31, 2020. The size of points represents the number of samples collected on each day. The line and shaded region showed the MLE and confidence interval fit of the logistic growth model.
Figure S3 Frequency of Sampling Spike 614G after April 15, Related to Figure 3 This shows frequency and numbers of Spike 614G and Spike 614D samples over time using 37 DT clusters detected before March 31, 2020. The size of points represents the number of samples collected on each day. The line and shaded region showed the MLE and confidence interval fit of the logistic growth model.CC BY · PubMed Central
Figure S4 The Estimated TMRCA for Each of 50 UK Clusters (Shaded Density) and Time of Each Sequence Sampled (Points), Related to Figure 3 Brown and gray respectively indicate Spike 614G and 614D clusters.
Figure S4 The Estimated TMRCA for Each of 50 UK Clusters (Shaded Density) and Time of Each Sequence Sampled (Points), Related to Figure 3 Brown and gray respectively indicate Spike 614G and 614D clusters.CC BY · PubMed Central
Figure S5 Distribution of Exponential Growth Rates (Left) and Rates of Decline (Right) for Spike 614G (Brown) and 614D (Gray) in Units of 1/Year, Related to Figure 3 Solid areas span the 95% credible interval. Points indicate the rates estimated for specific clusters, and are sized by the number of sequences in that cluster.
Figure S5 Distribution of Exponential Growth Rates (Left) and Rates of Decline (Right) for Spike 614G (Brown) and 614D (Gray) in Units of 1/Year, Related to Figure 3 Solid areas span the 95% credible interval. Points indicate the rates estimated for specific clusters, and are sized by the number of sequences in that cluster.CC BY · PubMed Central
Figure S6 Non-parametric Phylodynamic Estimates for Representative Clusters, Related to Figure 3 Estimated growth rates (A and C) and effective population size (B and D) for the two largest clusters with genotypes Spike 614D/G. The growth rate at the beginning of the time axis (Feb 1, 2020) is shown in panel E and provides a data point for the statistical comparisons between clusters. The size of points corresponds to the number of samples in each cluster.
Figure S6 Non-parametric Phylodynamic Estimates for Representative Clusters, Related to Figure 3 Estimated growth rates (A and C) and effective population size (B and D) for the two largest clusters with genotypes Spike 614D/G. The growth rate at the beginning of the time axis (Feb 1, 2020) is shown in panel E and provides a data point for the statistical comparisons between clusters. The size of points corresponds to the number of samples in each cluster.CC BY · PubMed Central
Figure 4 Clinical Severity in Patients in Association with the D614G Polymorphism and Age Clinical severity was measured on a four-point ordinal scale based on requirement for respiratory support. Upper panel: proportion of outcomes by age; lower panel: absolute counts. I&V, intubation and ventilation; NIV, non-invasive ventilation; HFNC, high-flow nasal cannulae; Oxygen, supplemental oxygen delivered by face mask or low-flow nasal cannulae.
Figure 4 Clinical Severity in Patients in Association with the D614G Polymorphism and Age Clinical severity was measured on a four-point ordinal scale based on requirement for respiratory support. Upper panel: proportion of outcomes by age; lower panel: absolute counts. I&V, intubation and ventilation; NIV, non-invasive ventilation; HFNC, high-flow nasal cannulae; Oxygen, supplemental oxygen delivered by face mask or low-flow nasal cannulae.CC BY · PubMed Central
Figure S7 Probability of Observing Spike 614G Virus in Patients Grouped by Age and Sex, Related to Figure 4 Panels on the lower diagonal show collected pairwise plots based on a UK-wide (England, Wales, Scotland, and Northern Ireland) multivariate dataset for the sample collection date, and the age and sex of the patient. Kernel Density Estimation (KDE) and count plots are on the diagonal. The upper right panel shows the estimated frequency of PCR cycle threshold (Ct) for D/G variants overlaid with kernel density estimates. Samples where the amino acid at position 614 was not recorded and samples with a Ct value of less than 14 or greater than 40 were excluded.
Figure S7 Probability of Observing Spike 614G Virus in Patients Grouped by Age and Sex, Related to Figure 4 Panels on the lower diagonal show collected pairwise plots based on a UK-wide (England, Wales, Scotland, and Northern Ireland) multivariate dataset for the sample collection date, and the age and sex of the patient. Kernel Density Estimation (KDE) and count plots are on the diagonal. The upper right panel shows the estimated frequency of PCR cycle threshold (Ct) for D/G variants overlaid with kernel density estimates. Samples where the amino acid at position 614 was not recorded and samples with a Ct value of less than 14 or greater than 40 were excluded.CC BY · PubMed Central

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Research works printed but not linked: 4

  1. du Plessis, 2020, Preliminary analysis of SARS-CoV-2 importation & establishment of UK transmission lineages, medRxiv
  2. Furuyama, 2020, Temporal data series of COVID-19 epidemics in the USA, Asia and Europe suggests a selective sweep of SARS-CoV-2 Spike D614G variant, arXiv
  3. Robertson, 2020, First report of COVID-19 in Scotland, Virological
  4. Yurkovetskiy, 2020, SARS-CoV-2 Spike protein variant D614G increases infectivity and retains sensitivity to antibodies that target the receptor binding domain, bioRxiv

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Volz, E., Hill, V., McCrone, J. T., Price, A., Jorgensen, D., O’Toole, Á., Southgate, J., Johnson, R., Jackson, B., Nascimento, F. F., Rey, S. M., Nicholls, S. M., Colquhoun, R. M., da Silva Filipe, A., Shepherd, J., Pascall, D. J., Shah, R., Jesudason, N., Li, K., Jarrett, R., Pacchiarini, N., Bull, M., Geidelberg, L., Siveroni, I., Koshy, C., Wise, E., Cortes, N., Lynch, J., Kidd, S., Mori, M., Fairley, D. J., Curran, T., McKenna, J. P., Adams, H., Fraser, C., Golubchik, T., Bonsall, D., Moore, C., Caddy, S. L., Khokhar, F. A., Wantoch, M., Reynolds, N., Warne, B., Maksimovic, J., Spellman, K., McCluggage, K., John, M., Beer, R., Afifi, S., Morgan, S., Marchbank, A., Price, A., Kitchen, C., Gulliver, H., Merrick, I., Southgate, J., Guest, M., Munn, R., Workman, T., Connor, T. R., Fuller, W., Bresner, C., Snell, L. B., Charalampous, T., Nebbia, G., Batra, R., Edgeworth, J., Robson, S. C., Beckett, A., Loveson, K. F., Aanensen, D. M., Underwood, A. P., Yeats, C. A., Abudahab, K., Taylor, B. E. W., Menegazzo, M., Clark, G., Smith, W., Khakh, M., Fleming, V. M., Lister, M. M., Howson-Wells, H. C., Berry, L., Boswell, T., Joseph, A., Willingham, I., Bird, P., Helmer, T., Fallon, K., Holmes, C., Tang, J., Raviprakash, V., Campbell, S., Sheriff, N., Loose, M. W., Holmes, N., Moore, C., Carlile, M., Wright, V., Sang, F., Debebe, J., Coll, F., Signell, A. W., Betancor, G., Wilson, H. D., Feltwell, T., Houldcroft, C. J., Eldirdiri, S., Kenyon, A., Davis, T., Pybus, O., du Plessis, L., Zarebski, A., Raghwani, J., Kraemer, M., Francois, S., Attwood, S., Vasylyeva, T., Torok, M. E., Hamilton, W. L., Goodfellow, I. G., Hall, G., Jahun, A. S., Chaudhry, Y., Hosmillo, M., Pinckert, M. L., Georgana, I., Yakovleva, A., Meredith, L. W., Moses, S., Lowe, H., Ryan, F., Fisher, C. L., Awan, A. R., Boyes, J., Breuer, J., Harris, K. A., Brown, J. R., Shah, D., Atkinson, L., Lee, J. C. D., Alcolea-Medina, A., Moore, N., Cortes, N., Williams, R., Chapman, M. 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K., Berger, D. J., Patel, G., Garcia-Casado, M. V., Dibling, T., McGuigan, S., Rogers, H. A., Hunter, A. D., Souster, E., Neaverson, A. S., Goodfellow, I., Loman, N. J., Pybus, O. G., Robertson, D. L., Thomson, E. C., Rambaut, A., & Connor, T. R.
Affiliations
  • Imperial College London (GB)
  • University of Birmingham (GB)
  • University of Glasgow (GB)
  • MRC University of Glasgow Centre for Virus Research (GB)
  • University of Cambridge (GB)
  • Royal Veterinary College (GB)
  • University of Edinburgh (GB)
  • Quadram Institute (GB)
  • Cardiff University (GB)
  • Public Health Wales (GB)
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2021-01
Volume
184
Issue
1
Pages
64-75.e11
ISSN
0092-8674 (ISSN-L)
DOI
10.1016/j.cell.2020.11.020
PMC
PMC7674007
OpenAlex
W3098697637
Cited by
1,006
References
63
Citations by year
2026: 23 · 2025: 36 · 2024: 75 · 2023: 128 · 2022: 290 · 2021: 423
FWCI
28.56
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
  • Northumbria Research Link (Northumbria University) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Acceda (Universidad de Las Palmas de Gran Canaria) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Lund University Publications (Lund University) (submittedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
  • University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
  • Spiral (Imperial College London) (submittedVersion, other-oa)
  • UEA Digital Repository (University of East Anglia) (submittedVersion)
  • Apollo (cc-by)
Funders
  • Biotechnology and Biological Sciences Research Council (BB/R012504/1, BB/M010996/1, BB/M009122/1)
  • European Commission (101003653)
  • Wellcome Trust (206298/Z/17/Z)
  • European Regional Development Fund
  • Medical Research Council (MR/L015080/1, MR/R015600/1, MC_UU_1201412)
  • Llywodraeth Cymru
  • CANDU Owners Group
  • European Research Council (725422)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
Keywords
SARS-CoV-2, spike protein, D614G mutation, positive selection, founder effect, viral transmissibility, pathogenicity, COVID-19 mortality, viral load, population genetics, phylogenetic clusters, United Kingdom
MeSH terms
Whole Genome Sequencing, COVID-19, SARS-CoV-2, Aspartic Acid, Glycine, United Kingdom, Humans, Mutation, Virulence, Genome, Viral, Amino Acid Substitution, Spike Glycoprotein, Coronavirus

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