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SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2
SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Background: since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. 

Methods: we present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. 

Results: we identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. 

Conclusions: as SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

COVID-19, Delta variant, Genetic diversity, Mutation, SARS-CoV-2, Transmission advantage
1471-2334
Eales, Oliver
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The COVID-19 Genomics UK (COG-UK) Consortium
Eales, Oliver
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Page, Andrew J.
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de Oliveira Martins, Leonardo
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Wang, Haowei
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Haw, David
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Jonnerby, Jakob
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Atchison, Christina
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Nunez, Rocio T.Martinez
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Eales, Oliver, Page, Andrew J. and de Oliveira Martins, Leonardo , The COVID-19 Genomics UK (COG-UK) Consortium (2022) SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2. BMC Infectious Diseases, 22 (1), [647]. (doi:10.1186/s12879-022-07628-4).

Record type: Article

Abstract

Background: since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. 

Methods: we present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. 

Results: we identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. 

Conclusions: as SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

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s12879-022-07628-4 - Version of Record
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Published date: 27 July 2022
Additional Information: Funding Information: The study was funded by the Department of Health and Social Care in England. Sequencing was provided through the COVID-19 Genomics UK Consortium (COG-UK) which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) [grant code: MC_PC_19027], and Genome Research Limited, operating as the Wellcome Sanger Institute.
Keywords: COVID-19, Delta variant, Genetic diversity, Mutation, SARS-CoV-2, Transmission advantage

Identifiers

Local EPrints ID: 469069
URI: http://eprints.soton.ac.uk/id/eprint/469069
ISSN: 1471-2334
PURE UUID: 9a5d6d46-cb90-489f-be53-0f69ebbe7dbf
ORCID for Jacqui A. Prieto: ORCID iD orcid.org/0000-0002-5524-6775
ORCID for Kordo Saeed: ORCID iD orcid.org/0000-0003-0123-0302
ORCID for David A. Simpson: ORCID iD orcid.org/0000-0001-9072-5088

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Date deposited: 06 Sep 2022 18:08
Last modified: 08 Nov 2022 02:55

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Contributors

Author: Oliver Eales
Author: Andrew J. Page
Author: Leonardo de Oliveira Martins
Author: Haowei Wang
Author: Barbara Bodinier
Author: David Haw
Author: Jakob Jonnerby
Author: Christina Atchison
Author: Samuel C. Robson
Author: Thomas R. Connor
Author: Nicholas J. Loman
Author: Tanya Golubchik
Author: Rocio T.Martinez Nunez
Author: David Bonsall
Author: Andrew Rambaut
Author: Luke B. Snell
Author: Rich Livett
Author: Catherine Ludden
Author: Sally Corden
Author: Eleni Nastouli
Author: Gaia Nebbia
Author: Ian Johnston
Author: Katrina Lythgoe
Author: M. Estee Torok
Author: Ian G. Goodfellow
Author: Kordo Saeed ORCID iD
Author: David K. Jackson
Author: Catherine Houlihan
Author: Dan Frampton
Author: William L. Hamilton
Author: Adam A. Witney
Author: James G. Shepherd
Author: Matthew D. Parker
Author: Sarah L. Buchan
Author: Christopher W. Holmes
Author: Christopher R. Jones
Author: Christopher Moore
Author: Thomas Williams
Author: Thomas Whalley
Author: Sophie Jones
Author: Sarah Taylor
Author: Charlotte A. Williams
Author: Louise Smith
Author: David G. Partridge
Author: Jamie Young
Author: Clare Pearson
Author: David J. Baker
Author: Richard Gregory
Corporate Author: The COVID-19 Genomics UK (COG-UK) Consortium

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