Report 10: 11th August 2020 – COVID-19 Genomics UK (COG-UK) Consortium
This report is provided at the request of SAGE and includes information on the ongoing state of the research being carried out. It should not be considered formal or informal advice. The conclusions of the ongoing scientific studies may be subject to change as further evidence becomes available and as such any firm conclusions would be premature.
- In just 5 months, COG-UK has sequenced and analysed more than 40K SARS-CoV genomes, accounting for ~50% of the global total.
- Beyond generating this unprecedented viral genomic dataset, COG-UK has already had a substantial impact on national and global efforts to understand and tackle the SARS-CoV-2 pandemic, as demonstrated by the suite of dedicated tools developed by COG-UK researchers, the growing list of ground-breaking publications using COG-UK data and tools, and by the increasing focus on integrating genomic insights into infection control decisions.
- Genomic analyses have demonstrated that cases of shock and multisystem inflammation in children positive for SARS-CoV-2 (known formally as paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS)) are not associated with specific polymorphisms in any viral gene.
Across 19 sequencing sites, the total number of SARS-CoV-2 genomes now sequenced by COG-UK stands at 40,035 (Figure 1a) which constitutes ~50% of the global total number of SARS-CoV-2 genomes sequenced (Figure 1b).
During 5 months since the inception of COG-UK, not only have an unprecedented number of viral genomes been sequenced and analysed, but the organisational, regulatory, laboratory and bioinformatic workflows, pipelines, tools and documentation underpinning this massive effort have been established, adapted or updated. Akin to assembling an aeroplane from parts while already in the process of taking off, hundreds of COG-UK researchers and individuals in support roles have maintained a furious pace to achieve milestones that under different circumstances would have been several years in the making. While COG-UK sequencing and analyses continues unabated, the advent of summer has allowed individual consortium members to take some time to recharge ahead of the next stages to come in the autumn and winter.
Recent improvements in sample handling and sequencing pipelines have enabled all positive Lighthouse samples to be processed as they arrive on site at the Wellcome Sanger Institute, which is a major milestone in our strategy for achieving prospective outbreak identification. Accordingly the use of COG-UK data is increasingly being integrated into the decision making process adopted by local and regional infection control teams. Work will continue to further reduce the time taken from a positive test at a diagnostic lab to QC genome data being made available for analysis and to better support infection control teams in generating and using genomic data.
A suite of dedicated bioinformatic platforms, pipelines and tools have been developed by COG-UK researchers (see ‘Summary of tools and pipelines developed by COG-UK’ below). In addition to forming the basis through which COG-UK viral genome data is analysed in the UK, many of these tools have become the gold standard approaches adopted by individual researchers and genomic consortia in countries around the world.
COG-UK researchers lead the world in applying genomic surveillance to understand the dynamics of the SARS-CoV-2 pandemic and to identify opportunities for intervention, resulting in the publication (or pre-printing) of 10 studies so far, with many more in the pipeline (see ‘Summary of COG-UK publications’ below).
In addition to these and other studies being undertaken, a major COG-UK initiative, the Hospital Onset Covid-19 Infection (HOCI) study, is now underway. The goal of HOCI is to determine empirically the impact that integrating real-time genomic sequencing can have on decision making by infection control teams (see ‘Progress update on COG-UK Hospital Onset Covid-19 Infection (HOCI) Study’ below).
Highlighted findings with public health implications
- Despite speculation to the contrary, a study of SARS-CoV-2 genomes from 61 children hospitalizedfor COVID-19 in London between late-March and mid-May 2020 found no evidence for specific single nucleotide polymorphisms to be associated with cases of paediatric inflammatory multisystemsyndrome temporally associated with SARS-CoV-2 (PIMS-TS).
Microreact visualization of SARS-CoV-2 lineage distribution
The latest data release into Microreact (Figure 2) shows 32,701 UK SARS-CoV-2 genomes highlighted on a tree of 69,358 global SARS-CoV-2 genomes. Lineage distributions are highlighted as pie charts on the map. Also shown is the global distribution on the spike protein residue 614 variants.
No evidence of viral polymorphisms associated with Paediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS).
Judith Breuer, Juanita Pang, Florencia A.T. Boshier (UCL Great Ormond Street Institute of Child Health, University College London), Nele Alders, Garth Dixon (Great Ormond Street Hospital for Children NHS Foundation Trust),
To determine whether cases of shock and multisystem inflammation in children positive for SARS-CoV-2 (known formally as paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS)) are associated with specific polymorphisms in any viral gene.
SARS-CoV-2 genomes were sequenced from 61 children hospitalized for COVID-19 in London between late-March and mid-May 2020, 36 of which were diagnosed with PIMS-TS, 11 of which were positive for SARS-CoV-2 viral RNA. Reads were quality checked and mapped to the SARS-CoV-2 reference genome prior to phylogenetic analysis.
A maximum likelihood phylogeny constructed using the paediatric COVID-19 cohort together with 130 SARS-CoV-2 sequences from community cases across North London revealed no clustering of viral sequences from PIMS-TS patients or non-PIMS-TS patients.
No single nucleotide polymorphisms (SNPs) were observed to be unique to genomes from PIMS-TS or other childhood cases and there was no difference in SNP distribution in the PIMS-TS, non-PIMS-TS or community cases. Looking at SARS-CoV-2 viral spike (S) protein in particular, which has previously been suggested as having the potential to drive the development of PIMS-TS, all genomes carried the D839 and A831 variants, while the majority of PIMS-ST (3/5), non PIMS-ST (6/8) and community cases (118/130) were 614G positive.
Overall, the data suggest that viruses causing PIMS-TS are representative of locally circulating SARS-CoV-2 and that there is no evidence for an association of PIMS-TS and the presence of new or unusual sequence polymorphisms.
Progress update on COG-UK Hospital Onset Covid-19 Infection (HOCI) Study
Judith Breuer (UCL Great Ormond Street Institute of Child Health, University College London)
Hospitals and healthcare settings have been shown to have a major role in the spread of SARS-CoV-2, including into the community. While rapid and repeated testing of patients and staff is key to identifying potential hospital outbreaks, it cannot tell us which infections are actually linked and therefore where to focus infection prevention and control (IPC) measures. In particular where the number of infections is also high in the community, it is difficult to distinguish hospital and community acquired infections using standard IPC1-3. Sequencing of pathogen genomes to identify closely matched sequences has been repeatedly shown to better identify hospital outbreaks than standard IPC measures alone1-3. Most studies are retrospective and therefore cannot easily interrupt evolving outbreaks. Recently however, rapid SARS-CoV-2 sequencing has been reported as able to identify sources of hospital outbreaks fast enough to change ongoing IPC practice and reduce further spread4. COG-UK Hospital Onset Covid Infection (COG-HOCI), a phase three interventional clinical trial aims to quantify just how useful rapid pathogen sequencing can be for IPC practice, by measuring changes in IPC, if any, prompted by the receipt of rapid SARS-CoV-2 sequencing results and determining whether this in turn reduces nosocomial spread of infection. The study is Urgent Public Health adopted.
COG-UK HOCI will involve over 20 NHS hospitals across the UK. All hospitals are linked to a COG-UK sequencing hub and will open as trial sites when evidence of increasing SARS-CoV-2 infection is reported. The clinical trial, which is supported by the UCL Comprehensive Clinical Trials Unit (CCTU) will use standardised Case Report Forms to measure the impact of delivery of a genomic sequencing data report to the infection prevention and control team, either within 48 hours or >4 days (to simulate a centralised sequencing facility) of sampling. The primary outcome measures will be:
- Whether rapid (<48 hours) availability of SARS-CoV-2 sequence data reduces the incidenceof IPC-defined HOCIs compared with delayed (>4 days) or standard of care (i.e. no sequencedata).
- Whether rapid genome data can identify previously undetected nosocomial transmission andhow this compares with delayed (>4 days) or no sequence data.
In addition we will use qualitative research methods to analyse the acceptability and feasibility of having SARS-CoV-2 sequence data for routine IPC practice and what would be required if routine sequencing for IPC were to be introduced across the NHS. Finally, COG-UK HOCI will carry out a health economic evaluation of sequencing for SARS-CoV-2 IPC.
- Full ethical approval.
- Urgent Public Health status.
- Completion of 7 case report forms.
- Completion of a sequence reporting tool (separately described, below).
- Completion of an implementation guide based on Behaviour Change Techniques, highlighting howbest to ensure viral sequencing and the SRT delivers positive outcomes in relation to reducingCOVID-19 other outbreaks.
- Completion of site set up protocols.
- Ongoing setup of hospitals and sequencing hubs across the UK*.
- Site initiation visits booked at lead sites in Sheffield Glasgow, London (IHT &GSTT).
*Portsmouth, Southampton, Cardiff, Swansea, Glasgow, Edinburgh, Liverpool, Leeds, Sheffield,Manchester, Stoke, Nottingham, Birmingham (2 sites), London (Imperial Healthcare Trust, Guys and StThomas trust, UCLH, Royal Free hospital Trust, Barts Healthcare Trust, St George’s Hospital Trust), Exeter.
Development of a Sequence Reporting Tool
Oliver Stirrup* (University College London), Josh Singer* (CVR Glasgow), Joseph Hughes (CVR Glasgow), Matt Parker (The University of Sheffield), David Partridge (Sheffield University Trust), Asif Tamuri (University College London), James Blackstone (University College London), Thushan de Silva (The University of Sheffield), Emma Thomson (The University of Glasgow), Judy Breuer (UCL Great Ormond Street Institute of Child Health, University College London).
Previous studies where sequence data have been used to inform IPC activity have relied on identifying putatively linked sequences from phylogenetic trees and then gathering metadata on the relevant patients to determine if it supports the observed linkage4. This process can delay full interpretation of sequence data for several days. In addition, the low substitution rate of SARS-CoV-2 means that identical sequences may not represent recent transmissions or hospital acquired infections, particularly if a sequence genotype in question is common in the community and or hospital. To overcome these barriers, we have developed a Sequence Reporting Tool (SRT).
The HOCI SRT uses a probability model to integrate viral sequences, patient metadata and sequence data on other patients in the ward, hospital and community, providing a likelihood that the “focus” HOCI patient acquired the virus on their current ward or elsewhere in the hospital. The HOCI SRT computes a report that can be generated as soon as the sequence data are available within 48 hours. The HOCI-SRT will enable rapid:
- Refuting of IPC-identified ward outbreaks where the HOCI patient and other patient sequences differ.
- Confirmation that a HOCI is part of an ward outbreak where HOCI patient’s sequence is closely matched to others on the ward.
- Identification of healthcare workers potentially linked to the HOCI focus case and other closely matched cases.
- Identification of other patients in the hospital potentially linked to the HOCI focus case.
- Identification of any other patients and staff with closely matched sequences who havebeen collocated with the HOCI focus case at any time within the previous three weeks.
The report generated by the SRT will provide a concise and easily interpreted summary of salient data regarding other sequences that could plausibly form an outbreak cluster within the ward or hospital that includes the focus case. The report will allow IPC decisions to be implemented quickly and thus maximise opportunities to use the sequence data to interrupt spread of infection. Preliminary results from a pilot of the HOCI-SRT using data from Glasgow and Sheffield has confirmed its favourable performance in relation to standard methods (paper in preparation).
Linking of the HOCI SRT to electronic patient records to incorporate detail of patient locations and patient and staff movements will further improve the probability readouts. Modification of the HOCI SRT for early identification of outbreaks in care homes and the community is planned.
- Roy S, Hartley J, Dunn H, Williams R, Williams CA, Breuer J. Whole-genome SequencingProvides Data for Stratifying Infection Prevention and Control Management of NosocomialInfluenza A. Clin Infect Dis. 2019;69(10):1649-1656.
- Brown JR, Roy S, Shah D, et al. Norovirus Transmission Dynamics in a Pediatric HospitalUsing Full Genome Sequences. Clin Infect Dis. 2019;68(2):222-228.
- Houldcroft CJ, Roy S, Morfopoulou S, et al. Use of Whole-Genome Sequencing of Adenovirusin Immunocompromised Pediatric Patients to Identify Nosocomial Transmission and Mixed-Genotype Infection. J Infect Dis. 2018;218(8):1261-1271.
- Meredith LW, Hamilton WL, Warne B, et al. Rapid implementation of SARS-CoV-2 sequencing toinvestigate cases of health-care associated COVID-19: a prospective genomic surveillance study. Lancet Infect Dis. 2020.
Summary of major tools and pipelines developed by COG-UK
In 5 months, COG-UK has sequenced more than 40,000 SARS-CoV-2 genomes, more than half of the global total. By comparison, the largest previous dataset for real-time virus epidemiology was ~1500 genomes from the West African Ebola outbreak, which were sequenced over the course of several years. Analysing genomic surveillance data and metadata on this scale and using it in real-time to inform disease control interventions is highly complex and entirely unprecedented. The task of grappling with this volume of genomic data has required COG-UK researchers to rapidly retool existing data management platforms and analytic approaches, as well as to develop entirely new pipelines and methods.
Below is a summary of the major data pipelines and analytical tools developed (or adapted) as part of COG-UK to date (See Figure 3 for a summary diagram of the relationship between the described tools). All of these tools are open source, in line with COG-UK’s commitment to open science, and sharing all data that we can as rapidly as possible. Most of the tools developed are currently hosted on MRC-CLIMB (Cloud Infrastructure for Microbial Bioinformatics).
COG-UK data and tools are being increasingly used in the UK and globally both for retrospective academic studies and to enable real-time genomic epidemiology to inform infection control strategies.
Majora (Malleable All-seeing Journal Of Research Artifacts)
Sam Nicholls (University of Birmingham)
Majora is a laboratory information management system (LIMS) developed as part of COG-UK. Majora enables information on samples and digital files to be stored together and can reconstruct the journey that a sample has taken from tube check-in at the lab through to data upload to a public database. The system uses a polymorphic artifact and process model, allowing for flexibility to store almost any metadata about any artifact. The initial version of Majora was online within 3 days, within 3 weeks it became the central repository for information about any sample within COG. Users upload metadata about their samples and sequencing to Majora which then makes that information available to all users and analysts in the consortium. The pipelines responsible for inbound and outbound data distribution link into Majora to find out what new samples to process and release.
Since March, Majora has been populated with over 40,000 samples and has served nearly 750,000 API requests within the consortium.
Sam Nicholls (University of Birmingham)
Elan is a reproducible workflow for enumerating and incorporating SARS-CoV-2 samples to ensure that files uploaded from across the consortium are valid. Elan is also responsible for conducting quality control and organising valid “artifacts” (consensus viral sequences and aligned reads) for use by analysts in downstream pipelines.
Anthony Underwood, Ben Taylor, Khalil Abudahab, David Aanensen (The Centre for Genomic Pathogen Surveillance, University of Oxford)
The metadata uploader is a standalone web application that allows COG-UK members to easily populate Majora with data, through dragging and dropping metadata files containing information about sequencing and metadata. Every sample sequenced and analysed by COG-UK has to go through Majora, Elan and the Metadata uploader, making them central to COG-UK data handling.
Josh Singer, David Robertson (MRC-University of Glasgow Centre for Virus Research)
CoV-GLUE is a publicly-accessible web application for the interpretation and analysis of SARS-CoV-2 genome sequences. CoV-GLUE is based on the GLUE software framework and is enabled by data from GISAID. It allows users to browse a database of amino acid replacements and coding region insertions and deletions observed in SARS-CoV-2 genome sequences from the pandemic. CoV-GLUE also allows users to analyse their own SARS-CoV-2 sequences by submitting them to the web application to receive an interactive report.
Pangolin (Phylogenetic Assignment of Named Global Outbreak LINeages)
Áine O’Toole, Verity Hill, JT McCrone, Emily Scher, Ben Jackson Andrew Rambaut (University of Edinburgh), Khali Abu-Dahab, Ben Taylor, Anthony Underwood, Corin Yeats and David Aanensen (The Centre for Genomic Pathogen Surveillance).
Pangolin is an open-source tool and web application developed to make it as easy as possible for researchers, public health workers and clinicians to obtain useful information from genome sequencing of SARS-CoV-2 by allowing them to assign lineages to genome sequences, view descriptive characteristics of the assigned lineages, view placement of the lineage in a global phylogeny and view the temporal and geographic distribution of the assigned lineages. Pangolin enables user samples to be contextualised within the global context by linking to Microreact (see below), which can visualize where and when sequenced samples of the same lineage have been observed. Pangolin is being used by researchers around the world, and as of the end of July, has assigned ~150,000 unique sequences globally.
Khalil Abudahab, Ben Taylor, Anthony Underwood, David Aanensen (The Centre for Genomic Pathogen Surveillance, University of Oxford)
Microreact is a web application that provides a simple, yet powerful, data linkage and visualization method for linking genomics to epidemiology, By linking phylogenetic trees together with geographic, temporal or other associated metadata research and public health audiences can easily interpret data. Microreact also encourages the open sharing of data. Within the Microreact COG-UK project, global SARS-CoV-2 lineage distributions (as defined by Pangolin) can be visualised together with, minimal metadata associated with genomes and a global tree indicating genome similarity. These data are currently updated when new genomes are processed and further automation will move data updates to close to real-time to enable the monitoring of trends in lineage distribution and movement. Microreact is used globally with several countries creating bespoke country-specific data views. Furthermore, local instances within PHW and PHS are enabling linkage of local sensitive data to genomic outputs in real-time.
Ben Jackson, Verity Hill, Rachel Colquhoun, Andrew Rambaut (University of Edinburgh)
Grapevine is a phylogenetics pipeline that operates (currently twice-weekly) on the UK SARS-CoV-2 genome sequences produced by Elan, to which it adds a dataset of sequences from the rest of the world, with the central aim of building a phylogenetic tree that captures the evolutionary relationship between all viruses sampled to date. This adds evolutionary context to samples’ epidemiological metadata, which together can be used to understand aspects such as transmission chains and introduction events. Grapevine defines and extracts UK SARS-CoV-2 clusters, assays sequences for genetic variants of interest (such as the D614G spike protein mutation), and assigns all sequences to a Pangolin global SARS-CoV-2 lineage. It produces the global tree and metadata used by Civet (below) to facilitate local cluster investigation, and by Microreact (below) to visualise the COG-UK data. For each run it automatically generates reports at UK, constituent nation, and regional levels, which summarise the geographic and genetic distribution of SARS-CoV-2 genomic samples in the UK.
Civet (Cluster Investigation & Virus Epidemiology Tool)
Áine O’Toole, Verity Hill, JT McCrone, Ben Jackson, Andrew Rambaut (University of Edinburgh)
Civet is an open source tool for cluster identification developed with ‘real-time’ genomics in mind. With the large phylogeny available through the COG-UK infrastructure on CLIMB, civet generates reports for sets of sequences of interest i.e. outbreak investigations. If the sequences are already on CLIMB and part of the large tree, civet will pull out the local context of those sequences, merging the smaller local trees as appropriate. If sequences haven’t yet been uploaded to CLIMB, for instance if they have just been sequenced, civet will find the closest sequence in the COG-UK database on climb, pull the local tree of that sequence out and add new sequences in. The local trees then get collapsed to display in detail only the sequences of interest so as not to inform investigations beyond what was suggested by epidemiological data. A report summarising the query sequences and rendering the collapsed trees is generated. The tips of these trees can be coloured by any categorical trait present in the input csv, and additional fields added to the tip labels. Optional figures may be added to describe the local background of UK lineages and to map the query sequences using coordinates, again colourable by a custom trait. Civet is a tool particularly suited to investigating outbreaks and reporting on new sequences produced across the UK.
Llama (Local lineage and monophyly assessment)
Áine O’Toole, Verity Hill, JT McCrone, Andrew Rambaut (University of Edinburgh)
Llama is an open source tool for pulling out local phylogenetic trees from a large tree (e.g. the global SARS-CoV-2 phylogeny) and enables the addition of new sequences directly to local trees.
Matt Bull (Public Health Wales)
ncov2019-artic-nf is a Nextflow pipeline for running the ARTIC network’s field bioinformatics tools (https://artic.network/ncov-2019/ncov2019-bioinformatics-sop.html) to take sequencing data (Illumina or Nanopore) and generate consensus genome sequences. The pipeline includes steps for basecalling, de-multiplexing, mapping, polishing and consensus generation.
Rob Johnson, Erik Volz (Imperial College London)
The phylodynamics dashboard is currently under development. The dashboard will provide an overview of growth and decline of SARS-CoV-2 lineages circulating in the UK. The dashboard will also facilitate exploration of data and visualization of trends over time and differences between regions.
Summary of COG-UK publications
Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity
Volz et al. medRxiv [preprint]
Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study
Meredith et al. Lancet Infect. Dis. 2020 Jul 14;S1473-3099(20)30562-4
No evidence of viral polymorphisms associated with Paediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS).
Pang et al. medRxiv [preprint]
periscope: sub-genomic RNA identification in SARS-CoV-2 ARTIC Network Nanopore Sequencing Data
Parker et al. bioRxiv [preprint]
CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing
Baker et al. bioRxiv [preprint]
Genomic epidemiology of SARS-CoV-2 spread in Scotland highlights the role of European travel in COVID-19 emergence
Da Silva Filipe et al. medRxiv [preprint]
An integrated national scale SARS-CoV-2 genomic surveillance network
The COVID-19 Genomics UK (COG-UK) consortium. Lancet Microbe. 2020 Jul; 1(3): e99–e100
Shared SARS-CoV-2 diversity suggests localised transmission of minority variants
Lythgoe et al. bioRxiv [preprint]
Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission
Rivett et al. eLife. 2020 May 11;9:e58728.
Spike mutation pipeline reveals the emergence of a more transmissible form of SARS-CoV-2
Korber et al. bioRxiv [preprint]
Download a PDF of this Report
Array ( [secondary_title] => Read the Wellcome Sanger Insitute's Blog post about their work and watch their video [excerpt] => Read the Wellcome Sanger Insitute's Blog post about their work and watch their video [byline_text] => Blog post and video by the Sanger Institute, a COG-UK Consortium partner [byline_date] => 20201023 [main_image] => 1221 [teaser_image] => [content] => In a <strong><a href="https://sangerinstitute.blog/2020/10/22/sequencing-covid-19-at-the-sanger-institute/" target="_blank" rel="noopener">blog post</a></strong> and <strong><a href="https://youtu.be/Fd40gunBTN0" target="_blank" rel="noopener">video</a></strong>, the Wellcome Sanger Institute takes you behind the scenes of its work to provide large-scale genome sequencing of thousands of COVID-19 samples as part of the COVID-19 Genomics UK (COG-UK) consortium. To read the blog post, please click here: <strong><a href="https://sangerinstitute.blog/2020/10/22/sequencing-covid-19-at-the-sanger-institute/" target="_blank" rel="noopener">Sequencing COVID-19 at the Sanger Institute</a></strong> The video is available below: <iframe src="https://www.youtube.com/embed/Fd40gunBTN0" width="560" height="315" frameborder="0" allowfullscreen="allowfullscreen"></iframe> [options_news_type] => Blog [options_exclude_from_feeds] => 0 [ID] => 1220 [post_title] => How a COG-UK Partner is helping to sequence tens of thousands of COVID-19 samples [post_type] => news_item [post_excerpt] => [post_content] => [post_url] => https://www.cogconsortium.uk/news_item/how-a-cog-uk-partner-is-helping-to-sequence-tens-of-thousands-of-covid-19-samples/ [post_name] => how-a-cog-uk-partner-is-helping-to-sequence-tens-of-thousands-of-covid-19-samples [created_at] => 2020-10-23 14:50:41 [updated_at] => 2020-10-23 14:50:41 [large_image_url] => /wp-content/uploads/2020/10/covid_sanger_blog-1024x391.jpg [main_image_url] => /wp-content/uploads/2020/10/covid_sanger_blog-1024x391.jpg [main_image_caption] => Wellcome Sanger Institute [image_string] => src="/wp-content/uploads/2020/10/covid_sanger_blog-1024x391.jpg" class="news-image" style="object-fit: cover" )
How a COG-UK Partner is helping to sequence tens of thousands of COVID-19 samples
Read the Wellcome Sanger Insitute's Blog post about their work and watch their video
Array ( [secondary_title] => Commentary for report 12 – 15th October 2020 [excerpt] => As of 22nd October, the COVID-19 Genomics UK (COG-UK) Consortium has sequenced more than 81,000 SARS-CoV-2 virus genomes from the UK, representing about 45 per cent of the global total. [byline_text] => Commentary [byline_date] => 20201023 [main_image] => 1225 [teaser_image] => [content] => As of 22<sup>nd</sup> October, the COVID-19 Genomics UK (COG-UK) Consortium has sequenced more than 81,000 SARS-CoV-2 virus genomes from the UK, representing about 45 per cent of the global total. Report 12 presents details of three separate studies using the genome data, and a summary of nationwide outbreak investigations that have used COG-UK genome data. The information shows the ongoing state of the research, and has not been peer-reviewed. Conclusions may change as more evidence becomes available. The first study is into a genetic mutation of the virus, termed N439K. This mutation results in a change to the Spike protein of the virus – the protein it uses to enter human cells. Because of its location, this mutation could affect a person’s immune response to the virus. The report stresses the need for systematic monitoring of virus mutations, especially when vaccinations begin. The second study details the use of viral genomic data in Norfolk, where the data has enabled local outbreak management. The third study assessed respiratory disease in cats, associated with human-to-cat transmission of SARS-CoV-2. Finally, there is a summary showing COG-UK data and tools have been used in over 120 SARS-CoV-2 outbreak investigations in the UK. <h3>N439K Mutation</h3> Researchers around the world have been monitoring genetic changes in the virus, which accumulate as it replicates and transmits. The aim is to understand if any changes, or mutations, have an effect on the virus’s function, the severity of disease it causes, or transmission. So far, no mutation seen has altered the disease severity that the virus causes. There is a focus on changes that affect the virus’s characteristic Spike protein. Like all coronaviruses, the SARS-CoV-2 virus has proteins that stick out of its core. These Spike proteins are the ‘crowns’ that give coronaviruses their name. It is this protein that allows the virus to attach to, and then enter, human cells. Any mutations that affect the Spike protein are vital to monitor, as they could potentially affect its function. It is also a part of the virus that our immune systems can ‘see’ and respond to. It <a href="https://www.cogconsortium.uk/news_item/commentary-cog-uk-report-9-25th-june-2020/">was reported previously</a> that a mutation in the Spike protein called D614G has increased in circulating viruses, in a way that is consistent with a slight increase in the rate of transmission. COG-UK researchers, led by <a href="https://www.gla.ac.uk/researchinstitutes/iii/staff/davidrobertson/">Professor David Robertson</a> and <a href="https://www.gla.ac.uk/researchinstitutes/iii/staff/emmathomson/">Professor Emma Thomson</a> at the University of Glasgow, assessed all mutations in the Spike protein. One of these - N439K – was of particular interest. N439K results in a change to the part of the Spike protein that binds to human cells. It is stable in the current virus population; it was seen in over 500 samples in Scotland early on in the UK epidemic, but then died out following the lockdown in March. It is now present again in virus samples from across Europe, the UK and the US. The wide spread of this mutation indicates the virus can thrive with such mutations – there is no detriment to its function. Once vaccinations begin at scale, the Spike protein will be under ‘selective pressure’, as many vaccines are targeted against it. It is possible that viruses with certain mutations will fare better under a vaccine-primed immune response than others. Ongoing, early-stage, laboratory studies support this hypothesis. Work has shown that virus with the N439K mutation is able to resist monoclonal antibodies – like those being trialled as treatments - yet still bind to its target on human cells. But unlike a monoclonal antibody treatment, vaccines will prompt the immune system to make a range of antibodies, and so even if the Spike protein can resist one, it is likely another will be able to neutralise the virus. The researchers stress the importance of systematically monitoring Spike protein mutations, finding and assessing new ones to understand their effects. This will be essential in the run up to any vaccine being introduced. The COG-UK team has set up a group, and systems, with the dedicated aim of monitoring new and existing mutations, prioritising those that need in-depth analyses. <h3>Local Outbreak Management</h3> Researchers led by <a href="https://quadram.ac.uk/people/andrew-page/">Dr Andrew Page at the Quadram Institute</a> in Norwich, report on the analysis of 1,035 SARS-CoV-2 genomes collected in Norfolk between March and August 2020. They combined genome sequence data with clinical data to understand the origin, genetic variation, transmission and spread of SARS-CoV-2 in the region. They confirmed an outbreak at a food-processing facility and ruled out a hospital setting as the source of another outbreak. Long term follow up found no evidence of reinfection. The team also found 16 viral variants, or lineages, in health care workers that were not present in patients, showing that PPE and infection control measures work to stop transmission of the virus. For full details, view the study on <a href="https://doi.org/10.1101/2020.09.28.20201475">MedRxiv</a>. <h3>Human to cat transmission</h3> <a href="https://www.gla.ac.uk/researchinstitutes/iii/staff/margarethosie/">Professor Margaret Hosie at the University of Glasgow</a> and colleagues looked at transmission of SARS-CoV-2 between humans and cats. Two cats from different COVID-19 infected households in the UK were shown to be infected with SARS-CoV-2 from humans. There is no evidence of cat-to-human transmission, or that any domestic animals play a role in the epidemiology of human infections with SARS-CoV-2. For full details, view the study on <a href="https://www.biorxiv.org/content/10.1101/2020.09.23.309948v1.full">BioRxiv</a>. <h3>Summary of studies using COG-UK genomic data</h3> COG-UK data and tools have been used in more than 120 live and retrospective SARS-CoV-2 outbreak investigations. This includes outbreaks in hospitals, communities, workplaces and settings managed by local authorities. For examples, see ‘<a href="https://www.cogconsortium.uk/wp-content/uploads/2020/09/8th-September-2020-Report-COVID-19-Genomics-UK-COG-UK-Consortium.pdf">COG-UK genomic surveillance in action</a>’. As the speed and scale of SARS-CoV-2 genome sequencing increases, the ability to use genomic data to investigate a wide range of scientific and public health questions is also growing. COG-UK aims to provide a large scale genomic surveillance service to support the investigation of more live outbreaks in the UK. [options_news_type] => Blog [options_exclude_from_feeds] => 0 [ID] => 1215 [post_title] => Commentary: COG-UK report 12 – 15th October 2020 [post_type] => news_item [post_excerpt] => [post_content] => [post_url] => https://www.cogconsortium.uk/news_item/commentary-cog-uk-report-12-15th-october-2020/ [post_name] => commentary-cog-uk-report-12-15th-october-2020 [created_at] => 2020-10-23 09:35:37 [updated_at] => 2020-10-24 05:37:41 [large_image_url] => /wp-content/uploads/2020/10/commentary_from_cogUK-1024x391.jpg [main_image_url] => /wp-content/uploads/2020/10/commentary_from_cogUK-1024x391.jpg [main_image_caption] => Hannah Olinger on Unsplash.com [image_string] => src="/wp-content/uploads/2020/10/commentary_from_cogUK-1024x391.jpg" class="news-image" style="object-fit: cover" )
Commentary: COG-UK report 12 – 15th October 2020
As of 22nd October, the COVID-19 Genomics UK (COG-UK) Consortium has sequenced more than 81,000 SARS-CoV-2 virus genomes from the UK, representing about 45 per cent of the global total.
Array ( [secondary_title] => <b>Please Note:</b> This report is provided at the request of SAGE and includes information on the ongoing state of the <span title="... research being carried out. It should not be considered formal or informal advice. The conclusions of the ongoing scientific studies may be subject to change as further evidence becomes available and as such any firm conclusions would be premature.">...</span> [excerpt] => COG-UK genome sequence data and tools have been used in more than 120 retrospective and live public health outbreak investigations in the UK since March 2020. Analysis of COG-UK and GISAID data highlights the need to establish a systematic approach for monitoring the appearance and spread of all variants of the SARS-CoV-2 virus [byline_text] => Report by the COVID-19 Genomics UK (COG-UK) Consortium [byline_date] => 20201016 [main_image] => 1183 [teaser_image] => [content] => <h2>Executive Summary</h2> <ul> <li>COG-UK genome sequence data and tools have been used in more than 120 retrospective and live public health outbreak investigations in the UK since March 2020.</li> <li>A viral lineage carrying a mutation, N439K, a probable antigenic variant owing to its location in the receptor binding motif of the SARS-CoV-2 spike protein, is now spreading in Europe (including 500+ infections in the UK). While there is no evidence that this variant will affect the efficacy of vaccines currently in development, it does highlight the need to establish a systematic approach for monitoring the appearance and spread of all variants and prioritising mutations of interest for further characterisation, in particular when selective pressure from mass vaccination programmes begins.</li> </ul> <hr /> <h2>COG-UK summary</h2> As described in <a href="https://www.cogconsortium.uk/wp-content/uploads/2020/09/8th-September-2020-Report-COVID-19-Genomics-UK-COG-UK-Consortium.pdf">COG-UK Report #11</a>, in addition to retrospective investigations, the consortium has been providing crucial support for the genomic surveillance of active SARS-CoV-2 outbreaks. An email survey of COG-UK site leads was used to collate information on the number of outbreaks in which investigations by the consortium using genomics have added value (Table 1). In total, COG-UK data and tools have been used in 120-166 live and retrospective SARS-CoV-2 outbreak investigations in public health and hospital settings in the UK to date. [caption id="attachment_1162" align="aligncenter" width="1024"]<a href="https://www.cogconsortium.uk/wp-content/uploads/2020/10/table1.jpg"><img class="wp-image-1162 size-large" src="https://www.cogconsortium.uk/wp-content/uploads/2020/10/table1-1024x143.jpg" alt="" width="1024" height="143" /></a> <strong>Table 1:</strong> A summary of live and retrospective outbreaks in the UK for which COG-UK and PHA researchers have used consortium genomic data and tools. Exceedance describes defined outbreaks, for instance in a workplace. Surveillance programmes describe requests to look at everything in a local authority area, school, care home etc. Ranges are reported as some sites were only able to provide estimates.[/caption] For a description of specific examples of the value added through the use of genomics by consortium members during outbreak investigations see <a href="https://www.cogconsortium.uk/wp-content/uploads/2020/09/8th-September-2020-Report-COVID-19-Genomics-UK-COG-UK-Consortium.pdf" target="_blank" rel="noopener">‘COG-UK genomic surveillance in action’, COG-UK Report #11</a>. As the transition to a new operational phase continues through late 2020 and into 2021, COG-UK will provide large scale genomic surveillance service to support the investigation of a growing proportion of live outbreaks in the UK. As described in the recent NERVTAG paper to SAGE, co-authored by COG-UK (<em>Is there evidence for genetic change in SARS-CoV-2 and if so, do mutations affect virus phenotype?</em>), there is increasing interest in monitoring mutations arising in the SARS-CoV-2 genome and determining whether these mutations have an impact on the biology of the virus, its transmission and the severity of the disease that it causes (See also ‘<em>A preliminary analysis of SARS-CoV-2 spike protein N439K lineages and surveillance of receptor binding mutations.</em>’ below). A COG-UK working group is being established to ensure that new and existing mutations are monitored in a systematic manner and that mutations of particular interest are prioritised for in depth analysis. As the speed and scale of SARS-CoV-2 genome sequencing increases, the ability to use genomic data to investigate a wide range of scientific and public health questions is also growing. Accordingly, COG-UK is strengthening its interactions with other SAGE sub-groups, research consortia and public health bodies in the UK, and globally, so that the opportunities provided by integrating genomics can be realised. Dr Andrew Page of the Quadram Institute, Norwich has recently agreed to represent COG-UK on the SAGE sub-group focussed on social care homes. Dr Ewan Harrison of the Wellcome Sanger Institute represents the consortium on the sub-group focussed on ethnicity, and Professor Judith Breuer of University College London on the nosocomial infection sub-group. All five Health and Social Care Trusts in Northern Ireland are joining the SIREN study (the PHE priority study to determine if prior SARS-CoV-2 infection in health care workers confers future immunity to re- infection), and the Belfast Health and Social Care Trust is expected to join COG-UK’s Hospital-Onset COVID-19 Infections study. Northern Ireland will therefore be represented in both of these important UK-wide studies, with viral genome sequencing/analysis via COG-UK. <hr /> <h2>Analysis updates</h2> <h3>A preliminary analysis of SARS-CoV-2 spike protein N439K lineages and surveillance of receptor binding domain mutations.</h3> <h4>Study leads</h4> David L Robertson<sup>1</sup>, Sebastian Maurer-Stroh<sup>2</sup>, Ana da Silva Filipe<sup>1</sup> and Emma C Thomson<sup>1</sup> 1. MRC-University of Glasgow Centre for Virus Research; 2. Bioinformatics Institute, Agency for Science, Technology and Research, Singapore <h4>Question addressed</h4> SARS-CoV-2 is continually accruing mutations as it replicates and transmits among the human population. While the majority of observed mutations have no effect on the biological properties of the virus and the rate of change is relatively slow, it is important that there is a systematic approach to identify new genetic changes and to assess their biological significance. While much attention has been focussed on the SARS-CoV-2 spike protein D614G mutation (See <a href="https://www.cogconsortium.uk/wp-content/uploads/2020/05/14th-May-2020-Report-COVID-19-Genomics-UK-COG-UK-Consortium.pdf" target="_blank" rel="noopener">COG-UK report #6</a>, <a href="https://www.cogconsortium.uk/wp-content/uploads/2020/07/25th-June-2020-Report-COVID-19-Genomics-UK-COG-UK-Consortium.pdf" target="_blank" rel="noopener">report #9</a> and Ref 1), other mutations in the spike protein may be of epidemiological and clinical relevance. This analysis describes the assessment of transmission and likely biological significance of one such mutation: N439K in the spike receptor binding motif is an example of a stable and circulating mutation in the receptor binding motif that binds to the ACE2 receptor on the surface of host cells to enable viral entry. <h4>Methodology</h4> Preliminary assessment of sampling proportions, phylogenetic distribution and the relationship between N/K at position 439 of the spike protein. <h4>Findings</h4> N439K was initially identified in a single lineage first detected in March 2020 and until recently was almost unique to Scotland where it infected more than 500 individuals (Figure 1). [caption id="attachment_1163" align="aligncenter" width="1024"]<a href="https://www.cogconsortium.uk/wp-content/uploads/2020/10/phylogenetic_tree_5000_scottish_genomes.jpg"><img class="wp-image-1163 size-large" src="https://www.cogconsortium.uk/wp-content/uploads/2020/10/phylogenetic_tree_5000_scottish_genomes-1024x395.jpg" alt="" width="1024" height="395" /></a> <strong>Figure 1:</strong> Phylogenetic tree of 5000 Scottish SARS-CoV-2 genomes from COG-UK dataset (17/07/20) highlighting D614G lineages (left panel) and N439K lineages (right panel). Note that the K-439 lineage and most N-439 lineages are also G-614.[/caption] This lineage also carries the D614G variant that has been associated with an increase in frequency among the population. In line with the cessation in viral transmission in Scotland coincident with the lockdown in spring 2020, this UK lineage is now extinct and has not been observed since the 20th June in South Lanarkshire. However, N439K has now been identified in another fast growing lineage that has been sampled between late June and mid-August in Romania, Norway, Switzerland, Ireland, Belgium, Germany and now in all parts of the UK (Figure 2). The apparent sudden rise in August/September appears to be linked to relaxation of control measures, the degree of sampling in these countries and its recent emergence in the UK with a high sampling rate. N439K has also been detected in four linked infections in the US and sporadically in genome data from elsewhere. [caption id="attachment_1164" align="aligncenter" width="1024"]<a href="https://www.cogconsortium.uk/wp-content/uploads/2020/10/phylogenetic_gisaid.jpg"><img class="wp-image-1164 size-large" src="https://www.cogconsortium.uk/wp-content/uploads/2020/10/phylogenetic_gisaid-1024x551.jpg" alt="" width="1024" height="551" /></a> <strong>Figure 2:</strong> A) Phylogenetic tree of SARS-CoV-2 genomes from the COG-UK data in the context of the GISAID dataset highlighting the original Scottish N439K lineage and the more recent and currently spreading European N439K lineage associated with multiple UK lineages. B) Number of weekly cases and country location of the two N439K lineages from mid-March to 02/10/2020.[/caption] Investigation of clinical outcomes from >1600 Scottish patients infected with either the lineage defined by 439K versus the wild-type lineage (439N) showed no significant difference in disease severity. Phylodynamic analysis demonstrated that the Scottish N439K lineage has a relatively fast growth rate in spreading through the population (analysis by Sam Lycett, Roslin Institute), but this is likely due to the D614G background of this lineage (Ref 1). Competitive virus growth experiments of these different mutants are underway at the MRC-University of Glasgow Centre for Virus Research. Investigation of clinical outcomes from >1600 Scottish patients infected with either the lineage defined by 439K versus the wild-type lineage (439N) showed no significant difference in disease severity. Phylodynamic analysis demonstrated that the Scottish N439K lineage has a relatively fast growth rate in spreading through the population (analysis by Sam Lycett, Roslin Institute), but this is likely due to the D614G background of this lineage (Ref 1). Competitive virus growth experiments of these different mutants are underway at the MRC-University of Glasgow Centre for Virus Research. <h4>Key Conclusions</h4> While SARS-CoV-2 genetic variation is accumulating, it is relatively constrained for an RNA virus. Some spike amino acid replacements do seem to be changing the biology of the virus (e.g. D614G), although there is no current evidence that N439K, or other variants in the receptor binding motif (such as T478I and V483I, shown to have antigenic significance) have increased the potential for transmission or altered disease severity. Importantly, these spike receptor binding domain variants appear to be relatively stable amino acid replacements that are not detrimental to viral fitness and are well tolerated in circulating lineages in the UK. This is a potential concern as vaccination programmes designed using these regions as targets begin to apply selective pressure on these lineages (see below for further discussion). <h4>Discussion</h4> In addition to N439K, other mutations are being observed in the spike receptor binding motif: S477N (>300 UK sequences), T478I (>100), S494P (>20), E484Q (>10), S477I (>10), E484Q (>10) and others at lower frequencies (Figure 3). [caption id="attachment_1165" align="aligncenter" width="1024"]<a href="https://www.cogconsortium.uk/wp-content/uploads/2020/10/fig3.jpg"><img class="wp-image-1165 size-large" src="https://www.cogconsortium.uk/wp-content/uploads/2020/10/fig3-1024x715.jpg" alt="" width="1024" height="715" /></a> <strong>Figure 3.</strong> Receptor binding surveillance for UK complete genomes. Mutations resulting in amino acid replacements in or near SARS-CoV-2’s spike receptor binding motif that have been observed by 2020-10-06 are shown. Replacements occurring at least twice are listed (top).[/caption] Collectively these demonstrate that mutations in the spike receptor binding motif are tolerated. The circulation of the N439K lineages demonstrates these viruses do not necessarily exhibit any apparent fitness cost. This is potentially concerning as this region is soon to be under selective pressure from a range of vaccine programmes. Some of the mutations in the receptor binding domain have been documented to confer resistance to neutralising antibodies and to influence interactions with the ACE2 receptor, which may facilitate the evolution of additional mutations in the surrounding region that can lead to viruses able circumvent the impact of those neutralizing antibodies. Support for this concern has been provide by laboratory experiments showing that it is possible to select for SARS-CoV-2 spike protein mutations in the receptor-binding domain (including N439K) that remain functional and able to bind ACE2 receptors but can confer resistance to monoclonal neutralising antibodies or convalescent plasma (Refs 2 and 3). It is therefore essential that a systematic approach is taken to identify and assess new genetic changes, in particular in regions important for host infection, viral transmission and for antigenicity. Whilst limited genomic diversity has emerged to date, this may change in the next phase of the epidemic as selective pressures exerted by vaccines, treatments and non-pharmaceutical interventions increases. As such, it is particularly important that surveillance of antigenic change is established in the lead up to the roll out of a vaccination program in the UK, since many of the vaccines under development target the spike protein. Accordingly COG-UK has established a working group to establish a mechanism to ensure that new and existing mutations are monitored in a systematic manner and that mutations of particular interest are prioritised for in depth genomic, phylodynamic and virological analyses. <h4>References</h4> 1. Volz, E. M, <em>et al</em>. Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity (2020) <em>medRxiv</em>, doi: <a href="https://doi.org/10.1101/2020.07.31.20166082" target="_blank" rel="noopener">https://doi.org/10.1101/2020.07.31.20166082</a>. 2. Weisblum, Y., Schmidt, F., <em>et al</em>. Escape from neutralizing antibodies by SARS-CoV-2 spike protein variants. (2020) <em>bioRxiv</em>, doi: <a href="https://doi.org/10.1101/2020.07.21.214759" target="_blank" rel="noopener">https://doi.org/10.1101/2020.07.21.214759</a>. 3. Li, Q. <em>et al</em>. The Impact of Mutations in SARS-CoV-2 Spike on Viral Infectivity and Antigenicity. (2020) <em>Cell</em>, doi: <a href="https://doi.org/10.1016/j.cell.2020.07.012" target="_blank" rel="noopener">https://doi.org/10.1016/j.cell.2020.07.012</a> <hr /> <h2>COG-UK recent publications</h2> <h3>Large scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management</h3> <em>MedRxiv</em> - doi: <a href="https://doi.org/10.1101/2020.09.28.20201475" target="_blank" rel="noopener">https://doi.org/10.1101/2020.09.28.20201475</a> <h4>Authors:</h4> Andrew J Page, Alison E Mather, Thanh Le Viet, Emma J Meader, Nabil-Fareed J Alikhan, Gemma L Kay, Leonardo de Oliveira Martins, Alp Aydin, David J Baker, Alexander J. Trotter, Steven Rudder, Ana P Tedim, Anastasia Kolyva, Rachael Stanley, Maria Diaz, Will Potter, Claire Stuart, Lizzie Meadows, Andrew Bell, Ana Victoria Gutierrez, Nicholas M Thomson, Evelien M Adriaenssens, Tracey Swingler, Rachel AJ Gilroy, Luke Griffith, Dheeraj K Sethi, Rose K Davidson, Robert A Kingsley, Luke Bedford, Lindsay J Coupland, Ian G Charles, Ngozi Elumogo, John Wain, Reenesh Prakash, Mark A Webber, SJ Louise Smith, Meera Chand, Samir Dervisevic, Justin O'Grady, The COVID-19 Genomics UK (COG-UK) consortium <h4>Summary:</h4> Between March and August 2020, over 3,200 COVID-19 cases were reported in Norfolk. 1565 positive clinical samples from 1376 cases were collected in four major hospitals, multiple minor hospitals, care facilities and community organisations within Norfolk and the surrounding area were collected and subjected to whole genome sequencing. 1035 cases resulted in genomes of sufficient quality for phylogenetic analysis, which revealed the presence of 26 distinct global lineages and 100 distinct UK lineages, with local evolution at a rate of 2 SNPs per month. Sequence data was combined with clinical metadata to understand the origin, genetic variation, transmission and spread of SARS-CoV-2 within the region. Highlights from this county-level analysis included the identification of a single sub-lineage associated with cases in 6 care facilities; confirming an outbreak at a food-processing facility; the ruling out of a nosocomial origin for another outbreak; and the identification of 16 lineages in health care workers not present in patients, demonstrating the effectiveness of infection control measures. The analysis also found that the D614G spike protein variant dominated in the samples, while longitudinal samples showed no evidence of reinfection. <hr /> <h3>Respiratory disease in cats associated with human-to-cat transmission of SARS-CoV-2 in the UK</h3> <em>BioRxiv</em> - doi: <a href="https://doi.org/10.1101/2020.09.23.309948" target="_blank" rel="noopener">https://doi.org/10.1101/2020.09.23.309948</a> <h4>Authors:</h4> Margaret J Hosie, Ilaria Epifano, Vanessa Herder, Richard J Orton, Andrew Stevenson, Natasha Johnson, Emma MacDonald, Dawn Dunbar, Michael McDonald, Fiona Howie, Bryn Tennant, Darcy Herrity, Ana Da Silva Filipe, Daniel G Streicker, Brian J Willett, Pablo R Murcia, Ruth F Jarrett, David L Robertson, William Weir, the COVID-19 Genomics UK (COG-UK) consortium <h4>Summary:</h4> During the COVID-19 pandemic, naturally occurring infections following transmission have been reported in domestic and non-domestic cats, dogs and mink. In this study, two cats from different COVID-19-infected households in the UK were shown to be infected with SARS-CoV-2 from humans. Infection was demonstrated using a range of approaches, including immunofluorescence, in situ hybridization, PCR testing. Post-mortem tissue samples for cat 1 displayed pathological and histological findings consistent with viral pneumonia, while cat 2 presented with rhinitis and conjunctivitis. Whole genome sequencing and analysis of the virus from cat 2 revealed five single nucleotide polymorphisms (SNPs) compared to the nearest sequenced UK human SARS-CoV-2 isolate (from the same UK county), although comparison with genomes from 9 other feline SARS-CoV-2 isolates revealed no shared cat-specific mutations. At present, there is no evidence of cat-to-human transmission or that cats, dogs or other domestic animals play any appreciable role in the epidemiology of human infections with SARS-CoV-2. <hr /> <h3>Download a PDF of this Report</h3> <ul> <li><strong><a href="https://www.cogconsortium.uk/wp-content/uploads/2020/10/15th-October-2020-Report-–-COVID-19-Genomics-UK-COG-UK-Consortium.pdf" target="_blank" rel="noopener">15th October 2020 Report – COVID-19 Genomics UK (COG-UK) Consortium.pdf</a></strong></li> </ul> [options_news_type] => Report [options_exclude_from_feeds] => 0 [ID] => 1161 [post_title] => Report 12: 15th October 2020 – COVID-19 Genomics UK (COG-UK) Consortium [post_type] => news_item [post_excerpt] => [post_content] => [post_url] => https://www.cogconsortium.uk/news_item/report-12-15th-october-2020/ [post_name] => report-12-15th-october-2020 [created_at] => 2020-10-16 09:38:49 [updated_at] => 2020-10-24 22:05:06 [large_image_url] => /wp-content/uploads/2020/10/report12_coguk-1024x391.jpg [main_image_url] => /wp-content/uploads/2020/10/report12_coguk-1024x391.jpg [main_image_caption] => [image_string] => src="/wp-content/uploads/2020/10/report12_coguk-1024x391.jpg" class="news-image" style="object-fit: cover" )
Report 12: 15th October 2020 – COVID-19 Genomics UK (COG-UK) Consortium
COG-UK genome sequence data and tools have been used in more than 120 retrospective and live public health outbreak investigations in the UK since March 2020. Analysis of COG-UK and GISAID data highlights the need to establish a systematic approach for monitoring the appearance and spread of all variants of the SARS-CoV-2 virus