Scalable neighbour search and alignment with uvaia (preprint)

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences, which uvaia alleviates by using measures of sequence similarity that consider partially ambiguous sites. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but also for improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance. (preprint)

Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks.

The new normal? Dynamics and scale of the SARS-CoV-2 variant Omicron epidemic in England (preprint)

Summary The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants which have led to substantial changes in the epidemiology of the virus. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant was first detected in late November 2021 and exhibited a high degree of immune evasion, leading to increased infection rates in many countries. However, estimates of the magnitude of the Omicron wave have relied mainly on routine testing data, which are prone to several biases. Here we infer the dynamics of the Omicron wave in England using PCR testing and genomic sequencing obtained by the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys testing random samples of the population of England. We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections in England during February-March 2022 as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct genomic variants, intermittent epidemics of similar magnitude as the Omicron wave may become the ‘new normal’.

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 (preprint)

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. Here 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. From 9 to 27 September 2021 (round 14) and 19 October to 5 November 2021 (round 15), all lineages sequenced within REACT-1 were Delta or a Delta sub-lineage with 44 unique lineages identified. The proportion of the original Delta variant (B.1.617.2) was found to be increasing between September and November 2021, which may reflect an increasing number of sub-lineages which have yet to be identified. The proportion of B.1.617.2 was greatest in London, which was further identified as a region with an increased level of genetic diversity. The Delta sub-lineage AY.4.2 was found to be robustly increasing in proportion, with a reproduction number 15% (8%, 23%) greater than its parent and most prevalent lineage, AY.4. 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. Though no difference in the viral load based on cycle threshold (Ct) values was identified, a lower proportion of those infected with AY.4.2 had symptoms for which testing is usually recommend (loss or change of sense of taste, loss or change of sense of smell, new persistent cough, fever), compared to AY.4 (p = 0.026). The evolutionary rate of SARS-CoV-2, as measured by the mutation rate, was found to be slowing down during the study period, with AY.4.2 further found to have a reduced mutation rate relative to AY.4. 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.

Replacement of the Alpha variant of SARS-CoV-2 by the Delta variant in Lebanon between April and June 2021 (preprint)

Background The COVID-19 pandemic continues to expand globally, with case numbers rising in many areas of the world, including the Eastern Mediterranean Region. Lebanon experienced its largest wave of COVID-19 infections from January to April 2021. Limited genomic surveillance was undertaken, with just twenty six SARS-CoV-2 genomes available for this period, nine of which were from travellers from Lebanon detected by other countries. Additional genome sequencing is thus needed to allow surveillance of variants in circulation. Methods Nine hundred and five SARS-CoV-2 genomes were sequenced using the ARTIC protocol. The genomes were derived from SARS-CoV-2-positive samples, selected retrospectively from the sentinel COVID-19 surveillance network, to capture diversity of location, sampling time, gender, nationality and age. Results Although sixteen PANGO lineages were circulating in Lebanon in January 2021, by February there were just four, with the Alpha variant accounting for 97% of samples. In the following two months, all samples contained the Alpha variant. However, this had changed dramatically by June and July, when all samples belonged to the Delta variant. Discussion This study provides a ten-fold increase in the number of SARS-CoV-2 genomes available from Lebanon. The Alpha variant, first detected in the UK, rapidly swept through Lebanon, causing the country’s largest wave to date, which peaked in January 2021. The Alpha variant was introduced to Lebanon multiple times despite travel restrictions, but the source of these introductions remains uncertain. The Delta variant was detected in Gambia in travellers from Lebanon in mid-May, suggesting community transmission in Lebanon several weeks before this variant was detected in the country. Prospective sequencing in June/July 2021 showed that the Delta variant had completely replaced the Alpha variant in under six weeks.

SARS-CoV-2 variants of concern dominate in Lahore, Pakistan in April 2021 (preprint)

BackgroundThe SARS-CoV-2 pandemic continues to expand globally, with case numbers rising in many areas of the world, including the Indian sub-continent. Pakistan has one of the world s largest population, of over 200 million people and is experiencing a severe third wave of infections caused by SARS-CoV-2 that begun in March 2021.In Pakistan, during third wave until now only 12 SARS-CoV-2 genomes have been collected and among these 9 are from Islamabad. This highlights the need for more genome sequencing to allow surveillance of variants in circulation. In fact more genomes are available among travellers with a travel history from Pakistan, than from within the country itself. MethodsFor a better understanding of the circulating variants in Lahore and surrounding areas with a combined population of 11.1 million, within a week of April 2021, 102 samples were sequenced. The samples were randomly collected from 2 hospitals with a diagnostic polymerase chain reaction (PCR) cutoff value of less than 25 cycles. ResultsAnalysis of the lineages shows that B.1.1.7 (first identified in the UK, Alpha variant) dominates, accounting for 97.9% (97/99) of cases, with B.1.351 (first identified in South Africa, Beta variant) accounting for 2.0% (2/99) of cases. No other lineages were observed. DiscussionIn depth analysis of the B.1.1.7 lineages indicates multiple separate introductions and subsequent establishment within the region. Eight samples were identical to genomes observed in Europe (7 UK, 1 Switzerland), indicating recent transmission. Genomes of other samples show evidence that these have evolved, indicating sustained transmission over a period of time either within Pakistan or other countries with low density genome sequencing. Vaccines remain effective against B.1.1.7, however the low level of B.1.351 against which some vaccines are less effective demonstrates the requirement for continued prospective genomic surveillance.

Genomic epidemiology of the SARS-CoV-2 epidemic in Zimbabwe: Role of international travel and regional migration in spread (preprint)

Zimbabwe reported its first case of SARS-Cov-2 infection in March 2020, and case numbers increased to more than 8,099 to 16th October 2020. An understanding of the SARS-Cov-2 outbreak in Zimbabwe will assist in the implementation of effective public health interventions to control transmission. Nasopharyngeal samples from 92,299 suspected and confirmed COVID-19 cases reported in Zimbabwe between 20 March and 16 October 2020 were obtained. Available demographic data associated with those cases identified as positive (8,099) were analysed to describe the national breakdown of positive cases over time in more detail (geographical location, sex, age and travel history). The whole genome sequence (WGS) of one hundred SARS-CoV-2-positive samples from the first 120 days of the epidemic in Zimbabwe was determined to identify their relationship to one another and WGS from global samples. Overall, a greater proportion of infections were in males (55.5%) than females (44.85%), although in older age groups more females were affected than males. Most COVID-19 cases (57 %) were in the 20-40 age group. Eight lineages, from at least 25 separate introductions into the region were found using comparative genomics. Of these, 95% had the D614G mutation on the spike protein which was associated with higher transmissibility than the ancestral strain. Early introductions and spread of SARS-CoV-2 were predominantly associated with genomes common in Europe and the United States of America (USA), and few common in Asia at this time. As the pandemic evolved, travel-associated cases from South Africa and other neighbouring countries were also recorded. Transmission within quarantine centres occurred when travelling nationals returning to Zimbabwe. International and regional migration followed by local transmission were identified as accounting for the development of the SARS-CoV-2 epidemic in Zimbabwe. Based on this, rapid implementation of public health interventions are critical to reduce local transmission of SARS-CoV-2. Impact of the predominant G614 strain on severity of symptoms in COVID-19 cases needs further investigation.

Large scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management (preprint)

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3,200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organisations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1,565 positive samples (172 per 100,000 population) from 1,376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6% of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. 1,035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically-distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a sublineage associated with 6 care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients indicating infection control measures were effective; found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.

CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing (preprint)

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 24 samples at a time. There is a need for a higher throughput method to reduce cost per genome. Here we present CoronaHiT, a method capable of multiplexing up to 95 small genomes on a single Nanopore flowcell, which uses transposase mediated addition of adapters and PCR based addition of symmetric barcodes. We demonstrate the method using 48 and 94 SARS-CoV-2 genomes per flowcell, amplified using the ARTIC protocol, and compare performance with Illumina and ARTIC ONT sequencing. Results demonstrate that all sequencing methods produce inaccurate genomes when the RNA extract from SARS-CoV-2 positive clinical sample has a cycle threshold (Ct) >= 32. Results from set same set of 23 samples with a broad range of Cts show that the consensus genomes have >90% coverage (GISAID criteria) for 78.2% of samples for CoronaHiT-48, 73.9% for CoronaHiT-94, 78.2% for Illumina and 73.9% for ARTIC ONT, and all have the same clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 94 SARS-CoV-2 genomes per nanopore flowcell without compromising the quality of the resulting genomes while reducing library preparation complexity and significantly reducing cost. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.