MAJORA: Continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance

Abstract

Genomic epidemiology has become an increasingly common tool for epidemic response. Recent technological advances have made it possible to sequence genomes rapidly enough to inform outbreak response, and cheaply enough to justify dense sampling of even large epidemics. With increased availability of sequencing it is possible for agile networks of sequencing facilities to collaborate on the sequencing and analysis of epidemic genomic data.In response to the ongoing SARS-CoV-2 pandemic in the United Kingdom, the COVID-19 Genomics UK (COG-UK) consortium was formed with the aim of rapidly sequencing SARS-CoV-2 genomes as part of a national-scale genomic surveillance strategy. The network consists of universities, academic institutes, regional sequencing centres and the four UK Public Health Agencies.We describe the development and deployment of Majora, an encompassing digital infrastructure to address the challenge of collecting and integrating both genomic sequencing data and sample-associated metadata produced across the COG-UK network. The system was designed and implemented pragmatically to stand up capacity rapidly in a pandemic caused by a novel virus. This approach has underpinned the success of COG-UK, which has rapidly become the leading contributor of SARS-CoV-2 genomes to international databases and has generated over 60,000 sequences to date.

Combined epidemiological and genomic analysis of nosocomial SARS-CoV-2 transmission identifies community social distancing as the dominant intervention reducing outbreaks

“…This contrasts with the 9 clusters on elective and intermediate sites, which by policy did not knowingly admit COVID-19 patients, where only three (3/9, 33%) included a community-onset or indeterminate case that could have plausibly originated the outbreak (Figure 2d; Supplemental Figure 2 for ward movements). The validity of creating these final 14 clusters was supported by comparing their lineage enrichment compared to community sequences reported to COG-UK consortium CLIMB database during the study period (27). Clusters were enriched by between 1 (for the smallest clusters) and 14-fold (median 4-fold) (Figure 2d, Table S7).…”

“…The validity of creating these final 14 clusters was supported by comparing their lineage enrichment compared to community sequences reported to COG-UK consortium CLIMB database during the study period (27).…”

“…For a given haplotype, the hospital frequency (H) was calculated by dividing the number of patients in the dataset by the total number of sequenced patients in our dataset (370). COG-UK consortium data in COV_GLUE was extracted on 29th June 2020 to assess community haplotype frequencies (27). To assist with SQL queries, a view from several tables was created with the following SQL query: Two numbers were used to calculate the community frequency,: the entire community population of relevance, and the number of patients with the given haplotype in the community population.…”

Establishment & lineage dynamics of the SARS-CoV-2 epidemic in the UK

“…All SARS-CoV-2 genomes available on GISAID ( 14 ) on 23 June 2020 were downloaded and combined with all SARS-CoV-2 genomes sequenced by the COG-UK consortium ( 15 ) by 26 June 2020 (available at https://www.cogconsortium.uk/data/). The pipeline used to collect and process raw SARS-CoV-2 sequence data and sample-associated metadata across the national COG-UK network is described in ( 37 ). We removed sequences that were from duplicate or environmental samples, those without exact collection dates, and those with large clusters of substitutions or large indels.…”

MrHAMER yields highly accurate single molecule viral sequences enabling analysis of intra-host evolution

“…Currently, viral genomics informs the detection and management of drug resistance to antiviral therapy in rapidly mutating viruses such as HIV, Influenza [1], HCV [2], and HBV [3]. Recently, the development of distributed viral genomics methodologies have allowed successful epidemiological surveillance of SARS-CoV2, ebolaviruses, Zika virus, and other emerging viruses [4,5]. However, technical challenges remain in the sequencing of rapidly-mutating RNA viruses which, due to their high intra-host diversity, require specialized sequencing approaches to allow the unambiguous identification of mutation patterns [6].…”