Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance

Abstract

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.

Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications

“…Having a standardized structure in place would also improve APIs and cloud query access to pathogen sequence data and associated contextual data, resulting in better third party visualisations, dashboards, analyses [ 48 ], risk assessment, etc. And finally, this standard would enable a single linkage point to other heavily used public genomic repositories, like GISAID [ 49 ], American Type Culture Collection (ATCC), Genome Portal [ 50 ], Joint Genome Institute Genomes OnLine Database (GOLD) [ 51 ], and others that hold the same or similar types of data, creating more interoperability between these databases.…”

Lessons learned: overcoming common challenges in reconstructing the SARS-CoV-2 genome from short-read sequencing data via CoVpipe2

“…Although amplicon-based approaches are widely used, these technologies are associated with flaws and limitations that must be considered to ensure that the genotypes obtained, and thus the resulting genome sequences, are reliable. 13 , 54 While some of these implementations might seem obvious and easy to fix, we frequently observed specific errors in the vast amount of consensus genome sequences sent to us via the DESH system.…”

“…Accurate primer clipping to avoid dilution and edge effects: Primer clipping is an essential step for amplicon sequencing data because primers are inherent to the reference sequence and can disguise true variants in the sample. 13 However, removing primers before the mapping step can result in unwanted edge effects. 55 For example, deletions located close to the end of amplicons may be soft-clipped by the mapping software and hence can not be called as variants subsequently ( Figure 2 ).…”

“… 12 A recent study also found significant differences between bioinformatics approaches that use the same input data but detect different variants in SARS-CoV-2 samples. 13 In addition, each technology and sequencing approach has its own advantages and limitations, challenging a harmonized genomic surveillance of the virus. 14 …”

Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications

“…Having a standardized structure in place would also improve APIs and cloud query access to pathogen sequence data and associated contextual data, resulting in better 3 rd party visualizations, dashboards, analyses (47), risk assessment, etc. And finally, this standard would enable a single linkage point to other heavily used public genomic repositories, like GISAID (48), American Type Culture Collection (ATCC), Genome Portal (49), Joint Genome Institute Genomes OnLine Database (GOLD) (50), and others that hold the same or similar types of data, creating more interoperability between these databases.…”