Episode 47: SARS-CoV-2 Rapid roundup and questions answered

In this episode of the microbinfie podcast, experts discuss the intricate challenges of SARS-CoV-2 genomic analysis, exploring lineage classification, mutation tracking, and the complexities of viral genome sequencing.

In this roundup, we delve into the latest questions and developments in SARS-CoV-2 genomics. This information is based on discussions and data recorded on 5 February 2021.

Topics Covered

• SNP and Lineage Assignment: Explore how the absence of even a single Single Nucleotide Polymorphism (SNP) can disrupt the assignment of a viral lineage, and understand the mechanism behind it.

• Lineage Descriptions: How are viral lineages defined with sequences of mutation events?

• Convergent Evolution: Is convergent evolution occurring in SARS-CoV-2? Discover the trends being observed.

• Co-Infections: Have different SARS-CoV-2 lineages been found co-infecting individuals?

• Nanopore Basecalling: Should you use High Accuracy (HAC) basecalling, and is acquiring a GPU for this purpose beneficial?

• Sequencing Logistics: Address the basic logistical challenges of sequencing in various parts of the world.

• Recombination Studies: Can the ARTIC protocol be used alongside Illumina technology to study recombination in SARS-CoV-2?

• Sequence Annotation: Learn how to annotate a SARS-CoV-2 sequence.

Useful Tools and Resources

• COV-GLUE: This is an essential tool for sequence annotation. Visit COV-GLUE for more information.

• Nextclade & SNPeff: For sequence analysis:

  • Convert FASTA files using Nextclade
  • Analyze VCF files with SNPeff

• Community Spread Detection: Use NextStrain to spot patterns and evidence of community spread.

• Types of Variants: Check out the GitHub repository cov-ert/type_variants for detailed information on variant types.

Call for Open Sharing

There's a strong ongoing appeal within the scientific community for the fully open sharing of coronavirus genome data. Open sharing is critical for global collaboration and combating the pandemic effectively. Read more about these efforts in the article: Nature Article.

Key Points

1. Viral Lineage Classification

• Single nucleotide polymorphisms (SNPs) can dramatically alter lineage assignments
• Machine learning approaches like Pangolin use decision tree methods for classification
• Phylogenetic placement and manual inspection are crucial for accurate lineage determination

2. Mutation Tracking and Evolution

• The E484K mutation ("eek") has been observed independently in multiple lineages
• Convergent evolution is still being investigated for viral mutations
• Careful epidemiological tracking is essential for understanding viral spread

3. Sequencing Challenges

• RNA degradation can lead to potential misinterpretation of genomic data
• Strict protocols and quality control are critical in viral genome sequencing
• Custom bioinformatics pipelines require extensive validation

Take-Home Messages

• Always manually verify algorithmic classifications
• Be cautious of potential contamination in genomic samples
• Collaborative, open data sharing is crucial for pandemic research