Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern

  1. Karthik Murugadoss
  2. Michiel J M Niesen
  3. Bharathwaj Raghunathan
  4. Patrick J Lenehan
  5. Pritha Ghosh
  6. Tyler Feener
  7. Praveen Anand
  8. Safak Simsek
  9. Rohit Suratekar
  10. Travis K Hughes
  11. Venky Soundararajan

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Abstract

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged, resulting in repeated COVID-19 surges. With over 6 million SARS-CoV-2 genomes sequenced, there is unprecedented data to decipher the evolution of fitter SARS-CoV-2 variants. Much attention has been directed to studying the functional importance of specific mutations in the Spike protein, but there is limited knowledge of genomic signatures shared by dominant variants. Here, we introduce a method to quantify the genome-wide distinctiveness of polynucleotide fragments (3- to 240-mers) that constitute SARS-CoV-2 sequences. Compared to standard phylogenetic metrics and mutational load, the new metric provides improved separation between Variants of Concern (VOCs; Reference = 89, IQR: 65–108; Alpha = 166, IQR: 149–181; Beta 131, IQR: 114–149; Gamma = 164, IQR: 150–178; Delta = 235, IQR: 217–255; and Omicron = 459, IQR: 395–521). Omicron's high genomic distinctiveness may confer an advantage over prior VOCs and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Evaluation of 883 lineages highlights that genomic distinctiveness has increased over time (R2 = 0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed. This study demonstrates the value of characterizing SARS-CoV-2 variants by genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that monitoring of genomic distinctiveness would facilitate rapid assessment of viral fitness.

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  1. Version published to 10.1093/pnasnexus/pgac018
  2. Version published to 10.1101/2021.12.23.21268315v2 on medRxiv
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    Table 2: Resources

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    For each pair of variants, we computed the Cohen’s D between the distributions of distinctive n-mer sequence counts using the following equation:The Jensen-Shannon (JS) Divergence values were computed using the SciPy package (version 1.7.3) in Python (version 3.7.10).
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Methodological Considerations and Study Limitations: Most of the analyses presented here refer to 9-mer polynucleotides, but it is reasonable to consider polynucleotides of various lengths. Indeed, we found that this metric was robust to smaller and larger polynucleotides, with particularly strong separation between some VOCs observed for n-mers between 15 and 30 nucleotides. The presented results based on 9-mers should be considered as an example to illustrate the utility of this metric rather than the definitive resolution. There are also some limitations to these analyses. First, the number of Omicron sequences currently available in the GISAID database is low compared to other VOCs such as Delta. Our protocol, which samples genomes with replacement, could result in oversampling of Omicron sequences. This limitation will be addressed in the coming months as more Omicron sequences are deposited. Second, while we consider all sliding nucleotide 9-mers, it is also worth exploring similar metrics of genomic diversity while constraining to protein-coding nucleotide n-mers or amino acid n-mers themselves. Third, both methods presented here compare one lineage to one or many others, and thus they are sensitive to the lineage composition in the complement group. For example, several Delta sublineages show relatively low polynucleotide distinctiveness through the A*(1-B) metric, but this is likely due to the fact that they are being compared to other Delta sublineages which are hig...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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    Results from scite Reference Check: We found no unreliable references.

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  4. Version published to 10.1101/2021.12.23.21268315v1 on medRxiv