# A solution to achieve sequencing from SARS-CoV-2 specimens with low viral loads: concatenation of reads from independent reactions

## TL;DR

This paper proposes a method to improve SARS-CoV-2 sequencing from low viral load samples by combining data from multiple sequencing runs.

## Contribution

The novel approach is sequencing in triplicate and concatenating reads to recover more genomic data from low viral load specimens.

## Key findings

- 28% of low viral load samples met standard quality coverage thresholds after read concatenation.
- 39% of samples showed more than 40% improvement in coverage.
- Lineage assignment became possible for 68.7% of samples previously unable to be classified.

## Abstract

During the pandemic, whole genome sequencing was critical to characterize SARS-CoV-2 for surveillance, clinical and therapeutical purposes. However, low viral loads in specimens often led to suboptimal sequencing, making lineage assignment and phylogenetic analysis difficult. We propose an alternative approach to sequencing these specimens that involves sequencing in triplicate and concatenation of the reads obtained using bioinformatics. This proposal is based on the hypothesis that the uncovered regions in each replicate differ and that concatenation would compensate for these gaps and recover a larger percentage of the sequenced genome.

Whole genome sequencing was performed in triplicate on 30 samples with Ct > 32 and the benefit of replicate read concatenation was assessed. After concatenation: i) 28% of samples reached the standard quality coverage threshold (> 90% genome covered > 30x); ii) 39% of samples did not reach the coverage quality thresholds but coverage improved by more than 40%; and iii) SARS-CoV-2 lineage assignment was possible in 68.7% of samples where it had been impaired.

Concatenation of reads from replicate sequencing reactions provides a simple way to access hidden information in the large proportion of SARS-CoV-2-positive specimens eliminated from analysis in standard sequencing schemes. This approach will enhance our potential to rule out involvement in outbreaks, to characterize reinfections and to identify lineages of concern for surveillance or therapeutical purposes.

The online version contains supplementary material available at 10.1186/s12985-024-02347-5.