Catching SARS-CoV-2 by Sequence Hybridization: a Comparative Analysis

Abstract

Controlling and monitoring the still ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic regarding geographical distribution, evolution, and emergence of new mutations of the SARS-CoV-2 virus is only possible due to continuous next-generation sequencing (NGS) and sharing sequence data worldwide. Efficient sequencing strategies enable the retrieval of increasing numbers of high-quality, full-length genomes and are, hence, indispensable. Two opposed enrichment methods, tiling multiplex PCR and sequence hybridization by bait capture, have been established for SARS-CoV-2 sequencing and are both frequently used, depending on the quality of the patient sample and the question at hand. Here, we focused on the evaluation of the sequence hybridization method by studying five commercially available sequence capture bait panels with regard to sensitivity and capture efficiency. We discovered the SARS-CoV-2-specific panel of Twist Bioscience to be the most efficient panel, followed by two respiratory panels from Twist Bioscience and Illumina, respectively. Our results provide on the one hand a decision basis for the sequencing community including a computation for using the full capacity of the flow cell and on the other hand potential improvements for the manufacturers. IMPORTANCE Sequencing the genomes of the circulating SARS-CoV-2 strains is the only way to monitor the viral spread and evolution of the virus. Two different approaches, namely, tiling multiplex PCR and sequence hybridization by bait capture, are commonly used to fulfill this task. This study describes for the first time a combined approach of droplet digital PCR (ddPCR) and NGS to evaluate five commercially available sequence capture panels targeting SARS-CoV-2. In doing so, we were able to determine the most sensitive and efficient capture panel, distinguish the mode of action of the various bait panels, and compute the number of read pairs needed to recover a high-quality full-length genome. By calculating the minimum number of read pairs needed, we are providing optimized flow cell loading conditions for all sequencing laboratories worldwide that are striving for maximizing sequencing output and simultaneously minimizing time, costs, and sequencing resources.

Keywords: NGS; SARS-CoV-2; adaptive mutations; ddPCR; enrichment; mutations; next-generation sequencing; sequence capture.

FIG 1

Graphical overview of the performed workflow. RNA input pools, differing in SARS-CoV-2 concentration, were subject to reverse transcription and second-strand analysis before entering three different library preparation methods. For better statistics, each RNA input pool was used three times during each library preparation method and for each bait panel tested. Before sequence hybridization, the triplicates were pooled by mass, resulting in five pools per bait, which were sequenced on an Illumina MiSeq after the enrichment process.

FIG 2

Comparison of the quality control parameters after library preparation by three different methods. (a) Mean library size obtained by the analysis of the fragment size of the triplicates per input pool. Usage of the Illumina Nextera Flex protocol results in the largest libraries, followed by the libraries of Twist Bioscience and NEBNext. (b) Concentrations of the individual libraries were analyzed with a Qubit fluorometer. Combining the values of the triplicates per input pool resulted in a mean concentration per pool. Here, the libraries produced by the Twist Bioscience protocol reached the highest mean concentration, followed by the libraries of the Illumina Nextera Flex and the NEBNext protocols. (c) Mean library mass was determined by the measured concentration and the elution volume. Here again, the Twist Bioscience libraries succeeded those of the Illumina Nextera Flex and NEBNext.

FIG 3

Analysis of the hybridization sequence capture by ddPCR. (a and b) SARS-CoV-2-specific libraries were quantified by primers targeting ORF1a, while nontarget libraries were quantified by the presence of human ubiquitin C (UBC). The ORF1a/UBC ratio was plotted before (a) and after (b) the enrichment, with the highest ratio shown for the two Illumina panels, followed by the two Twist Bioscience panels and the MyBaits panel. (c and d) The change in ORF1a and UBC was plotted by dividing the counted concentration of ORF1a and UBC, respectively, after the enrichment with the respective concentration before the enrichment. The strongest change in ORF1a was observed by the two Twist Bioscience panels, while the strongest reduction in UBC was detected with the Illumina panels.

FIG 4

Analysis of the efficiency of the sequence hybridization panels by NGS. (a) The numbers of SARS-CoV-2 mapping reads out of a subset of 130,000 reads were plotted against the pools, with the highest mapping ratio shown for the Twist Bioscience SARS-CoV-2 panel. (b) Breadth of coverage, defined by the number of covered bases of the SARS-CoV-2 genome, was compared for all panels. Use of the Twist Bioscience SARS-CoV-2 panel led to a nearly complete coverage of the SARS-CoV-2 genome already in pool 2, while the respiratory panels of Twist Bioscience and Illumina reached the full breadth of coverage in pool 3. (c) Comparison of the panels in regard to reaching a full-length genome with a coverage of 20×.