A Parallel Algorithm for Designing Primer and Probe for Accurate Detection of Severe Acute Respiratory Syndrome Coronavirus

Abstract

The spread of the SARS-CoV-2 in many countries has led to multiple SARS-CoV-2 variants, and this makes accurate detection of SARS-CoV-2 difficult. The reverse transcription real-time polymerase chain reaction (RT-PCR) is a widely used gold-standard method to detect SARS-CoV-2, and accurate designing of primers and probes is crucial to prevent false negative results, especially with the rise of new dangerous variants. Therefore, it is significant to determine primers and probes targeting conserved regions in the genome sequence to diagnose many variants of SARS-CoV-2. In this paper, we propose a novel and efficient method for identifying PCR primers and probe sequences by evaluating sequences belonging to SARS-CoV-2 variant of concern and variants of interest. We propose 13 primer and probe sets by analyzing 54,524 sequences in Alpha variant, 25,465 sequences in Beta variant, 53,501 sequences in Gamma variant, 46,225 sequences in Delta variant, and 43,682 sequences in Omicron variant from GISAID. Furthermore, we analyzed 1,008 sequences in Lambda variant as well as 5,844 sequences in Mu variant to extract primer and probe sets from GISAID. The proposed primer and probe sets were validated in 406,757 new SARS-CoV-2 unique genomes collected from NCBI. In silico evaluation presented that the proposed set of primers and probes are found inside about 99% of SARS-CoV-2 genome sequences. Designed primers present a higher potential to detect the main SARS-CoV-2 recent variant of concerns and the variants of interests. The superiority of the proposed method is also highlighted by comparing the state-of-the-art PCR primer and probe sets based on the number of mismatches for various types of SARS-CoV-2 genomes.