Agnostic Sequencing for Detection of Viral Pathogens.

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.

Evaluation of miniaturized Illumina DNA preparation protocols for SARS-CoV-2 whole genome sequencing.

The global pandemic caused by SARS-CoV-2 has increased the demand for scalable sequencing and diagnostic methods, especially for genomic surveillance. Although next-generation sequencing has enabled large-scale genomic surveillance, the ability to sequence SARS-CoV-2 in some settings has been limited by the cost of sequencing kits and the time-consuming preparations of sequencing libraries. We compared the sequencing outcomes, cost and turn-around times obtained using the standard Illumina DNA Prep kit protocol to three modified protocols with fewer clean-up steps and different reagent volumes (full volume, half volume, one-tenth volume). We processed a single run of 47 samples under each protocol and compared the yield and mean sequence coverage. The sequencing success rate and quality for the four different reactions were as follows: the full reaction was 98.2%, the one-tenth reaction was 98.0%, the full rapid reaction was 97.5% and the half-reaction, was 97.1%. As a result, uniformity of sequence quality indicated that libraries were not affected by the change in protocol. The cost of sequencing was reduced approximately seven-fold and the time taken to prepare the library was reduced from 6.5 hours to 3 hours. The sequencing results obtained using the miniaturised volumes showed comparability to the results obtained using full volumes as described by the manufacturer. The adaptation of the protocol represents a lower-cost, streamlined approach for SARS-CoV-2 sequencing, which can be used to produce genomic data quickly and more affordably, especially in resource-constrained settings.

A case report of brainstem hemorrhage due to Rhizopus delemar-induced encephalitis diagnosed by metagenomic next-generation sequencing (mNGS).

BACKGROUND: Rhizopus delemar is an invasive fungal pathogen that can cause fatal mucormycosis in immunodeficient individuals. Encephalitis caused by R. delemar is rare and difficult to diagnose early. Clinical detection methods for R. delemar include blood fungal culture, direct microscopic examination, and histopathological examination, but the detection is often inadequate for clinical diagnosis and can easily lead to missed diagnosis with delayed treatment. CASE PRESENTATION: We report a case of a 47-year-old male with brainstem hemorrhage caused by encephalitis due to R. delemar. The patient had a history of hypertension, type 2 diabetes, and irregular medication. No pathogens were detected in cerebrospinal fluid (CSF) and nasopharyngeal secretion cultures. R. delemar was identified by metagenomic next-generation sequencing (mNGS) in CSF, and in combination with the patient's clinical characteristics, encephalitis caused by R. delemar was diagnosed. Antibiotic treatment using amphotericin B liposome in combination with posaconazole was given immediately. However, due to progressive aggravation of the patient's symptoms, he later died due to brainstem hemorrhage after giving up treatment. CONCLUSIONS: mNGS technique is a potential approach for the early diagnosis of infections, which can help clinicians provide appropriate antibiotic treatments, thus reducing the mortality and disability rate of patients.

RAPIDprep: A Simple, Fast Protocol for RNA Metagenomic Sequencing of Clinical Samples.

Emerging infectious disease threats require rapid response tools to inform diagnostics, treatment, and outbreak control. RNA-based metagenomics offers this; however, most approaches are time-consuming and laborious. Here, we present a simple and fast protocol, the RAPIDprep assay, with the aim of providing a cause-agnostic laboratory diagnosis of infection within 24 h of sample collection by sequencing ribosomal RNA-depleted total RNA. The method is based on the synthesis and amplification of double-stranded cDNA followed by short-read sequencing, with minimal handling and clean-up steps to improve processing time. The approach was optimized and applied to a range of clinical respiratory samples to demonstrate diagnostic and quantitative performance. Our results showed robust depletion of both human and microbial rRNA, and library amplification across different sample types, qualities, and extraction kits using a single workflow without input nucleic-acid quantification or quality assessment. Furthermore, we demonstrated the genomic yield of both known and undiagnosed pathogens with complete genomes recovered in most cases to inform molecular epidemiological investigations and vaccine design. The RAPIDprep assay is a simple and effective tool, and representative of an important shift toward the integration of modern genomic techniques with infectious disease investigations.

Minimal requirements for ISO15189 validation and accreditation of three next generation sequencing procedures for SARS-CoV-2 surveillance in clinical setting.

Rapid and recurrent breakthroughs of new SARS-CoV-2 strains (variants) have prompted public health authorities worldwide to set up surveillance networks to monitor the circulation of variants of concern. The use of next-generation sequencing technologies has raised the need for quality control assessment as required in clinical laboratories. The present study is the first to propose a validation guide for SARS-CoV-2 typing using three different NGS methods fulfilling ISO15189 standards. These include the assessment of the risk, specificity, accuracy, reproducibility, and repeatability of the methods. Among the three methods used, two are amplicon-based involving reverse transcription polymerase chain reaction (Artic v3 and Midnight v1) on Oxford Nanopore Technologies while the third one is amplicon-based using reverse complement polymerase chain reaction (Nimagen) on Illumina technology. We found that all methods met the quality requirement (e.g., 100% concordant typing results for accuracy, reproducibility, and repeatability) for SARS-CoV-2 typing in clinical setting. Additionally, the typing results emerging from each of the three sequencing methods were compared using three widely known nomenclatures (WHO, Pangolineage, and Nextclade). They were also compared regarding single nucleotide variations. The outcomes showed that Artic v3 and Nimagen should be privileged for outbreak investigation as they provide higher quality results for samples that do not meet inclusion criteria for analysis in a clinical setting. This study is a first step towards validation of laboratory developed NGS tests in the context of the new European regulation for medical devices and in vitro diagnostics.

SARS-CoV-2 Sequencing for Variant Surveillance.

In this chapter, next-generation sequencing of the entire viral genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is described. Successful sequencing of the SARS-CoV-2 virus is dependent upon quality of the specimen, adequate coverage of the entire genome, and up-to-date annotation. Some of the advantages of performing SARS-CoV-2 surveillance using next-generation sequencing are scalability, high-throughput, cost, and full genome analysis. Some of the disadvantages can be expensive instrumentation, large upfront reagent and supply costs, increased time-to-result, computational needs, and complicated bioinformatics. This chapter will provide an overview of a modified FDA Emergency Use Authorization procedure for the genomic sequencing of SARS-CoV-2. The procedure is also referred to as the research use only (RUO) version.

Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Data.

The massive amount of genomic data appearing for SARS-CoV-2 since the beginning of the COVID-19 pandemic has challenged traditional methods for studying its dynamics. As a result, new methods such as Pangolin, which can scale to the millions of samples of SARS-CoV-2 currently available, have appeared. Such a tool is tailored to take as input assembled, aligned, and curated full-length sequences, such as those found in the GISAID database. As high-throughput sequencing technologies continue to advance, such assembly, alignment, and curation may become a bottleneck, creating a need for methods that can process raw sequencing reads directly. In this article, we propose Reads2Vec, an alignment-free embedding approach that can generate a fixed-length feature vector representation directly from the raw sequencing reads without requiring assembly. Furthermore, since such an embedding is a numerical representation, it may be applied to highly optimized classification and clustering algorithms. Experiments on simulated data show that our proposed embedding obtains better classification results and better clustering properties contrary to existing alignment-free baselines. In a study on real data, we show that alignment-free embeddings have better clustering properties than the Pangolin tool and that the spike region of the SARS-CoV-2 genome heavily informs the alignment-free clusterings, which is consistent with current biological knowledge of SARS-CoV-2.

A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2.

Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log10 at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.

TaME-seq2: tagmentation-assisted multiplex PCR enrichment sequencing for viral genomic profiling.

BACKGROUND: Previously developed TaME-seq method for deep sequencing of HPV, allowed simultaneous identification of the human papillomavirus (HPV) DNA consensus sequence, low-frequency variable sites, and chromosomal integration events. The method has been successfully validated and applied to the study of five carcinogenic high-risk (HR) HPV types (HPV16, 18, 31, 33, and 45). Here, we present TaME-seq2 with an updated laboratory workflow and bioinformatics pipeline. The HR-HPV type repertoire was expanded with HPV51, 52, and 59. As a proof-of-concept, TaME-seq2 was applied on SARS-CoV-2 positive samples showing the method's flexibility to a broader range of viruses, both DNA and RNA. RESULTS: Compared to TaME-seq version 1, the bioinformatics pipeline of TaME-seq2 is approximately 40× faster. In total, 23 HPV-positive samples and seven SARS-CoV-2 clinical samples passed the threshold of 300× mean depth and were submitted to further analysis. The mean number of variable sites per 1 kb was ~ 1.5× higher in SARS-CoV-2 than in HPV-positive samples. Reproducibility and repeatability of the method were tested on a subset of samples. A viral integration breakpoint followed by a partial genomic deletion was found in within-run replicates of HPV59-positive sample. Identified viral consensus sequence in two separate runs was > 99.9% identical between replicates, differing by a couple of nucleotides identified in only one of the replicates. Conversely, the number of identical minor nucleotide variants (MNVs) differed greatly between replicates, probably caused by PCR-introduced bias. The total number of detected MNVs, calculated gene variability and mutational signature analysis, were unaffected by the sequencing run. CONCLUSION: TaME-seq2 proved well suited for consensus sequence identification, and the detection of low-frequency viral genome variation and viral-chromosomal integrations. The repertoire of TaME-seq2 now encompasses seven HR-HPV types. Our goal is to further include all HR-HPV types in the TaME-seq2 repertoire. Moreover, with a minor modification of previously developed primers, the same method was successfully applied for the analysis of SARS-CoV-2 positive samples, implying the ease of adapting TaME-seq2 to other viruses.

DeepSelectNet: deep neural network based selective sequencing for oxford nanopore sequencing.

BACKGROUND: Nanopore sequencing allows selective sequencing, the ability to programmatically reject unwanted reads in a sample. Selective sequencing has many present and future applications in genomics research and the classification of species from a pool of species is an example. Existing methods for selective sequencing for species classification are still immature and the accuracy highly varies depending on the datasets. For the five datasets we tested, the accuracy of existing methods varied in the range of [Formula: see text] 77 to 97% (average accuracy < 89%). Here we present DeepSelectNet, an accurate deep-learning-based method that can directly classify nanopore current signals belonging to a particular species. DeepSelectNet utilizes novel data preprocessing techniques and improved neural network architecture for regularization. RESULTS: For the five datasets tested, DeepSelectNet's accuracy varied between [Formula: see text] 91 and 99% (average accuracy [Formula: see text] 95%). At its best performance, DeepSelectNet achieved a nearly 12% accuracy increase compared to its deep learning-based predecessor SquiggleNet. Furthermore, precision and recall evaluated for DeepSelectNet on average were always > 89% (average [Formula: see text] 95%). In terms of execution performance, DeepSelectNet outperformed SquiggleNet by [Formula: see text] 13% on average. Thus, DeepSelectNet is a practically viable method to improve the effectiveness of selective sequencing. CONCLUSIONS: Compared to base alignment and deep learning predecessors, DeepSelectNet can significantly improve the accuracy to enable real-time species classification using selective sequencing. The source code of DeepSelectNet is available at https://github.com/AnjanaSenanayake/DeepSelectNet .

Magnetic hydrogel particles improve nanopore sequencing of SARS-CoV-2 and other respiratory viruses.

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with Nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40 × improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher automation platform.

Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases.

The outbreak of COVID-19 has positively impacted the NGS market recently. Targeted sequencing (TS) has become an important routine technique in both clinical and research settings, with advantages including high confidence and accuracy, a reasonable turnaround time, relatively low cost, and fewer data burdens with the level of bioinformatics or computational demand. Since there are no clear consensus guidelines on the wide range of next-generation sequencing (NGS) platforms and techniques, there is a vital need for researchers and clinicians to develop efficient approaches, especially for the molecular diagnosis of diseases in the emergency of the disease and the global pandemic outbreak of COVID-19. In this review, we aim to summarize different methods of TS, demonstrate parameters for TS assay designs, illustrate different TS panels, discuss their limitations, and present the challenges of TS concerning their clinical application for the molecular diagnosis of human diseases.

AccuVIR: an ACCUrate VIRal genome assembly tool for third-generation sequencing data.

MOTIVATION: RNA viruses tend to mutate constantly. While many of the variants are neutral, some can lead to higher transmissibility or virulence. Accurate assembly of complete viral genomes enables the identification of underlying variants, which are essential for studying virus evolution and elucidating the relationship between genotypes and virus properties. Recently, third-generation sequencing platforms such as Nanopore sequencers have been used for real-time virus sequencing for Ebola, Zika, coronavirus disease 2019, etc. However, their high per-base error rate prevents the accurate reconstruction of the viral genome. RESULTS: In this work, we introduce a new tool, AccuVIR, for viral genome assembly and polishing using error-prone long reads. It can better distinguish sequencing errors from true variants based on the key observation that sequencing errors can disrupt the gene structures of viruses, which usually have a high density of coding regions. Our experimental results on both simulated and real third-generation sequencing data demonstrated its superior performance on generating more accurate viral genomes than generic assembly or polish tools. AVAILABILITY AND IMPLEMENTATION: The source code and the documentation of AccuVIR are available at https://github.com/rainyrubyzhou/AccuVIR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PredictION: a predictive model to establish the performance of Oxford sequencing reads of SARS-CoV-2.

The optimization of resources for research in developing countries forces us to consider strategies in the wet lab that allow the reuse of molecular biology reagents to reduce costs. In this study, we used linear regression as a method for predictive modeling of coverage depth given the number of MinION reads sequenced to define the optimum number of reads necessary to obtain >200X coverage depth with a good lineage-clade assignment of SARS-CoV-2 genomes. The research aimed to create and implement a model based on machine learning algorithms to predict different variables (e.g., coverage depth) given the number of MinION reads produced by Nanopore sequencing to maximize the yield of high-quality SARS-CoV-2 genomes, determine the best sequencing runtime, and to be able to reuse the flow cell with the remaining nanopores available for sequencing in a new run. The best accuracy was -0.98 according to the R squared performance metric of the models. A demo version is available at https://genomicdashboard.herokuapp.com/.

Screening for differentially expressed microRNAs in BALF and blood samples of infected COVID-19 ARDS patients by small RNA deep sequencing.

BACKGROUND: The pandemic COVID-19 has caused a high mortality rate and poses a significant threat to the population of the entire world. Due to the novelty of this disease, the pathogenic mechanism of the disease and the host cell's response are not yet fully known, so lack of evidence prevents a definitive conclusion about treatment strategies. The current study employed a small RNA deep-sequencing approach for screening differentially expressed microRNA (miRNA) in blood and bronchoalveolar fluid (BALF) samples of acute respiratory distress syndrome (ARDS) patients. METHODS: In this study, BALF and blood samples were taken from patients with ARDS (n = 5). Control samples were those with suspected lung cancer candidates for lung biopsy (n = 3). Illumina high-throughput (HiSeq 2000) sequencing was performed to identify known and novel miRNAs differentially expressed in the blood and BALFs of ARDS patients compared with controls. RESULTS: Results showed 2234 and 8324 miRNAs were differentially expressed in blood and BALF samples, respectively. In BALF samples, miR-282, miR-15-5p, miR-4485-3p, miR-483-3p, miR-6891-5p, miR-200c, miR-4463, miR-483-5p, and miR-98-5p were upregulated and miR-15a-5p, miR-548c-5p, miR-548d-3p, miR-365a-3p, miR-3939, miR-514-b-5p, miR-513a-3p, miR-513a-5p, miR-664a-3p, and miR-766-3p were downregulated. On the contrary, in blood samples miR-15b-5p, miR-18a-3p, miR-486-3p, miR-486-5p, miR-146a-5p, miR-16-2-3p, miR-6501-5p, miR-365-3p, miR-618, and miR-623 were top upregulated miRNAs and miR-21-5p, miR-142a-3p, miR-181-a, miR-31-5p, miR-99-5p, miR-342-5p, miR-183-5p, miR-627-5p, and miR-144-3p were downregulated miRNAs. Network functional analysis for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), in ARDS patients' blood and BALF samples, showed that the target genes were more involved in activating inflammatory and apoptosis process. CONCLUSION: Based on our results, the transcriptome profile of ARDS patients would be a valuable source for understanding molecular mechanisms of host response and developing clinical guidance on anti-inflammatory medication.

Rapid genotyping of targeted viral samples using Illumina short-read sequencing data.

The most important information about microorganisms might be their accurate genome sequence. Using current Next Generation Sequencing methods, sequencing data can be generated at an unprecedented pace. However, we still lack tools for the automated and accurate reference-based genotyping of viral sequencing reads. This paper presents our pipeline designed to reconstruct the dominant consensus genome of viral samples and analyze their within-host variability. We benchmarked our approach on numerous datasets and showed that the consensus genome of samples could be obtained reliably without further manual data curation. Our pipeline can be a valuable tool for fast identifying viral samples. The pipeline is publicly available on the project's GitHub page (https://github.com/laczkol/QVG).

Simultaneous SARS-CoV-2 Genome Sequencing of 384 Samples on an Illumina MiSeq Instrument through Protocol Optimization.

In the present study, we propose a high-throughput sequencing protocol using aNextera XT Library DNA kit on an Illumina MiSeq instrument. We made major modifications to this library preparation in order to multiplex 384 samples in a single Illumina flow cell. To validate our protocol, we compared the sequences obtained with the modified Illumina protocol to those obtained with the GridION Nanopore protocol. For the modified Illumina protocol, our results showed that 94.9% (357/376) of the sequences were interpretable, with a viral genome coverage between 50.5% and 99.9% and an average depth of 421×. For the GridION Nanopore protocol, 94.6% (356/376) of the sequences were interpretable, with a viral genome coverage between 7.0% and 98.6% and an average depth of 2123×. The modified Illumina protocol allows for gaining EUR 4744 and returning results of 384 samples in 53.5 h versus four times 55.5 h with the standard Illumina protocol. Our modified MiSeq protocol yields similar genome sequence data as the GridION Nanopore protocol and has the advantage of being able to handle four times more samples simultaneously and hence is much less expensive.

Genomic surveillance of SARS-CoV-2 by sequencing the RBD region using Sanger sequencing from North Kerala.

Next Generation Sequencing (NGS) is the gold standard for the detection of new variants of SARS-CoV-2 including those which have immune escape properties, high infectivity, and variable severity. This test is helpful in genomic surveillance, for planning appropriate and timely public health interventions. But labs with NGS facilities are not available in small or medium research settings due to the high cost of setting up such a facility. Transportation of samples from many places to few centers for NGS testing also produces delays due to transportation and sample overload leading in turn to delays in patient management and community interventions. This becomes more important for patients traveling from hotspot regions or those suspected of harboring a new variant. Another major issue is the high cost of NGS-based tests. Thus, it may not be a good option for an economically viable surveillance program requiring immediate result generation and patient follow-up. The current study used a cost-effective facility which can be set up in a common research lab and which is replicable in similar centers with expertise in Sanger nucleotide sequencing. More samples can be processed at a time and can generate the results in a maximum of 2 days (1 day for a 24 h working lab). We analyzed the nucleotide sequence of the Receptor Binding Domain (RBD) region of SARS-CoV-2 by the Sanger sequencing using in-house developed methods. The SARS-CoV-2 variant surveillance was done during the period of March 2021 to May 2022 in the Northern region of Kerala, a state in India with a population of 36.4 million, for implementing appropriate timely interventions. Our findings broadly agree with those from elsewhere in India and other countries during the period.

Analyzing viral epitranscriptomes using nanopore direct RNA sequencing.

RNA modifications are a common occurrence across all domains of life. Several chemical modifications, including N6-methyladenosine, have also been found in viral transcripts and viral RNA genomes. Some of the modifications increase the viral replication efficiency while also helping the virus to evade the host immune system. Nonetheless, there are numerous examples in which the host's RNA modification enzymes function as antiviral factors. Although established methods like MeRIP-seq and miCLIP can provide a transcriptome- wide overview of how viral RNA is modified, it is difficult to distinguish between the complex overlapping viral transcript isoforms using the short read-based techniques. Nanopore direct RNA sequencing (DRS) provides both long reads and direct signal readings, which may carry information about the modifications. Here, we describe a refined protocol for analyzing the RNA modifications in viral transcriptomes using nanopore technology.

Confirming Multiplex RT-qPCR Use in COVID-19 with Next-Generation Sequencing: Strategies for Epidemiological Advantage.

Rapid identification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the variants of concern (VOC) and tracking this pandemic. However, NGS is complex and expensive for large-scale adoption, and epidemiological monitoring with NGS alone could be unattainable in limited-resource settings. In this study, we explored the application of RT-qPCR-based detection of the variant identified by NGS. We analyzed a total of 78 deidentified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole-genome sequencing and then compared with two commercially available RT-qPCR assays for spike protein mutation(s). The data showed good concordance between RT-qPCR and NGS analysis for specific SARS-CoV-2 lineages and characteristic mutations. RT-qPCR assays are quick and cost-effective and thus can be implemented in synergy with NGS for screening NGS-identified mutations of SARS-CoV-2 for clinical and epidemiological interest. Strategic use of NGS and RT-qPCR can offer several COVID-19 epidemiological advantages.