Advances in developmental biology using next-generation sequencing (NGS): Workshop for next-generation researchers.

This is a meeting report of "The workshop of research and techniques using next-generation sequencing (NGS) for developmental biology 2022." About 20 researchers attended the workshop. We discuss their NGS studies and techniques.

Identification of Torquetenovirus Species in Patients with Kawasaki Disease Using a Newly Developed Species-Specific PCR Method.

A next-generation sequencing (NGS) study identified a very high viral load of Torquetenovirus (TTV) in KD patients. We aimed to evaluate the feasibility of a newly developed quantitative species-specific TTV-PCR (ssTTV-PCR) method to identify the etiology of KD. We applied ssTTV-PCR to samples collected from 11 KD patients and 22 matched control subjects who participated in our previous prospective study. We used the NGS dataset from the previous study to validate ssTTV-PCR. The TTV loads in whole blood and nasopharyngeal aspirates correlated highly (Spearman's R = 0.8931, p < 0.0001, n = 33), supporting the validity of ssTTV-PCR. The ssTTV-PCR and NGS results were largely consistent. However, inconsistencies occurred when ssTTV-PCR was more sensitive than NGS, when the PCR primer sequences mismatched the viral sequences in the participants, and when the NGS quality score was low. Interpretation of NGS requires complex procedures. ssTTV-PCR is more sensitive than NGS but may fail to detect a fast-evolving TTV species. It would be prudent to update primer sets using NGS data. With this precaution, ssTTV-PCR can be used reliably in a future large-scale etiological study for KD.

Metagenomics characterization of respiratory viral RNA pathogens in children under five years with severe acute respiratory infection in the Free State, South Africa.

Prompt detection of viral respiratory pathogens is crucial in managing respiratory infection including severe acute respiratory infection (SARI). Metagenomics next-generation sequencing (mNGS) and bioinformatics analyses remain reliable strategies for diagnostic and surveillance purposes. This study evaluated the diagnostic utility of mNGS using multiple analysis tools compared with multiplex real-time PCR for the detection of viral respiratory pathogens in children under 5 years with SARI. Nasopharyngeal swabs collected in viral transport media from 84 children admitted with SARI as per the World Health Organization definition between December 2020 and August 2021 in the Free State Province, South Africa, were used in this study. The obtained specimens were subjected to mNGS using the Illumina MiSeq system, and bioinformatics analysis was performed using three web-based analysis tools; Genome Detective, One Codex and Twist Respiratory Viral Research Panel. With average reads of 211323, mNGS detected viral pathogens in 82 (97.6%) of the 84 patients. Viral aetiologies were established in nine previously undetected/missed cases with an additional bacterial aetiology (Neisseria meningitidis) detected in one patient. Furthermore, mNGS enabled the much needed viral genotypic and subtype differentiation and provided significant information on bacterial co-infection despite enrichment for RNA viruses. Sequences of nonhuman viruses, bacteriophages, and endogenous retrovirus K113 (constituting the respiratory virome) were also uncovered. Notably, mNGS had lower detectability rate for severe acute respiratory syndrome coronavirus 2 (missing 18/32 cases). This study suggests that mNGS, combined with multiple/improved bioinformatics tools, is practically feasible for increased viral and bacterial pathogen detection in SARI, especially in cases where no aetiological agent could be identified by available traditional methods.

Validation of a new strategy for the identification of SARS-CoV-2 variants by sequencing the spike gene by Sanger.

INTRODUCTION: The emergence of multiple variants of SARS-CoV-2 during the COVID-19 pandemic is of great world concern. Until now, their analysis has mainly focused on next-generation sequencing. However, this technique is expensive and requires sophisticated equipment, long processing times, and highly qualified technical personnel with experience in bioinformatics. To contribute to the analysis of variants of interest and variants of concern, increase the diagnostic capacity, and process samples to carry out genomic surveillance, we propose a quick and easy methodology to apply, based on Sanger sequencing of 3 gene fragments that code for protein spike. METHODS: Fifteen positive samples for SARS-CoV-2 with a cycle threshold below 25 were sequenced by Sanger and next-generation sequencing methodologies. The data obtained were analyzed on the Nextstrain and PANGO Lineages platforms. RESULTS: Both methodologies allowed the identification of the variants of interest reported by the WHO. Two samples were identified as Alpha, 3 Gamma, one Delta, 3 Mu, one Omicron, and 5 strains were close to the initial Wuhan-Hu-1 virus isolate. According to in silico analysis, key mutations can also be detected to identify and classify other variants not evaluated in the study. CONCLUSION: The different SARS-CoV-2 lineages of interest and concern are classified quickly, agilely, and reliably with the Sanger sequencing methodology.

Clinical characteristics of the host DNA-removed metagenomic next-generation sequencing technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology.

Background: Metagenomic next-generation sequencing (mNGS) technology has been central in detecting infectious diseases and helping to simultaneously reveal the complex interplay between invaders and their hosts immune response characteristics. However, it needs to be rigorously assessed for clinical utility. The present study is the first to evaluate the clinical characteristics of the host DNA-removed mNGS technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology. Methods: 46 swab specimens collected from COVID-19 patients were assayed by two approved commercial RT-qPCR kits and mNGS. The evolutionary tree of SARS-CoV-2 was plotted using FigTree directly from one sample. The workflow of removing the host and retaining the host was compared to investigate the influence of host DNA removal on the performances of mNGS. Functional enrichment analysis of DEGs and xCell score were used to explore the characteristics of host local immune signaling. Results: The detection rate of mNGS achieved 92.9% (26/28) for 28 samples with a Ct value ≤ 35 and 81.1% (30/37) for all 46 samples. The genome coverage of SARS-CoV-2 could reach up to 98.9% when the Ct value is about 20 in swab samples. Removing the host could enhance the sensitivity of mNGS for detecting SARS-CoV-2 from the swab sample but does not affect the species abundance of microbes RNA. Improving the sequencing depth did not show a positive effect on improving the detection sensitivity of SARS-CoV-2. Cell type enrichment scores found multiple immune cell types were differentially expressed between patients with high and low viral load. Conclusions: The host DNA-removed mNGS has great potential utility and superior performance on comprehensive identification of SARS-CoV-2 and rapid traceability, revealing the microbiome's transcriptional profiles and host immune responses.

Next Generation Sequencing Revolutionizes Organismal Biology Research in Bats.

The advent of next generation sequencing technologies (NGS) has greatly accelerated our understanding of critical aspects of organismal biology from non-model organisms. Bats form a particularly interesting group in this regard, as genomic data have helped unearth a vast spectrum of idiosyncrasies in bat genomes associated with bat biology, physiology, and evolution. Bats are important bioindicators and are keystone species to many eco-systems. They often live in proximity to humans and are frequently associated with emerging infectious diseases, including the COVID-19 pandemic. Nearly four dozen bat genomes have been published to date, ranging from drafts to chromosomal level assemblies. Genomic investigations in bats have also become critical towards our understanding of disease biology and host-pathogen coevolution. In addition to whole genome sequencing, low coverage genomic data like reduced representation libraries, resequencing data, etc. have contributed significantly towards our understanding of the evolution of natural populations, and their responses to climatic and anthropogenic perturbations. In this review, we discuss how genomic data have enhanced our understanding of physiological adaptations in bats (particularly related to ageing, immunity, diet, etc.), pathogen discovery, and host pathogen co-evolution. In comparison, the application of NGS towards population genomics, conservation, biodiversity assessment, and functional genomics has been appreciably slower. We reviewed the current areas of focus, identifying emerging topical research directions and providing a roadmap for future genomic studies in bats.

Pneumonia During the COVID-19 Pandemic in Hubei Province, China: a Case Report of Mucormycosis.

BACKGROUND: Mucor infection cannot be ignored in patients with pulmonary shadowing with cavitation. This paper reports a case of mucormycosis during the COVID-19 pandemic in Hubei Province, China. METHODS: An anesthesiology doctor was initially diagnosed as COVID-19 due to changes in lung imaging. After anti-infective, anti-viral, and symptomatic supportive treatment, some of symptoms were relieved. But some symptoms -'chest pain and discomfort', accompanied by chest sulking and short breath after activities, did not ease. At last, Lichtheimia ramose was detected later by metagenomic next generation sequencing (mNGS) in the bronchoalveolar lavage fluid (BALF). RESULTS: After adjusting amphotericin B for anti-infective treatment, the patient's infection lesions were shrunk and the symptoms were significantly relieved. CONCLUSIONS: The diagnosis of invasive fungal infections is very difficult, and mNGS can make an accurate pathogenic diagnosis of invasive fungal diseases for the clinic and provide a basis for clinical treatment.

NGS implementation for monitoring SARS-CoV-2 variants in Chicagoland: An institutional perspective, successes and challenges.

Identification of SARS-CoV-2 lineages has shown to provide invaluable information regarding treatment efficacy, viral transmissibility, disease severity, and immune evasion. These benefits provide institutions with an expectation of high informational upside with little insight in regards to practicality with implementation and execution of such high complexity testing in the midst of a pandemic. This article details our institution's experience implementing and using Next Generation Sequencing (NGS) to monitor SARS-CoV-2 lineages in the northern Chicagoland area throughout the pandemic. To date, we have sequenced nearly 7,000 previously known SARS-CoV-2 positive samples from various patient populations (e.g., outpatient, inpatient, and outreach sites) to reduce bias in sampling. As a result, our hospital was guided while making crucial decisions about staffing, masking, and other infection control measures during the pandemic. While beneficial, establishing this NGS procedure was challenging, with countless considerations at every stage of assay development and validation. Reduced staffing prompted transition from a manual to automated high throughput workflow, requiring further validation, lab space, and instrumentation. Data management and IT security were additional considerations that delayed implementation and dictated our bioinformatic capabilities. Taken together, our experience highlights the obstacles and triumphs of SARS-CoV-2 sequencing.

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.

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.

Carryover Contamination-Controlled Amplicon Sequencing Workflow for Accurate Qualitative and Quantitative Detection of Pathogens: a Case Study on SARS-CoV-2.

Carryover contamination during amplicon sequencing workflow (AMP-Seq) put the accuracy of the high-throughput detection for pathogens at risk. The purpose of this study is to develop a carryover contaminations-controlled AMP-Seq (ccAMP-Seq) workflow to enable accurate qualitative and quantitative detection for pathogens. By using the AMP-Seq workflow to detect SARS-CoV-2, Aerosols, reagents and pipettes were identified as potential sources of contaminations and ccAMP-Seq was then developed. ccAMP-Seq used filter tips and physically isolation of experimental steps to avoid cross contamination, synthetic DNA spike-ins to compete with contaminations and quantify SARS-CoV-2, dUTP/uracil DNA glycosylase system to digest the carryover contaminations, and a new data analysis procedure to remove the sequencing reads from contaminations. Compared to AMP-Seq, the contamination level of ccAMP-Seq was at least 22-folds lower and the detection limit was also about an order of magnitude lower-as low as one copy/reaction. By testing the dilution series of SARS-CoV-2 nucleic acid standard, ccAMP-Seq showed 100% sensitivity and specificity. The high sensitivity of ccAMP-Seq was further confirmed by the detection of SARS-CoV-2 from 62 clinical samples. The consistency between qPCR and ccAMP-Seq was 100% for all the 53 qPCR-positive clinical samples. Seven qPCR-negative clinical samples were found to be positive by ccAMP-Seq, which was confirmed by extra qPCR tests on subsequent samples from the same patients. This study presents a carryover contamination-controlled, accurate qualitative and quantitative amplicon sequencing workflow that addresses the critical problem of pathogen detection for infectious diseases. IMPORTANCE Accuracy, a key indicator of pathogen detection technology, is compromised by carryover contamination in the amplicon sequencing workflow. Taking the detection of SARS-CoV-2 as case, this study presents a new carryover contamination-controlled amplicon sequencing workflow. The new workflow significantly reduces the degree of contamination in the workflow, thereby significantly improving the accuracy and sensitivity of the SARS-CoV-2 detection and empowering the ability of quantitative detection. More importantly, the use of the new workflow is simple and economical. Therefore, the results of this study can be easily applied to other microorganism, which has great significance for improving the detection level of microorganism.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis.

BACKGROUND: Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF. METHODS: We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. RESULTS: A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B). CONCLUSIONS: This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Wastewater surveillance of SARS-CoV-2 genomic populations on a country-wide scale through targeted sequencing.

SARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020-July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries.

SARS-CoV-2 spike gene Sanger sequencing methodology to identify variants of concern.

The global demand for rapid identification of circulating SARS-CoV-2 variants of concern has led to a shortage of commercial kits. Therefore, this study aimed to develop and validate a rapid, cost-efficient genome sequencing protocol to identify circulating SARS-CoV-2 (variants of concern). Sets of primers flanking the SARS-CoV-2 spike gene were designed, verified and then validated using 282 nasopharyngeal positive samples for SARS-CoV-2. Protocol specificity was confirmed by comparing these results with SARS-CoV-2 whole-genome sequencing of the same samples. Out of 282 samples, 123 contained the alpha variant, 78 beta and 13 delta, which were indicted using in-house primers and next-generation sequencing; the numbers of variants found were 100% identical to the reference genome. This protocol is easily adaptable for detection of emerging variants during the pandemic.

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.

Combined Use of RT-qPCR and NGS for Identification and Surveillance of SARS-CoV-2 Variants of Concern in Residual Clinical Laboratory Samples in Miami-Dade County, Florida.

Over the course of the COVID-19 pandemic, SARS-CoV-2 variants of concern (VOCs) with increased transmissibility and immune escape capabilities, such as Delta and Omicron, have triggered waves of new COVID-19 infections worldwide, and Omicron subvariants continue to represent a global health concern. Tracking the prevalence and dynamics of VOCs has clinical and epidemiological significance and is essential for modeling the progression and evolution of the COVID-19 pandemic. Next generation sequencing (NGS) is recognized as the gold standard for genomic characterization of SARS-CoV-2 variants, but it is labor and cost intensive and not amenable to rapid lineage identification. Here we describe a two-pronged approach for rapid, cost-effective surveillance of SARS-CoV-2 VOCs by combining reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) and periodic NGS with the ARTIC sequencing method. Variant surveillance by RT-qPCR included the commercially available TaqPath COVID-19 Combo Kit to track S-gene target failure (SGTF) associated with the spike protein deletion H69-V70, as well as two internally designed and validated RT-qPCR assays targeting two N-terminal-domain (NTD) spike gene deletions, NTD156-7 and NTD25-7. The NTD156-7 RT-qPCR assay facilitated tracking of the Delta variant, while the NTD25-7 RT-qPCR assay was used for tracking Omicron variants, including the BA.2, BA.4, and BA.5 lineages. In silico validation of the NTD156-7 and NTD25-7 primers and probes compared with publicly available SARS-CoV-2 genome databases showed low variability in regions corresponding to oligonucleotide binding sites. Similarly, in vitro validation with NGS-confirmed samples showed excellent correlation. RT-qPCR assays allow for near-real-time monitoring of circulating and emerging variants allowing for ongoing surveillance of variant dynamics in a local population. By performing periodic sequencing of variant surveillance by RT-qPCR methods, we were able to provide ongoing validation of the results obtained by RT-qPCR screening. Rapid SARS-CoV-2 variant identification and surveillance by this combined approach served to inform clinical decisions in a timely manner and permitted better utilization of sequencing resources.