The case began in December 2022, when a 40-year-old male patient presented with symptomatic COVID-19 at the Sonoma County Public Health Laboratory. The patient, who had received a bivalent booster vaccination on October 24, 2022, following earlier doses in 2021, reported symptom onset on December 4, including fever above 38 degrees Celsius, chills, cough, and headache consistent with a mild influenza-like illness. He had been in close contact with a confirmed COVID-19 case and had a prior history of testicular teratoma, but no hospitalization or complications were reported. A nasal specimen collected on December 13, 2022 tested positive for SARS-CoV-2 RNA by an FDA-authorized reverse transcription real-time PCR assay targeting the ORF1ab and nucleocapsid genes, yielding a cycle threshold value of 22, indicative of a substantial viral load in the sample.

To characterize the virus genetically, the laboratory extracted RNA from 300 microliters of the nasal specimen using an automated Chemagic 360 Extractor and prepared a sequencing library with the Clear Dx SARS-CoV-2 Kit from Clear Labs. This automated workflow begins with complementary DNA synthesis from the extracted RNA, followed by multiplex tiling PCR using a panel of barcoded target capture primers to amplify the complete viral genome. After purification with Ampure XP beads to remove excess primers and short amplification products, the amplicons underwent a second round of PCR to incorporate a second set of barcodes using rapid library primers from Oxford Nanopore Technologies. Sequencing adapters were then ligated to the dual-barcoded amplicons, and the finished library was loaded onto a MinION flow cell and sequenced on a GridION instrument for 12 hours.

Bioinformatic processing was carried out with the TheiaCoV_ClearLabs workflow version 2.3.0 on the Terra platform, which employs a reference-based assembly approach using the Wuhan-Hu-1 reference genome. Raw reads were subjected to quality control and adapter trimming, human-derived reads were removed with the NCBI SRA Human Scrubber tool, and the remaining de-hosted reads were aligned to the reference with minimap2. After primer trimming, variant calling and consensus generation were performed with Medaka based on allele frequency thresholds. The sequencing run produced 75,041 raw reads, of which 42,135 were classified as SARS-CoV-2 reads. The resulting consensus genome, designated CA-SCPHL-22-02592, spanned 29,574 nucleotides with 100 percent coding-complete coverage and a mean read depth of 1,112-fold, providing an exceptionally high-quality assembly for downstream analysis.

Lineage assignment placed the virus in Pango lineage BQ.1.1.5 within Nextstrain clade 22E, an Omicron sublineage known to be circulating locally at the time of infection. However, during genome annotation the analysts identified something far less ordinary: a 69-nucleotide in-frame deletion at genomic positions 3272 to 3340 within nsp3 of the ORF1a gene. Because Nanopore sequencing can be prone to insertion-deletion errors, the team rigorously assessed read-level support for the deletion using a custom Python script that parsed CIGAR strings from the alignment file. After quality filtering, 707 of 718 informative reads spanning the deletion breakpoints supported the deletion, corresponding to 98.47 percent read support, with only 11 reads supporting the wild-type sequence. Applying a more stringent filter requiring a mean read quality score of at least 20 yielded consistent results, with 98.30 percent support, providing strong evidence that the deletion is biological rather than an artifact of the sequencing platform.

A search of the GISAID database revealed just how rare this event is. Among 17,624,674 SARS-CoV-2 genomes available at the time, only 23 contained the ORF1a delta-69 deletion at these positions. The earliest sequence carrying the deletion was collected in December 2021 in Brazil and the most recent in March 2023 in the Brazilian Amazon. Strikingly, the deletion appeared across multiple Pango lineages and Nextstrain clades, including both Delta and Omicron variants: four sequences belonged to AY.99.2, one each to BA.1 and BA.1.1, four to BA.2, one to BQ.1, ten to BQ.1.1.5, and two to XBB.1.5.102. This distribution suggests the deletion is not lineage-specific and may arise independently in different viral genetic backgrounds. Notably, nearly all of the BQ.1.1.5 sequences harboring the deletion, with the exception of one from Sweden, were detected in California and exhibited nucleotide sequence identity between 99.96 and 100 percent, hinting at a localized cluster of related viruses.

To place the finding in evolutionary context, the team performed phylogenetic and cluster analysis using the TheiaCoV_Augur_Run workflow, which executes subcommands from the Nextstrain Augur toolkit to generate maximum-likelihood and time-resolved phylogenetic trees visualized in the Auspice web application. The analysis grouped the deletion-containing genomes with representatives of 207 distinct deletion patterns identified within ORF1a positions 3250 to 3350. Broader mining of GISAID identified 2,817 high-coverage sequences carrying deletions of varying lengths in this region, observed across Alpha, Beta, Delta, Epsilon, Iota, Gamma, Kappa, Mu, and Omicron clades as well as recombinant lineages, with the majority belonging to the Delta clade. These deletions of varying lengths within the 3250 to 3350 window had not been previously described in this systematic form, underscoring how a single unusual case can open a window onto a broader landscape of viral genetic diversity.

The functional implications of the deletion remain speculative but are grounded in what is known about nsp3 biology. ORF1a encodes a large polyprotein that is proteolytically processed into multiple non-structural proteins essential for viral replication and host interaction, and nsp3 is the largest and most functionally diverse of these, containing domains involved in proteolytic processing, replication complex organization, and interactions with host factors. The ORF1a delta-69 deletion lies predominantly within the N-terminal hypervariable region of nsp3, with a small portion extending into the ADP-ribose-1-phosphatase domain, also known as the macrodomain or Mac1. This region sits outside the well-characterized catalytic papain-like protease domain and is associated with protein-protein interactions and structural organization. Structural and evolutionary analyses of SARS-CoV-2 proteins indicate that insertions and deletions tend to occur in flexible, surface-exposed regions that tolerate localized sequence variation without disrupting overall protein architecture, consistent with the deletion’s placement in the hypervariable region.

Nevertheless, the partial overlap with the Mac1 domain is noteworthy because this domain counteracts host ADP-ribosylation-mediated antiviral responses, thereby facilitating viral replication and immune evasion. Although the deletion does not encompass the full domain, its partial overlap with a functional region raises the possibility of effects on domain stability or host interaction, and alterations within nsp3 could influence host-virus interactions and contribute to functional differences between SARS-CoV-2 and related coronaviruses such as SARS-CoV. The authors caution that, given the limited functional data available for this specific deletion and its rarity, these potential effects remain speculative. Confirmation using orthogonal approaches such as RT-PCR with flanking primers or Sanger sequencing would further strengthen confidence in the finding, and future studies using reverse genetics systems, protein structural modeling, and in vitro replication assays will be needed to assess any effects on viral replication, host interaction, and immune modulation.

The study also carries practical implications for diagnostics and surveillance. Deletions in viral genomes can affect the performance of molecular assays, particularly those relying on RT-PCR, where primer or probe binding sites could be disrupted, and they are equally relevant for amplicon-based enrichment approaches used prior to sequencing. A limitation of the work is the lack of clinical metadata for the other genomes harboring the ORF1a delta-69 deletion in public databases, which made it impossible to assess whether the deletion is associated with specific clinical outcomes or disease severity. The consensus genome from this case has been deposited in GISAID under accession number EPI_ISL_16171374, and the custom Python code used to quantify read-level deletion support is publicly available on GitHub. As SARS-CoV-2 continues to evolve, the integration of next-generation sequencing into routine surveillance frameworks remains essential for detecting emerging mutations, characterizing their functional consequences, and informing public health response and diagnostic strategies.

Subject of Research: A rare in-frame deletion in the SARS-CoV-2 ORF1a nsp3 gene detected through genomic surveillance

Article Title: Genomic monitoring of SARS-CoV-2 uncovers rare in-frame deletion in ORF1a (nsp3) gene: A case report

Article References: Goraichuk, I. V., Critchett, L., Gonzalez, C., Rubin, J., & Rees, R. (2026). Genomic monitoring of SARS-CoV-2 uncovers rare in-frame deletion in ORF1a (nsp3) gene: A case report. Heliyon, 12(15), Article e45522. https://doi.org/10.1016/j.heliyon.2026.e45522

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45522

Keywords: SARS-CoV-2, genomic surveillance, ORF1a, nsp3, in-frame deletion, next-generation sequencing, Oxford Nanopore, GISAID, BQ.1.1.5, Omicron, macrodomain, public health laboratory

The study, led by Zaineb Hamzaoui and colleagues at Charles Nicolle Hospital and the Faculty of Medicine of Tunis, drew on a national sentinel network spanning all 24 Tunisian governorates. The network combined 85 community-based influenza-like illness sites in primary health care centers with 11 hospital-based severe acute respiratory infection departments at university hospitals, all operating under WHO 2014 case definitions. Between November 1, 2021 and September 30, 2025, the laboratory received 8,635 nasopharyngeal swabs through this system and confirmed 1,020 SARS-CoV-2 infections by real-time RT-PCR, an overall positivity rate of 11.8 percent. Under the study protocol, every positive sample with a cycle threshold value below 30 was attempted for whole-genome sequencing, a threshold chosen because higher Ct values typically yield incomplete genomes and unreliable lineage assignment.

The technical workflow relied on viral RNA extraction with the Chemagic 360 instrument, library preparation using Illumina RNA Prep with Enrichment and the Respiratory Virus Oligo Panel, and sequencing on an Illumina iSeq 100. Consensus genomes were built against the Wuhan-Hu-1 reference, quality-checked in Nextclade, and cross-validated with Genome Detective before Pango lineage and GISAID clade assignment. Of the 820 sequencing attempts, 669 genomes—81.6 percent—passed quality control and were deposited in GISAID, representing 65.6 percent of all RT-PCR-confirmed infections diagnosed at the reference laboratory during the study period. That proportion is unusually high for a middle-income setting and approaches international benchmarks for adequate genomic surveillance. Mapped read proportions were consistently high, typically at or above 0.9, lending confidence to the mutation counts derived from the data.

Geographic representativeness emerged as one of the study’s strongest findings. The researchers computed an equity index for each governorate, comparing its share of national sequences with its share of national positives, and found that the distribution of sequences closely tracked the distribution of cases, with a Pearson correlation of 0.992 across the 24 governorates. Median governorate-level sequencing coverage among RT-PCR-positive samples was 60.0 percent, with an interquartile range of 28.6 to 88.9 percent. Coverage was generally higher in densely populated coastal regions, often reaching 80 percent or more, while several central and southern areas fell below 40 percent and a few interior governorates contributed no genomes at all. The equity index flagged relative under-sampling in 12 of 24 governorates and over-sampling in one, though most imbalances occurred in governorates with very few confirmed cases, limiting their impact on the national picture.

Turnaround time—the interval between specimen collection and genome submission to GISAID—was more heterogeneous. The overall median was 99 days, with an interquartile range of 60 to 146 days, and only 43.5 percent of genomes were submitted within 90 days of collection. Nearly 15 percent of sequences experienced delays exceeding 200 days, concentrated among genomes collected in 2022 and 2023. The picture improved markedly in later years: median turnaround fell to 38 days in 2024 and 67 days in 2025, and no delays beyond 200 days were observed among genomes collected in 2024 or 2025. Within higher-volume governorates, median turnaround ranged from 22 days in Sousse to 167 days in Ariana. The authors note that international guidance recommends sharing sequence data within roughly 21 days of collection, a benchmark that accelerates variant detection and risk assessment, and they point to streamlining specimen transport and bioinformatics workflows as routes to improvement.

The lineage data reveal a strikingly dynamic viral landscape. XBB and its descendants accounted for the largest share of genomes at 25.0 percent, followed by BA.4/BA.5 lineages at 22.1 percent, JN.1 and its descendants at 13.6 percent, BA.2 at 12.6 percent, and BA.1 at 9.0 percent. Residual Delta lineages represented 8.7 percent, with the remaining 9.1 percent belonging to other lineages, including pre-Omicron variants and non-XBB recombinants. Nearly all genomes fell within the Omicron-associated GISAID clades GK and GRA. Within these broad categories, a handful of individual Pango lineages—most notably BA.2, BA.5.2, AY.122, BA.1.1, BA.5.2.20, and XBB.2.3.11—contributed the largest shares, while most Omicron sublineages each accounted for less than 2 percent of genomes, a long tail of rare variants underlying the aggregated groups.

The mutational trajectories documented in the dataset chart the virus’s continuing diversification on the Omicron backbone. Early Delta, BA.1, and BA.2 genomes carried roughly 30 to 50 amino acid substitutions relative to the Wuhan-Hu-1 reference, whereas later XBB and JN.1 sublineages frequently exceeded 70 to 80 substitutions, with some recombinants approaching 100. Amino acid deletions also accumulated progressively, reaching 18 to 19 in some JN.1-related genomes. Phylogenetic placement using the Nextclade reference tree showed that Tunisian genomes did not form country-specific outlier clusters but were fully embedded within globally circulating clades: early sequences from late 2021 clustered in Delta clade 21J, while subsequent genomes distributed across successive Omicron clades from 21K and 21L through 22B and 22E to the 23D/23E and 24A through 24H clades corresponding to XBB and JN.1 lineages. This pattern, consistent with repeated introductions rather than long-term local persistence of restricted clusters, mirrors findings from other North African and Mediterranean settings.

Epidemiological curves tied each wave of positivity to the establishment or replacement of a dominant lineage. Testing volumes rose recurrently each winter, peaking in January 2023, but SARS-CoV-2 positivity followed its own rhythm, with substantial peaks in mid-2022 and mid-2023 alongside winter surges. The BA.5.2 wave crested in May through July 2022, the recombinant XBB.2.3.11 drove a surge in July and August 2023, and a JN.1 wave in winter 2023-2024 gave way to extensive circulation of JN.1 offspring through 2024 and 2025. The authors emphasize that these off-season outbreaks underscore that SARS-CoV-2 has not yet settled into the strict winter seasonality of influenza and can still generate waves whenever new immune-evasive variants emerge. The dynamics broadly paralleled those observed across North Africa, the Eastern Mediterranean, and Southern Europe, where KP.3.1.1 and related JN.1 descendants predominated by mid-2024.

Because the sequencing platform sat within a multiplex respiratory surveillance framework, the study also captured viral co-detections. Among the 669 sequenced SARS-CoV-2-positive samples, 92—13.8 percent—showed co-detection with at least one other respiratory virus. Rhinovirus was the most frequent companion at 2.8 percent, followed by adenovirus at 1.5 percent, influenza A/H3N2 at 1.3 percent, and respiratory syncytial virus at 1.2 percent. Influenza viruses were involved in 16 co-detections, or 2.4 percent of sequenced cases. The predominance of rhinovirus aligns with pandemic-era literature showing that rhinovirus and enterovirus persisted or re-emerged earlier than enveloped respiratory viruses, which were markedly suppressed during the first phase of the COVID-19 pandemic. Influenza detections, absent during the 2020-2021 season, resumed once broader multiplex testing was reintroduced from the 2021-2022 season onward.

The authors are candid about the limitations. Clinical metadata were available for only 46.5 percent of sequenced cases, and age data were missing for 8.8 percent of patients, with completeness varying by year and governorate. The Ct-based inclusion criterion may have biased the cohort toward higher viral load infections and earlier sampling timepoints, and the phylogenetic component relied on reference-tree placement rather than de novo reconstruction, precluding formal inference of transmission clusters or introduction counts. The dataset also reflects the ILI/SARI sentinel sampling frame rather than the entirety of national COVID-19 testing. Even so, the study demonstrates that an influenza-based sentinel network in a middle-income country can deliver sustained, geographically near-proportional SARS-CoV-2 genomic surveillance at high sequencing quality. By combining near-proportional sampling across governorates with multipathogen testing, the Tunisian platform offers a scalable model for tracking future SARS-CoV-2 variants and other emerging respiratory pathogens, positioning integrated sentinel surveillance as a pragmatic foundation for pandemic preparedness in the region.

Subject of Research: Genomic surveillance of SARS-CoV-2 Omicron lineage dynamics in Tunisia

Article Title: Genomic surveillance of SARS-CoV-2 in Tunisia during the omicron era: insights from the national influenza & other respiratory viruses laboratory

Article References: Hamzaoui, Z., Ferjani, S., Bouchouicha, T., Charaa, L., Landolsi, I., Medini, I., Ben Ali, R., Chammam, S., Abid, S., Kanzari, L., Ben Sassi, M., Trabelsi, S., & Boutiba Ben Boubaker, I. (2026). Genomic surveillance of SARS-CoV-2 in Tunisia during the omicron era: insights from the national influenza & other respiratory viruses laboratory. Virology Journal, 23(1), Article 215. https://doi.org/10.1186/s12985-026-03262-7

Image Credits: AI Generated

DOI: 10.1186/s12985-026-03262-7

Keywords: SARS-CoV-2, Omicron, genomic surveillance, Tunisia, whole-genome sequencing, Pango lineages, GISAID, JN.1, XBB, respiratory viruses, influenza sentinel network, co-detection