Descriptive genomic surveillance study uncovers successive replacement of BQ, XBB, and JN.1 lineages in clinical SARS-CoV-2 isolates, highlighting the value of ongoing pathogen sequencing.
Introduction. Continued genomic surveillance remains important after the end of the COVID-19 Public Health Emergency of International Concern, particularly in countries underrepresented in global sequencing datasets. Material and methods. This descriptive longitudinal genomic surveillance study included 270 SARS-CoV-2 consensus genome sequences obtained from archived clinical specimens collected in the Republic of Moldova between 3 January 2023 and 20 August 2024. Specimens with sufficient viral RNA and a real-time RT-PCR cycle-threshold value of Ct <25 were selected. Sequencing was performed with the Illumina COVIDSeq workflow on the MiSeq Dx platform. Consensus generation and lineage assignment used DRAGEN COVID Lineage v4.0.7, Pangolin and Nextclade v3.16.0. Results. Monthly sequencing volume varied from 1 to 81 specimens. BQ.1 predominated in January 2023 (23/40; 57.5%), followed by XBB-derived lineages. XBB.1.5 and XBB.1.9 each accounted for 14/28 sequences (50.0%) in April 2023. JN.1 represented 3/9 sequences (33.3%) in December 2023, 11/13 (84.6%) in January 2024 and all four sequences analyzed in April 2024. In July 2024, KP.3.1.1 accounted for 2/4 sequences (50.0%), while KP.3 and KP.3.3 each accounted for 1/4 (25.0%). The most frequently detected spike substitutions included G142D (201/270) and K417N (172/270). Discussion. The sequence distribution showed successive replacement of BQ-, XBB- and JN.1-derived lineages. Substantial variation in monthly sample numbers and selection of specimens from hospitalized patients limit population-level interpretation of the reported frequencies. Conclusions. The study describes SARS-CoV-2 lineage dynamics and recurrent spike substitutions among specimens sequenced in the Republic of Moldova. The findings support continued genomic surveillance using standardized sampling, transparent quality criteria and timely data sharing.
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Svetlana Colac (2026) studied this question.
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