Natural killer (NK) cells represent a critical component of antiviral immunity, demonstrating remarkable adaptability during infections such as human cytomegalovirus (hCMV) and SARS-CoV-2. Recent advances in single-cell transcriptomics have revealed the clonally expanding NK cell populations with distinct functional profiles, blurring the traditional boundaries between innate and adaptive immunity. However, the functional heterogeneity and immunological significance of these clones remain incompletely understood. Our aim was to dissect clonal NK cell heterogeneity using published scRNA-seq datasets from hCMV-seropositive, seronegative, and COVID-19 patients, focusing on cluster-specific gene expression patterns. Our computational pipeline employed Seurat-based integration and high-resolution clustering of datasets from hCMV-seropositive (n = 5) and seronegative (n = 2) donors, along with COVID-19 patients (n = 2). We analyzed datasets using Seurat 5 in R. Quality-controlled data were normalized (SCTransform), integrated (batch-corrected), and clustered (UMAP). Differential gene expression (Wilcoxon test, log2FC 0.25, p-adj