Starting in 2019, the COVID-19 pandemic is a global threat that is difficult to monitor. SARS-CoV-2 is known to undergo frequent mutations, including SNPs and deletions, which seem to be transmitted together, forming clusters that define specific lineages. Reverse-Transcription quantitative PCR (RT-qPCR) has been used for SARS-CoV-2 diagnosis and is still considered the gold standard method. Our Eukaryotic Host Pathogens Interaction (EHPI) laboratory received six SARS-CoV-2-positive samples from a Sicilian private analysis laboratory, four of which showed a dropout of the E gene. Our sequencing data revealed the presence of a synonymous mutation (c.26415 C > T, TAC > TAT) in the E gene of all four samples showing the dropout in RT-qPCR. Interestingly, these samples also harbored three other mutations (S137L—Orf1ab; N439K—S gene; A156S—N gene), which had a very low diffusion rate worldwide. This combination suggested that these mutations may be linked to each other and more common in a specific area than in the rest of the world. Thus, we decided to analyze the 103 sequences in our internal database in order to confirm or disprove our “mutation cluster hypothesis”. Within our database, one sample showed the synonymous mutation (c.26415 C > T, TAC > TAT) in the E gene. This work underlines the importance of territorial epidemiological surveillance by means of NGS and the sequencing of samples with clinical and or technical particularities, e.g., post-vaccine infections or RT-qPCR amplification failures, to allow for the early identification of these SNPs. This approach may be an effective method to detect new mutational clusters and thus to predict new emerging SARS-CoV-2 lineages before they spread globally.