Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2)

This dataset presents computational analyses of two SARS-CoV-2 BioSamples sequenced in December 2025, processed to assess the genomic presence of mutations associated with pemivibart (VYD2311) monoclonal antibody escape. The samples (SRR36268464, SRR36225071) were retrieved from the NCBI Sequence Read Archive (SRA) and represent publicly available, real-world viral specimens collected during the final month of 2025, <b>the most recent temporal window available at the time of analysis.</b><br>Processing was performed using the PEMI-ESC v2.0 bioinformatics pipeline (Python-based, open-source methodology), which includes read quality control (fastp), alignment to NC_045512.2 (BWA-MEM), variant calling (iVar, bcftools), Spike protein reconstruction, and codon-resolved interrogation of five canonical escape positions: R346, S371, K444, F456, and F486.The package includes, for each sample:Trimmed FASTQ readsAligned BAM filesVariant calls (VCF and tabular reports)Spike amino acid and nucleotide sequencesStructured mutation status reportsNo clinical, phenotypic, or resistance interpretations are provided. This is a purely observational genomic resource intended for independent validation, integration with public health databases, or inclusion in larger surveillance meta-analyses. Additional samples will be added in future versions of this dataset.<b>Note:</b>Analysis was performed using a custom Python-based bioinformatics pipeline developed for <b>high-throughput surveillance of pemivibart (VYD2311) escape mutations in SARS-CoV-2</b>. The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. Full source code and version details are available upon request.<b>PEMI-ESC v2.0</b> <i>Pemivibart Escape Mutation Analyzer v2.0</i> is the 2nd version and well improved version of our bioinformatics pipeline version. <b>PEMI-ESC v2.0</b> methods paper is pending and will be released.Study by: [e-mail]

本数据集针对2025年12月测序的两株严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）生物样本开展计算分析，旨在评估与培米维单抗（pemivibart，VYD2311）单克隆抗体逃逸相关突变的基因组存在情况。所使用的样本（SRR36268464、SRR36225071）从NCBI序列读取档案（NCBI Sequence Read Archive, SRA）获取，为2025年最后一个月采集的公开可用真实病毒标本，<b>即本次分析时可获得的最新时间窗口内的样本</b>。<br>数据分析采用基于Python的开源生物信息学流程PEMI-ESC v2.0完成，该流程涵盖读取质量控制（fastp）、比对至参考序列NC_045512.2（BWA-MEM）、变异检出（iVar、bcftools）、刺突蛋白序列重构，以及对5个经典逃逸位点（R346、S371、K444、F456、F486）开展密码子分辨率水平的解析检测。<br>本数据集为每个样本提供以下内容：修剪后的FASTQ读数文件、比对后的BAM文件、变异检出结果（VCF格式及表格报告）、刺突蛋白氨基酸与核苷酸序列、结构化突变状态报告。<br>本数据集未提供任何临床、表型或耐药性解读，仅为纯观测性基因组资源，可用于独立验证、与公共卫生数据库整合，或纳入更大规模的监测荟萃分析。后续版本将新增更多样本。<br><b>注：</b>本次分析使用专为<b>SARS-CoV-2中培米维单抗（VYD2311）逃逸突变的高通量监测</b>开发的定制化Python生物信息学流程完成。该流程整合了现有开源工具（fastp、BWA-MEM、samtools、iVar、bcftools），并针对参考序列NC_045512.2的5个经典受体结合域（Receptor Binding Domain, RBD）位点（R346、S371、K444、F456、F486）实现了<b>密码子感知型变异检出</b>。完整源代码与版本详情可申请获取。<br><b>PEMI-ESC v2.0</b> <i>即培米维单抗逃逸突变分析器v2.0（Pemivibart Escape Mutation Analyzer v2.0）</i>，是本团队开发的该生物信息学流程的第二代优化版本。其方法学论文正在审稿中，后续将正式发布。<br>本研究由[e-mail]完成