Abstract The genetic diversity of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in non-human hosts is more poorly understood. Although whole-genome sequencing (WGS) has found extensive application in characterizing the genetic diversity of SARS-CoV-2 isolates over the past two years, current protocols are aimed solely at identifying mutants circulating in human hosts. This approach could potentially miss new biologically relevant SARS-CoV-2 variants that may emerge as this virus continuously interacts with disparate non-human hosts. The proposed research, therefore, focuses on the establishment of a validated standard operating procedure (SOP) to directly sequence and analyze SARS-CoV-2 in clinical animal specimens using the metagenomic RNA-Seq approach. Compared with the most widely used multiplex PCR targeted amplicon sequencing approach (MTA-Seq), this unbiased metagenomic RNA-Seq approach faithfully covers the entire viral genome and increases the odds of detecting new and unique variants that may not be present in human populations. We will use archived SARS-CoV-2 positive samples originated from diagnostic cases to evaluate two novel library preparation systems, which are known either for the universal reduction of host background (Zymo-Seq Ribo-Free Total RNA kit) or for enhancement of viral genome amplification sensitivity with single primer isothermal amplification (SPIA) (Revelo RNA-Seq Library Kit). The libraries will then be sequenced on both the Illumina iSeq and MiSeq platforms. We will compare the performance of both kits for WGS on the basis of sequencing depth, genome coverage, sequencing uniformity, and detection limits. Bioinformatic analyses will be performed in the public Galaxy server and its GalaxyTrakr instance. The fully validated SOP developed from this project will be submitted to FDA Vet-LIRN for distribution to other member laboratories. On completion, this work will significantly enhance the capabilities of Vet- LIRN laboratories and strengthen collaboration across the network.