Viral populations within an infected host are composed of viral particles with a spectrum of genetic mutations rather than a unified genome. This phenomenon is referred to as viral “quasispecies,” and has been useful for the understanding of viral transmission and early detection of new viral variants. Next generation sequencing (NGS) has enabled the study of these quasispecies for many viral species, notably Influenza A and B, Human Immunodeficiency Virus (HIV), Foot and Mouth Disease Virus (FMDV), and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV2), and established protocols and computer analysis tools have been developed for these species. Some of the most important viruses, such as emerging and exotic disease agents, however, do not have replicatable protocols or software tools capable of producing valid output from their sequence data. Here, we present Yet Another Viral Subspecies Analysis Pipeline (YAVSAP). YAVSAP is a fully automated bioinformatic pipeline built from the ground up to identify and analyze viral quasispecies of any arbitrary virus in human and veterinary samples. YAVSAP provides reference-based genome mapping of both long- and short-read sequencing reads to any reference genome that the user chooses, identifies subconsensus variants and haplotypes, and assesses the phylogenies of all viral sequences found within a sample. YAVSAP is written in Nextflow and conforms to the nf-core initiative’s standards, which allows it to run on low-end computers, high performance computing (HPC) clusters, or anything in between with zero configuration. YAVSAP has been tested on viruses of interest to veterinary medicine and public health, including Japanese Encephalitis Virus (JEV), Influenza D Virus (IDV), Bovine Coronavirus (BCoV), SARS CoV2, and Rift Valley Fever Virus (RVFV), and can correctly identify consensus genomes and quasispecies within samples containing each of these viruses. This tool provides a means for biologists with little bioinformatic experience to analyze deep sequence data while correcting for many of the pitfalls associated with previous and current analysis platforms. YAVSAP is open source software and is publicly available at https://github.com/ksumngs/yavsap.

Enteric disease is the predominant cause of morbidity and mortality in young mammals including pigs. Viral species involved in porcine enteric disease complex (PEDC) include rotaviruses, coronaviruses, picornaviruses, astroviruses and pestiviruses among others. The virome of three groups of swine samples submitted to the Kansas State University Veterinary Diagnostic Laboratory for routine testing were assessed, namely, a Rotavirus A positive (RVA) group, a Rotavirus co-infection (RV) group and a Rotavirus Negative (RV Neg) group. All groups were designated by qRT-PCR results testing for Porcine Rotavirus A, B, C and H such that samples positive for RVA only went in the RVA group, samples positive for >1 rotavirus went in the RV group and samples negative for all were grouped in the RVNeg group. All of the animals had clinical enteric disease resulting in scours and swollen joints/lameness, enlarged heart and/or a cough. All samples were metagenomic sequenced and analyzed for viral species composition that identified 14 viral species and eight bacterial viruses/phages. Sapovirus and Escherichia coli phages were found at a high prevalence in RVA and RV samples but were found at low or no prevalence in the RV Neg samples. Picobirnavirus was identified at a high proportion and prevalence in RV Neg and RV samples but at a low prevalence in the RVA group. A sequence analysis of the possible host of Picobirnaviruses revealed fungi as the most likely host. Non-rotaviral diversity was highest in RVA samples followed by RV then RV Neg samples. Various sequences were extracted from the sample reads and a phylogenetic update was provided showing a high prevalence of G9 and P[23] RVA genotypes. These data are important for pathogen surveillance and control measures