Genomic Sequencing Technologies in Veterinary Medicine: Principles, Applications, and Diagnostic Integration

Introduction

Genomic sequencing technologies have transformed veterinary medicine by enabling high-resolution characterization of pathogens, host genomes, and microbial communities [1, 106]. The ability to determine the complete nucleotide sequence of an organism's genome provides unprecedented insights into virulence determinants, antimicrobial resistance (AMR) mechanisms, evolutionary dynamics, and host-pathogen interactions [2, 150]. In veterinary diagnostics, sequencing has moved from a research tool to an increasingly applied modality for outbreak investigation, AMR surveillance, and complex disease diagnosis [3, 69]. This article reviews the core sequencing platforms, their biophysical principles, and their specific applications in veterinary medicine, with a focus on molecular diagnostics.

Sequencing Platforms and Biophysical Principles

Short-Read Sequencing by Synthesis

Short-read sequencing platforms rely on clonal amplification of DNA fragments followed by cyclic reversible termination chemistry [2, 1]. The process begins with library preparation: genomic DNA is fragmented, end-repaired, and adapter-ligated. Fragments are then clonally amplified on a solid surface, typically through bridge amplification. During sequencing, a DNA polymerase incorporates fluorescently labeled nucleotides that are imaged after each incorporation cycle. The resulting fluorescence signals are processed to generate base calls with per-base quality scores. Short-read platforms typically produce read lengths of 75–300 base pairs (bp) with high accuracy (greater than 99.9%) [2, 1]. The primary advantage of short-read sequencing is its high throughput and low per-base cost, making it suitable for whole-genome sequencing (WGS) of bacterial isolates, targeted amplicon sequencing, and metagenomic profiling [106, 128].

Long-Read Single-Molecule Sequencing

Long-read sequencing technologies directly sequence single DNA molecules without amplification, thereby avoiding PCR bias [149]. These platforms measure changes in electrical current or optical signals as nucleotides pass through a biological nanopore or as a polymerase incorporates labeled nucleotides. Read lengths can exceed 10 kilobases (kb) and often reach 100 kb or more [149]. The error rate of raw long-read data is higher (approximately 5–15%) than short-read data, but recent algorithmic improvements and hybrid assembly approaches have substantially improved consensus accuracy [149]. Long-read sequencing is particularly valuable for resolving repetitive genomic regions, detecting structural variants, and sequencing RNA molecules directly [50, 149]. In veterinary virology, direct RNA sequencing has been used to characterize epitranscriptomic modifications in transmissible gastroenteritis virus [50].

Hybrid Sequencing Approaches

Hybrid sequencing combines short-read and long-read data to leverage the strengths of both platforms [149]. Short reads provide high accuracy for base-level resolution, while long reads span repetitive elements and resolve complex genomic rearrangements. This approach has been applied to generate chromosome-level assemblies for livestock species, including wild boar [4] and endangered birds such as the steppe eagle [5]. Hybrid assembly is also used for pathogen genomes, enabling the complete reconstruction of plasmids and mobile genetic elements that carry AMR genes [6, 60].

Applications in Veterinary Diagnostics

Pathogen Detection and Characterization

Genomic sequencing enables the unbiased detection of known and novel pathogens directly from clinical samples [7, 102]. Metagenomic next-generation sequencing (mNGS) involves sequencing all nucleic acids present in a sample, followed by computational subtraction of host sequences and taxonomic classification of microbial reads [86, 102]. This approach has been used to identify novel viruses, such as a novel bovine adenovirus [8] and a paramyxovirus in rodents [9]. In poultry, high-throughput sequencing identified pathogens associated with broiler bronchial obstruction syndrome [7]. For vector-borne diseases, mNGS has been applied to detect tick-borne apicomplexan parasites [10] and to characterize the microbiota of lice [11].

Antimicrobial Resistance Prediction

WGS allows the prediction of AMR phenotypes by detecting resistance genes and mutations [2, 128]. The European Committee on Antimicrobial Susceptibility Testing (EUCAST) has updated guidelines for using WGS to infer susceptibility profiles [2]. In veterinary settings, WGS has been used to characterize AMR in methicillin-resistant staphylococci from dogs and cats [12], in Escherichia coli from food animals [63, 127], and in Salmonella from poultry [129]. The detection of plasmid-mediated resistance genes, such as mcr-1 for colistin resistance, is critical for One Health surveillance [13, 14, 60]. Genomic analysis also reveals the role of mobile genetic elements in disseminating resistance across species and environments [51, 108].

Outbreak Investigation and Molecular Epidemiology

During infectious disease outbreaks, genomic sequencing provides the resolution needed to trace transmission chains and identify the source of infection [1, 94]. Core genome multilocus sequence typing (cgMLST) and single-nucleotide polymorphism (SNP) analysis are commonly used to compare isolates [104]. In livestock, WGS has been applied to investigate outbreaks of Streptococcus suis [15], Getah virus [16], and porcine reproductive and respiratory syndrome virus (PRRSV) [17, 58]. For avian influenza, concurrent circulation of H5N1 and H9N2 subtypes enhances reassortment, and genomic surveillance is essential for monitoring viral evolution [18]. Similarly, whole-genome analysis of Campylobacter jejuni and C. coli in poultry systems reveals geographic clustering and population structure [19, 94].

Host Genomics and Inherited Diseases

Sequencing technologies are also applied to the host genome for the study of inherited disorders, production traits, and disease resistance [83]. Whole-genome copy number variation analysis has identified genomic regions associated with resistance to Haemonchus contortus in sheep [20]. Chromosome-level assemblies for livestock species facilitate the mapping of quantitative trait loci and the identification of causal variants for monogenic disorders [4, 65]. In companion animals, genomic analysis of canine oral melanomas has revealed long non-coding RNA profiles that may serve as biomarkers [74]. The application of sequencing to veterinary oncology is expanding, with critical questions emerging regarding the clinical utility of genomic diagnostics [69].

Metagenomics and Microbiome Analysis

Metagenomic sequencing characterizes the entire microbial community in a sample, providing insights into dysbiosis and polymicrobial infections [86, 138]. In bovine mastitis, metagenomic deep sequencing has revealed associations between microbiome signatures and disease severity [86]. For uterine infections in dairy cattle, microbiome analysis has been used to evaluate alternative treatments such as intrauterine dextrose [138]. In wildlife, metagenomics has been employed to detect bat coronaviruses [21] and to characterize the gut microbiota of ectoparasites [11].

Bioinformatics and Data Analysis

The analysis of genomic sequencing data requires robust bioinformatics pipelines [3, 147]. Key steps include quality control, read alignment or assembly, variant calling, and annotation. For bacterial WGS, tools for AMR gene detection and MLST are widely used [2, 147]. The National Center for Biotechnology Information (NCBI) provides databases for genome submission and comparative analysis, which are essential for veterinary virology and molecular diagnostics [see related article: The Role of the National Center for Biotechnology Information (NCBI) in Veterinary Virology and Molecular Diagnostics]. Similarly, the European Bioinformatics Institute (EMBL-EBI) offers resources for sequence analysis and data sharing [see related article: The European Bioinformatics Institute (EMBL-EBI): A Comprehensive Reference for Veterinary Computational Biology].

The following Mermaid diagram illustrates a typical workflow for genomic sequencing in veterinary diagnostics:

flowchart TD
    A[Clinical Sample Collection] --> B[Nucleic Acid Extraction]
    B --> C[Library Preparation]
    C --> D[Sequencing]
    D --> E[Raw Data Processing]
    E --> F[Quality Control]
    F --> G{Analysis Type}
    G --> H[Pathogen Detection]
    G --> I[AMR Prediction]
    G --> J[Phylogenetic Analysis]
    G --> K[Metagenomic Profiling]
    H --> L[Taxonomic Classification]
    I --> M[Resistance Gene Detection]
    J --> N[SNP/MLST Analysis]
    K --> O[Community Composition]
    L --> P[Interpretation & Reporting]
    M --> P
    N --> P
    O --> P

Comparison of Sequencing Approaches

The following table summarizes key characteristics of short-read and long-read sequencing platforms as applied in veterinary contexts.

Challenges and Future Directions

Despite its potential, the routine implementation of genomic sequencing in veterinary diagnostics faces several challenges. These include the need for standardized protocols, bioinformatics expertise, and cost-effective infrastructure [3, 69]. Data interpretation remains complex, particularly for predicting phenotypic resistance from genotypic data [2, 147]. The integration of sequencing data with clinical and epidemiological information is essential for actionable insights [1, 106].

Emerging technologies, such as CRISPR-based diagnostics and isothermal amplification combined with sequencing, offer rapid, point-of-care alternatives [22, 23, 24, 52, 92]. For example, recombinase-aided amplification (RAA) coupled with Cas12a detection has been developed for porcine circovirus type 2 [22, 52] and foot-and-mouth disease virus [23]. These methods bridge the gap between traditional molecular diagnostics and high-throughput sequencing.

The One Health approach emphasizes the interconnectedness of human, animal, and environmental health [3, 150]. Genomic sequencing of pathogens from animal reservoirs, food products, and the environment is critical for monitoring emerging zoonotic threats [25, 13, 26, 127]. Advances in portable sequencing technologies enable real-time surveillance in resource-limited settings [107, 149].

Conclusion

Genomic sequencing technologies have become indispensable tools in veterinary medicine, offering unparalleled resolution for pathogen characterization, AMR surveillance, outbreak investigation, and host genomics. The complementary use of short-read and long-read platforms, combined with robust bioinformatics analysis, provides a comprehensive view of the molecular landscape of animal diseases. As costs decrease and workflows become more streamlined, genomic sequencing is poised to become a routine component of veterinary diagnostic laboratories, supporting evidence-based clinical decisions and global health surveillance.

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Disclaimer: This article is for educational and informational purposes only. It is not intended to substitute for professional veterinary advice, diagnosis, treatment, or regulatory guidance. Always consult a licensed veterinarian or qualified specialist regarding animal health, disease diagnosis, and therapeutic decisions.