Overview
Paratuberculosis, a chronic enteric disease caused by Mycobacterium avium subspecies paratuberculosis (MAP), poses significant economic and welfare challenges in cattle. Recent advances in RNA-Sequencing (RNA-Seq) have enabled researchers to move beyond expression profiling and toward the discovery of coding sequence variants that may influence disease susceptibility. In particular, whole-transcriptome analyses can identify deleterious variants in candidate genes associated with bovine paratuberculosis, offering new angles for diagnosis, management, and genetic selection.
What is the whole-transcriptome approach?
The whole-transcriptome approach examines the complete set of RNA transcripts expressed in tissue samples, capturing both coding and regulatory information. By focusing on coding SNPs (cSNPs) that alter amino acids, researchers can predict changes to protein structure and function. When such deleterious variants occur in genes implicated in the host response to MAP infection, they may modulate susceptibility, progression, or clinical outcome of paratuberculosis.
From RNA-Seq data to deleterious variants
RNA-Seq data provide reads that align to transcripts and, after rigorous quality control, enable variant calling within expressed regions. The workflow typically includes alignment to a reference genome, transcript assembly, and SNP discovery focused on protein-coding exons. Computational prediction tools assess potential deleterious effects on protein function, prioritizing variants for functional validation. This pipeline helps distinguish neutral polymorphisms from those with plausible roles in disease susceptibility.
Candidate genes and biological relevance
Candidate genes frequently highlighted in bovine paratuberculosis studies encode immune regulators, signaling molecules, and pathways that govern macrophage function and granuloma formation. Deleterious variants in these genes could perturb antigen presentation, cytokine networks, or bacterial clearance, thereby altering host resilience to MAP infection. By integrating transcriptomic evidence with genomic variation, researchers can strengthen the causal links between specific variants and disease phenotypes.
Key considerations in interpretation
Several factors influence the interpretation of deleterious variants identified via whole-transcriptome RNA-Seq: tissue choice, stage of infection, and the balance between expressed versus non-expressed regions. Since RNA-Seq reflects the transcriptome at a given time, some functionally important variants in non-expressed tissues or at other time points may be missed. Validation in independent cohorts and functional assays—such as protein modeling, cellular assays, or animal studies—are essential to confirm predicted effects on protein function and disease susceptibility.
Implications for diagnostics and breeding
Discoveries of deleterious variants in paratuberculosis-related genes have practical implications. If validated, such variants could become elements of genetic risk scores to inform selective breeding programs aimed at reducing MAP susceptibility. In parallel, molecular diagnostics might incorporate specific cSNPs as biomarkers for early detection or prognosis, improving herd health management and economic outcomes for dairy and beef operations.
Future directions
Integrating whole-transcriptome RNA-Seq with whole-genome sequencing and epigenetic profiling will provide a more comprehensive view of the host response to MAP. Longitudinal studies across diverse cattle populations, coupled with functional validation, will help clarify which deleterious variants consistently influence paratuberculosis outcomes. Collaborative efforts across genomics, veterinary medicine, and farm management are likely to accelerate translation from discovery to practical tools.
Conclusion
Whole-transcriptome identification of deleterious variants in candidate paratuberculosis genes represents a promising avenue to understand disease susceptibility in cattle. By focusing on cSNPs with predicted functional impacts, researchers can uncover genetic factors that shape MAP infection outcomes, informing both diagnostic strategies and selective breeding programs to promote herd resilience.
