Omics & gene networks

Filling the gaps: From genomic predictions to functional understanding of immune competence in livestock

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Abstract

High-dimensional molecular data enhances traditional genetic analyses by adding functional layers between genotype and phenotype, helping to understand biological mechanisms underlying genetic variation. We are filling these gaps for immune competence (IC), a trait critical for sustainable livestock production. After developing protocols to measure cell-mediated (Cell-IR) and antibody-mediated (Ab-IR) immune responses assessed during weaning stress, we've assembled a large Australian dataset, including genotypes and phenotypes for over 10,000 cattle across five pure and two crossbreeds, and 5,022 Merino sheep. Our foundational work established that IC traits are moderately heritable in cattle (h² ~ 0.30), whereas in sheep they ranged from 0.36 for Cell-IR to 0.52 for Ab-IR. IC was delivered to industry as the ImmuneDEX trait, which is a weighted metric combining Cell-IR and Ab-IR, providing superior genetic parameters (h²=0.37 for Angus cattle and h²=0.49 for sheep) and enabling simultaneous selection of the two traits. Critically, we observed negative genetic correlations between IC and growth traits (rg = -0.38 with weaning weight) in Angus cattle, indicating energetic limitation or prioritisation within the animal. That means indiscriminate selection for increased productivity may have concerning health and welfare implications and is likely unsustainable in the long term. This pattern was then confirmed in other cattle breeds and sheep, with varying strengths. In addition, low IC phenotype Angus steers showed 6.1% mortality versus 0% in high IC groups, with health costs of AUS$103/head versus AUS$4/head respectively, during feedlot finishing. Together, these results point to the importance of a breeding strategy that aims to eliminate low responders while avoiding pushing for all high responders, as there is likely a production cost associated with the latter. Moving beyond quantitative genetics, we employed single-cell RNA sequencing on >29,000 PBMCs from Angus cattle with divergent Cell-IR phenotypes. Potential key drivers of vaccine response included elevated NKT inflammatory response in low Cell-IR, and increased CD8-γδ T cell and pro-inflammatory myeloid activity in high Cell-IR, providing the first high-resolution immune cell atlas linking cellular composition to functional phenotypes in cattle. Additionally, we identified circulating microRNA signatures predictive of IC in cattle, with pre-vaccination miR-150 levels particularly associated with IC scores, suggesting the potential for practical early-life selection tools even in nonvaccinated animals. In both cattle and sheep, we have identified strong genomic signals associated with IC. We are now exploring cross-species signals and biological processes to determine the optimal balance between production and health. Our current multi-omics approach integrates time-series mucosal microbiome and blood transcriptome data across critical production periods. We're uncovering dynamic host-microbiome interactions and hypothesising the microbiome mediates the "performance gap" between actual and genomically predicted phenotypes. This presentation will provide an update on our multifaceted approach to understanding and improving livestock immune competence.

Keywords: 2026

How to Cite:

Alexandre, P., Reverter, A., Wilson, A., Bell, A., Farr, R., Legrand, T., Porto-Neto, L., Hine, B. & Ingham, A., (2026) “Filling the gaps: From genomic predictions to functional understanding of immune competence in livestock”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286076. doi: https://doi.org/10.31274/wcgalp.23847

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