Investigation of cattle immune variation through systems immunology approaches

The immune system is a highly complex network of cells, tissues, and organs that collectively function to protect the host from pathogenic threats. Given the extensive influence of immune responses on various pathologies, it is essential to understand the variability of immune responses within populations and how such variation relates to susceptibility to infections and immune-mediated diseases. In recent years, several human cohort studies have underscored the importance of understanding immune system diversity, leveraging advanced technologies such as genomics and bioinformatics within a systems immunology framework. However, similar approaches have yet to be widely applied to animal populations. Therefore, this thesis investigated the distinct role of genetic and non-genetic factors in modulating immune response variability in cattle.
In the first part of the thesis, we investigated how the genetic and non-genetic factors shape immune variation at the bulk-level. By establishing a comprehensive immunophenotyping framework, over 200 immune parameters both at steady state and following ex vivo blood leukocyte stimulation were quantified. Our results revealed that inter-individual but not intra-individual differences account for the majority of immune variation. In contrast to genetic factors, non-genetic factors primarily explain inter-individual differences in baseline and stimulated cytokine profiles. Additionally, genome-wide association studies (GWAS) identified several genome-wide significant genetic variants associated with immune phenotypes. Co-localization analyses further revealed the shared genetic polymorphisms in cis-expression quantitative trait loci (cis-eQTL) for IL-8, cis-protein QTL (cis-pQTL) for IL-8, and genetic determinants of cow Livability. Finally, we predicted cytokine production in response to stimulation based on individual immune cell composition and genetic factors using machine learning.
In the second part of the thesis, we performed single-cell eQTL mapping (~0.7 million cells and 9 million SNPs across 48 individuals) to investigate cell type-specific gene expression regulation in peripheral blood mononuclear cells (PBMCs) following lipopolysaccharide stimulation at the single-cell level. This study identified cell-type-specific eQTLs, revealing 341 genes whose expression was significantly associated with genetic variants, of which 206 (76.2%) were modulated in response to stimulation (i.e., response QTLs). Notably, some response QTLs influenced the co-expression of other genes, highlighting the complex regulatory landscape of immune gene expression. Moreover, we showed that eQTLs can exert dynamic allelic effects during the transition from CD14⁺ to CD16⁺ monocytes. We also identified a variability QTL (vQTL) affecting DAB2 expression, a negative regulator of LPS response, in monocytes upon stimulation. Finally, co-localization analyses identified among these QTLs candidate loci potentially linked to clinically relevant traits.
Altogether, by employing a systems immunology approach, this thesis delineates the distinct roles of genetic and non-genetic factors in shaping immune variation in cattle. Integrating such approaches across species has the potential to advance not only animal health but also our broader understanding of mammalian immune responses.