Longitudinal transcriptome analysis of cattle infected with Theileria parva.

The apicomplexan cattle parasite Theileria parva is a major barrier to improving the livelihoods of smallholder farmers in Africa, killing over one million cattle on the continent each year. Although exotic breeds not native to Africa are highly susceptible to the disease, previous studies have illustrated that such breeds often show innate tolerance to infection by the parasite. The mechanisms underlying this tolerance remain largely unclear. To better understand the host response to T. parva infection we characterised the transcriptional response over 15 days in tolerant and susceptible cattle (n = 29) naturally exposed to the parasite. We identify key genes and pathways activated in response to infection as well as, importantly, several genes differentially expressed between the animals that ultimately survived or succumbed to infection. These include genes linked to key cell proliferation and infection pathways. Furthermore, we identify response expression quantitative trait loci containing genetic variants whose impact on the expression level of nearby genes changes in response to the infection. These therefore provide an indication of the genetic basis of differential host responses. Together these results provide a comprehensive analysis of the host transcriptional response to this under-studied pathogen, providing clues as to the mechanisms underlying natural tolerance to the disease.

Optical mapping compendium of structural variants across global cattle breeds.

Structural variants (SV) have been linked to important bovine disease phenotypes, but due to the difficulty of their accurate detection with standard sequencing approaches, their role in shaping important traits across cattle breeds is largely unexplored. Optical mapping is an alternative approach for mapping SVs that has been shown to have higher sensitivity than DNA sequencing approaches. The aim of this project was to use optical mapping to develop a high-quality database of structural variation across cattle breeds from different geographical regions, to enable further study of SVs in cattle. To do this we generated 100X Bionano optical mapping data for 18 cattle of nine different ancestries, three continents and both cattle sub-species. In total we identified 13,457 SVs, of which 1,200 putatively overlap coding regions. This resource provides a high-quality set of optical mapping-based SV calls that can be used across studies, from validating DNA sequencing-based SV calls to prioritising candidate functional variants in genetic association studies and expanding our understanding of the role of SVs in cattle evolution.