US-UK BBSRC-NIFA Collab-Reassembly of cattle immune gene clusters for quantitative analysis

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Since livestock were first domesticated approximately 10,000 years ago they have been selectively bred for desirable traits. Traditional genetic improvement using measurable traits and animal pedigrees has been very successful, particularly to increase production in important livestock species. The result today is a plethora of different breeds that are particularly suited for different environments or types of production, e.g. dairy and beef cattle. However within most livestock populations there is considerable amount of variation that has never been exploited during selective breeding. As the global demand for food increases rapidly, the demand for livestock improvement is escalating. As a consequence of this demand and recent advances in technology, it is now possible to inform breeding strategies based on the animal's genome sequence. In cattle this has been made possible through the characterisation of nearly 800,000 single nucleotide polymorphisms (SNPs) identified in cattle genomes. Rather than having to sequence the whole genome of each animal, rapid identification of SNPs that are associated with parentage, productive traits or breed composition allows for breeding decisions to be made earlier in an animal's life. Unknown animals with no phenotypic data can then be assessed solely on their SNP genotype and their breeding values calculated. This method of genomic selection is now widely used by cattle breeding companies.However, as with any young technology, problems remain. If regions of the genome are very variable between individuals and/or very repetitive it is difficult to identify SNPs that can be screened by the genotyping technology. There are several highly variable and repetitive immune gene complexes in mammalian genomes which have a fundamental role in disease resistance and responses to vaccines. Moreover these regions have evolved this complexity, at least in part, to combat rapidly evolving pathogens. In cattle, we have identified that the current SNPs do not cover three large and vital immune gene complexes, and to a large extent these complexes have not been assembled in the current genome builds. The validation of SNPs for use in genotyping relies upon an accurate genome assembly over the region the SNP is located; therefore this further compounds the problem. Ultimately the current technology is not yet able to type for genetic markers associated with important immune genes that are likely to influence health and disease resistance traits.Cattle possess a pool of natural genetic diversity that has evolved to counter rapidly evolving pathogens that cannot yet be selected for using genomics. We propose to develop the tools to utilise this diversity to improve health and disease resistance traits in cattle. Building on our initial assemblies of these gene complexes, we will assemble these genomic regions in many individuals to characterise the extent a large structural variation. Existing short whole genome sequence reads from > 30 individuals will then be aligned to these larger regions, alongside other publically available sequence datasets. By targeting these regions, it will be possible to identify and validate suitable SNPs, even those at low frequency, which will then be incorporated into a genotyping platform. The utility of this tool will then be tested by genotyping a herd of cattle that display differential disease resistance to bovine tuberculosis, a complex disease that is known to involve a genetic component and is influenced by the gene complexes we are targeting in this study. Ultimately we envisage that these markers can then be incorporated into current and future genotyping technologies to improve disease resistance in cattle through selective breeding.