Towards sustainable agriculture: Using genomics to understand Cryptosporidium infection in cattle breeds

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Only during 2017, ~1.9 million cattle were lost to nonpredator causes, with respiratory problems accounting for the highest percentage of losses (26.9%), followed by digestive problems (15.4%) (USDA), representing a combined death loss valued at $3.87 billion. One of the main digestive diseases is cryptosporidiosis, caused by the protozoan parasite Cryptosporidium. In cattle, and especially for intensive cattle farming systems, cryptosporidiosis is considered globally endemic, with a prevalence of Cryptosporidium in stool samples of European cattle herds reported to range from 13% to 93%. Although this high economic cost, relatively few tools are currently available to combat it, with no existing vaccine and only one drug of limited utility. We have recently identified cattle resistant to Cryptosporidium infection in several EU farms, and the aim of this project is to understand the genetic basis of this resistance. To do so, the student will combine bioinformatics and wet-lab techniques to genotype animals from UK and EU farms. Then using state-of-the-art population genomics techniques, they will identify genomic regions differentiating infected from healthy animals. The study will then be expanded to include cattle breeds from South Asian origin with the aim to identify resistant breeds worldwide.