Canine hip dysplasia : Understanding the genetic basis to apply Genomic Selection : A Master Thesis in Veterinary Medicine

Canine hip dysplasia (CHD) is the most prevalent orthopaedic disease in large breeds of dogs such as the German Shepherd Dog, Golden and Labrador Retriever, Bernese Mountain Dog. It is characterized by an abnormal formation of the hip joints leading different degrees of laxity and subluxation with subsequent formation of progressive osteoarthritis. Nowadays the CHD diagnosis is carried out by physical examination, including the evaluation of hip pain, and the degree of hip laxity with the Ortolani test in young dogs, while in mature dogs the range of motion and pain of hip joint are evaluated. Moreover, the X-rays are essential to confirm the diagnosis and to establish the severity of the disease. Hip scoring (classes from A to E, according to increasing severity in the FCI classification) is a procedure used to determine the degree of hip dysplasia in dogs and it is the sum of the points awarded for each of the radiographic features of hip joints. The results of several studies reported in literature highlight that selective breeding programs, based on genetic and genomic information, are valid alternative to reduce the incidence of CHD in dogs. CHD is a complex trait, which expression is influenced by genetic, nutritional, environmental and hormonal factors. Several quantitative trait loci (QTL) on different chromosomes have been found to contribute to this trait expression in various dog breeds, including Labrador retrievers. The aim of this Master Thesis in Veterinary Medicine is to target resequence the genome of a sample Labrador retrievers dogs in a case/control (dogs classified as A/D-E) study of CHD under a selective DNA pooling approach (SDP). Blood samples will be collected during the routine CHD diagnosis practices and genomic DNA will be extracted with a commercial kit. The chromosome regions that will be investigated will be chosen on the bases of those reported in literature and associated with CHD. The resulting sequencing data will help to find new genomic/genetic variations which may be involved in the disease occurrence.