Project description:BackgroundAlopecia is defined as the partial or complete absence of hair from areas of the body where it normally grows. Alopecia secondary to an infectious disease or parasitic infestation is commonly seen in cattle. It can also have metabolic causes, for example in newborn calves after a disease event such as diarrhoea. In the article, the investigation of a herd problem of acquired alopecia in Belgian Blue (BB) crossbred calves is described.Case presentationSeveral BB crossbred calves had presented with moderate to severe non-pruritic alopecia in a single small herd located in Southern Germany. The referring veterinarian had ruled out infectious causes, including parasitic infection and had supplemented calves with vitamins (vitamins A, B1, B2, B3, B5, B6, B7, B9, B12, C, and K3) orally. Results of the diagnostic workup at the Clinic for Ruminants are presented for three affected calves and findings from a farm visit are discussed. Because of these investigations, an additional four calves were brought to the referral clinic within the first week of life, and before onset of alopecia, in order to study the course of the condition; however, these calves never developed any signs of alopecia during their clinic stay.ConclusionsBecause all other plausible differential diagnoses were ruled out during our investigation, we concluded that the documented alopecia was due to malabsorption of dietary fat and consecutive disruption of lipid metabolism leading to telogen or anagen effluvium. In this particular case, this was caused by a mixing error of milk replacer in conjunction with insufficiently tempered water. We conclude that nutritional, management or environmental factors alone can lead to moderate to severe alopecia in calves in the absence of a prior or concurrent disease event or infectious cause.
Project description:Inbreeding coefficients can be estimated either from pedigree data or from genomic data, and with genomic data, they are either global or local (when the linkage map is used). Recently, we developed a new hidden Markov model (HMM) that estimates probabilities of homozygosity-by-descent (HBD) at each marker position and automatically partitions autozygosity in multiple age-related classes (based on the length of HBD segments). Our objectives were to: (1) characterize inbreeding with our model in an intensively selected population such as the Belgian Blue Beef (BBB) cattle breed; (2) compare the properties of the model at different marker densities; and (3) compare our model with other methods.When using 600 K single nucleotide polymorphisms (SNPs), the inbreeding coefficient (probability of sampling an HBD locus in an individual) was on average 0.303 (ranging from 0.258 to 0.375). HBD-classes associated to historical ancestors (with small segments ? 200 kb) accounted for 21.6% of the genome length (71.4% of the total length of the genome in HBD segments), whereas classes associated to more recent ancestors accounted for only 22.6% of the total length of the genome in HBD segments. However, these recent classes presented more individual variation than more ancient classes. Although inbreeding coefficients obtained with low SNP densities (7 and 32 K) were much lower (0.060 and 0.093), they were highly correlated with those obtained at higher density (r = 0.934 and 0.975, respectively), indicating that they captured most of the individual variation. At higher SNP density, smaller HBD segments are identified and, thus, more past generations can be explored. We observed very high correlations between our estimates and those based on homozygosity (r = 0.95) or on runs-of-homozygosity (r = 0.95). As expected, pedigree-based estimates were mainly correlated with recent HBD-classes (r = 0.56).Although we observed high levels of autozygosity associated with small HBD segments in BBB cattle, recent inbreeding accounted for most of the individual variation. Recent autozygosity can be captured efficiently with low-density SNP arrays and relatively simple models (e.g., two HBD classes). The HMM framework provides local HBD probabilities that are still useful at lower SNP densities.