Genetic evaluation of Addison's disease in the Portuguese Water Dog

BACKGROUND: Addison's disease, also known as hypoadrenocorticism, has been reported in many individual dogs, although some breeds exhibit a greater incidence than the population as a whole. Addison's is presumed to be an autoimmune mediated hereditary defect but the mode of inheritance remains unclear. In particular, the heritability and mode of inheritance have not been defined for the Portuguese Water Dog although Addison's is known to be prevalent in the breed. RESULTS: The analyses present clear evidence that establishes Addison's disease as an inherited disorder in the Portuguese Water Dog with an estimate of heritability of 0.49 (± 0.16); there were no differences in risk for disease across sexes (p > 0.49). Further, the complex segregation analysis provides suggestive evidence that Addison's disease in the Portuguese Water Dog is inherited under the control of a single, autosomal recessive locus. CONCLUSION: The high heritability and mode of inheritance of Addison's disease in the Portuguese Water Dog should enable the detection of segregating markers in a genome-wide scan and the identification of a locus linked to Addison's. Though the confirmation of Addison's disease as an autosomal recessive disorder must wait until the gene is identified, breeders of these dogs may wish to keep the present findings in mind as they plan their breeding programs to select against producing affected dogs

Inclusion of genetically identical animals to a numerator relationship matrix and modification of its inverse

In the field of animal breeding, estimation of genetic parameters and prediction of breeding values are routinely conducted by analyzing quantitative traits. Using an animal model and including the direct inverse of a numerator relationship matrix (NRM) into a mixed model has made these analyses possible. However, a method including a genetically identical animal (GIA) in NRM if genetic relationships between pairs of GIAs are not perfect, is still lacking. Here, we describe a method to incorporate GIAs into NRM using a K matrix in which diagonal elements are set to 1.0, off-diagonal elements between pairs of GIAs to (1-x) and the other elements to 0, where x is a constant less than 0.05. The inverse of the K matrix is then calculated directly by a simple formula. Thus, the inverse of the NRM is calculated by the products of the lower triangular matrix that identifies the parents of each individual, its transpose matrix, the inverse of the K matrix and the inverse of diagonal matrix D, in which the diagonal elements comprise a number of known parents and their inbreeding coefficients. The computing method is adaptable to the analysis of a data set including pairs of GIAs with imperfect relationships

Congenital Sensorineural Deafness in Australian Stumpy-Tail Cattle Dogs Is an Autosomal Recessive Trait That Maps to CFA10

Congenital sensorineural deafness is an inherited condition found in many dog breeds, including Australian Stumpy-tail Cattle Dogs (ASCD). This deafness is evident in young pups and may affect one ear (unilateral) or both ears (bilateral). The genetic locus/loci involved is unknown for all dog breeds. The aims of this study were to determine incidence, inheritance mechanism, and possible association of congenital sensorineural deafness with coat colour in ASCD and to identify the genetic locus underpinning this disease.A total of 315 ASCD were tested for sensorineural deafness using the brain stem auditory evoked response (BAER) test. Disease penetrance was estimated directly, using the ratio of unilaterally to bilaterally deaf dogs, and segregation analysis was performed using Mendel. A complete genome screen was undertaken using 325 microsatellites spread throughout the genome, on a pedigree of 50 BAER tested ASCD in which deafness was segregating. Fifty-six dogs (17.8%) were deaf, with 17 bilaterally and 39 unilaterally deaf. Unilaterally deaf dogs showed no significant left/right bias (p = 0.19) and no significant difference was observed in frequencies between the sexes (p = 0.18). Penetrance of deafness was estimated as 0.72. Testing the association of red/blue coat colour and deafness without accounting for pedigree structure showed that red dogs were 1.8 times more likely to be deaf (p = 0.045). The within family association between red/blue coat colour and deafness was strongly significant (p = 0.00036), with red coat colour segregating more frequently with deafness (COR = 0.48). The relationship between deafness and coat speckling approached significance (p = 0.07), with the lack of statistical significance possibly due to only four families co-segregating for both deafness and speckling. The deafness phenotype was mapped to CFA10 (maximum linkage peak on CFA10 -log10 p-value = 3.64), as was both coat colour and speckling. Fine mapping was then performed on 45 of these 50 dogs and a further 48 dogs (n = 93). Sequencing candidate gene Sox10 in 6 hearing ASCD, 2 unilaterally deaf ASCD and 2 bilaterally deaf ASCD did not reveal any disease-associated mutations.Deafness in ASCD is an incompletely penetrant autosomal recessive inherited disease that maps to CFA10

International Veterinary Epilepsy Task Force consensus report on epilepsy definition, classification and terminology in companion animals

Dogs with epilepsy are among the commonest neurological patients in veterinary practice and therefore have historically attracted much attention with regard to definitions, clinical approach and management. A number of classification proposals for canine epilepsy have been published during the years reflecting always in parts the current proposals coming from the human epilepsy organisation the International League Against Epilepsy (ILAE). It has however not been possible to gain agreed consensus, “a common language”, for the classification and terminology used between veterinary and human neurologists and neuroscientists, practitioners, neuropharmacologists and neuropathologists. This has led to an unfortunate situation where different veterinary publications and textbook chapters on epilepsy merely reflect individual author preferences with respect to terminology, which can be confusing to the readers and influence the definition and diagnosis of epilepsy in first line practice and research studies. In this document the International Veterinary Epilepsy Task Force (IVETF) discusses current understanding of canine epilepsy and presents our 2015 proposal for terminology and classification of epilepsy and epileptic seizures. We propose a classification system which reflects new thoughts from the human ILAE but also roots in former well accepted terminology. We think that this classification system can be used by all stakeholders

Genetic properties of feed efficiency parameters in meat-type chickens

<p>Abstract</p> <p>Background</p> <p>Feed cost constitutes about 70% of the cost of raising broilers, but the efficiency of feed utilization has not kept up the growth potential of today's broilers. Improvement in feed efficiency would reduce the amount of feed required for growth, the production cost and the amount of nitrogenous waste. We studied residual feed intake (RFI) and feed conversion ratio (FCR) over two age periods to delineate their genetic inter-relationships.</p> <p>Methods</p> <p>We used an animal model combined with Gibb sampling to estimate genetic parameters in a pedigreed random mating broiler control population.</p> <p>Results</p> <p>Heritability of RFI and FCR was 0.42-0.45. Thus selection on RFI was expected to improve feed efficiency and subsequently reduce feed intake (FI). Whereas the genetic correlation between RFI and body weight gain (BWG) at days 28-35 was moderately positive, it was negligible at days 35-42. Therefore, the timing of selection for RFI will influence the expected response. Selection for improved RFI at days 28-35 will reduce FI, but also increase growth rate. However, selection for improved RFI at days 35-42 will reduce FI without any significant change in growth rate. The nature of the pleiotropic relationship between RFI and FCR may be dependent on age, and consequently the molecular factors that govern RFI and FCR may also depend on stage of development, or on the nature of resource allocation of FI above maintenance directed towards protein accretion and fat deposition. The insignificant genetic correlation between RFI and BWG at days 35-42 demonstrates the independence of RFI on the level of production, thereby making it possible to study the molecular, physiological and nutrient digestibility mechanisms underlying RFI without the confounding effects of growth. The heritability estimate of FCR was 0.49 and 0.41 for days 28-35 and days 35-42, respectively.</p> <p>Conclusion</p> <p>Selection for FCR will improve efficiency of feed utilization but because of the genetic dependence of FCR and its components, selection based on FCR will reduce FI and increase growth rate. However, the correlated responses in both FI and BWG cannot be predicted accurately because of the inherent problem of FCR being a ratio trait.</p

Partitioning of feed intake into maintenance and gain in growing beef cattle: Evaluation of conventional and Bayesian analyses

The robustness of efficiency estimates depends on theoretical consistency of models from which those estimates are developed; functional forms of the variables must be globally consistent with theoretical properties regarding feed utilization for maintenance and gain in growing and finishing cattle. Model parameter estimates and their dimensions must be unique or estimates of feed utilization and gain will not reflect reality. A linear equation commonly used to estimate daily DMI by the ith individual animal (ADFIi), based on mean weight and gain during a feeding period, was evaluated to determine if that model was correctly specified and if the vector predicted ADFI differed from the vector observed ADFI. Three independently gathered data sets were evaluated using a multiple linear regression model; variability described by that model failed to capture observed variability in the data (lack of fit, P &lt; 0.10), and predicted ADFI differed from observed (P &lt; 0.05); for 1 of the 3 data sets, residuals were not normally distributed (P &lt; 0.001). Functional forms of the variables in the first model evaluated, characterizing ADFI required for maintenance (b1 × BW0.75) and gain (b2 × ADG), were consistent with neither published empirical nor theoretical relationships among ADFI, BW, and ADG. Parameter estimates determined for that linear model were not BLUE. Better fits among final BW, initial BW, and ADFI were found for a first-order relationship, in which final BW was a function of initial BW and ADFI, as indicated by R2 &gt; 0.90. The linear model and, to a lesser degree, the first nonlinear model lacked theoretical and global consistency. A second nonlinear model, which described retained energy as a function of ME intake, best fit the data, and functional forms of variables describing ME intake at maintenance and the efficiency of ME utilization for gain were consistent with theoretical estimates found in the literature. Changes in feed intake and live BW in linear and nonlinear models failed to adequately describe efficiencies of metabolic processes, which are better characterized by changes in retained energy as a function of ME intake in nonlinear models

Partitioning of feed intake into maintenance and gain in growing beef cattle: Evaluation of conventional and Bayesian analyses

The robustness of efficiency estimates depends on theoretical consistency of models from which those estimates are developed; functional forms of the variables must be globally consistent with theoretical properties regarding feed utilization for maintenance and gain in growing and finishing cattle. Model parameter estimates and their dimensions must be unique or estimates of feed utilization and gain will not reflect reality. A linear equation commonly used to estimate daily DMI by the th individual animal (ADFI), based on mean weight and gain during a feeding period, was evaluated to determine if that model was correctly specified and if the vector predicted ADFI differed from the vector observed ADFI. Three independently gathered data sets were evaluated using a multiple linear regression model; variability described by that model failed to capture observed variability in the data (lack of fit, &lt; 0.10), and predicted ADFI differed from observed ( &lt; 0.05); for 1 of the 3 data sets, residuals were not normally distributed ( &lt; 0.001). Functional forms of the variables in the first model evaluated, characterizing ADFI required for maintenance ( × BW) and gain ( × ADG), were consistent with neither published empirical nor theoretical relationships among ADFI, BW, and ADG. Parameter estimates determined for that linear model were not BLUE. Better fits among final BW, initial BW, and ADFI were found for a first-order relationship, in which final BW was a function of initial BW and ADFI, as indicated by &gt; 0.90. The linear model and, to a lesser degree, the first nonlinear model lacked theoretical and global consistency. A second nonlinear model, which described retained energy as a function of ME intake, best fit the data, and functional forms of variables describing ME intake at maintenance and the efficiency of ME utilization for gain were consistent with theoretical estimates found in the literature. Changes in feed intake and live BW in linear and nonlinear models failed to adequately describe efficiencies of metabolic processes, which are better characterized by changes in retained energy as a function of ME intake in nonlinear models