Genetic parameters in Finnish blue fox population: Pelt character and live animal grading traits

Abstract

Finnish blue fox farmers breed for increased litter size and pelt size, and improved fur quality. Some farmers select pelt size and fur quality indirectly using live animal evaluations (grading traits). In order to be able to define breeding goals properly, heritabilities and genetic correlations were estimated for size traits and fur quality traits. There were four pelt character traits (pelt size, pelt colour darkness, pelt colour clarity and pelt quality) measured on dried skins, and six grading traits (animal size, grading colour darkness, grading colour clarity, underfur density, guard hair coverage and grading quality). The data included 54,680 animals born during the years 1987–2002, originating from seven farms. The heritabilities were high for pelt colour darkness and grading colour darkness, moderate for pelt size and low for other traits. In general, heritability of a pelt character trait was higher than its corresponding grading trait. Genetic correlations within the pelt character traits were low (～0.11) and within the grading traits mainly moderate or high (～0.44). There was high genetic correlation between pelt darkness and grading darkness, pelt quality and grading density, pelt size and animal size; between pelt quality and grading quality and between pelt colour darkness and grading guard hair coverage. This suggests that selection of pelt character traits via grading traits in most cases is relatively effective.     

New fertility traits in breeding value evaluation of Finnish blue fox

Abstract

Fertility traits have been included in the Finnish blue fox breeding goal for several generations. However, genetic trend in reproductive performance has been undesired due to unfavorable correlations to other important traits such as animal size (AS). The aim of this study was to estimate genetic parameters for pregnancy rate (PREG) and felicity (FEL), and their genetic correlations to litter size (LS) and AS. The estimated heritabilities were low for PREG (0.028) and FEL (0.049). The genetic correlations between LS and PREG (0.63), and LS and FEL (0.75) were clearly positive. Thus, on an average females having genetically larger LS have higher PREG and FEL. The genetic correlation between AS and PREG was close to zero (?0.05), but correlation between AS and FEL was moderate (?0.27) indicating that larger animals are more likely barren or to lose their pups during pregnancy or right after birth.     

Bull Selection in MOET Nucleus Breeding Schemes with Limited Testing Capacity

Centralized multiple ovulation and embryo transfer (MOET) nucleus breeding schemes with limited testing capacity were compared with a conventional artificial insemination (AI) scheme using a simulation. The donor cows were selected after their first lactation. In the hybrid MOET schemes, bulls were progeny tested in the AI population. In comparison, two other schemes used nucleus-born adult bulls only. The best hybrid scheme gave 77% or 40% better genetic response in milk protein yield than that estimated in the national AI scheme when the assumed genetic progress in the AI scheme was low or high, respectively. The best scheme had acceptable coefficients of variation of genetic response, although the rate of inbreeding was 2.5 times higher than in the national AI scheme. The schemes using adult bulls had lower responses and higher rates of inbreeding than the hybrid schemes. The outstanding performance of the hybrid schemes was due to more successful cow selection path than in a conventional AI scheme. A high accuracy of selection of bulls was also important.     

Agricultural soil acidity and phosphorus leaching risk at farm level in two focus areas

Poland has the largest agricultural area within the Baltic Sea drainage basin and reducing the risk of phosphorus (P) and nitrogen (N) leaching from Polish soils to water is therefore essential. Increased acidity is known to reduce soil fertility and may trigger P leaching from non-calcareous soils. As part of advisor training, 25 farms each in Pomerania and north-western Mazovia were visited and 1500?ha arable soil, including 180?ha grassland soil, were monitored in 2013–2014. The soil was mainly coarse textured, but 25% of the Pomeranian farms were dominated by silty or clayey soils. More or less regular drainage systems were found on 20% of the farms, while 50% had simpler, older (>30 years) systems with a few single pipes. The farmers often used only ammonium sulphate or other acidifying N mineral fertiliser. Median pH on the Pomeranian farms, analysed in potassium chloride solution [pH_(KCl)], was 5.2 and liming was advised for fields on most (72%) of these farms. Soil P content, measured by double-lactate extraction (P_DL), was positively and significantly correlated (Pearson coefficient 0.57; p?DL (P given in elemental form) tended to be lower on dairy farms and arable farms and was significantly lower (mean 51?mg?P_DL?kg^?1 soil) on mixed farms (with just a few cows and poultry) than on pig farms (mean 122?mg?P_DL?kg^?1 soil). Farm-gate balances indicated deficits of P and potassium (K) on many of the small mixed farms in Pomerania and the soil can be expected to be nutrient depleted. In contrast, the pig farms demonstrated surplus farm-gate P balances (mean 27?kg?ha^?1). The P leaching risk is discussed relative to soil threshold values and to results from Swedish long-term field experiments.     

DON content in oat grains in Norway related to weather conditions at different growth stages

High concentrations of the mycotoxin deoxynivalenol (DON), produced by Fusarium graminearum have occurred frequently in Norwegian oats recently. Early prediction of DON levels is important for farmers, authorities and the Cereal Industry. In this study, the main weather factors influencing mycotoxin accumulation were identified and two models to predict the risk of DON in oat grains in Norway were developed: (1) as a warning system for farmers to decide if and when to treat with fungicide, and (2) for authorities and industry to use at harvest to identify potential food safety problems. Oat grain samples from farmers’ fields were collected together with weather data (2004–2013). A mathematical model was developed and used to estimate phenology windows of growth stages in oats (tillering, flowering etc.). Weather summarisations were then calculated within these windows, and the Spearman rank correlation factor calculated between DON-contamination in oats at harvest and the weather summarisations for each phenological window. DON contamination was most clearly associated with the weather conditions around flowering and close to harvest. Warm, rainy and humid weather during and around flowering increased the risk of DON accumulation in oats, as did dry periods during germination/seedling growth and tillering. Prior to harvest, warm and humid weather conditions followed by cool and dry conditions were associated with a decreased risk of DON accumulation. A prediction model, including only pre-flowering weather conditions, adequately forecasted risk of DON contamination in oat, and can aid in decisions about fungicide treatments.     

Identification of the SP22 Sperm Protein in Santa Inês and Dorper Rams

The sperm membrane protein referred to as SP22 has been identified in different species and, at least in rats, is highly correlated with fertility. The goals of this study were to identify and to quantify the SP22 protein on spermatozoa from adult rams (Dorper and Santa Inês breeds), and to correlate its levels to morphological and kinematics parameters. SP22 on ram sperm was effectively quantified by both enzyme‐linked immunosorbent assay (ELISA) and fluorescein isothiocyanate immunostaining analysis and the two methods were significantly correlated (R² = 0.70). Clustering analysis of motility parameters obtained by computer‐assisted semen analysis system was used to establish that three distinct kinematic subpopulations with different vigour and progressiveness coexistent within ejaculate. While there were significant differences in the distribution of the three subpopulations in the rams, there was no significant correlation between the proportion of each subpopulation in the rams and the SP22 levels. Quantification of SP22 immunostaining intensity was not correlated with any of the sperm parameters. However, SP22 levels obtained by ELISA were negatively correlated with morphological abnormalities and positively correlated with membrane integrity (three variable R² = 0.47). Future breeding studies are now needed to validate that this protein is a biomarker of fertility in this species.     

The Bacterial (Vibrio alginolyticus) Production of Tetrodotoxin in the Ribbon Worm Lineus longissimus—Just a False Positive?

We test previous claims that the bacteria Vibrio alginolyticus produces tetrodotoxin (TTX) when living in symbiosis with the nemertean Lineus longissimus by a setup with bacteria cultivation for TTX production. Toxicity experiments on the shore crab, Carcinus maenas, demonstrated the presence of a paralytic toxin, but evidence from LC-MS and electrophysiological measurements of voltage-gated sodium channel–dependent nerve conductance in male Wistar rat tissue showed conclusively that this effect did not originate from TTX. However, a compound of similar molecular weight was found, albeit apparently non-toxic, and with different LC retention time and MS/MS fragmentation pattern than those of TTX. We conclude that C. maenas paralysis and death likely emanate from a compound <5 kDa, and via a different mechanism of action than that of TTX. The similarity in mass between TTX and the Vibrio-produced low-molecular-weight, non-toxic compound invokes that thorough analysis is required when assessing TTX production. Based on our findings, we suggest that re-examination of some published claims of TTX production may be warranted.     

Idiopathic eosinophilic meningoencephalitis in Rottweiler dogs: three cases (1992–1997)

We report three cases of eosinophilic meningitis in young male Rottweiler type dogs in New Zealand. No cause for the disease was identified. There were variable clinical signs referable to central nervous system dysfunction, and a variable response to treatment.     

Change in genetic correlation due to selection using animal model evaluation

SUMMARY: Monte Carlo simulation and analytical calculations were used to study the effect of selection on genetic correlation between two traits. The simulated breeding program was based on a closed adult multiple ovulation and embryo transfer nucleus breeding scheme. Selection was on an index calculated using multi-trait animal model (AM). Analytical formulae applicable to any evaluation method were derived to predict change in genetic (co)variance due to selection under multi-trait selection using different evaluation methods. Two formulae were investigated, one assuming phenotypic selection and the other based on a recursive two-generation AM selection index. The recursive AM method approximated information due to relatives by a relationship matrix of two generations. Genetic correlation after selection was compared under different levels of initial genetic and environmental correlations with two different selection criteria. Changes in genetic correlation were similar in simulation and analytical predictions. After one round of selection the recursive AM method and the simulation gave similar predictions while the phenotypic selection predicted usually more change in genetic correlation. After several rounds of selection both analytical formulae predicted more change in genetic correlation than the simulation. ZUSAMMENFASSUNG: ?nderung der genetischen Korrelation bei Selektion mit einem Tiermodell Der Selektionseffekt auf die genetische Korrelation zwischen zwei Merkmalen wurde mit Hilfe von Monte Carlo-Simulation und analytischen Berechnungen untersucht. Ein geschlossener Adulter - MOET (Multiple Ovulation and Embryo Transfer) Zuchtplan wurde simuliert. Die Selektion gründete sich auf einen Index, der die Zuchtwertsch?tzung des Mehrmerkmals-Tiermodells benutzte. Analytische Formeln für die Voraussage der ?nderung der genetischen (Ko)varianz unter multivariate Selektion für verschiedene Zuchtwertsch?tzungsmethode wurden deduziert. Zwei Formeln wurden studiert, die erste nahm ph?notypische Auswahl an und die andere gründete sich auf ein wiederholte Mehrmerkmals-Tiermodell von zwei Generationen. Das wiederholte Mehrmerkmals-Tiermodell approximierte die Information aus den Verwandten mit Hilfe einer Verwandtschaftsmatrix der zwei Generationen. Die genetische Korrelation nach der Selektion aus der Simulation und den analytischen Formeln wurde mit verschiedenen reellen genetischen und umweltbedingten Korrelationen mit zwei Selektionskriterien verglichen. Sie ?nderte sich ?hnlich bei Simulation und analytischen Formeln. Nach einem Selektionszyklus kamen das wiederholte Mehrmerkmals-Tiermodell und die Simulation zu gleichen Voraussagen, aber die ph?notypische Selektion sagte mehr ?nderung voraus. Nach mehreren selektierten Generationen sagten die beiden analytischen Formeln mehr ?nderung in der genetischen Korrelation voraus als die Simulation. RéSUMé: Changement de corrélation génétique du à la sélection en utilisant une évaluation de type modèle animal Une simulation Monte Carlo et des calculs analytiques ont été utilisés pour étudier l'effet de la sélection sur la corrélation génétique entre deux caractères. Le programme de sélection simulé a été basé sur le schéma d'un noyau de sélection adulte et fermé avec superovulation et transfert embryonnaire. La sélection portait sur un indice calculé à partir d'un modèle animal multicaractères (AM). Des formules analytiques applicables à n'importe quelle méthode d'évaluation ont été développées pour prédire le changement de (co)variance génétique du à la sélection multicaractères en utilisant différentes méthodes d'évaluation. Deux formules ont été étudiées, l'une supposant une sélection phénotypique et l'autre basée sur un index de sélection de type AM sur deux générations. La méthode AM récurrente prenait en compte l'information des apparentés de manière approximative à travers la matrice de parenté sur deux générations. La corrélation génétique après sélection a été comparée à différents niveaux de corrélations génétique et environnementale pour deux critères de sélection différents. Les changements de corrélation génétique étaient similaires dans les simulations et les prédictions analytiques. Après un cycle de sélection, la méthode récurrente AM et la simulation donnaient les prédictions similaires alors que la sélection phénotypique prédisait habituellement des changements de corrélations génétiques plus importants. Après plusieurs cycles de sélection, les deux formules analytiques prédisaient des changements de corrélation plus importants que la simulation. RéSUMé: Cambio en la correlación genética debido a selección usando evaluaciones con modelo animal Se estudió el efecto de la selección sobre la correlación genética entre dos caracteres utilizando simulación de Monte Carlo y cálculos analíticos. El esquema de selección simulado estuvo basado en un núcleo adulto y cerrado de ovulación multiple y transferencia de embriones. El criterio de selección fue un indice calculado a partir de un modelo animal multicarácter (AM). Se derivaron fórmulas analíticas aplicables a cualquier método de evaluación para predecir cambios debidos a selección en las (co)varianzas genéticas bajo selección multicarácter usando distintos métodos de valoración. Se investigaron dos fórmulas, una que asumía selección fenotípica y la otra basada en un índice de selección AM recurrente con dos generaciones. El método AM recurrente aproximaba la información de parientes a través de una matriz de relaciones aditivas que contemplaba dos generaciones. La correlación genética tras la selección fue comparada bajo distintos niveles de correlación genética y ambiental iniciales con dos criterios de selección diferentes. Los cambios en correlatión genética fueron similares en las predicciones analíticas y con simulación. Tras un ciclo de selección, el método AM recurrente y la simulación produjeron predicciones similares mientras que la selección fenotípica predijo, generalmente, más cambio en la correlación genética. Después de varios ciclos de selección, las dos fórmulas analíticas predijeron más cambios en la correlación genética que la simulación.