Effect of using Acacia mearnsii tannin extract as a feed additive on nutritional variables and productive performance in dairy cows grazing a temperate pasture

This study was carried out to evaluate the impact of including Acacia mearnsii tannin extract (TA) as a feed additive on nutrition and productive performance of dairy cows grazing a high‐quality temperate pasture and receiving supplementation with a concentrate feedstuff. Fourteen multiparous Holstein cows were assigned to either of the following treatments: concentrate without or with 20 g TA/kg dry matter (DM). Concentrate intake accounted for 32% of the total DM intake. Tannin addition increased the herbage DM intake by 22% (p < .05). There was no effect of TA inclusion on milk yield, milk composition, milk nitrogen (N) excretion, milk and plasma urea‐N concentration, urinary excretion of total N, urea‐N, and purine derivatives. However, TA inclusion increased the N intake and retention, total N excretion in manure, fecal N to urine N ratio, and decreased the dietary N efficiency for milk production and the percentage of ingested N excreted in urine (p < .05). In conclusion, supplementing dairy cows grazing a high‐quality temperate pasture with a concentrate containing 20 g TA/kg DM showed the potential of decreasing the proportion of ingested N excreted in urine without affecting the productive performance.     

Using a simplified field progestagen method to assess ovarian activity in female African elephants

Non-invasive endocrine monitoring is an important conservation tool frequently used to support the management of wildlife species. Investigating ovarian activity and pregnancy rates of free-ranging African elephants can enhance our knowledge about the physiology of this highly social and long-lived species. The utility of a new, field-friendly progestagen enzymeimmunoassay (EIA) method was tested by monitoring ovarian activity of 40 females in Addo Elephant National Park (AENP), South Africa. Fecal samples were collected opportunistically from known individuals (June 2007–September 2009) and fecal progestagen metabolites (FPM) were extracted in the field and analyzed on-site using a visual, qualitative EIA. Those results were compared to the laboratory quantitative EIA assessment of hormone concentrations in the U.S. Qualitative FPM concentrations were strongly correlated with quantitative concentrations (r_s = 0.72). Fecal samples collected from pregnant elephants (n = 22) had significantly higher FPM concentrations than non-pregnant individuals, and month of gestation was the strongest predictor of FPM concentrations. Endocrine profiles suggested that five older females were no longer cycling normally. Simplified field endocrine techniques could transform endangered species research under field conditions and provide reliable and economical new tools for making sensible conservation management decisions based on real-time hormone results.     

Genetic conservation of five endangered Spanish donkey breeds

The genetic diversity of most livestock species is being reduced, and it is not possible to preserve all of these livestock breeds. In order to preserve as much of the genetic diversity as possible, we must first have a robust method of measuring genetic diversity among breeds. Three different methods of study that graphically represent relationships among breeds are presented; Weitzman's method, principal component analysis (PCA) and a neighbour‐joining tree with allele sharing. Diversity was evaluated on the basis of 15 microsatellite markers typed over a total of 513 DNA samples collected from five Spanish donkey breeds. Breed differentiation was confirmed by the clustering based on the genetic distances between individuals, which essentially grouped all individuals in discrete clusters. The genetic distance among breeds was used to measure the global diversity of the set in breeds considered, and to evaluate the marginal loss of diversity attached to each breed. The Catalana breed appeared to be the most ‘unique’ in the set considered. In addition to this, the usefulness of global evaluations of diversity using molecular markers to choose breeds is worthy of conservation.     

Indirect biomass estimations in Collembola

We propose coefficients for regressions relating dry weight to body or tergite length in Folsomia candida, Entomobrya schoetti, Sminthurus viridis, and Hypogastrura vernalis (Collembola). Measurements were made on large batches of preserved, identified specimens. Batches were dessicated completely by critical-point drying and weighed. We compare our data with other published models and critically review the literature, finding questionable records.     

The legacy of Columbus in American horse populations assessed by microsatellite markers

Criollo horse populations descend from horses brought from the Iberian Peninsula over the period of colonization (15th to 17th century). They are spread throughout the Americas and have potentially undergone genetic hybridization with other breeds in the recent past. In this study, 25 autosomal microsatellites were genotyped in 50 horse breeds representing Criollo populations from 12 American countries (27 breeds), breeds from the Iberian Peninsula (19), one breed each from France and Morocco and two cosmopolitan horse breeds (Thoroughbred and Arabian). The genetic relationships among breeds identified five clusters: Celtic; Iberian; North American with Thoroughbred influence; most Colombian breeds; and nearly all other Criollo breeds. The group of “all other Criollo breeds” had the closest genetic relationship with breeds originating from the Iberian Peninsula, specifically with the Celtic group. For the whole set of Criollo breeds analysed, the estimated genetic contribution from other breeds was approximately 50%, 30% and 20% for the Celtic, Iberian and Arab-Thoroughbred groups, respectively. The spatial distribution of genetic diversity indicates that hotspots of genetic diversity are observed in populations from Colombia, Ecuador, Brazil, Paraguay and western United States, possibly indicating points of arrival and dispersion of Criollo horses in the American continent. These results indicate that Criollo breeds share a common ancestry, but that each breed has its own identity.     

Genetic parameter estimation and implementation of the genetic evaluation for gaits in a breeding program for assisted-therapy in donkeys

Genetic analyses in donkeys are likely to face compromises in terms of sample size and population structure. This study aims at implementing a suitable model to estimate breeding values and genetic parameters for gaits in Andalusian donkeys. Empirical observation revealed that ambling donkeys (showing a slightly uneven, non-isochronous 1–2, 3–4 lateral sequence gait) did not walk (i.e. presented an isochronous, even 1-2-3-4 sequence gait) and vice versa. However, the two donkey groups could trot, equally. In this study, 2700 gait records were registered from 300 donkeys. The sample included 1350 gait records from 169 ambling/trotting donkeys and 1350 gait records from 131 walking/trotting donkeys. Fixed effects included year, season, sex, farm/owner, husbandry system, weather, ground type and appraisers. Weight and age were included as covariates. MTDFREML software was used to estimate (co)variance components, genetic parameters and predict breeding values and their accuracies in both sets, separately. Gaits’ heritability?±?SE estimates were 0.56?±?0.155, 0.53?±?0.317 and 0.67?±?0.166 for amble, walk and trot, respectively. Genetic correlations were 0.31?±?0.216, 0.42?±?0.115 and 0.28?±?0.178, for amble and walk, amble and trot and walk and trot, respectively. Not all gaits are suitable to treat every human sensomotor condition. We developed a locomotion selection index, assessing the relative loss/gain in index accuracy when each gait modality was excluded to develop different gait specific therapeutic lines to genetically select the best performing donkeys from each gait modality. Our results suggest that gait genetic lines could be developed and may be potential selection criteria to consider in assisted-therapy donkey breeding programs.     

Combined use of principal component analysis and random forests identify population‐informative single nucleotide polymorphisms: application in cattle breeds

The genetic identification of the population of origin of individuals, including animals, has several practical applications in forensics, evolution, conservation genetics, breeding and authentication of animal products. Commercial high‐density single nucleotide polymorphism (SNP) genotyping tools that have been recently developed in many species provide information from a large number of polymorphic sites that can be used to identify population‐/breed‐informative markers. In this study, starting from Illumina BovineSNP50 v1 BeadChip array genotyping data available from 3711 cattle of four breeds (2091 Italian Holstein, 738 Italian Brown, 475 Italian Simmental and 407 Marchigiana), principal component analysis (PCA) and random forests (RFs) were combined to identify informative SNP panels useful for cattle breed identification. From a PCA preselected list of 580 SNPs, RFs were computed using ranking methods (Mean Decrease in the Gini Index and Mean Accuracy Decrease) to identify the most informative 48 and 96 SNPs for breed assignment. The out‐of‐bag (OOB) error rate for both ranking methods and SNP densities ranged from 0.0 to 0.1% in the reference population. Application of this approach in a test population (10% of individuals pre‐extracted from the whole data set) achieved 100% of correct assignment with both classifiers. Linkage disequilibrium between selected SNPs was relevant (r² > 0.6) only in few pairs of markers indicating that most of the selected SNPs captured different fractions of variance. Several informative SNPs were in genes/QTL regions that affect or are associated with phenotypes or production traits that might differentiate the investigated breeds. The combination of PCA and RF to perform SNP selection and breed assignment can be easily implemented and is able to identify subsets of informative SNPs useful for population assignment starting from a large number of markers derived by high‐throughput genotyping platforms.