John M. Henshall

Accuracy of estimated genomic breeding values for wool and meat traits in a multi-breed sheep population

Estimated breeding values for the selection of more profitable sheep for the sheep meat and wool industries are currently based on pedigree and phenotypic records. With the advent of a medium-density DNA marker array, which genotypes ∼50000 ovine single nucleotide polymorphisms, a third source of information has become available. The aim of this paper was to determine whether this genomic information can be used to predict estimated breeding values for wool and meat traits. The effects of all single nucleotide polymorphism markers in a multi-breed sheep reference population of 7180 individuals with phenotypic records were estimated to derive prediction equations for genomic estimated breeding values (GEBV) for greasy fleece weight, fibre diameter, staple strength, breech wrinkle score, weight at ultrasound scanning, scanned eye muscle depth and scanned fat depth. Five hundred and forty industry sires with very accurate Australian sheep breeding values were used as a validation population and the accuracies of GEBV were assessed according to correlations between GEBV and Australian sheep breeding values . The accuracies of GEBV ranged from 0.15 to 0.79 for wool traits in Merino sheep and from 0.07 to 0.57 for meat traits in all breeds studied. Merino industry sires tended to have more accurate GEBV than terminal and maternal breeds because the reference population consisted mainly of Merino haplotypes. The lower accuracy for terminal and maternal breeds suggests that the density of genetic markers used was not high enough for accurate across-breed prediction of marker effects. Our results indicate that an increase in the size of the reference population will increase the accuracy of GEBV.

Adaptability in tropical beef cattle: genetic parameters of growth, adaptive and temperament traits in a crossbred population

Adaptability in tropical beef cattle can be assessed by measurable traits such as growth under the influence of environmental stressors, by parasite resistance as measured by indicator traits such as tick counts (TICK) and faecal egg counts of worms (EPG), by heat resistance as measured by indicator traits such as rectal temperatures (TEMP) and coat scores (COAT) and, to a certain extent, temperament of the animal as measured by flight time (FT). Data from a crossbreeding experiment involving various genotypes derived from tropically adapted British, Sanga-derived, Zebu cross, Zebu and Continental beef cattle breeds were analysed to estimate variance components and genetic parameters of growth, adaptive and temperament traits. Breed group differences were accounted for by including fractional coefficients of direct and maternal additive and dominance genetic effects as covariates. In the univariate analyses, 6 models were compared ranging from the simplest model with animal as the only random effect to the full model comprising direct and maternal additive genetic variance and their covariance and the permanent environment effect due to dam (growth traits) and animal (adaptive and temperament traits). The heritability estimates were 0.41, 0.21, 0.19, 0.28, 0.41 and 0.15 for birth weight (BWT), weaning weight (WWT), preweaning average daily gain (PREADG), yearling weight (YWT), final weight at about 18 months of age (FWT) and post-weaning average daily gain (POADG), respectively. The maternal component of additive genetic variance as a proportion of phenotypic variance in BWT, WWT and PREADG was 0.15, 0.10 and 0.10, respectively. The heritability estimates for TICK, EPG, TEMP, COAT and FT were 0.13, 0.24, 0.12, 0.26 and 0.20, respectively. High positive genetic and phenotypic correlations were observed among growth traits. Low (insignificant) genetic correlations were observed between TICK, EPG and growth traits. However, genetic correlations between growth traits and heat tolerance traits (TEMP and COAT) were moderately negative implying that as the ability of an animal to handle heat stress increases, growth also increases at the genetic level. Genetic correlations among TICK, EPG and TEMP were moderately positive, suggesting that closely-linked genes affect these adaptive traits. The significant negative genetic relationship between TEMP and FT suggests that cattle with high heat resistance have desirable temperament. With the increasing crossbred populations in the northern Australian beef cattle industry, the best breeding strategy should aim to exploit both crossbreeding and within population selection to make improvements in growth, adaptive and temperament traits to increase overall productivity of the enterprise.

The distribution of SNP marker effects for faecal worm egg count in sheep, and the feasibility of using these markers to predict genetic merit for resistance to worm infections

SummaryGenetic resistance to gastrointestinal worms is a complex trait of great importance in both livestock and humans. In order to gain insights into the genetic architecture of this trait, a mixed breed population of sheep was artificially infected with Trichostrongylus colubriformis (n=3326) and then Haemonchus contortus (n=2669) to measure faecal worm egg count (WEC). The population was genotyped with the Illumina OvineSNP50 BeadChip and 48 640 single nucleotide polymorphism (SNP) markers passed the quality controls. An independent population of 316 sires of mixed breeds with accurate estimated breeding values for WEC were genotyped for the same SNP to assess the results obtained from the first population. We used principal components from the genomic relationship matrix among genotyped individuals to account for population stratification, and a novel approach to directly account for the sampling error associated with each SNP marker regression. The largest marker effects were estimated to explain an average of 0·48% (T. colubriformis) or 0·08% (H. contortus) of the phenotypic variance in WEC. These effects are small but consistent with results from other complex traits. We also demonstrated that methods which use all markers simultaneously can successfully predict genetic merit for resistance to worms, despite the small effects of individual markers. Correlations of genomic predictions with breeding values of the industry sires reached a maximum of 0·32. We estimate that effective across-breed predictions of genetic merit with multi-breed populations will require an average marker spacing of approximately 10 kbp.

Administration of serotonin inhibitor p-Chlorophenylalanine induces pessimistic-like judgement bias in sheep

Judgement bias has potential as a measure of affective state in animals. The serotonergic system may be one mechanism involved with the formation of negative judgement biases. It was hypothesised that depletion of brain serotonin would induce negative judgement biases in sheep. A dose response trial established that 40 mg/kg of p-Chlorophenylalanine (pCPA) administered to sheep for 3 days did not affect feeding motivation or locomotion required for testing judgement biases. Thirty Merino ewes (10 months old) were trained to an operant task for 3 weeks. Sheep learnt to approach a bucket when it was placed in one corner of the testing facility to receive a feed reward (go response), and not approach it when in the alternate corner (no-go response) to avoid a negative reinforcer (exposure to a dog). Following training, 15 sheep were treated with pCPA (40 mg/kg daily) for an extended duration (5 days). Treated and control sheep were tested for judgement bias following 3 and 5 days of treatment, and again 5 days after cessation of treatment. Testing involved the bucket being presented in ambiguous locations between the two learnt locations, and the response of the sheep (go/no-go) measured their judgement of the bucket locations. Following 5 days of treatment, pCPA-treated sheep approached the most positive ambiguous location significantly less than control sheep, suggesting a pessimistic-like bias (treatment × bucket location interaction F(1,124.6)=49.97, p=0.011). A trend towards a significant interaction was still evident 5 days after the cessation of pCPA treatment (p=0.068), however no significant interaction was seen on day 3 of testing (p=0.867). These results support the suggestion that judgement bias is a cognitive measure of affective state, and that the serotonergic pathway may be involved.

The Genetic Architecture of Climatic Adaptation of Tropical Cattle

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

Evaluation of a new approach for the estimation of the time of the LH surge in dairy cows using vaginal temperature and electrodeless conductivity measurements

The objective of the study was to test the effectiveness of a new type of conductivity sensor, along with vaginal temperature, at identifying the LH peak associated with estrus in dairy cows. Twelve mature non-lactating Holstein-Friesian cows had their estrous cycles synchronized on two occasions, and then data were collected for the following spontaneous cycles. An indwelling electrodeless plastic-coated toroidal conductivity sensor, which also recorded temperature, was placed in the vagina throughout the cycle. Blood samples were collected for LH measurement, and ultrasound scanning used to confirm ovulation. Although there was a relationship between vaginal mucus conductivity measured by the toroidal sensor and the timing of the LH surge, it was not sufficiently robust in individual cows to be able to identify the time of the LH surge. The mean increase in vaginal temperature at estrus was 0.48 degrees C. An algorithm was developed which used the detected individual cow temperature peak to test the relationship with the LH peak. In 16 out of 21 cases where ovulation was confirmed and data existed, the estimated individual peak was within 4h of the LH surge, in three cases it was +/-6h, and in two instances it was early. In conclusion, the temperature algorithm was able to identify the time of the LH surge and thus predict time of ovulation in a way that would allow effective AI, although this result needs to be tested in lactating cows. However, the toroidal conductivity sensing method was not able to produce data of sufficient quality to develop a predictive relationship in individual cows.

Design and phenotyping procedures for recording wool, skin, parasite resistance, growth, carcass yield and quality traits of the SheepGENOMICS mapping flock

A major aim of the research program known as SheepGENOMICS was to deliver DNA markers for commercial breeding programs. To that end, a resource flock was established, comprehensively phenotyped and genotyped with DNA markers. The flock of nearly 5000 sheep, born over two consecutive years, was extensively phenotyped, with more than 100 recorded observations being made on most of the animals. This generated more than 460000 records over 17 months of gathering information on each animal. Here, we describe the experimental design and sample-collection procedures, and provide a summary of the basic measurements taken. Data from this project are being used to identify collections of genome markers for estimating genomic breeding values for new sheep industry traits.

A single nucleotide polymorphism on chromosome 10 is highly predictive for the polled phenotype in Australian Merino sheep

The aim of this study was to fine map the genomic location of the Horns locus in the Australian Merino sheep population and to identify markers that can be used to predict the horn phenotype. A linkage disequilibrium analysis of horn data from Australian Merino sheep mapped the Horns locus to a small region on chromosome 10. A single nucleotide polymorphism in the region was found to be highly predictive for the polled phenotype in an experimental population of Merino sheep. This was owing to a dominance effect of one of the alleles when inherited maternally. It was suggested that a genetic test would provide a good predictor of the polled phenotype. Finally, an evaluation of industry data showed that the SNP is at very different frequencies in Poll Merino sheep that have been bred for polledness (based on phenotype alone) compared with the Merino sheep breed.

Behavioral aspects of electronic bull separation and mate allocation in multiple-sire mating paddocks

Controlling spatial positioning of cattle through use of electronic collars could provide new ways to farm under extensive conditions. This study examined the potential for bulls to be controlled during mating using mild electric shocks delivered through radio-controlled collars. Eighteen Belmont Red bulls were fitted with collars containing the Global Positioning System and that were able to emit a mild electric shock (500 mW) at the top of the neck behind the poll. Eighteen Belmont Red cows were fitted with Global Positioning System collars only. The experiment was replicated 3 times in 3 paddocks. Each paddock contained 2 bulls and 1 cow in induced estrus. On d 1, the bulls were either assigned to the cow or not assigned to the cow, and on d 2, the assignments were reversed, and bulls received the other treatment using a new cow. Treatments were applied for 2 h on each day. The nonassigned bull received a mild electric shock on approach to either the cow or to a bull, whereas the assigned bull received a mild electric shock on approach to the other bull only. The electric shock was applied when the bulls were within approximately 10 m and moving toward the nonallowed animal. The electric shock was terminated when the animal responded by stopping movement toward the nonallowed animal. In the first 10 min, nonassigned bulls spent less time within 5 m of the cow (P = 0.03) than assigned bulls. Assigned bulls spent more time close to the cow during the entire 120 min on d 1 than on d 2 (P = 0.014). On d 1, the assigned bulls moved more toward the cow and the nonassigned bull than they did on d 2 (P = 0.02). Assigned bulls displayed more sexual behaviors than nonassigned bulls (P = 0.004). Nonassigned bulls were sometimes observed not to approach the cow despite a change in its location. This suggests that the bull associated the electric shock with the cow and not with the location in which it received the electric shock. Instances were observed in which the cow pursued the nonassigned bull, in which case the bull did not receive an electric shock, and this may reflect the preference of the cow. This study demonstrated that bulls can be separated and prevented from approaching a cow in estrus using a mild electric shock. However, mate allocation was not completely successful due to the potential for cow preference for certain bulls.

Estimating the effect of SNP genotype on quantitative traits from pooled DNA samples

BackgroundStudies to detect associations between DNA markers and traits of interest in humans and livestock benefit from increasing the number of individuals genotyped. Performing association studies on pooled DNA samples can provide greater power for a given cost. For quantitative traits, the effect of an SNP is measured in the units of the trait and here we propose and demonstrate a method to estimate SNP effects on quantitative traits from pooled DNA data.MethodsTo obtain estimates of SNP effects from pooled DNA samples, we used logistic regression of estimated allele frequencies in pools on phenotype. The method was tested on a simulated dataset, and a beef cattle dataset using a model that included principal components from a genomic correlation matrix derived from the allele frequencies estimated from the pooled samples. The performance of the obtained estimates was evaluated by comparison with estimates obtained using regression of phenotype on genotype from individual samples of DNA.ResultsFor the simulated data, the estimates of SNP effects from pooled DNA are similar but asymptotically different to those from individual DNA data. Error in estimating allele frequencies had a large effect on the accuracy of estimated SNP effects. For the beef cattle dataset, the principal components of the genomic correlation matrix from pooled DNA were consistent with known breed groups, and could be used to account for population stratification. Correctly modeling the contemporary group structure was essential to achieve estimates similar to those from individual DNA data, and pooling DNA from individuals within groups was superior to pooling DNA across groups. For a fixed number of assays, pooled DNA samples produced results that were more correlated with results from individual genotyping data than were results from one random individual assayed from each pool.ConclusionsUse of logistic regression of allele frequency on phenotype makes it possible to estimate SNP effects on quantitative traits from pooled DNA samples. With pooled DNA samples, genotyping costs are reduced, and in cases where trait records are abundant this approach is promising to obtain SNP associations for marker-assisted selection.