Evaluation and optimal utilisation of the international linear type classification schemes

End of project reportThe authors would like to acknowledge the Irish Cattle Breeding Federation for access to their excellent database for use in this study and to the Irish Holstein-Friesian Association for financial support of this studyThe main objectives of this study were: 1) to evaluate the phenotypic associations between linear type traits and survival in New Zealand and identify potential new traits for inclusion in the type classification scheme in Ireland, and 2) to quantify the potential of linear type traits scored in Ireland as early predictors of genetic merit for fertility and survival in Ireland

A note on the design and testing of single teatcups for automatic milking systems

peer-reviewedIn automatic milking units single independent teatcups or shell/liner combinations are required. The milking characteristics of three designs of single-teatcup milking units were compared with a conventional milking unit in a pipeline milking system. The combined weight of each single-teatcup shell and liner used in the single-teatcup units was 0.18 kg, 0.38 kg or 0.56 kg. The conventional milking cluster had a claw volume of 150 mL and a weight of 3.16 kg. The single sets of teatcups were applied manually and removed automatically when milk flow from the four teatcups reached 0.2 kg/min. The experiment involved a latin square design with four groups of Friesian cows (10 cows/group), four 2-day periods and four treatments. At a flow rate of 4 L/min during simulated milking the mean vacuum level at the teat-end (artificial teat) during the “bphase” of pulsation was 43.8 kPa with the conventional milking unit and 33 kPa for the three single-teatcup units. The corresponding mean and minimum teat-end vacuum in the “d-phase” were 38.46 kPa and 29.54 kPa, respectively, for the conventional system and 24.95 kPa and 17.59 kPa, respectively, for the single-teatcup configuration. The light teatcup (weight 0.18 kg) gave longer time to milk letdown, longer milking time and both lower peak and average milk flow than the conventional cluster

Breeding the dairy cow of the future: what do we need?

peer-reviewedGenetics is responsible for approximately half the observed changes in animal performance in well structured breeding programs. Key characteristics of the dairy cow of the future include (1) production of a large quantity of high-value output (i.e. milk and meat), (2) good reproductive performance, (3) good health status, (4) good longevity, (5) no requirement for a large quantity of feed, yet being able to eat sufficient feed to meet its requirements, (6) easy to manage (i.e. easy calving, docile), (7) good conformation (over and above reflective of health, reproductive performance and longevity), (8) low environmental footprint, and (9) resilience to external perturbations. Pertinent and balanced breeding goals must be developed and implemented to achieve this type of animal; excluding any characteristic from the breeding goal could be detrimental for genetic gain in this characteristic. Attributes currently not explicitly considered in most dairy-cow breeding objectives include product quality, feed intake and efficiency, and environmental footprint; animal health is poorly represented in most breeding objectives. Lessons from the past deterioration in reproductive performance in the global Holstein population remind us of the consequences of ignoring or failing to monitor certain animal characteristics. More importantly, however, current knowledge clearly demonstrates that once unfavourable trends have been identified and the appropriate breeding strategy implemented, the reversal of genetic trends is achievable, even for low-heritability traits such as reproductive performance. Genetic variation exists in all the characteristics described. In the genomics era, the relevance of heritability statistics for most traits is less; the exception is traits not amenable to routine measurement in large populations. Phenotyping strategies (e.g. more detailed phenotypes, larger population) will remain a key component of an animal breeding strategy to achieve the cow of the future as well as providing the necessary tools and information to monitor performance. The inclusion of genomic information in genetic evaluations is, and will continue, to improve the accuracy of genetic evaluations, which, in turn, will augment genetic gain; genomics, however, can also contribute to gains in performance over and above support of increased genetic gain. Nonetheless, the faster genetic gain and thus reduced ability to purge out unfavourable alleles necessitates the appropriate breeding goal and breeding scheme and very close monitoring of performance, in particular for traits not included in the breeding goals. Developments in other disciplines (e.g. reproductive technologies), coupled with commercial struggle for increased market share of the breeding industry, imply a possible change in the landscape of dairy-cow breeding in the future

Evaluation and development of animal breeding in Ireland

End of project reportThe primary objectives of this study were: 1) to annually evaluate the pertinence of the Irish dairy cattle breeding index, the Economic Breeding Index (EBI) and where necessary modify, 2) to evaluate the potential of do-it-yourself milk recording as an alternative to current supervised methods of milk recording, and 3) to estimate the level and rate of accumulation of inbreeding in Irish dairy and beef cattle, to quantify its effects on traits of economic importance, and to develop remedial measures to minimise the future accumulation of inbreeding in Ireland

Genetics of bovine respiratory disease in cattle: can breeding programs reduce the problem?

peer-reviewedGenetics is responsible for approximately half the observed change in performance internationally in well-structured cattle breeding programs. Almost all, if not all, individual characteristics, including animal health, have a genetic basis. Once genetic variation exists then breeding for improvement is possible. Although the heritability of most health traits is low to moderate, considerable exploitable genetic variation does exist. From the limited studies undertaken, and mostly from limited datasets, the direct heritability of susceptibility to BRD varied from 0.07 to 0.22 and the maternal heritability (where estimated) varied from 0.05 to 0.07. Nonetheless, considerable genetic variation clearly exists; the genetic standard deviation for the direct component (binary trait), although differing across populations, varied from 0.08 to 0.20 while the genetic standard deviation for the maternal component varied from 0.04 to 0.07. Little is known about the genetic correlation between genetic predisposition to BRD and animal performance; the estimation of these correlations should be prioritized. (Long-term) Breeding strategies to reduce the incidence of BRD in cattle should be incorporated into national BRD eradication or control strategies

Breeding a better cow—Will she be adaptable?

peer-reviewedAdaption is a process that makes an individual or population more suited to their environment. Long-term adaptation is predicated on ample usable genetic variation. Evolutionary forces influencing the extent and dynamics of genetic variation in a population include random drift, mutation, recombination, selection, and migration; the relative importance of each differs by population (i.e., drift is likely to be more influential in smaller populations) and number of generations exposed to selection (i.e., mutation is expected to contribute substantially to genetic variability following many generations of selection). The infinitesimal model, which underpins most genetic and genomic evaluations, assumes that each quantitative trait is controlled by an infinitely large number of unlinked and non-epistatic loci, each with an infinitely small effect. Under the infinitesimal model, selection is not expected to noticeably alter the allele frequencies, despite a potential substantial change in the population mean; the exception is in the first few generations of selection when genetic variance is expected to decline, after which it stabilizes. Despite the common use of the heritability statistic in quantitative genetics as a descriptor of adaption or response to selection, it is arguably the coefficient of genetic variation that is more informative to gauge adaptation potential and should, therefore, always be cited in such studies; for example, the heritability of fertility traits in dairy cows is generally low, yet the coefficient of genetic variation for most traits is comparable to many other performance traits, thus supporting the observed rapid genetic gain in fertility performance in dairy populations. Empirical evidence from long-term selection studies, across a range of animal and plant species, fails to support the premise that selection will deplete genetic variability. Even after 100 yr (synonymous with 100 generations) of selection in corn for high protein or oil content, there appears to be no obvious plateauing in the response to selection. Although populations in several selection experiments did reach a selection limit after multiple generations of directional selection, this does not equate to an exhaustion of genetic variance; such a declaration is supported by the observed rapid responses to reverse selection once implemented in long-term selection studies. New technologies such as genome-wide enabled selection and genome editing, as well as having the potential to accelerate genetic gain, could also increase the genetic variation, or at least reduce the erosion of genetic variance over time. In conclusion, there is no evidence, either theoretical or empirical, to indicate that dairy cow breeding programs will be unable to adapt to evolving challenges and opportunities, at least not because of an absence of ample genetic variability

Relationship between dairy cow genetic merit and profit on commercial spring calving dairy farms

peer-reviewedBecause not all animal factors influencing profitability can be included in total merit breeding indices for profitability, the association between animal total merit index and true profitability, taking cognisance of all factors associated with costs and revenues, is generally not known. One method to estimate such associations is at the herd level, associating herd average genetic merit with herd profitability. The objective of this study was to primarily relate herd average genetic merit for a range of traits, including the Irish total merit index, with indicators of performance, including profitability, using correlation and multiple regression analyses. Physical, genetic and financial performance data from 1131 Irish seasonal calving pasture-based dairy farms were available following edits; data on some herds were available for more than 1 year of the 3-year study period (2007 to 2009). Herd average economic breeding index (EBI) was associated with reduced herd average phenotypic milk yield but with greater milk composition, resulting in higher milk prices. Moderate positive correlations (0.26 to 0.61) existed between genetic merit for an individual trait and average herd performance for that trait (e.g. genetic merit for milk yield and average per cow milk yield). Following adjustment for year, stocking rate, herd size and quantity of purchased feed in the multiple regression analysis, average herd EBI was positively and linearly associated with net margin per cow and per litre as well as gross revenue output per cow and per litre. The change in net margin per cow per unit change in the total merit index was h1.94 (s.e.50.42), which was not different from the expectation of h2. This study, based on a large data set of commercial herds with accurate information on profitability and genetic merit, confirms that, after accounting for confounding factors, the change in herd profitability per unit change in herd genetic merit for the total merit index is within expectations

Low-density genotype panel for both parentage verification and discovery in a multi-breed sheep population

peer-reviewedThe generally low usage of artificial insemination and single-sire mating in sheep, compounded by mob lambing (and lambing outdoors), implies that parentage assignment in sheep is challenging. The objective here was to develop a low-density panel of single nucleotide polymorphisms (SNPs) for accurate parentage verification and discovery in sheep. Of particular interest was where SNP selection was limited to only a subset of chromosomes, thereby eliminating the ability to accurately impute genome-wide denser marker panels. Data used consisted of 10,933 candidate SNPs on 9,390 purebred sheep. These data consisted of 1,876 validated genotyped sire–offspring pairs and 2,784 validated genotyped dam–offspring pairs. The SNP panels developed consisted of 87 SNPs to 500 SNPs. Parentage verification and discovery were undertaken using 1) exclusion, based on the sharing of at least one allele between candidate parent–offspring pairs, and 2) a likelihood-based approach. Based on exclusion, allowing for one discordant offspring–parent genotype, a minimum of 350 SNPs was required when the goal was to unambiguously identify the true sire or dam from all possible candidates. Results suggest that, if selecting SNPs across the entire genome, a minimum of 250 carefully selected SNPs are required to ensure that the most likely selected parent (based on the likelihood approach) was, in fact, the true parent. If restricting the SNPs to just a subset of chromosomes, the recommendation is to use at least a 300-SNP panel from at least six chromosomes, with approximately an equal number of SNPs per chromosome

Association between body condition score and live weight in pasture-based Holstein-Friesian dairy cows

peer-reviewedThe objective was to quantify the strength of the relationship between body condition score (BCS) and live weight (LW) in pasture-based Holstein-Friesian dairy cattle, and to determine the kg LW per unit BCS. A total of 26021 test-day records with information on both BCS (1–10 scale, where 1 is emaciated and 10 is obese) and LW across 1110 lactations from one research farm were used in the analysis. Correlation and regression analyses were used to determine the degree of association between BCS and LW in different parities, stages of the inter-calving interval and years. Correlations between BCS and LW were relatively consistent, with the mean correlation between BCS and LW across all data of 0·55 implying that differences in BCS explain approximately 30% of the variation in LW. Significantly different regressions of LW on BCS were present within stage of inter-calving interval by parity subclasses. Excluding calving, LW per unit BCS varied from 17 kg (early to mid lactation in parity 1) to 36 kg (early lactation in parity 4 and 5). However, LW per unit BCS was greatest at calving varying from 44 kg in first parity animals to 62 kg in second parity animals. On average, 1 BCS unit equated to 31 kg LW across all data

Detection of selection signatures in dairy and beef cattle using high-density genomic information

peer-reviewedBackground Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs. Results Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (FST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the FST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global FST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection. Conclusions This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.This study was financially supported by a grant from the Irish Department of Agriculture, Food and Marine Research Stimulus Fund (11/S/112), the Agricultural Science and Technology Innovation Program (No. ASTIP-IAS-TS-6) and the Natural Science Foundation of China (No. 31200927)