Research in the ABRD encompasses nutrition, fertility, breeding, health and welfare. Research activities focus on producing profitable animals and the corresponding management strategies to deliver the productivity, sustainability and product quality targets set out in Ireland’s Food Harvest 2020 vision. The ABRD uses a powerful combination of established animal science techniques, as well as cutting-edge molecular and computational biology tools, to answer relevant industry research questions. Our focus is on dairy and beef cattle and sheep. We have developed animal models that are divergent for a range of economically important traits.

Recent Submissions

  • Evaluating Established Methods for Rumen 16S rRNA Amplicon Sequencing With Mock Microbial Populations

    McGovern, Emily; Waters, Sinead M.; Blackshields, Gordon; McCabe, Matthew S.; FACCE-JPI; Teagasc Walsh Fellowship Programme; 2014231 (Frontiers, 2018-06-25)
    The rumen microbiome scientific community has utilized amplicon sequencing as an aid in identifying potential community compositional trends that could be used as an estimation of various production and performance traits including methane emission, animal protein production efficiency, and ruminant health status. In order to translate rumen microbiome studies into executable application, there is a need for experimental and analytical concordance within the community. The objective of this study was to assess these factors in relation to selected currently established methods for 16S phylogenetic community analysis on a microbial community standard (MC) and a DNA standard (DS; ZymoBIOMICSTM). DNA was extracted from MC using the RBBC method commonly used for microbial DNA extraction from rumen digesta samples. 16S rRNA amplicon libraries were generated for the MC and DS using primers routinely used for rumen bacterial and archaeal community analysis. The primers targeted the V4 and V3–V4 region of the 16S rRNA gene and samples were subjected to both 20 and 28 polymerase chain reaction (PCR) cycles under identical cycle conditions. Sequencing was conducted using the Illumina MiSeq platform. As the bacteria contained in the microbial mock community were well-classified species, and for ease of explanation, we used the results of the Basic Local Alignment Search Tool classification to assess the DNA, PCR cycle number, and primer type. Sequence classification methodology was assessed independently. Spearman’s correlation analysis indicated that utilizing the repeated bead beating and column method for DNA extraction in combination with primers targeting the 16S rRNA gene using 20 first-round PCR cycles was sufficient for amplicon sequencing to generate a relatively accurate depiction of the bacterial communities present in rumen samples. These results also emphasize the requirement to develop and utilize positive mock community controls for all rumen microbiomic studies in order to discern errors which may arise at any step during a next-generation sequencing protocol.
  • Improved detection of biomarkers in cervico-vaginal mucus (CVM) from postpartum cattle

    Adnane, Mounir; Kelly, Paul; Chapwanya, Aspinas; Meade, Kieran G; O’Farrelly, Cliona; The Algerian Ministry for High Education and Scientific Research; University of Tiaret, Algeria; Department of Agriculture, Food and the Marine, Ireland; ofarrecl-HRB-HRA_POR/2012/37; 13/S/472 (Biomed Central, 2018-09-29)
    Background In the postpartum cow, early diagnosis of uterine disease is currently problematic due to the lack of reliable, non-invasive diagnostic methods. Cervico-vaginal mucus (CVM) is an easy to collect potentially informative source of biomarkers for the diagnosis and prognosis of uterine disease in cows. Here, we report an improved method for processing CVM from postpartum dairy cows for the measurement of immune biomarkers. CVM samples were collected from the vagina using gloved hand during the first two weeks postpartum and processed with buffer alone or buffer containing different concentrations of the reducing agents recommended in standard protocols: Dithiothriotol (DTT) or N-Acetyl-L-Cysteine (NAC). Total protein was measured using the bicinchoninic acid (BCA) assay; interleukin 6 (IL-6), IL-8 and α1-acid glycoprotein (AGP) were measured by ELISA. Results We found that use of reducing agents to liquefy CVM affects protein yield and the accuracy of biomarker detection. Our improved protocol results in lower protein yields but improved detection of cytokines and chemokines. Using our modified method to measure AGP in CVM we found raised levels of AGP at seven days postpartum in CVM from cows that went on to develop endometritis. Conclusion We conclude that processing CVM without reducing agents improves detection of biomarkers that reflect uterine health in cattle. We propose that measurement of AGP in CVM during the first week postpartum may identify cows at risk of developing clinical endometritis.
  • Spatial patterns of Fasciola hepatica and Calicophoron daubneyi infections in ruminants in Ireland and modelling of C. daubneyi infection

    Naranjo-Lucena, Amalia; Munita Corbalán, María P; Martínez-Ibeas, Ana M; McGrath, Guy; Murray, Gerard; Casey, Mícheál; Good, Barbara; Sayers, Riona; Mulcahy, Grace; Zintl, Annetta; European Union; Department of Agriculture, Food and the Marine, Ireland; 635408); 13/S/405 (Biomed Central, 2018-09-29)
    Background Fasciola hepatica has always represented a threat to Irish livestock because the Irish climate is highly suitable for the main local intermediate host of the parasite, the snail Galba truncatula. The recent clinical emergence of infections due to Calicophoron daubneyi has raised the question of whether the two parasites, which share a niche during part of their life-cycles, interact in some way. Here, we used geographical information systems (GIS) to analyse the distribution of both parasites in cattle and sheep. We also developed the first predictive model of paramphistomosis in Ireland. Results Our results indicated that, in cattle, liver fluke infection is less common than rumen fluke infection and does not exhibit the same seasonal fluctuations. Overall, we found that cattle had a higher likelihood of being infected with rumen fluke than sheep (OR = 3.134, P < 0.01). In addition, infection with one parasite increased the odds of infection with the other in both host species. Rumen fluke in cattle showed the highest spatial density of infection. Environmental variables such as soil drainage, land cover and habitat appeared to be the most important risk factors for C. daubneyi infection, followed by rainfall and vegetation. Overall the risk of infection with this parasite was predicted to be higher in the west of the country. Conclusions This study shows differences between the infection rates and spatial patterns of bovine and ovine infections with F. hepatica and C. daubneyi in Ireland. Whether the reasons for this are due to susceptibility, exposure and/or management factors is yet to be determined. Furthermore, the rumen fluke model indicates distinct risk factors and predicted distribution to those of F. hepatica, suggesting potential biological differences between both parasite species.
  • Residual feed intake phenotype and gender affect the expression of key genes of the lipogenesis pathway in subcutaneous adipose tissue of beef cattle

    McKenna, Clare; Porter, Richard; Keogh, Kate; Waters, Sinead M.; McGee, Mark; Kenny, David; Teagasc Walsh Fellowship Programme (Biomed Central, 2018-09-20)
    Background Feed accounts for up to 75% of costs in beef production systems, thus any improvement in feed efficiency (FE) will benefit the profitability of this enterprise. Residual feed intake (RFI) is a measure of FE that is independent of level of production. Adipose tissue (AT) is a major endocrine organ and the primary metabolic energy reservoir. It modulates a variety of processes related to FE such as lipid metabolism and glucose homeostasis and thus measures of inter-animal variation in adiposity are frequently included in the calculation of the RFI index. The aim of this study was to determine the effect of phenotypic RFI status and gender on the expression of key candidate genes related to processes involved in energy metabolism within AT. Dry matter intake (DMI) and average daily gain (ADG) were measured over a period of 70 d for 52 purebred Simmental heifers (n = 24) and bulls (n = 28) with an initial BW±SD of 372±39.6 kg and 387±50.6 kg, respectively. Residual feed intake was calculated and animals were ranked within gender by RFI into high (inefficient; n = 9 heifers and n = 8 bulls) and low (efficient; n = 9 heifers and n = 8 bulls) groups. Results Average daily gain ±SD and daily DMI ±SD for heifers and bulls were 1.2±0.4 kg and 9.1±0.5 kg, and 1.8±0.3 kg and 9.5±1 kg respectively. High RFI heifers and bulls consumed 10% and 15% more (P < 0.05) than their low RFI counterparts, respectively. Heifers had a higher expression of all genes measured than bulls (P < 0.05). A gender × RFI interaction was detected for HMGCS2(P < 0.05) in which high RFI bulls tended to have lower expression of HMGCS2 than low RFI bulls (P < 0.1), whereas high RFI heifers had higher expression than low RFI heifers (P < 0.05) and high RFI bulls (P < 0.05). SLC2A4 expression was consistently higher in subcutaneous AT of low RFI animals across gender. Conclusion The findings of this study indicate that low RFI cattle exhibit upregulation of the molecular mechanisms governing glucose metabolism in adipose tissue, in particular, glucose clearance. The decreased expression of SLC2A4 in the inefficient cattle may result in less efficient glucose metabolism in these animals. We conclude that SLC2A4 may be a potential biomarker for RFI in cattle.
  • Culicoides species composition and abundance on Irish cattle farms: implications for arboviral disease transmission

    Collins, Áine B; Mee, John F; Doherty, Michael L; Barrett, Damien J; England, Marion E; Teagasc Walsh Fellowship Programme (Biomed Central, 2018-08-17)
    Background Following the emergence of Schmallenberg virus (SBV) in Ireland in 2012, a sentinel herd surveillance program was established in the south of Ireland with the primary aim of investigating the species composition and abundance of Culicoides on livestock farms in the region. Methods Ultraviolet-light trapping for Culicoides was carried out on 10 sentinel farms. Each site was sampled fortnightly over 16 weeks (21st July to 5th November 2014). One Onderstepoort Veterinary Institute UV light trap was run overnight at each site and catches were transferred immediately into 70% ethanol. Culicoides were morphologically identified to species level. Collection site habitats were characterised using the Phase 1 habitat survey technique (Joint Nature Conservation Committee). Results A total of 23,929 individual Culicoides from 20 species was identified, including one species identified in Ireland for the first time, Culicoides cameroni. The most abundant species identified were Culicoides obsoletus/Culicoides scoticus (38%), Culicoides dewulfi (36%), Culicoides pulicaris (9%), Culicoides chiopterus (5%) and Culicoides punctatus (5%), comprising 93% of all Culicoides specimens identified. Collection site habitats were dominated by improved grassland and a combination of broadleaf woodland and native woodland species. Conclusions The most abundant species of Culicoides identified were the putative vectors of bluetongue virus (BTV) and SBV in northern Europe. Their presence and abundance demonstrates the potential for future transmission of arboviruses among livestock in this region.
  • Effect of feeding colostrum at different volumes and subsequent number of transition milk feeds on the serum immunoglobulin G concentration and health status of dairy calves

    Conneely, Muireann; Berry, Donagh P.; Murphy, J. P.; Lorenz, I.; Doherty, M. L.; Kennedy, Emer (Elsevier for American Dairy Science Association, 2014-09)
    Transfer of sufficient IgG to the newborn calf via colostrum is vital to provide it with adequate immunological protection and resistance to disease. The objectives of the present study were to compare serum IgG concentration and health parameters of calves (1) fed different volumes of colostrum [7, 8.5, or 10% of body weight (BW)] within 2 h of birth and (2) given 0, 2, or 4 subsequent feedings of transition milk (i.e., milkings 2 to 6 postcalving). Ninety-nine dairy calves were fed 7, 8.5, or 10% of BW in colostrum within 2 h of birth and given 0, 2, or 4 subsequent feedings of transition milk. The concentration of IgG in the serum of calves was measured at 24, 48, 72, and 642 h of age by an ELISA. The apparent efficiency of absorption for IgG was determined. Health scores were assigned to calves twice per week and all episodes of disease were recorded. The effect of experimental treatment on calf serum IgG concentration differed by the age of the calf. Calves fed 8.5% of BW in colostrum had a greater mean serum IgG concentration than calves fed 7 or 10% of BW at 24, 48, and 72 h of age. At 642 h of age, serum IgG concentrations of calves fed 8.5% of BW (24.2 g/L) and calves fed 10% of BW (21.6 g/L) did not differ, although the serum IgG concentration of calves fed 8.5% of BW was still greater than that of calves fed 7% of BW (20.7 g/L). No difference in serum IgG concentration existed between calves fed 7% of BW and those fed 10% of BW at any age. No significant effect of number of subsequent feedings of transition milk on calf serum IgG concentration was detected. The apparent efficiency of absorption of calves fed 8.5% of BW in colostrum (38%) was greater than calves fed 7% of BW in colostrum (26%) and tended to be greater than in calves fed 10% of BW (29%). Calves fed further feedings of transition milk after the initial feeding of colostrum had a lower odds (0.62; 95% confidence interval: 0.41 to 0.93) of being assigned a worse eye/ear score (i.e., a more copious ocular discharge or pronounced ear droop) and a lower odds (0.5; 95% confidence interval: 0.32 to 0.79) of being assigned a worse nasal score (i.e., a more copious and purulent nasal discharge) during the study period relative to calves that received no further feedings of transition milk. In conclusion, calves fed 8.5% of BW in colostrum within 2 h of birth achieved a greater concentration of IgG in serum in the first 3 d of life than calves fed either 7 or 10% of BW. Feeding calves transition milk subsequently reduced their odds of being assigned a worse eye/ear and nasal score.
  • Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

    Bouwman, Aniek C.; et al; Purfiled, Deirdre C; Berry, Donagh P.; Department of Agriculture, Food and the Marine, Ireland; Science Foundation Ireland; German Federal Ministry of Education and Research; Deutsche Forschungsgemeinschaft; Breed4Food; European Commission; Dairy Futures Cooperative Research Centre; Genome Canada project; 11/S/112; 14/IA/2576; 0315527B; PA 2789/1-1; BO-22.04-011-001-ASG-LR; 317697 (Nature Publishing Group, 2018-02-19)
    Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.
  • Whole genome association study identifies regions of the bovine genome and biological pathways involved in carcass trait performance in Holstein-Friesian cattle

    Doran, Anthony G.; Berry, Donagh P.; Creevy, Christopher J.; Department of Agriculture, Food and the Marine, Ireland; Teagasc Walsh Fellowship Programme; Science Foundation Ireland; Irish Cattle Breeding Federation; RSF-06-0353; 11/S/112; 2009183; 07/SK/B1236A (Biomed Central, 2014-10)
    Background Four traits related to carcass performance have been identified as economically important in beef production: carcass weight, carcass fat, carcass conformation of progeny and cull cow carcass weight. Although Holstein-Friesian cattle are primarily utilized for milk production, they are also an important source of meat for beef production and export. Because of this, there is great interest in understanding the underlying genomic structure influencing these traits. Several genome-wide association studies have identified regions of the bovine genome associated with growth or carcass traits, however, little is known about the mechanisms or underlying biological pathways involved. This study aims to detect regions of the bovine genome associated with carcass performance traits (employing a panel of 54,001 SNPs) using measures of genetic merit (as predicted transmitting abilities) for 5,705 Irish Holstein-Friesian animals. Candidate genes and biological pathways were then identified for each trait under investigation. Results Following adjustment for false discovery (q-value < 0.05), 479 quantitative trait loci (QTL) were associated with at least one of the four carcass traits using a single SNP regression approach. Using a Bayesian approach, 46 QTL were associated (posterior probability > 0.5) with at least one of the four traits. In total, 557 unique bovine genes, which mapped to 426 human orthologs, were within 500kbs of QTL found associated with a trait using the Bayesian approach. Using this information, 24 significantly over-represented pathways were identified across all traits. The most significantly over-represented biological pathway was the peroxisome proliferator-activated receptor (PPAR) signaling pathway. Conclusions A large number of genomic regions putatively associated with bovine carcass traits were detected using two different statistical approaches. Notably, several significant associations were detected in close proximity to genes with a known role in animal growth such as glucagon and leptin. Several biological pathways, including PPAR signaling, were shown to be involved in various aspects of bovine carcass performance. These core genes and biological processes may form the foundation for further investigation to identify causative mutations involved in each trait. Results reported here support previous findings suggesting conservation of key biological processes involved in growth and metabolism.
  • Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows

    McParland, Sinead; Lewis, Eva; Kennedy, Emer; Moore, S. G.; McCarthy, B.; O'Donovan, Michael; Butler, Stephen T.; Pryce, J. E.; Berry, Donagh P.; Department of Agriculture, Food and the Marine, Ireland; Marie Curie project International Research Staff Exchange Scheme SEQSEL; 13/S4/96 (Elsevier for American Dairy Science Association, 2014-09)
    Interest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (REX) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (REX = 0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (REX = 0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions.
  • Does iodine supplementation of the prepartum dairy cow diet affect serum immunoglobulin G concentration, iodine, and health status of the calf?

    Conneely, Muireann; Berry, Donagh P.; Sayers, Riona; Murphy, J. P.; Doherty, M. L.; Lorenz, I.; Kennedy, Emer (Elsevier for American Dairy Science Association, 2014-08)
    Absorption of adequate IgG from colostrum is critical to provide the newborn calf with adequate immunological protection and resistance to disease. Excessive iodine supplementation of the prepartum ewe reduces IgG absorption of her offspring; it is possible that excessive iodine supplementation of the prepartum dairy cow may similarly impair the ability of the calf to acquire immunological protection. The objectives of this study were to determine whether the iodine status, health status, and ability of calves to absorb IgG from colostrum were affected by prepartum iodine supplementation strategies of their dams. Dairy cows (n = 127) received one of the following levels of iodine supplementation precalving: 15 mg of iodine/kg of dietary dry matter (DM) (HI); no additional iodine supplementation (MI); 5 mg/kg of dietary DM (SI); and 15 mg of iodine/kg of DM for the first 3.5 wk of the precalving period and no additional supplementation for the second 3.5 wk (HMI). Calves were assigned to 1 of 6 experimental treatments, based on the prepartum iodine supplementation treatment of their dam and the precalving treatment group of the cows from which the colostrum fed was obtained: (1) HI_HI: born to HI dams, fed HI colostrum (i.e., colostrum produced by cows in the HI group); (2) MI_MI: born to MI dams, fed MI colostrum; (3) SI_SI: born to SI dams, fed SI colostrum; (4) HI_MI: born to HI dams, fed MI colostrum; (5) MI_HI: born to MI dams, fed HI colostrum; and (6) HMI_HMI: born to HMI dams, fed HMI colostrum. Concentration of calf serum IgG and plasma inorganic iodine (PII) was measured at 0 and 24 h of age. Apparent efficiency of absorption for IgG was determined. Health scores were assigned to calves twice weekly and all episodes of disease were recorded. Cow experimental treatment group affected calf PII at 0 h of age; the PII of calves born to HI dams (987.2 µg/L) was greater than that of calves born to MI dams (510.1 µg/L), SI (585.2 µg/L), and HMI dams (692.9 µg/L). Calf experimental treatment group affected calf PII at 24 h of age; the PII of HI_HI (1,259.2 µg/L) and HI_MI (1,177.8 µg/L) calves was greater than MI_MI (240.7 µg/L), SI_SI (302.2 µg/L), HMI_HMI (320.7 µg/L), and MI_HI (216.3 µg/L) calves. No effect of experimental treatment was observed on the concentration of IgG measured in calf serum at 24 h of age, or on apparent efficiency of absorption. Experimental treatment had no effect on the likelihood of a calf being assigned a worse nasal, eye and ear, cough, or fecal score within the study period, nor did it affect the probability of a calf receiving treatment for a disease a greater number of times. Prepartum iodine supplementation of cows at 15mg/kg of DM increased the iodine levels in their calves at birth and 24 h of age, but did not affect their ability to absorb IgG from colostrum. Supplementation with iodine above the minimum requirements established by the National Research Council was unnecessary to ensure appropriate iodine levels in calves at birth.
  • Differentially Expressed Genes in Endometrium and Corpus Luteum of Holstein Cows Selected for High and Low Fertility Are Enriched for Sequence Variants Associated with Fertility

    Moore, Stephen G.; Pryce, J. E.; Hayes, B. J.; Chamberlain, A. J.; Kemper, K. E.; Berry, Donagh P.; McCabe, Matthew; Cormican, Paul; Lonergan, P.; Fair, T.; Butler, Stephen T.; Department of Agriculture, Food and the Marine, Ireland; Teagasc Walsh Fellowship Programme; National Development Plan; Irish Dairy Levy Research Trust; 13/S/528 (Oxford University Press, 2015-11)
    Despite the importance of fertility in humans and livestock, there has been little success dissecting the genetic basis of fertility. Our hypothesis was that genes differentially expressed in the endometrium and corpus luteum on Day 13 of the estrous cycle between cows with either good or poor genetic merit for fertility would be enriched for genetic variants associated with fertility. We combined a unique genetic model of fertility (cattle that have been selected for high and low fertility and show substantial difference in fertility) with gene expression data from these cattle and genome-wide association study (GWAS) results in ∼20 000 cattle to identify quantitative trait loci (QTL) regions and sequence variants associated with genetic variation in fertility. Two hundred and forty-five QTL regions and 17 sequence variants associated primarily with prostaglandin F2alpha, steroidogenesis, mRNA processing, energy status, and immune-related processes were identified. Ninety-three of the QTL regions were validated by two independent GWAS, with signals for fertility detected primarily on chromosomes 18, 5, 7, 8, and 29. Plausible causative mutations were identified, including one missense variant significantly associated with fertility and predicted to affect the protein function of EIF4EBP3. The results of this study enhance our understanding of 1) the contribution of the endometrium and corpus luteum transcriptome to phenotypic fertility differences and 2) the genetic architecture of fertility in dairy cattle. Including these variants in predictions of genomic breeding values may improve the rate of genetic gain for this critical trait.
  • Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia

    de Haas, Y.; Pryce, J. E.; Calus, M. P. L.; Wall, E.; Berry, Donagh P.; Lovendahl, P.; Krattenmacher, N.; Miglior, F.; Weigel, K.; Spurlock, D.; MacDonald, K. A.; Hulsegge, B.; Veerkamp, R. F.; European Commission; gDMI consortium; 317697 (Elsevier for American Dairy Science Association, 2015-07)
    With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in Holstein-Friesian dairy cattle, data from 10 research herds in Europe, North America, and Australasia were combined. The DMI records were available on 10,701 parity 1 to 5 records from 6,953 cows, as well as on 1,784 growing heifers. Predicted DMI at 70 d in milk was used as the phenotype for the lactating animals, and the average DMI measured during a 60- to 70-d test period at approximately 200 d of age was used as the phenotype for the growing heifers. After editing, there were 583,375 genetic markers obtained from either actual high-density single nucleotide polymorphism (SNP) genotypes or imputed from 54,001 marker SNP genotypes. Genetic correlations between the populations were estimated using genomic REML. The accuracy of genomic prediction was evaluated for the following scenarios: (1) within-country only, by fixing the correlations among populations to zero, (2) using near-unity correlations among populations and assuming the same trait in each population, and (3) a sharing data scenario using estimated genetic correlations among populations. For these 3 scenarios, the data set was divided into 10 sub-populations stratified by progeny group of sires; 9 of these sub-populations were used (in turn) for the genomic prediction and the tenth was used for calculation of the accuracy (correlation adjusted for heritability). A fourth scenario to quantify the benefit for countries that do not record DMI was investigated (i.e., having an entire country as the validation population and excluding this country in the development of the genomic predictions). The optimal scenario, which was sharing data, resulted in a mean prediction accuracy of 0.44, ranging from 0.37 (Denmark) to 0.54 (the Netherlands). Assuming near-unity among-country genetic correlations, the mean accuracy of prediction dropped to 0.40, and the mean within-country accuracy was 0.30. If no records were available in a country, the accuracy based on the other populations ranged from 0.23 to 0.53 for the milking cows, but were only 0.03 and 0.19 for Australian and New Zealand heifers, respectively; the overall mean prediction accuracy was 0.37. Therefore, there is a benefit in collaboration, because phenotypic information for DMI from other countries can be used to augment the accuracy of genomic evaluations of individual countries.
  • Genetic parameters of ovarian and uterine reproductive traits in dairy cows

    Carthy, T. R.; Ryan, D. P.; Fitzgerald, A. M.; Evans, R. D.; Berry, Donagh P.; Department of Agriculture, Food and the Marine, Ireland; European Commission; 11/S/133 (Elsevier for American Dairy Science Association, 2015-04)
    The objective of the study was to estimate genetic parameters of detailed reproductive traits derived from ultrasound examination of the reproductive tract as well as their genetic correlations with traditional reproductive traits. A total of 226,141 calving and insemination records as well as 74,134 ultrasound records from Irish dairy cows were used. Traditional reproductive traits included postpartum interval to first service, conception, and next calving, as well as the interval from first to last service; number of inseminations, pregnancy rate to first service, pregnant within 42 d of the herd breeding season, and submission in the first 21 d of the herd breeding season were also available. Detailed reproductive traits included resumed cyclicity at the time of ultrasound examination, incidence of multiple ovulations, incidence of early postpartum ovulation, heat detection, ovarian cystic structures, embryo loss, and uterine score; the latter was a subjectively assessed on a scale of 1 (little fluid with normal uterine tone) to 4 (large quantity of fluid with a flaccid uterine tone). Variance (and covariance) components were estimated using repeatability animal linear mixed models. Heritability for all reproductive traits were generally low (0.001–0.05), with the exception of traits related to cyclicity postpartum, regardless if defined traditionally (0.07; calving to first service) or from ultrasound examination [resumed cyclicity at the time of examination (0.07) or early postpartum ovulation (0.10)]. The genetic correlations among the detailed reproductive traits were generally favorable. The exception was the genetic correlation (0.29) between resumed cyclicity and uterine score; superior genetic merit for cyclicity postpartum was associated with inferior uterine score. Superior genetic merit for most traditional reproductive traits was associated with superior genetic merit for resumed cyclicity (genetic correlations ranged from −0.59 to −0.36 and from 0.56 to 0.70) and uterine score (genetic correlations ranged from −0.47 to 0.32 and from 0.25 to 0.52). Genetic predisposition to an increased incidence of embryo loss was associated with both an inferior uterine score (0.24) and inferior genetic merit for traditional reproductive traits (genetic correlations ranged from −0.52 to −0.42 and from 0.33 to 0.80). The results from the present study indicate that selection based on traditional reproductive traits, such as calving interval or days open, resulted in improved genetic merit of all the detailed reproductive traits evaluated in this study. Additionally, greater accuracy of selection for calving interval is expected for a relatively small progeny group size when detailed reproductive traits are included in a multitrait genetic evaluation.
  • Development of an index to rank dairy females on expected lifetime profit

    Kelleher, M. M.; Amer, P. R.; Shalloo, Laurence; Evans, R. D.; Byrne, T. J.; Buckley, Frank J.; Berry, Donagh P. (Elsevier for American Dairy Science Association, 2015-03)
    The objective of this study was to develop an index to rank dairy females on expected profit for the remainder of their lifetime, taking cognizance of both additive and nonadditive genetic merit, permanent environmental effects, and current states of the animal including the most recent calving date and cow parity. The cow own worth (COW) index is intended to be used for culling the expected least profitable females in a herd, as well as inform purchase and pricing decisions for trading of females. The framework of the COW index consisted of the profit accruing from (1) the current lactation, (2) future lactations, and (3) net replacement cost differential. The COW index was generated from estimated performance values (sum of additive genetic merit, nonadditive genetic merit, and permanent environmental effects) of traits, their respective net margin values, and transition probability matrices for month of calving, survival, and somatic cell count; the transition matrices were to account for predicted change in a cow’s state in the future. Transition matrices were generated from 3,156,109 lactation records from the Irish national database between the years 2010 and 2013. Phenotypic performance records for 162,981 cows in the year 2012 were used to validate the COW index. Genetic and permanent environmental effects (where applicable) were available for these cows from the 2011 national genetic evaluations and used to calculate the COW index and their national breeding index values (includes only additive genetic effects). Cows were stratified per quartile within herd, based on their COW index value and national breeding index value. The correlation between individual animal COW index value and national breeding index value was 0.65. Month of calving of the cow in her current lactation explained 18% of the variation in the COW index, with the parity of the cow explaining an additional 3 percentage units of the variance in the COW index. Females ranking higher on the COW index yielded more milk and milk solids and calved earlier in the calving season than their lower ranking contemporaries. The difference in phenotypic performance between the best and worst quartiles was larger for cows ranked on COW index than cows ranked on the national breeding index. The COW index is useful to rank females before culling or purchasing decisions on expected profit and is complementary to the national breeding index, which identifies the most suitable females for breeding replacements.
  • Breeding the dairy cow of the future: what do we need?

    Berry, Donagh P. (CSIRO, 2015-06)
    Genetics 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.
  • Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

    Visentin, G.; McDermott, A.; McParland, Sinead; Berry, Donagh P.; Kenny, O. A.; Brodkorb, Andre; Fenelon, Mark; de Marchi, M.; European Commission (Elsevier for American Dairy Science Association, 2015-07)
    Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n = 713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000 cm−1 were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60 min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60 min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation.
  • Machine learning algorithms for the prediction of conception success to a given insemination in lactating dairy cows

    Henpstalk, K.; McParland, Sinead; Berry, Donagh P.; European Commission (Elsevier for American Dairy Science Association, 2015-06)
    The ability to accurately predict the conception outcome for a future mating would be of considerable benefit for producers in deciding what mating plan (i.e., expensive semen or less expensive semen) to implement for a given cow. The objective of the present study was to use herd- and cow-level factors to predict the likelihood of conception success to a given insemination (i.e., conception outcome not including embryo loss); of particular interest in the present study was the usefulness of milk mid-infrared (MIR) spectral data in augmenting the accuracy of the prediction model. A total of 4,341 insemination records with conception outcome information from 2,874 lactations on 1,789 cows from 7 research herds for the years 2009 to 2014 were available. The data set was separated into a calibration data set and a validation data set using either of 2 approaches: (1) the calibration data set contained records from all 7 farms for the years 2009 to 2011, inclusive, and the validation data set included data from the 7 farms for the years 2012 to 2014, inclusive, or (2) the calibration data set contained records from 5 farms for all 6 yr and the validation data set contained information from the other 2 farms for all 6 yr. The prediction models were developed with 8 different machine learning algorithms in the calibration data set using standard 10-times 10-fold cross-validation and also by evaluating in the validation data set. The area under curve (AUC) for the receiver operating curve varied from 0.487 to 0.675 across the different algorithms and scenarios investigated. Logistic regression was generally the best-performing algorithm. The AUC was generally inferior for the external validation data sets compared with the calibration data sets. The inclusion of milk MIR in the prediction model generally did not improve the accuracy of prediction. Despite the fair AUC for predicting conception outcome under the different scenarios investigated, the model provided a reasonable prediction of the likelihood of conception success when the high predicted probability instances were considered; a conception rate of 85% was evident in the top 10% of inseminations ranked on predicted probability of conception success in the validation data set.
  • Factors associated with the financial performance of spring-calving, pasture-based dairy farms

    Ramsbottom, George; Horan, Brendan; Berry, Donagh P.; Roche, J. R. (Elsevier for American Dairy Science Association, 2015-03)
    As land becomes a limiting resource for pasture-based dairy farming, the inclusion of purchased supplementary feeds to increase milk production per cow (through greater dry matter intake) and per hectare (through increased stocking rate) is often proposed as a strategy to increase profitability. Although a plausible proposition, virtually no analysis has been done on the effect of such intensification on the profitability of commercial pasture-based dairy farm businesses. The objective of this study was to characterize the average physical and financial performance of dairy systems differing in the proportion of the cow’s diet coming from grazed pasture versus purchased supplementary feeds over 4 yr, while accounting for any interaction with geographic region. Physical, genetic, and financial performance data from 1,561 seasonal-calving, pasture-based dairy farms in Ireland were available between the years 2008 and 2011; data from some herds were available for more than 1 yr of the 4-yr study period, providing data from 2,759 dairy farm-years. The data set was divided into geographic regions, based on latitude, rainfall, and soil characteristics that relate to drainage; these factors influence the length of the pasture growth season and the timing of turnout to pasture in spring and rehousing in autumn. Farms were also categorized by the quantity of feed purchased; farms in which cows received <10, 11–20, 21–30, or >30% of their annual feed requirements from purchased feed were considered to be categories representative of increasing levels of system intensification. Geographic region was associated with differences in grazing days, pasture harvested per hectare, milk production per cow and per hectare, and farm profitability. Farms in regions with longer grazing seasons harvested a greater amount of pasture [an additional 19 kg of dry matter (DM)/ha per grazing day per hectare], and greater pasture harvested was associated with increased milk component yield per hectare (58.4 kg of fat and 51.4 kg of protein more per tonne of DM pasture harvested/ha) and net profit per hectare (€268/ha more per tonne of DM harvested). Milk yield and yield of milk components per cow and per hectare increased linearly with increased use of purchased feed (additional 30.6 kg of milk fat and 26.7 kg of milk protein per tonne of DM purchased feed per hectare), but, on average, pasture harvested/hectare and net profit/hectare declined (−0.60 t of DM/ha and −€78.2/ha, respectively) with every tonne of DM supplementary feed purchased per hectare. The results indicate an effect of purchased feeds not usually accounted for in marginal economic analyses (e.g., milk to feed price ratio): the decline in pasture harvested/hectare, with the costs of producing the unutilized pasture in addition to the cost of feed resulting in a lower profit. In conclusion, greater milk component yields per cow were associated with increased profit per hectare, and a greater use of purchased feeds was associated with an increase in the yield of milk components. However, on average, increasing yield of milk components through the supply of purchased feeds to pasture-based cows was associated with a decline in pasture harvested per hectare and profitability. The decline in pasture harvested per hectare with increased use of purchased supplements per cow is probably the primary reason for the low milk production response and the failure to capitalize on the potential benefits of purchased supplements, with the associated costs of growing the unutilized pasture, in conjunction with increased nonfeed variable and fixed costs outweighing the increased milk production and revenue from supplementation. Farmers considering intensification through use of purchased supplements to increase the stock-carrying capacity of the farm (i.e., stocking rate) must ensure that they focus on management of pasture and total cost control to capture the potential benefits of supplementary feed use.
  • Genetic parameters of dairy cow energy intake and body energy status predicted using mid-infrared spectrometry of milk

    McParland, Sinead; Kennedy, Emer; Lewis, Eva; Moore, S. G.; McCarthy, B.; O'Donovan, M.; Berry, Donagh P.; Department of Agriculture, Food and the Marine, Ireland; European Commission; Marie Curie project International Research Staff Exchange Scheme SEQSEL; 13/S4/96; KBBE-211708; 13/S4/96; KBBE-211708 (Elsevier for American Dairy Science Association, 2014-12)
    Energy balance (EB) and energy intake (EI) are heritable traits of economic importance. Despite this, neither trait is explicitly included in national dairy cow breeding goals due to a lack of routinely available data from which to compute reliable breeding values. Mid-infrared (MIR) spectrometry, which is performed during routine milk recording, is an accurate predictor of both EB and EI. The objective of this study was to estimate genetic parameters of EB and EI predicted using MIR spectrometry. Measured EI and EB were available for 1,102 Irish Holstein-Friesian cows based on actual feed intake and energy sink data. A subset of these data (1,270 test-day records) was used to develop equations to predict EI, EB, and daily change in body condition score (ΔBCS) and body weight (ΔBW) using the MIR spectrum with or without milk yield also as a predictor variable. Accuracy of cross-validation of the prediction equations was 0.75, 0.73, 0.77, and 0.70 for EI, EB, ΔBCS, and ΔBW, respectively. Prediction equations were applied to additional spectral data, yielding up to 94,653 records of MIR-predicted EI, EB, ΔBCS, and ΔBW available for variance component estimation. Variance components were estimated using repeatability animal linear mixed models. Heritabilities of MIR-predicted EI, EB, ΔBCS, and ΔBW were 0.20, 0.10, 0.07, and 0.06, respectively; heritability estimates of the respective measured traits were 0.35, 0.16, 0.07, and 0.08, respectively. The genetic correlation between measured and MIR-predicted EI was 0.84 and between measured and MIR-predicted EB was 0.54, indicating that selection based on MIR-predicted EI or EB would improve true EI or EB. Genetic and phenotypic associations between EI and both the milk production and body-change traits were generally in agreement, regardless of whether measured EI or MIR-predicted EI was considered. Higher-yielding animals of higher body weight had greater EI. Predicted EB was negatively genetically correlated with milk yield (genetic correlation = −0.29) and positively genetically correlated with both milk fat and protein percent (genetic correlation = 0.17 and 0.16, respectively). Least squares means phenotypic EI of 198 animals stratified as low, average, and high estimated breeding values for MIR-predicted EI (animal phenotypes were not included in the genetic evaluation) were 154.3, 156.0, and 163.3 MJ/d, corroborating that selection on MIR-predicted EI will, on average, result in differences in phenotypic true EI.
  • Genetics of bovine respiratory disease in cattle: can breeding programs reduce the problem?

    Berry, Donagh P.; Department of Agriculture, Food and the Marine, Ireland (Cambridge University Press, 2014-12)
    Genetics 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.

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