• Accuracy of predicting milk yield from alternative milk recording schemes

      Berry, Donagh; Olori, V. E.; Cromie, A. R.; Veerkamp, Roel F.; Rath, Myles V; Dillon, Pat; Teagasc Walsh Fellowship Programme (Cambridge University Press, 2005-02)
      The effect of reducing the frequency of official milk recording and the number of recorded samples per test-day on the accuracy of predicting daily yield and cumulative 305-day yield was investigated. A control data set consisting of 58 210 primiparous cows with milk test-day records every 4 weeks was used to investigate the influence of reduced milk recording frequencies. The accuracy of prediction of daily yield with one milk sample per test-day was investigated using 41 874 testday records from 683 cows. Results show that five or more test-day records taken at 8-weekly intervals (A8) predicted 305-day yield with a high level of accuracy. Correlations between 305-day yield predicted from 4-weekly recording intervals (A4) and from 8-weekly intervals were 0.99, 0.98 and 0.98 for milk, fat and protein, respectively. The mean error in estimating 305-day yield from the A8 scheme was 6.8 kg (s.d. 191 kg) for milk yield, 0.3 kg (s.d. 10 kg) for fat yield, and −0.3 kg (s.d. 7 kg) for protein yield, compared with the A4 scheme. Milk yield and composition taken during either morning (AM) or evening (PM) milking predicted 24-h yield with a high degree of accuracy. Alternating between AM and PM sampling every 4 weeks predicted 305-day yield with a higher degree of accuracy than either all AM or all PM sampling. Alternate AM-PM recording every 4 weeks and AM + PM recording every 8 weeks produced very similar accuracies in predicting 305-day yield compared with the official AM + PM recording every 4 weeks.
    • Dairy cattle breeding objectives combining production and non-production traits for pasture based systems in Ireland.

      Berry, Donagh; Buckley, Frank; Dillon, Pat; Veerkamp, Roel F. (Teagasc, 2005-11-01)
      The objectives of this study were: 1) to estimate genetic (co) variances among body condition score, body weight, milk production, linear type traits and fertility, and 2) to investigate the presence of genotype by environment interactions for milk production, body condition score, and body weight, in Irish grass based seasonal calving herds. Genetic parameters were estimated from a potential 8928 primiparous and multiparous Holstein-Friesian cows over two years (1999 and 2000). Heritability estimates for body condition score (BCS) and body weight (BW) were found to be moderate to high; estimates ranged from 0.27 to 0.51 for BCS, and from 0.39 to 0.61 for BW. Heritability estimates for BCS change and BW change at different stages of lactation were all less than 0.11. Heritability for the linear type traits varied from 0.11 to 0.43. Phenotypic and genetic correlations between BCS and BW at the same stage of lactation were all close to 0.50 indicating that approximately 25% of the genetic and phenotypic variation in BW may be attributed to differences in BCS. Genetic correlations between BCS and milk yield tended to be negative (-0.14 to –0.51) and genetic correlations between BW and milk yield were close to zero (-0.07 to 0.09). However, the genetic correlations between BW adjusted for differences in BCS were positive (0.15 to 0.39). Genetic correlations between BCS and the fertility traits investigated were all favourable, indicating that cows with a superior genetic merit for BCS are on average likely to be served sooner, receive less services and have higher pregnancy rates. The genetic correlations between linear type traits and milk yield indicate that selection for milk production has resulted in taller, deeper cows that tend to be more angular and have less body condition. Genetically these cows are predisposed to inferior reproductive efficiency. Moderate genetic correlations were found between some of the linear type traits investigated and somatic cell count. A comparison of BCS, as recorded by Teagasc personnel (scale 1-5) and Holstein herd-book classifiers (scale 1-9) indicated consistency between the two sources. Phenotypic and genetic correlations of 0.54 and 0.86, respectively, were observed between the two measurement sources on the same animals. Genotype by environment interactions, were found for milk yield across different silage quality environments, and for BCS across different herd-year milk yield, concentrate, grazing severity and silage quality environments.
    • Genetic analysis of atypical progesterone profiles in Holstein-Friesian cows from experimental research herds

      Nyman, S.; Johanssen, K.; de Koning, D. J.; Berry, Donagh; Veerkamp, Roel F.; Wall, E.; Beeglund, B. (Elsevier for American Dairy Science Association, 2014-11)
      The objective of this study was to quantify the genetic variation in normal and atypical progesterone profiles and investigate if this information could be useful in an improved genetic evaluation for fertility for dairy cows. The phenotypes derived from normal profiles included cycle length traits, including commencement of luteal activity (C-LA), interluteal interval, luteal phase length. and interovulatory interval. In total, 44,977 progesterone test-day records were available from 1,612 lactations on 1,122 primiparous and multiparous Holstein-Friesian cows from Ireland, the Netherlands, Sweden, and the United Kingdom. The atypical progesterone profiles studied were delayed cyclicity, prolonged luteal phase, and cessation of cyclicity. Variance components for the atypical progesterone profiles were estimated using a sire linear mixed model, whereas an animal linear mixed model was used to estimate variance components for the cycle length traits. Heritability was moderate for delayed cyclicity (0.24 ± 0.05) and C-LA (0.18 ± 0.04) but low for prolonged luteal phase (0.02 ± 0.04), luteal phase length (0.08 ± 0.05), interluteal interval (0.08 ± 0.14), and interovulatory interval (0.03 ± 0.04). No genetic variation was detected for cessation of cyclicity. Commencement of luteal activity, luteal phase length, and interovulatory interval were moderately to strongly genetically correlated with days from calving to first service (0.35 ± 0.12, 0.25 ± 0.14, and 0.76 ± 0.24, respectively). Delayed cyclicity and C-LA are traits that can be important in both genetic evaluations and management of fertility to detect (earlier) cows at risk of compromised fertility. Delayed cyclicity and C-LA were both strongly genetically correlated with milk yield in early lactation (0.57 ± 0.14 and 0.45 ± 0.09, respectively), which may imply deterioration in these traits with selection for greater milk yield without cognizance of other traits.
    • Genetic relationships among linear type traits, milk yield, body weight, fertility and somatic cell count in primiparous dairy cows

      Berry, Donagh; Buckley, Frank; Dillon, Pat; Evans, R. D.; Veerkamp, Roel F.; Allied Irish Bank; AI Managers Association; Holstein-Friesian Society of Great Britain and Ireland (Teagasc (Agriculture and Food Development Authority), Ireland, 2004)
      Phenotypic and genetic (co)variances among type traits, milk yield, body weight, fertility and somatic cell count were estimated. The data analysed included 3,058 primiparous spring-calving Holstein-Friesian cows from 80 farms throughout the south of Ireland. Heritability estimates for the type traits varied from 0.11 to 0.43. Genetic correlations among some type traits were very strong and may indicate the possibility of reducing the number of traits assessed on each animal; the genetic correlation between angularity and body condition score was –0.84. Genetic correlations between all type traits (except body condition score, udder depth and teat length) and milk yield were positive and ranged from 0.08 to 0.69. The possibility of selecting for body weight may be achievable within a national progeny-testing programme using type traits within a selection index. Moderate to strong genetic correlations existed between some type traits and the various fertility measures and somatic cell count indicating the opportunity of indirect selection for improved fertility and health of animals using type traits within a selection index; however, the standard errors of some of the genetic correlations were large and should thus be treated with caution. Genetically taller, wider, deeper, more angular cows with tighter, stronger, shallower udders were predisposed to have inferior pregnancy rates to first service and require more services.
    • Genome-wide associations for feed utilisation complex in primiparous Holstein–Friesian dairy cows from experimental research herds in four European countries

      Veerkamp, Roel F.; Coffey, Mike P.; Berry, Donagh; de Haas, Y.; Strandberg, E.; Bovenhuis, H.; Calus, M. P. L.; Wall, E.; European Union; KBBE-211708 (Cambridge University Press, 2012-06)
      Genome-wide association studies for difficult-to-measure traits are generally limited by the sample size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with the feed utilisation complex: fat and protein corrected milk yield (FPCM), dry matter intake (DMI), body condition score (BCS) and live-weight (LW). Phenotypic data and 37 590 single nucleotide polymorphisms (SNPs) were available on up to 1629 animals. Genetic parameters of the traits were estimated using a linear animal model with pedigree information, and univariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. The variation in the phenotypes explained by the SNPs on each chromosome was related to the size of the chromosome and was relatively consistent for each trait with the possible exceptions of BTA4 for BCS, BTA7, BTA13, BTA14, BTA18 for LW and BTA27 for DMI. For LW, BCS, DMI and FPCM, 266, 178, 206 and 254 SNPs had a Bayes factor .3, respectively. Olfactory genes and genes involved in the sensory smell process were overrepresented in a 500 kbp window around the significant SNPs. Potential candidate genes were involved with functions linked to insulin, epidermal growth factor and tryptophan.
    • Genome-wide associations for fertility traits in Holstein–Friesian dairy cows using data from experimental research herds in four European countries

      Berry, Donagh; Bastiaansen, J. W. M.; Veerkamp, Roel F.; Wijga, S.; Wall, E.; Berglund, B.; Calus, M. P. L.; European Union; KBBE-211708 (Cambridge University Press, 2012-01)
      Genome-wide association studies for difficult-to-measure traits are generally limited by the sample population size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with traditional measures of fertility, as well as a fertility phenotype derived from milk progesterone profiles. Traditional fertility measures investigated were days to first heat, days to first service, pregnancy rate to first service, number of services and calving interval (CI); post-partum interval to the commencement of luteal activity (CLA) was derived using routine milk progesterone assays. Phenotypic and genotypic data on 37 590 single nucleotide polymorphisms (SNPs) were available for up to 1570 primiparous cows. Genetic parameters were estimated using linear animal models, and univariate and bivariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. Heritability estimates of the traditional fertility traits varied from 0.03 to 0.16; the heritability for CLA was 0.13. The posterior quantitative trait locus (QTL) probabilities, across the genome, for the traditional fertility measures were all ,0.021. Posterior QTL probabilities of 0.060 and 0.045 were observed for CLA on SNPs each on chromosome 2 and chromosome 21, respectively, in the univariate analyses; these probabilities increased when CLA was included in the bivariate analyses with the traditional fertility traits. For example, in the bivariate analysis with CI, the posterior QTL probability of the two aforementioned SNPs were 0.662 and 0.123. Candidate genes in the vicinity of these SNPs are discussed. The results from this study suggest that the power of genome-wide association studies in cattle may be increased by sharing of data and also possibly by using physiological measures of the trait under investigation.
    • 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; Lovendahl, P.; Krattenmacher, N.; Miglior, F.; Weigel, K.; Spurlock, D.; et al. (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.
    • International genetic evaluations for feed intake in dairy cattle through the collation of data from multiple sources

      Berry, Donagh; Coffey, Mike P.; Pryce, J. E.; de Haas, Y.; Lovendahl, P.; Krattenmacher, N.; Crowley, J.J.; Wang, Z.; Spurlock, D.; Weigel, K.; et al. (Elsevier for American Dairy Science Association, 2014-04-13)
      Feed represents a large proportion of the variable costs in dairy production systems. The omission of feed intake measures explicitly from national dairy cow breeding objectives is predominantly due to a lack of information from which to make selection decisions. However, individual cow feed intake data are available in different countries, mostly from research or nucleus herds. None of these data sets are sufficiently large enough on their own to generate accurate genetic evaluations. In the current study, we collate data from 10 populations in 9 countries and estimate genetic parameters for dry matter intake (DMI). A total of 224,174 test-day records from 10,068 parity 1 to 5 records of 6,957 cows were available, as well as records from 1,784 growing heifers. Random regression models were fit to the lactating cow test-day records and predicted feed intake at 70 d postcalving was extracted from these fitted profiles. The random regression model included a fixed polynomial regression for each lactation separately, as well as herd-year-season of calving and experimental treatment as fixed effects; random effects fit in the model included individual animal deviation from the fixed regression for each parity as well as mean herd-specific deviations from the fixed regression. Predicted DMI at 70 d postcalving was used as the phenotype for the subsequent genetic analyses undertaken using an animal repeatability model. Heritability estimates of predicted cow feed intake 70 d postcalving was 0.34 across the entire data set and varied, within population, from 0.08 to 0.52. Repeatability of feed intake across lactations was 0.66. Heritability of feed intake in the growing heifers was 0.20 to 0.34 in the 2 populations with heifer data. The genetic correlation between feed intake in lactating cows and growing heifers was 0.67. A combined pedigree and genomic relationship matrix was used to improve linkages between populations for the estimation of genetic correlations of DMI in lactating cows; genotype information was available on 5,429 of the animals. Populations were categorized as North America, grazing, other low input, and high input European Union. Albeit associated with large standard errors, genetic correlation estimates for DMI between populations varied from 0.14 to 0.84 but were stronger (0.76 to 0.84) between the populations representative of high-input production systems. Genetic correlations with the grazing populations were weak to moderate, varying from 0.14 to 0.57. Genetic evaluations for DMI can be undertaken using data collated from international populations; however, genotype-by-environment interactions with grazing production systems need to be considered.
    • Merging and characterising phenotypic data on conventional and rare traits from dairy cattle experimental resources in three countries

      Banos, G.; Coffey, Mike P.; Veerkamp, Roel F.; Berry, Donagh; Wall, E.; European Union; RERAD; KBBE-211708 (Cambridge University Press, 2012-01)
      This study set out to demonstrate the feasibility of merging data from different experimental resource dairy populations for joint genetic analyses. Data from four experimental herds located in three different countries (Scotland, Ireland and the Netherlands) were used for this purpose. Animals were first lactation Holstein cows that participated in ongoing or previously completed selection and feeding experiments. Data included a total of 60 058 weekly records from 1630 cows across the four herds; number of cows per herd ranged from 90 to 563. Weekly records were extracted from the individual herd databases and included seven traits: milk, fat and protein yield, milk somatic cell count, liveweight, dry matter intake and energy intake. Missing records were predicted with the use of random regression models, so that at the end there were 44 weekly records, corresponding to the typical 305-day lactation, for each cow. A total of 23 different lactation traits were derived from these records: total milk, fat and protein yield, average fat and protein percentage, average fat-to-protein ratio, total dry matter and energy intake and average dry matter intake-to-milk yield ratio in lactation weeks 1 to 44 and 1 to 15; average milk somatic cell count in lactation weeks 1 to 15 and 16 to 44; average liveweight in lactation weeks 1 to 44; and average energy balance in lactation weeks 1 to 44 and 1 to 15. Data were subsequently merged across the four herds into a single dataset, which was analysed with mixed linear models. Genetic variance and heritability estimates were greater (P,0.05) than zero for all traits except for average milk somatic cell count in weeks 16 to 44. Proportion of total phenotypic variance due to genotype-by-environment (sire-by-herd) interaction was not different (P.0.05) from zero. When estimable, the genetic correlation between herds ranged from 0.85 to 0.99. Results suggested that merging experimental herd data into a single dataset is both feasible and sensible, despite potential differences in management and recording of the animals in the four herds. Merging experimental data will increase power of detection in a genetic analysis and augment the potential reference population in genome-wide association studies, especially of difficult-to-record traits.
    • Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

      Bouwman, Aniek C.; Hayes, Ben J.; Purfield, Deirdre C; Berry, Donagh; Chamberlain, Amanda J.; Hurtado Ponce, Carla; Sargolzaei, Mehdi; Schenkel, Flavio S.; Sahana, Goutam; Govignon-Gion, Armelle; et al. (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.