F. Malchiodi

Genetic analysis of superovulatory response of Holstein cows in Canada

Superovulation of dairy cattle is frequently used in Canada. The cost of this protocol is high, and so is the variability of the outcome. Knowing the superovulatory potential of a donor cow could influence the breeders decision to superovulate it or not. The main objective of this study was to perform a genetic analysis for superovulatory response of Holstein cows in Canada using data recorded by Holstein Canada, and to investigate if these data could be used for genetic evaluation. Data contained the total number of embryos and the number of viable embryos from every successful flushing performed across Canada. After editing, 137,446 records of superovulation performed between 1992 and 2014 were analyzed. A univariate repeatability animal model analysis was performed for both total number of embryos and number of viable embryos. Because both data and residuals did not follow a normal distribution, records were subject to either logarithmic or Anscombe transformation. Using logarithmic transformation, heritability estimates (SE) of 0.15 (0.01) and 0.14 (0.01) were found for total number of embryos and number of viable embryos, respectively. Using Anscombe transformation, heritability estimates (SE) of 0.17 (0.01) and 0.14 (0.01) were found for total number of embryos and number of viable embryos, respectively. The genetic correlation between the 2 traits was estimated at 0.97 using logarithmic transformation and 0.95 using Anscombe transformation. Breeding values were estimated for 54,463 cows, and 3,513 sires. Only estimated breeding values of sires having a reliability higher than 40% were considered for estimated breeding values correlations with other routinely evaluated traits. The results showed that selection for a higher response to superovulation would lead to a slight decrease in milk production, but an improvement for functional traits, including all reproduction traits. In all cases, the estimated correlations are either low or modest. We conclude that genetic selection for increased superovulatory response in donors is possible; daughters of sires with high estimated breeding values for superovulatory response will tend to yield more embryos, whereas the additive effect of service sire seems not to contribute to the variability of the 2 superovulation traits and was not significantly correlated with the additive effect of the donor.

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.

Genetic analysis of groups of mid-infrared predicted fatty acids in milk

The objective of this study was to investigate genetic variability of mid-infrared predicted fatty acid groups in Canadian Holstein cattle. Genetic parameters were estimated for 5 groups of fatty acids: short-chain (4 to 10 carbons), medium-chain (11 to 16 carbons), long-chain (17 to 22 carbons), saturated, and unsaturated fatty acids. The data set included 49,127 test-day records from 10,029 first-lactation Holstein cows in 810 herds. The random regression animal test-day model included days in milk, herd-test date, and age-season of calving (polynomial regression) as fixed effects, herd-year of calving, animal additive genetic effect, and permanent environment effects as random polynomial regressions, and random residual effect. Legendre polynomials of the third degree were selected for the fixed regression for age-season of calving effect and Legendre polynomials of the fourth degree were selected for the random regression for animal additive genetic, permanent environment, and herd-year effect. The average daily heritability over the lactation for the medium-chain fatty acid group (0.32) was higher than for the short-chain (0.24) and long-chain (0.23) fatty acid groups. The average daily heritability for the saturated fatty acid group (0.33) was greater than for the unsaturated fatty acid group (0.21). Estimated average daily genetic correlations were positive among all fatty acid groups and ranged from moderate to high (0.63-0.96). The genetic correlations illustrated similarities and differences in their origin and the makeup of the groupings based on chain length and saturation. These results provide evidence for the existence of genetic variation in mid-infrared predicted fatty acid groups, and the possibility of improving milk fatty acid profile through genetic selection in Canadian dairy cattle.

Prediction of milk fatty acid content with mid-infrared spectroscopy in Canadian dairy cattle using differently distributed model development sets

The fatty acid profile of milk is a prevailing issue due to the potential negative or positive effects of different fatty acids to human health and nutrition. Mid-infrared spectroscopy can be used to obtain predictions of otherwise costly fatty acid phenotypes in a widespread and rapid manner. The objective of this study was to evaluate the prediction of fatty acid content for the Canadian dairy cattle population from mid-infrared spectral data and to compare the results produced by altering the partial least squares (PLS) model development set used. The PLS model development sets used to develop the predictions were reference fatty acids expressed as (1) grams per 100 g of fatty acid, (2) grams per 100 g of milk, (3) the natural logarithmic transform of grams per 100 g of milk, and (4) subsets of samples randomly selected by removing excess records around the mean to present a more uniform distribution, repeated 10 times. Gas chromatography measured fatty acid concentration and spectral data for 2,023 milk samples of 373 cows from 4 breeds and 44 herds were used in the model development. The coefficient of determination of cross-validation (Rcv2) increased when fatty acids were expressed on a per 100 g of milk basis compared with on a per 100 g of fat basis for all examined fatty acids. The logarithmic transformation used to create a more Gaussian distribution in the development set had little effect on the prediction accuracy. The individual fatty acids C12:0, C14:0, C16:0, C18:0, C18:1n-9 cis, and saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain fatty acid groups had (Rcv2) greater than 0.70. When model development was performed with subsets of the original samples, slight increases in (Rcv2) values were observed for the majority of fatty acids. The difference in (Rcv2) between the top- and bottom-performing prediction equation across the different subsets for a single predicted fatty acid was on average 0.055 depending on which samples were randomly selected to be used in the PLS model development set. Predictions for fatty acids with high accuracies can be used to monitor fatty acid contents for cows in milk recording programs and possibly for genetic evaluation.

Genetic parameters for hoof health traits estimated with linear and threshold models using alternative cohorts

A national genetic evaluation program for hoof health could be achieved by using hoof lesion data collected directly by hoof trimmers. However, not all cows in the herds during the trimming period are always presented to the hoof trimmer. This preselection process may not be completely random, leading to erroneous estimations of the prevalence of hoof lesions in the herd and inaccuracies in the genetic evaluation. The main objective of this study was to estimate genetic parameters for individual hoof lesions in Canadian Holsteins by using an alternative cohort to consider all cows in the herd during the period of the hoof trimming sessions, including those that were not examined by the trimmer over the entire lactation. A second objective was to compare the estimated heritabilities and breeding values for resistance to hoof lesions obtained with threshold and linear models. Data were recorded by 23 hoof trimmers serving 521 herds located in Alberta, British Columbia, and Ontario. A total of 73,559 hoof-trimming records from 53,654 cows were collected between 2009 and 2012. Hoof lesions included in the analysis were digital dermatitis, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, and white line disease. All variables were analyzed as binary traits, as the presence or the absence of the lesions, using a threshold and a linear animal model. Two different cohorts were created: Cohort 1, which included only cows presented to hoof trimmers, and Cohort 2, which included all cows present in the herd at the time of hoof trimmer visit. Using a threshold model, heritabilities on the observed scale ranged from 0.01 to 0.08 for Cohort 1 and from 0.01 to 0.06 for Cohort 2. Heritabilities estimated with the linear model ranged from 0.01 to 0.07 for Cohort 1 and from 0.01 to 0.05 for Cohort 2. Despite a low heritability, the distribution of the sire breeding values showed large and exploitable variation among sires. Higher breeding values for hoof lesion resistance corresponded to sires with a higher prevalence of healthy daughters. The rank correlations between estimated breeding values ranged from 0.96 to 0.99 when predicted using either one of the 2 cohorts and from 0.94 to 0.99 when predicted using either a threshold or a linear model.

Variation in fat globule size in bovine milk and its prediction using mid-infrared spectroscopy

The objectives of this study were to investigate the sources of variation in milk fat globule (MFG) size in bovine milk and its prediction using mid-infrared (MIR) spectroscopy. Mean MFG size was measured in 2,076 milk samples from 399 Ayrshire, Brown Swiss, Holstein, and Jersey cows, and expressed as volume moment mean (D[4,3]) and surface moment mean (D[3,2]). The mid-infrared spectra of the samples and milk performance data were also recorded during routine milk recording and testing. The effects of breed, herd nested within breed, days in milk, season, milking period, age at calving, parity, and individual animal on the variation observed in MFG size were investigated. Breed, herd nested within breed, days in milk, season, and milking period significantly affected mean MFG size. Milk fat globule size was the largest at the beginning of lactation and subsequently decreased. Milk samples with the smallest MFG on average came from Holstein cows, and those with the largest were from Jersey and Brown Swiss cows. Partial least squares regression was used to predict MFG size from MIR spectra of samples with a calibration data set containing 2,034 and 2,032 samples for D[4,3] and D[3,2], respectively. Coefficients of determination of cross validation for D[4,3] and D[3,2] prediction models were 0.51 and 0.54, respectively. The associated ratio of performance deviation values were 1.43 and 1.48 for D[4,3] and D[3,2], respectively. With these models, individual mean MFG size could not be accurately predicted, but results may be sufficient to screen samples for having either small or large MFG on average. Significant but low correlations of D[4,3] and D[3,2] with milk fat yield were estimated (0.16 and 0.21, respectively). Significant and moderate Pearson correlation coefficients for fat percent with D[4,3] and D[3,2] were assessed (0.34 and 0.36, respectively). This correlation was greater between milk fat percentage and predicted MFG size than with measured MFG size with coefficients of 0.47 and 0.49 for D[4,3] and D[3,2], respectively. The MIR prediction equations are potentially overusing the correlation between fat and MFG size and exploiting the strong relationship between the MIR spectra and total milk fat. However, the predictions of MFG size are able to determine variation in mean globule size beyond what would be achieved just by looking at the correlation with fat production.

Genome-wide association study and in silico functional analysis of the number of embryos produced by Holstein donors

Superovulation or ovum pick-up and in vitro fertilization are technologies used to produce an increased number of embryos from elite females. Embryo production traits have been shown to be heritable, but the genes that cause this variability have not yet been assessed. The main objectives of this study were to perform a genome-wide association study (GWAS) to find single nucleotide polymorphisms (SNP) associated with embryo production traits and to identify candidate genes affecting the number of embryos produced by Holstein donors in Canada that may provide insight into the regulation of embryo production. Breeding values were estimated and de-regressed for all donors and sires using a data set of 150,971 records of superovulation or ovum pick-up and in vitro fertilization. A total of 11,607 animals were genotyped, but of that number only 5,118 were genotyped with at least a 50K SNP panel and had a de-regressed estimated breeding value reliability of at least 10%. For the GWAS, 606,406 imputed SNP on 29 autosomal chromosomes were considered after applying quality control measures. A single-SNP univariate mixed linear animal model was used to perform the GWAS, and a 5% false discovery rate was applied to adjust for multiple testing. We found 36 and 14 significant SNP associated with the total number of embryos and the number of viable embryos, respectively, with most of them located on chromosome 11. Using these significant SNP, positional genes located within 10,000 bp upstream and downstream of the SNP were retrieved. Thirteen genes were harboring or near the significant SNP for the total number of embryos, 4 of them also being near the significant SNP for viable embryos. Some of these genes (CRB2, DENND1A, MAD1L1, NDUFA8, PTGS1) could be considered as potential positional candidate genes related to the number of embryos produced by a donor. This list will need to be validated in an independent population to confirm the role of the genes for embryo production.

Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from -0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future.

Genetic analysis for quality of frozen embryos produced by Holstein cattle donors in Canada

The number of embryos produced by Holstein donors has been shown to be heritable, so it could be possible to genetically select for this trait to improve the efficiency of the assisted reproductive technology (ART) in dairy cattle. Another important parameter to consider for achieving good results from ART is embryo quality because embryos of good quality have more chance of producing live offspring. The possibility of using genetic selection for increasing the quality of embryo produced from ART has yet to be assessed. The objective of this study was, therefore, to perform a genetic analysis of embryo quality of Holstein donors in Canada using data recorded by Holstein Canada. The data set used was missing quality score data for embryos transferred fresh into a recipient, so the analyses were only performed for frozen embryos. With most traits in the Canadian dairy industry being evaluated with linear models, embryo quality was also evaluated with this class of models. However, considering the categorical nature of embryo quality, a threshold model was also evaluated. Embryo quality data were analyzed with either a univariate linear animal model or a univariate binomial threshold animal model. Genetic parameters estimated from the different models were comparable. A low heritability was found for the donor (0.04 ± <0.01) and the service sire (0.02 ± <0.01), but the repeatability estimate for the donor was higher (0.17), indicating that it was worthwhile to use a repeated records model. Overall, considering the low genetic parameters estimated, slow genetic progress is expected for the quality of frozen embryos produced by Canadian Holstein donors. Rank correlations were calculated between breeding values estimated from different models. High correlations were found between all models, indicating that no substantial re-ranking of the animals is expected from the different models. So, even though a threshold model is better suited for the analysis of categorical data, a linear model could be used for the analysis of embryo quality because it is less computationally demanding.

Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits

The objective of this research was to estimate the genetic correlations between milk mid-infrared-predicted fatty acid groups and production traits in first-parity Canadian Holsteins. Contents of short-chain, medium-chain, long-chain, saturated, and unsaturated fatty acid groupings in milk samples can be predicted using mid-infrared spectral data for cows enrolled in milk recording programs. Predicted fatty acid group contents were obtained for 49,127 test-day milk samples from 10,029 first-parity Holstein cows in 810 herds. Milk yield, fat and protein yield, fat and protein percentage, fat-to-protein ratio, and somatic cell score were also available for these test days. Genetic parameters were estimated for the fatty acid groups and production traits using multiple-trait random regression test day models by Bayesian methods via Gibbs sampling. Three separate 8- or 9-trait analyses were performed, including the 5 fatty acid groups with different combinations of the production traits. Posterior standard deviations ranged from <0.001 to 0.01. Average daily genetic correlations were negative and similar to each other for the fatty acid groups with milk yield (-0.62 to -0.59) and with protein yield (-0.32 to -0.25). Weak and positive average daily genetic correlations were found between somatic cell score and the fatty acid groups (from 0.25 to 0.36). Stronger genetic correlations with fat yield, fat and protein percentage, and fat-to-protein ratio were found with medium-chain and saturated fatty acid groups compared with those with long-chain and unsaturated fatty acid groups. Genetic correlations were very strong between the fatty acid groups and fat percentage, ranging between 0.88 for unsaturated and 0.99 for saturated fatty acids. Daily genetic correlations from 5 to 305 d in milk with milk, protein yield and percentage, and somatic cell score traits showed similar patterns for all fatty acid groups. The daily genetic correlations with fat yield at the beginning of lactation were decreasing for long-chain and unsaturated fatty acid groups and increasing for short-chain fatty acids. Genetic correlations between fat percentage and fatty acids were increasing at the beginning of lactation for short- and medium-chain and saturated fatty acids, but slightly decreasing for long-chain and unsaturated fatty acid groups. These results can be used in defining fatty acid traits and breeding objectives.