Review: Opportunities and challenges for the genetic selection of dairy calf disease traits.

Interest in dairy cow health continues to grow as we better understand health's relationship with production potential and animal welfare. Over the past decade, efforts have been made to incorporate health traits into national genetic evaluations. However, they have focused on the mature cow, with calf health largely being neglected. Diarrhoea and respiratory disease comprise the main illnesses with regard to calf health. Conventional methods to control calf disease involve early separation of calves from the dam and housing calves individually. However, public concern regarding these methods, and growing evidence that these methods may negatively impact calf development, mean the dairy industry may move away from these practices. Genetic selection may be a promising tool to address these major disease issues. In this review, we examined current literature for enhancing calf health through genetics and discussed alternative approaches to improve calf health via the use of epidemiological modelling approaches, and the potential of indirectly selecting for improved calf health through improving colostrum quality. Heritability estimates on the observed scale for diarrhoea ranged from 0.03 to 0.20, while for respiratory disease, estimates ranged from 0.02 to 0.24. The breadth in these ranges is due, at least in part, to differences in disease prevalence, population structure, data editing and models, as well as data collection practices, which should be all considered when comparing literature values. Incorporation of epidemiological theory into quantitative genetics provides an opportunity to better determine the level of genetic variation in disease traits, as it accounts for disease transmission among contemporaries. Colostrum intake is a major determinant of whether a calf develops either respiratory disease or diarrhoea. Colostrum traits have the advantage of being measured and reported on a continuous scale, which removes the issues classically associated with binary disease traits. Overall, genetic selection for improved calf health is feasible. However, to ensure the maximum response, first steps by any industry members should focus efforts on standardising recording practices and encouragement of uploading information to genetic evaluation centres through herd management software, as high-quality phenotypes are the backbone of any successful breeding programme.

Estimates of genetic parameters for rumination time, feed efficiency, and methane production traits in first lactation Holstein cows.

The large-scale recording of traits such as feed efficiency and methane emissions for use in genetic improvement programs is complex, costly, and time-consuming. Therefore, heritable traits that can be continuously recorded in dairy herds and are correlated to feed efficiency and methane emission traits could provide useful information for genetic evaluation. Rumination time has been suggested to be associated with feed efficiency, methane production (methane emission in g/day), and production traits at the phenotypic level. Therefore, the objective of this study was to investigate the genetic relationships among rumination time, feed efficiency, methane and production traits using 7,358 records from 656 first lactation Holstein cows. The estimated heritabilities were moderate for rumination time (0.45 ± 0.14), methane production (0.36 ± 0.12), milk yield (0.40 ± 0.08), fat yield (0.29 ± 0.06), protein yield (0.32 ± 0.07), and energy corrected milk (0.28 ± 0.07), while low and non-significant for feed efficiency (0.15 ± 0.07), which was defined as the residual of the multiple linear regression of DMI on ECM and MBW. A favorable negative genetic correlation was estimated between rumination time and methane production (-0.53 ± 0.24), while a positive favorable correlation was estimated between rumination time and energy corrected milk (0.49 ± 0.11). The estimated genetic correlation of rumination time with feed efficiency (-0.01 ± 0.17) was not significantly different from zero but showed a trend of a low correlation with dry matter intake (0.21 ± 0.13, P = 0.11). These results indicate that rumination time is genetically associated with methane production and milk production traits, but high standard errors indicate that further analyses should be conducted to verify these findings when more data for rumination time, methane production and feed efficiency become available.

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle.

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy-corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first-lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and the United States), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth-order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs.

Investigating the potential for genetic selection of dairy calf disease traits using management data.

Genetic selection could be a tool to help improve the health and welfare of calves; however, to date, there is limited research on the genetics of calfhood diseases. This study aimed to understand the current impact of calf diseases, by investigating incidence rates, estimating genetic parameters, and providing industry recommendations to improve calf disease recording practices on farms. Available calf disease data composed of 69,695 Holstein calf disease records for respiratory problems (RESP) and diarrhea (DIAR), from 62,361 calves collected on 1,617 Canadian dairy herds from 2006 to 2021. Single- and multiple-trait analysis using both a threshold and linear animal model for each trait were evaluated. Furthermore, each trait was analyzed using 2 scenarios with respect to minimum disease incidence threshold criterion (herd-year incidence of at least 1% and 5%) to highlight the effect of different filtering thresholds on selection potential. Observed scale heritability estimates for RESP and DIAR ranged from 0.02 to 0.07 across analyses, while estimated genetic correlations between the traits ranged from 0.50 to 0.62. Sires were compared based on their estimated breeding value and their diseased daughter incidence rates. On average, calves born to the bottom 10% of sires were 1.8 times more likely to develop RESP and 1.9 times to develop DIAR compared with daughters born to the top 10% of sires. Results from the current study are promising for the inclusion of both DIAR and RESP in Canadian genetic evaluations. However, for effective genetic evaluation, standardized approaches on data collection and industry outreach to highlight the importance of collecting and uploading this information to herd management software is required. In particular, it is important that the herd management software is accessible to the national milk recording system to allow for use in national genetic evaluation.

Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data.

Heat stress is a prominent issue in livestock production, even for intensively housed dairy herds in Canada. Production records and meteorological data can be combined to assess heat tolerance in dairy cattle. The overall aim of this study was to evaluate the possibility of genetic evaluation for heat tolerance in Canadian dairy cattle. The 2 specific objectives were (1) to estimate the genetic parameters for milk, fat, and protein yield for Holsteins while accounting for high environmental heat loads, and (2) to determine if a genotype-by-environment interaction causes reranking of top-ranked sires between environments with low and high heat loads. A repeatability test-day model with a heat stress function was used to evaluate the genetic merit for milk, fat, and protein yield under heat stress and at thermal comfort for first parity in 5 regions in Canada. The heat stress function for each trait was defined using a specific temperature-humidity index (THI) threshold. The purpose of this function was to quantify the level of heat stress that was experienced by the dairy cattle. The estimated genetic correlation between the general additive genetic effect and the additive effect on the slope of the change in the trait phenotype for milk, fat, and protein yield ranged from -0.16 to -0.30, -0.20 to -0.44, and -0.28 to -0.42, respectively. These negative correlations imply that there is an antagonistic relationship between sensitivity to heat stress and level of production. The heritabilities for milk, fat, and protein yield at 15 units above the THI threshold ranged from 0.15 to 0.27, 0.11 to 0.15, and 0.11 to 0.15, respectively. Finally, the rank correlations between the breeding values from a repeatability model with no heat stress effect and the breeding values accounting for heat stress for the 100 top-ranked bulls indicated possible interaction between milk production traits and THI, resulting in substantial reranking of the top-ranked sires in Canada, especially for milk yield. This is the first study to implement weather data from the NASA POWER database in a genetic evaluation of heat tolerance in dairy cattle. The NASA POWER database is a novel alternative meteorological resource that is potentially more reliable and consistent and with broader coverage than weather station data increasing the number of animals that could be included in a heat stress evaluation.

Phenotypic analysis of heat stress in Holsteins using test-day production records and NASA POWER meteorological data.

Weather station data and test-day production records can be combined to quantify the effects of heat stress on production traits in dairy cattle. However, meteorological data sets that are retrieved from ground-based weather stations can be limited by spatial and temporal data gaps. The National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASA POWER) database provides meteorological data over regions where surface measurements are sparse or nonexistent. The first aim of this study was to determine whether NASA POWER data are a viable alternative resource of weather data for studying heat stress in Canadian Holsteins. The results showed that average, minima, and maxima ambient temperature and dewpoint temperature as well as 4 different types of temperature-humidity index (THI) values from NASA POWER were highly correlated to the corresponding values from weather stations (regression R2 > 0.80). However, the NASA POWER values for the daily average, minima, and maxima wind speed and relative humidity were poorly correlated to the corresponding weather station values (regression R2 = 0.10 to 0.49). The second aim of this study was to quantify the influence of heat stress on Canadian dairy cattle. This was achieved by determining the THI values at which milk, protein, and fat yield started to decline due to heat stress as well as the rates of decline in these traits after the respective thresholds, using segmented polynomial regression models. This was completed for both primiparous and multiparous cows from 5 regions in Canada (Ontario, Quebec, British Columbia, the Prairies, and the Atlantic Maritime). The results showed that all production traits were negatively affected by heat stress and that the patterns of responses for milk, fat, and protein yields to increasing THI differed from each other. We found 3 THI thresholds for milk yield, 1 for fat yield, and 2 for protein yield. All thresholds marked a change in rate of decrease in production yield per unit THI, except for the first milk yield threshold, which marked a greater rate of increase. The first thresholds for milk yield ranged between 47 and 50, the second thresholds ranged between 61 and 69, and the third thresholds ranged between 72 and 76 THI units. The single THI threshold for fat yield ranged between 48 and 55 THI units. Finally, the first and second thresholds ranged between 58 and 62 THI units and 72 and 73 THI units for protein yield, respectively.

Erratum to "Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle" (JDS Commun. 3:114-119).

[This corrects the article DOI: 10.3168/jdsc.2021-0150.].

Evaluation of updated Feed Saved breeding values developed in Australian Holstein dairy cattle.

Although selection for increased milk production traits has led to a genetic increase in body weight (BW), the genetic gain in milk production has exceeded the gain in BW, so gross feed efficiency has improved. Nonetheless, greater gains may be possible by directly selecting for a measure of feed efficiency. Australia first introduced Feed Saved (FS) estimated breeding value (EBV) in 2015. Feed Saved combines residual feed intake (RFI) genomic EBV and maintenance requirements calculated from mature BW EBV. The FS EBV was designed to enable the selection of cows for reduced energy requirements with similar milk production. In this study, we used a reference population of 3,711 animals in a multivariate analysis including Australian heifers (AUSh), Australian cows (AUSc), and overseas cows (OVEc) to update the Australian EBV for lifetime RFI (i.e., a breeding value that incorporated RFI in growing and lactating cows) and to recalculate the FS EBV in Australian Holstein bulls (AUSb). The estimates of genomic heritabilities using univariate (only AUSc or AUSh) to trivariate (including the OVEc) analyses were similar. Genomic heritabilities for RFI were estimated as 0.18 for AUSc, 0.27 for OVEc, and 0.36 for AUSh. The genomic correlation for RFI between AUSc and AUSh was 0.47 and that between AUSc and OVEc was 0.94, but these estimates were associated with large standard errors (range: 0.18-0.28). The reliability of lifetime RFI (a component of FS) in the trivariate analysis (i.e., including OVEc) increased from 11% to 20% compared with the 2015 model and was greater, by 12%, than in a bivariate analysis in which the reference population included only AUSc and AUSh. By applying the prediction equation of the 2020 model, the average reliability of the FS EBV in 20,816 AUSb that were born between 2010 and 2020 improved from 33% to 43%. Previous selection strategies-that is, using the predecessor of the Balanced Performance Index (Australian Profit Ranking index) that did not include FS-have resulted in an unfavorable genetic trend in FS. However, this unfavorable trend has stabilized since 2015, when FS was included in the Balanced Performance Index, and is expected to move in a favorable direction with selection on Balanced Performance Index or the Health Weighted Index. Doubling the reference population, particularly by incorporating international data for feed efficiency, has improved the reliability of the FS EBV. This could lead to increased genetic gain for feed efficiency in the Australian industry.

Machine learning classification of breeding protocol descriptions from Canadian Holsteins.

Dairy farmers are motivated to ensure cows become pregnant in an optimal and timely manner. Although timed artificial insemination (TAI) is a successful management tool in dairy cattle, it masks an animal's innate fertility performance, likely reducing the accuracy of genetic evaluations for fertility traits. Therefore, separating fertility traits based on the recorded management technique involved in the breeding process or adding the breeding protocol as an effect to the model can be viable approaches to address the potential bias caused by such management decisions. Nevertheless, there is a lack of specificity and uniformity in the recording of breeding protocol descriptions by dairy farmers. Therefore, this study investigated the use of 8 supervised machine learning algorithms to classify 1,835 unique breeding protocol descriptions from 981 herds into the following 2 classes: TAI or other than TAI. Our results showed that models that used a stacking classifier algorithm had the highest Matthews correlation coefficient (0.94 ± 0.04, mean ± SD) and maximized precision and recall (F1-score = 0.96 ± 0.03) on test data. Nonetheless, their F1-scores on test data were not different from 5 out of the other 7 algorithms considered. Altogether, results presented herein suggest machine learning algorithms can be used to produce robust models that correctly identify TAI protocols from dairy cattle breeding records, thus opening the opportunity for unbiased genetic evaluation of animals based on their natural fertility.

Genome-wide association study using haplotype libraries and repeated-measures model to identify candidate genomic regions for stillbirth in Holstein cattle.

Reduced fertility is one of the main causes of economic losses on dairy farms, resulting in economic losses estimated at $938 per stillbirth case in Holstein herds. The identification of genomic regions associated with stillbirth could help to develop better management and breeding strategies aimed to reduce the frequency of undesirable gestation outcomes. Here, 10,570 cows and 50,541 birth records were used to perform a haplotype-based GWAS. A total of 41 significantly associated pseudo-SNPs (haplotypes within haplotype blocks converted to a binary classification) were identified after Bonferroni adjustment for multiple tests. A total of 117 positional candidate genes were annotated within or close (in a 200-kb interval) to significant pseudo-SNPs (haplotype blocks). The guilt-by-association functional prioritization identified 31 potential functional candidate genes for reproductive performance out of the 117 positional candidate genes annotated. These genes play crucial roles in biological processes associated with pregnancy persistence, fetus development, immune response, among others. These results helped us to better understand the genetic basis of stillbirth in dairy cattle and may be useful for the prediction of stillbirth in Holstein cattle, helping to reduce the related economic losses caused by this phenotype.

Genome-wide association study and pathway analysis for carcass fatness in Nellore cattle measured by ultrasound.

Identifying genes or genomic regions influencing carcass-quality traits such as fatness (FTN) is essential to optimize the genetic selection processes in beef cattle. The aim of this study was to identify genomic regions associated with FTN in Nellore cattle as well as to elucidate the metabolic pathways related to the phenotypic expression. Ultrasound-based measurements of FTN were collected in 11 750 animals, with 39 903 animals in the pedigree file. Additionally, 1440 animals were genotyped using the GGP-indicus 35K SNP panel, which contained 33 623 SNPs after quality control. Twenty genes related to FTN were found on 11 chromosomes, explaining 12.96% of the total additive genetic variance. Gene ontology revealed seven genes: NR1L2, PKD2, GSK3ß, EXT1, RAD51B, SORCS1 and DPH6, associated with important processes related to FTN. In addition, novel candidate genes (MAATS1, LYPD1, CDK5RAP2, RAD51B, c13H2Oorf96 and TRAPPC11) were detected and could provide further knowledge to uncover genetic regions associated to carcass fatness in beef cattle.

Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle.

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.

Associations between feed efficiency and aspects of lactation curves in primiparous Holstein dairy cattle.

Genetic selection for improved feed efficiency in dairy cattle has received renewed attention over the last decade to address the needs of a growing global population. As milk yield is a critical component of feed efficiency metrics in dairy animals, our objective was to evaluate the associations between feed efficiency in primiparous Holstein cattle and parameters of a mathematical model describing individual lactation curves. The Dijkstra lactation curve model was fit to individual lactation records from 34 Holstein heifers with previously estimated measures of feed efficiency. We found that the optimal fit of the Dijkstra model was achieved using daily milk yield records up to 21 d in milk to capture the rise to peak milk yield and using monthly dairy herd improvement records for the remainder of lactation to accurately characterize lactation persistency. In the period of lactation before peak milk yield, improved feed efficiency was associated with a faster increase in daily milk yield over a shorter period of time at the expense of increased mobilization of body reserves; this serves to reinforce the concept that dairy cattle are primarily capital breeders versus income breeders. Feed efficiency in the period following peak lactation, as measured by gross feed efficiency, return over feed costs, and net energy efficiency of lactation, was positively associated with higher peak milk yield. The findings in early lactation suggest that estimates of feed efficiency could be improved by evaluating feed efficiency relative to conception, rather than parturition and lactation, to better account for the energy stored and released from body reserves in capital breeding.

Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins.

Genetic improvement is a crucial tool to deal with the increasing demand for high quality, sustainably produced dairy. Breeding programs are based on genetic parameters, such as heritability and genetic correlations, for economically important traits in a population. In this study, we estimated population genetic parameters and genetic trends for 67 traits evaluated on heifers and first-lactation Canadian Holstein cows. The data consisted of approximately 500,000 records with pedigree information collected from 1980 to 2019. Genetic parameters were estimated using bivariate linear animal models under a Bayesian approach. Analyses for the 67 traits resulted in 2,211 bivariate combinations, from which the estimated genetic parameters are reported here. The most highly heritable traits were fat percent (0.66) and protein percent (0.69), followed by stature (0.47). Lowest heritabilities (0.01) were observed for disease-related traits, such as lameness and toe ulcer, and calf survival. The genetic correlations between gestation length, calf size, and calving ease measured on both heifer and cows were close to unity. On the other hand, traits such as body condition score and pin width, cystic ovaries and sole ulcer, rear teat placement, and toe ulcer were genetically unrelated. This study reports genetic parameters that have not been previously published for Canadian Holstein cows, and provides updates of those previously estimated. These estimates are useful for building new indexes, updating existing selection indexes, and for predicting correlated responses due to inclusion of novel traits in the breeding programs.

Genetic parameters for methane emission traits in Australian dairy cows.

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF6 tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration.

Discovering lethal alleles across the turkey genome using a transmission ratio distortion approach.

Deviation from Mendelian inheritance expectations (transmission ratio distortion, TRD) has been observed in several species, including the mouse and humans. In this study, TRD was characterized in the turkey genome using both allelic (specific- and unspecific-parent TRD) and genotypic (additive- and dominance-TRD) parameterizations within a Bayesian framework. In this study, we evaluated TRD for 23 243 genotyped Turkeys across 56 393 autosomal SNPs. The analyses included 500 sires, 2013 dams and 11 047 offspring (trios). Three different haplotype sliding windows of 4, 10 and 20 SNPs were used across the autosomal chromosomes. Based on the genotypic parameterizations, 14 haplotypes showed additive and dominance TRD effects highlighting regions with a recessive TRD pattern. In contrast, the allelic model uncovered 12 haplotype alleles with the allelic TRD pattern which showed an underrepresentation of heterozygous offspring in addition to the absence of homozygous animals. For regions with the allelic pattern, only one particular region showed a parent-specific TRD where the penetrance was high via the dam, but low via the sire. The gene set analysis uncovered several gene ontology functional terms, Reactome pathways and several Medical Subject Headings that showed significant enrichment of genes associated with TRD. Many of these gene ontology functional terms (e.g. mitotic spindle assembly checkpoint, DRM complex and Aneuploidy), Reactome pathways (e.g. Mismatch repair) and Medical Subject Headings (e.g. Adenosine monophosphate) are known to be related to fertility, embryo development and lethality. The results of this study revealed potential novel candidate lethal haplotypes, functional terms and pathways that may enhance breeding programs in Turkeys through reducing mortality and improving reproduction rate.

Genomic analyses for predicted milk fatty acid composition throughout lactation in North American Holstein cattle.

Milk fat composition has important implications in the nutritional and processing properties of milk. Additionally, milk fat composition is associated with cow physiological and health status. The main objectives of this study were (1) to estimate genetic parameters for 5 milk fatty acid (FA) groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted from milk infrared spectra using a large data set; (2) to predict genomic breeding values using a longitudinal single-step genomic BLUP approach; and (3) to conduct a single-step GWAS aiming to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA, and consequently, to understand the underlying biology of these traits. We used 629,769 test-day records of 201,465 first-parity Holstein cows from 6,105 herds. A total of 8,865 genotyped (Illumina BovineSNP50K BeadChip, Illumina, San Diego, CA) animals were considered for the genomic analyses. The average daily heritability ranged from 0.24 (unsaturated FA) to 0.47 (medium-chain and saturated FA). The reliability of the genomic breeding values ranged from 0.56 (long-chain fatty acid) to 0.74 (medium-chain fatty acid) when using the default τ and ω scaling parameters, whereas it ranged from 0.58 (long-chain fatty acid) to 0.73 (short-chain fatty acid) when using the optimal τ and ω values (i.e., τ = 1.5 and ω = 0.6), as defined in a previous study in the same population. Relevant chromosomal regions were identified in Bos taurus autosomes 5 and 14. The proportion of the variance explained by 20 adjacent single nucleotide polymorphisms ranged from 0.71% (saturated FA) to 15.12% (long-chain FA). Important candidate genes and pathways were also identified. In summary, our results contribute to a better understanding of the genetic architecture of predicted milk FA in dairy cattle and reinforce the relevance of using genomic information for genetic analyses of these traits.

Short communication: Time-dependent genetic parameters and single-step genome-wide association analyses for predicted milk fatty acid composition in Ayrshire and Jersey dairy cattle.

Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS, FGF10, and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle.

Symposium review: Multiple-trait single-step genomic evaluation for hoof health.

Hoof lesions represent an important issue in modern dairy herds, with reported prevalence in different countries ranging from 40 to 70%. This high prevalence of hoof lesions has both economic and social consequences, resulting in increased labor expenses and decreasing animal production, longevity, reproduction, health, and welfare. Therefore, a key goal of dairy herds is to reduce the incidence of hoof lesions, which can be achieved both by improving management practices and through genetic selection. The Canadian dairy industry has recently released a hoof health sub-index. This national genetic evaluation program for hoof health was achieved by creating a centralized data collection system that routinely transfers data recorded by hoof trimmers into a coherent and sustainable national database. The 8 most prevalent lesions (digital dermatitis, interdigital dermatitis, interdigital hyperplasia, heel horn erosion, sole hemorrhage, sole ulcer, toe ulcer, and white line lesion) in Canada are analyzed with a multiple-trait model using a single-step genomic BLUP method. Estimated genomic breeding values for each lesion are combined into a sub-index according to their economic value and prevalence. In addition, data recorded within this system were used to create an interactive management report for dairy producers by Canadian DHI, including the prevalence of lesions on farm, their trends over time, and benchmarks with provincial and national averages.

The dynamic behavior of feed efficiency in primiparous dairy cattle.

A variety of measures are currently used to evaluate feed efficiency in livestock, with some of the most popular being the linear regression of nutrient intake on the various energy sinks of the cohort being evaluated. The adoption of novel on-farm technologies has greatly increased the breadth and depth of data being collected on a daily basis, which creates the opportunity for the implementation of more advanced feed efficiency models. The objectives of the current study were to leverage data collected using high-throughput biometric technologies to evaluate changes of early-lactation feed efficiency on a daily basis and to develop a novel measure of feed efficiency based on the NRC net energy model. Daily records of nutrient intake, fat- and protein-corrected milk yield, body weight, and body condition score were used to model 7 different indices of feed efficiency (gross feed efficiency, return over feed costs, residual feed intake, residual net energy intake, and net energy efficiencies of lactation, maintenance, and body reserve flux) in primiparous Holstein heifers (n = 40) from 0 to 150 d in milk. We observed that feed efficiency was dynamic and fluctuated over the course of the experimental period regardless of the efficiency measure used, but most measures followed similar trends in changes of efficiency on a day-to-day basis. Of the measures evaluated, return over feed costs would be most suited for management purposes due to practicality and simplicity, whereas other measures, such as the efficiency of net energy flux to and from body reserves, present potential targets for inclusion in breeding goals. Net energy efficiency of lactation was estimated to have higher repeatability compared with residual feed or energy intake, which may reduce the time required to estimate whole-lactation efficiency. Because decreased net energy balance was strongly correlated with increased efficiency for all indices evaluated, future work investigating the associations of feed efficiency with the magnitude and duration of negative energy balance is warranted.