Effects of feeding rumen-protected lysine during the postpartum period on performance and amino acid profile in dairy cows: A meta-analysis.

Lysine is one of the limiting AA in the diets of dairy cows and is typically fed as rumen-protected Lys (RPL). We hypothesized that supplementation of RPL during the postpartum period would improve the productive performance in dairy cows. Objectives were to use meta-analytic methods to explore the effects of feeding RPL on performance and blood AA profile in lactating dairy cows. An additional objective was to identify an optimal concentration (%) of Lys in MP (LYSMP) and determine if responses to LYSMP were associated with the concentration (%) of Met in MP (METMP). The literature was systematically reviewed, and 13 experiments, comprising 40 treatment means and 594 lactating cows, were included in the meta-analysis. All experiments had a nonsupplemental control (CON; n = 17 treatment means), or a group supplemented with RPL (n = 23 treatment means). Cows supplemented with RPL were supplied additionally with a mean (±standard deviation) 19.3 ± 10.3 g/d metabolizable Lys (5.1-40.6 g/d). Meta-analytical statistics were used to estimate the weighted mean difference in STATA. Mixed models were fitted to the data to investigate the linear and quadratic effects of LYSMP, METMP, and interactions between LYSMP and METMP. All models included the random effect of experiment and weighting by the inverse of the SE of the means squared. Cows that began receiving RPL in early lactation (≤90 DIM) or for an extended duration (≥70 DIM) produced 1.51 kg/d more milk compared with CON cows. Increasing digestible LYSMP from 6.5% to 8.5% linearly increased yields of milk, FCM, ECM, and milk fat by 1.8, 2.5, 2.4, and 0.10 kg/d, respectively, and tended to increase milk protein yield and body weight gain by 0.07 and 0.09 kg/d, respectively, without a concurrent increase in DMI. Interactions between the linear effects of LYSMP and METMP were observed for FCM/DMI or ECM/DMI. In a diet with low METMP (e.g., 1.82% of MP), a digestible supply of 7.40% LYSMP would result in 1.46 and 1.47 kg/kg FCM/DMI or ECM/DMI, respectively; however, with high digestible METMP (e.g., 2.91% of MP), supplying 7.40% of digestible LYSMP would result in 1.68 and 1.62 kg/kg FCM/DMI or ECM/DMI, respectively. Increasing digestible LYSMP from 6.5% to 8.5% linearly increased blood concentrations of Lys by 16.6 µM, whereas blood concentrations of Met and Ala decreased by 4.6 and 6.0 µM, respectively. Nevertheless, an interaction was also observed between LYSMP and METMP for blood concentrations of total EAA because as METMP increased, the positive response to LYSMP on total EAA was also increased, suggesting a competitive mobilization of AA and their utilization in various body tissues. Only 4 out of the 13 experiments in this meta-analysis involved primiparous cows; thus, insufficient data were available to understand the role of supplemental RPL in primiparous cows. Collectively, feeding RPL improved productive performance, and the increments were maximized up to 9.25% of LYSMP in multiparous dairy cows.

Endometrial responsiveness to interferon-tau and its association with subsequent reproductive performance in dairy heifers.

Our objectives were to evaluate the endometrial responsiveness of dairy heifers to an intrauterine infusion of recombinant bovine interferon-tau (rbIFN-τ) and to associate endometrial responses to rbIFN-τ with subsequent reproductive performance. In Experiments 1 and 2, cyclic heifers were enrolled in a 5-d CIDR Cosynch program for estrous synchronization, and blood sampling and ultrasonography examinations were performed on d 0, 4, 7, 11, and 14 of the estrous cycle. In Experiment 1, heifers were randomly assigned to receive an intrauterine infusion containing 2 µg of rbIFN-τ (rbIFN-τ = 19) or saline (CTRL = 19) into the uterine horn ipsilateral to the corpus luteum (CL) on d 14 of the estrous cycle. Six hours after the infusion, the infused uterine horn was flushed for sampling of the uterine luminal fluid (ULF) for analyses of composition, and the endometrium was biopsied for transcriptomics. In Experiment 2, 100 heifers received an intrauterine infusion of rbIFN-τ, and the same procedures for uterine sample collection described in Experiment 1 were performed. After the intrauterine test, heifers were enrolled in a breeding program and classified as highly fertile (HF; pregnant at first AI) or subfertile (SF; not pregnant at first AI). Statistical analyses were performed using linear regression models, which included the effects of treatment (Experiment 1: CTRL vs. rbIFN-τ) or fertility group (Experiment 2: HF vs. SF) and block of samples. Intrauterine infusion of rbIFN-τ increased the expression of classical interferon-stimulated genes in the endometrium (e.g., ISG15, MX1, OAS2, IRF9, and USP18), and an antiviral response was predicted to be the main downstream effect of the transcriptome changes. In addition, rbIFN-τ increased the abundance of cholesterol, glycerol, and the overall concentration of oxylipins in the ULF. Analysis of endometrial transcriptome between HF and SF heifers revealed important differences in the expression of proteins associated with cell signaling, metabolism, attachment, and migration, with a large representation of genes encoding extracellular matrix proteins. In general, differently expressed genes were expected to be downregulated by IFN-τ but seemed to fail to be downregulated in SF heifers, resulting in higher expression in SF compared with HF heifers. Subfertile heifers had lower concentrations of glycerol and an altered profile of oxylipins in the ULF, with lower abundance of oxylipins derived from arachidonic acid and dihomo-γ-linolenic acid, and greater abundance of oxylipins derived from linoleic acid. Measurements of ovarian function did not differ between groups and, therefore, did not influence the observed results in uterine biology. In conclusion, the endometrial responsiveness to IFN-τ is variable among individuals and associated with subsequent fertility of heifers, indicating that communication between conceptus and endometrium is critical for the uterine receptivity and survival of pregnancy.

Assessing different cross-validation schemes for predicting novel traits using sensor data: an application to dry matter intake and residual feed intake using milk spectral data.

Feed efficiency is important for economic profitability of dairy farms; however, recording daily dry matter intakes (DMI) is expensive. Our objective was to investigate the potential use of milk mid-infrared (MIR) spectral data to predict proxy phenotypes for DMI based on different cross-validation schemes. We were specifically interested in comparisons between a model that included only MIR data (Model M1), a model that incorporated different energy sink predictors, such as body weight, body weight change, and milk energy (Model M2), and an extended model that incorporated both energy sinks and MIR data (Model M3). Models M2 and M3 also included various cow level variables (stage of lactation, age at calving, parity) such that any improvement in model performance from M2 to M3, whether through a smaller root mean squared error (RMSE) or a greater squared predictive correlation (R2), could indicate a potential benefit of MIR to predict residual feed intake. The data used in our study originated from a multi-institutional project on the genetics of feed efficiency in US Holsteins. Analyses were conducted on 2 different trait definitions based on different period lengths: averaged across weeks vs. averaged across 28-d. Specifically, there were 19,942 weekly records on 1,812 cows across 46 experiments or cohorts and 3,724 28-d records on 1,700 cows across 43 different cohorts. The cross-validation analyses involved 3 different k-fold schemes. First, a 10-fold cow-independent cross-validation was conducted whereby all records from any one cow were kept together in either training or test sets. Similarly, a 10-fold experiment-independent cross-validation kept entire experiments together whereas a 4-fold herd-independent cross-validation kept entire herds together in either training or test sets. Based on cow-independent cross-validation for both weekly and 28-d DMI, adding MIR predictors to energy sinks (Models M3 vs M2) significantly (P < 10-10) reduced average RMSE to 1.59 kg and increased average R2 to 0.89. However, adding MIR to energy sinks (M3) to predict DMI either within an experiment-independent or herd-independent cross-validation scheme seemed to demonstrate no merit (P > 0.05) compared with an energy sink model (M2) for either R2 or RMSE (respectively, 0.68 and 2.55 kg for M2 in herd-independent scheme). We further noted that with broader cross-validation schemes, i.e., from cow-independent to experiment-independent to herd-independent schemes, the mean and slope bias increased. Given that proxy DMI phenotypes for cows would need to be almost entirely generated in herds having no DMI or training data of their own, herd-independent cross-validation assessments of predictive performance should be emphasized. Hence, more research on predictive algorithms suitable for broader cross-validation schemes and a more earnest effort on calibration of spectrophotometers against each other should be considered.

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.

Characterization of semen type prevalence and allocation in Holstein and Jersey females in the United States.

Our objective was to characterize semen type prevalence and allocation to inseminate US Holstein and Jersey females by year, parity, service number, and herd size. A secondary objective was to identify the prevalence of beef breed sires selected to create beef × Holstein and beef × Jersey crossbred calves. The final data set included 8,244,653 total inseminations of 4,880,752 Holstein females across 9,155 herds, and 435,267 total inseminations of 266,058 Jersey females across 2,759 herds from October 2019 to July 2021. This data set represents approximately 42 and 27% of the total dairy cows and heifers, respectively, across approximately 40% of the total licensed dairy herds in the continental United States. Holstein and Jersey females were inseminated with 1 of 4 semen types: (1) beef, (2) conventional, (3) sexed, or (4) other dairy. The top 4 beef breeds used to produce beef × Holstein and beef × Jersey crossbred calves, respectively, were Angus (55.1 and 39.1%), Limousin (13.9, and 23.5%), Simmental (11.7 and 20.5%), and Crossbreed Beef (11.3 and 4.8%). From 2019 to 2021, the use of sexed semen to inseminate Holstein and Jersey females increased from 11.0 and 24.5% to 17.7 and 32.1%, respectively, and the use of beef semen to inseminate Holstein and Jersey females increased from 18.2 and 11.4% to 26.1 and 21.2%, respectively. The use of beef semen to inseminate Holstein and Jersey females increased with increasing parity and service number, whereas the use of sexed semen decreased with increasing parity and service number supporting that farmers used sexed semen more aggressively in higher fertility and younger females with greater genetic merit. Overall, the increase in sexed and beef semen inseminations was driven primarily by larger herds. In conclusion, sexed and beef semen inseminations in US Holstein and Jersey females increased from 2019 to 2021 and was allocated differentially based on parity and service number. This increase was driven primarily by larger dairy herds possibly due to differences in reproductive performance and economies of scale.

Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project Genomic Management Tools to Optimise Resilience and Efficiency, and the Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle.

Feeding behavior parameters and temporal patterns in mid-lactation Holstein cows across a range of residual feed intake values.

Residual feed intake (RFI) is a measurement of the difference between actual and predicted feed intake when adjusted for energy sinks; more efficient cows eat less than predicted (low RFI) and inefficient cows eat more than predicted (high RFI). Data evaluating the relationship between RFI and feeding behaviors (FB) are limited in dairy cattle; therefore, the objective of this study was to determine daily and temporal FB in mid-lactation Holstein cows across a range of RFI values. Mid-lactation Holstein cows (n = 592 multiparous; 304 primiparous) were enrolled in 17 cohorts at 97 ± 26 d in milk (± standard deviation), and all cows within a cohort were fed a common diet using automated feeding bins. Cow RFI was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for parity, days in milk, milk energy, metabolic body weight and change, and experiment. The associations between RFI and FB at the level of meals and daily totals were evaluated using mixed models with the fixed effect of RFI and the random effects of cow and cohort. Daily temporal FB analyses were conducted using 2-h blocks and analyzed using mixed models with the fixed effects of RFI, time, RFI × time, and cohort, and the random effect of cow (cohort). There was a positive linear association between RFI and DMI in multiparous cows and a positive quadratic relationship in primiparous cows, where the rate of increase in DMI was less at higher RFI. Eating rate, DMI per meal, and size of the largest daily meal were positively associated with RFI. Daily temporal analysis of FB revealed an interaction between RFI and time for eating rate in multiparous and primiparous cows. The eating rate increased with greater RFI at 11 of 12 time points throughout the day, and eating rate differed across RFI between multiple time points. There tended to be an interaction between RFI and time for eating time and bin visits in multiparous cows but not primiparous cows. Overall, there was a time effect for all FB variables, where DMI, eating time and rate, and bin visits were greatest after the initial daily feeding at 1200 h, increased slightly after each milking, and reached a nadir at 0600 h (6 h before feeding). Considering the relationship between RFI and eating rate, additional efforts to determine cost-effective methods of quantifying eating rate in group-housed dairy cows is warranted. Further investigation is also warranted to determine if management strategies to alter FB, especially eating rate, can be effective in increasing feed efficiency in lactating dairy cattle.

Predicting dry matter intake in mid-lactation Holstein cows using point-in-time data streams available on dairy farms.

Quantifying dry matter intake (DMI) in lactating dairy cows is important for determining feed efficiency; however, there are no methods for economically quantifying individual cow DMI on dairy farms where cows are group-fed. Attempts have been made to model DMI using cow factors, milk production, milk infrared spectra, and behavioral sensors with reasonable success. Other data streams are available on the farm that may contribute to DMI predictions. In this study, our objective was to model DMI with multiple linear regression using data from a single point-in-time that can easily be accessed on-farm. Candidate predictor variables included cow descriptors, milk yield and composition, milk fatty acid profile, and production and efficiency predicting transmitting abilities (PTA). Observations of DMI were obtained from 350 cows across 6 cohorts using individual feed bunks. The cow to bunk ratio was 2:1, with an overall bunk occupation rate of 32% throughout the day. The following models were developed sequentially with milk data obtained from a single morning milking and other data from the same day: model B (production, metabolic body weight, body condition score, lactation category, and week of lactation), model BC [model B + fatty acid (FA) content], model BY (model B + FA yield), model BPE (model B + production and efficiency PTA), model BYP (model BY + production PTA), model BYE (model BY + efficiency PTA), and model BYPE (model BY + production and efficiency PTA). Outcome variables predicted in these models were the DMI on the previous day or current day relative to the morning milk sample. The predictions for DMI on the previous day outperformed current day DMI in every model for which they were both determined. Addition of milk FA and PTA as candidate predictor variable types to the models resulted in enhanced predictive ability, with incremental enhancements when combined. The most robust model (BYPE) included cow descriptors, protein and FA yields, and PTA for milk and residual feed intake. Model BYPE described 21 to 32% more of the variation in DMI (based on concordance correlation coefficient) than when other common DMI models were applied to the same data set. Overall, reasonable performance of models including single point-in-time cow descriptors, milk and FA production, and production and efficiency PTA commonly available to dairy farmers through dairy herd improvement programs offer an opportunity for on-farm prediction of DMI, yet further improvement may be possible.

Multiple-trait random regression modeling of feed efficiency in US Holsteins.

Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter intake (DMI) records on many more cows, especially from commercial environments. Recent multiple-trait random regression (MTRR) modeling developments have facilitated days in milk (DIM)-specific inferences on RFI and FS, particularly in modeling the effect of change in metabolic body weight (MBW). The MTRR analyses, using daily data on the core traits of DMI, MBW, and milk energy (MilkE), were conducted separately for 2,532 primiparous and 2,379 multiparous US Holstein cows from 50 to 200 DIM. Estimated MTRR variance components were used to derive genetic RFI and FS and DIM-specific genetic partial regressions of DMI on MBW, MilkE, and change in MBW. Estimated daily heritabilities of RFI and FS varied across lactation for both primiparous (0.05-0.07 and 0.11-0.17, respectively) and multiparous (0.03-0.13 and 0.10-0.17, respectively) cows. Genetic correlations of RFI across DIM varied (>0.05) widely compared with FS (>0.54) within either parity class. Heritability estimates based on average lactation-wise measures were substantially larger than daily heritabilities, ranging from 0.17 to 0.25 for RFI and from 0.35 to 0.41 for FS. The partial genetic regression coefficients of DMI on MBW (0.11 to 0.16 kg/kg0.75 for primiparous and 0.12 to 0.14 kg/kg0.75 for multiparous cows) and of DMI on MilkE (0.45 to 0.68 kg/Mcal for primiparous and 0.36 to 0.61 kg/Mcal for multiparous cows) also varied across lactation. In spite of the computational challenges encountered with MTRR, the model potentially facilitates an efficient strategy for harnessing more data involving a wide variety of data recording scenarios for genetic evaluations on feed efficiency.

Targeted sequencing reveals candidate causal variants for dairy bull subfertility.

Bull fertility is a key factor for successful reproductive performance in dairy cattle. Since the semen from a single bull can be used to inseminate hundreds of cows, one subfertile bull could have a major impact on herd reproductive efficiency. We have previously identified five genomic regions, located on BTA8 (72.2 Mb), BTA9 (43.7 Mb), BTA13 (60.2 Mb), BTA17 (63.3 Mb), and BTA27 (34.7 Mb), that show large dominance effects on bull fertility. Each of these regions explained about 5-8% of the observed differences in sire conception rate between Holstein bulls. Here, we aimed to identify candidate causal variants responsible for this variation using targeted sequencing (10 Mb per region). For each genomic region, two DNA pools were constructed from n ≈ 20 high-fertility and n ≈ 20 low-fertility Holstein bulls. The DNA-sequencing analysis included reads quality control (using FastQC), genome alignment (using BWA and ARS-UCD1.2), variant calling (using GATK) and variant annotation (using Ensembl). The sequencing depth per pool varied from 39× to 51×. We identified a set of nonsense mutations, missense mutations, and frameshift variants carried by low-fertility bulls. Notably, some of these variants were classified as strong candidate causal variants, i.e., mutations with deleterious effects located on genes exclusively/highly expressed in testis. Genes affected by these candidate causal variants include AK9, TTLL9, TCHP, and FOXN4. These results could aid in the development of novel genomic tools that allow early detection and culling of subfertile bull calves.

Assessing feed efficiency in early and mid lactation and its associations with performance and health in Holstein cows.

Objectives were to evaluate the associations between residual dry matter (DM) intake (RFI) and residual N intake (RNI) in early lactation, from 1 to 5 wk postpartum, and in mid lactation, from 9 to 15 wk postpartum, and assess production performance and risk of diseases in cows according to RFI in mid lactation. Data from 4 experiments including 399 Holsteins cows were used in this study. Intakes of DM and N, yields of milk components, body weight, and body condition were evaluated daily or weekly for the first 105 d postpartum. Milk yield by 305 d postpartum was also measured. Incidence of disease was evaluated for the first 90 d postpartum and survival up to 300 d postpartum. Residual DM and N intake were calculated in early and mid lactation as the observed minus the predicted values, which were based on linear models that accounted for major energy or N sinks, including daily milk energy or N output, metabolic body weight, and daily body energy or N changes, and adjusting for parity, season of calving, and treatment within experiment. Cows were ranked by RFI and RNI in mid lactation and categorized into quartiles (Q1 = smallest RFI, to Q4 = largest RFI). Increasing efficiency in mid lactation resulted in linear decreases in RFI (depicted from Q1 to Q4; -0.93, -0.05, -0.04, and 0.98 kg/d), DMI (16.0, 16.9, 17.3, and 18.4 kg/d), net energy for lactation (NEL) intake (26.8, 28.4, 29.0, and 30.8 Mcal/d), and NEL balance (-9.0, -8.1, -8.2, and -5.5 Mcal/d) during early lactation, but no differences were observed in body NEL or N changes or yield of energy-corrected milk in the first 5 wk of lactation. Residual DM intake in mid lactation was associated with RFI (Pearson r = 0.43, and Spearman ρ = 0.32) and RNI (r = 0.44, ρ = 0.36) in early lactation, and with RNI in mid lactation (r = 0.91, ρ = 0.84). Similarly, RNI in mid lactation was associated with RNI in early lactation (r = 0.42, ρ = 0.35). During the first 15 wk postpartum, more efficient cows in mid lactation consumed 3.5 kg/d less DM (Q1 = 19.3 vs. Q4 = 22.8 kg/d) and were more N efficient (Q1 = 31.6 vs. Q4 = 25.8%), at the same time that yields of milk (Q1 = 39.0 vs. Q4 = 39.4 kg/d), energy-corrected milk (Q1 = 38.6 vs. Q4 = 39.3 kg/d), and milk components did not differ compared with the quartile of least efficient cows. Furthermore, RFI in mid lactation was not associated with 305-d milk yield, incidence of diseases in the first 90 d postpartum, or survival by 300 d postpartum. Collectively, rankings of RFI and RNI are associated and repeatable across lactation stages. The most feed-efficient cows were also more N efficient in early and mid lactation. Phenotypic selection of RFI based on measurements in mid lactation is associated with improved efficiency without affecting production or health in dairy cows.

Genetic dissection of reproductive performance of dairy cows under heat stress.

Heat stress negatively impacts the reproductive performance of dairy cows. The main objective of this study was to dissect the genetic basis underlying dairy cow fertility under heat stress conditions. Our first goal was to estimate genetic components of cow conception across lactations considering heat stress. Our second goal was to reveal individual genes and functional gene-sets that explain a cow's ability to conceive under thermal stress. Data consisted of 74 221 insemination records on 13 704 Holstein cows. Multitrait linear repeatability test-day models with random regressions on a function of temperature-humidity index values were used for the analyses. Heritability estimates for cow conception under heat stress were around 2-3%, whereas genetic correlations between general and thermotolerance additive genetic effects were negative and ranged between -0.35 and -0.82, indicating an unfavorable relationship between cows' ability to conceive under thermo-neutral vs. thermo-stress conditions. Whole-genome scans identified at least six genomic regions on BTA1, BTA10, BTA11, BTA17, BTA21 and BTA23 associated with conception under thermal stress. These regions harbor candidate genes such as BRWD1, EXD2, ADAM20, EPAS1, TAOK3, and NOS1, which are directly implicated in reproductive functions and cellular response to heat stress. The gene-set enrichment analysis revealed functional terms related to fertilization, developmental biology, heat shock proteins and oxidative stress, among others. Overall, our findings contribute to a better understanding of the genetics underlying the reproductive performance of dairy cattle under heat stress conditions and point out novel genomic strategies for improving thermotolerance and fertility via marker-assisted breeding.

Transcriptomic analysis of eyelid pigmentation in Hereford cattle.

The study of skin color in cattle holds both economic and scientific interest. Several ocular diseases of cattle have been associated with low pigmentation of the eyelids, including ocular squamous cell carcinoma and infectious keratoconjunctivitis, the two most common ocular diseases affecting cattle production. Although low eyelid pigmentation is a well-known risk factor for various ocular diseases, the genetic and biological basis of this relationship is largely unknown. We investigated the transcriptome of eyelid skin in Hereford cattle using RNA-sequencing technology. Two contrasting groups were evaluated: steers that were completely pigmented and steers with no pigmentation in both eyelids. Most of the up-regulated genes in pigmented samples are directly implicated in melanogenesis and melanosome development, whereas up-regulated genes in non-pigmented samples are implicated in cancer development and the immune system, among other functions. Interestingly, network analysis comparing pigmented vs. non-pigmented samples revealed significant differences in the co-expression patterns of genes related to melanosome, pigmentation and defense response to bacteria, showing higher gene activity, greater co-expression patterns and tighter co-regulation mechanisms in pigmented samples. Overall, our findings indicate that bovine eyelid pigmentation depends on the expression of many genes involved not only in pigmentation and melanosome function but also related to inflammatory response, infection and tumoral pathways.

Early genomic prediction of daughter pregnancy rate is associated with improved reproductive performance in Holstein dairy cows.

The use of genomic testing for selecting replacement heifers in commercial farms has recently attracted much attention. Fertility traits are among the most complex, hard to measure, and lowly heritable traits, and hence they can benefit the most from genomic testing. The objectives of this study were to assess the relationship between early genomic prediction of daughter pregnancy rate (GDPR) and pregnancy at the first service (P1), pregnancy at the end of lactation (PEND), number of services for conception (NSFC), days from calving to first service (TP1), and days open (TPEND). Data for GDPR, milk production, and reproductive outcomes from 1,401 multiparous and 3,044 primiparous Holstein cows from 4 commercial farms with the same reproductive management were used in the analyses. All animals were genotyped and genomically evaluated as heifers before first breeding, so no phenotypic data were available for predicting genomic merits. In addition, all animals were genotyped and evaluated as heifers before first breeding, so no phenotypic data were available for prediction. Data for GDPR and milk production were categorized in quartiles. The statistical models included GDPR, farm-year-season of the first insemination, milk yield, breeding code (estrus detection or timed artificial insemination), and the interaction terms as potential predictors for the different reproductive outcomes evaluated. Data were analyzed separately for primiparous and multiparous cows. The proportion of cows bred by estrus detection increased linearly from lowest to highest GDPR in primiparous cows. There were positive associations of GDPR for P1, PEND, NSFC, TP1, and TPEND in both primiparous and multiparous cows. For instance, positive GDPR effects in multiparous cows included a 15.7% higher P1 (47.6% vs. 31.9%), 11.9% higher PEND (84.9% vs. 73.0%), and 48.0-d shorter TPEND (139.8 vs. 175.7 d) for the highest quartile compared with the lowest quartile. Milk yield affected PEND in multiparous cows, and TPEND and NSFC affected PEND in primiparous cows. The only significant interaction between GDPR and milk production was detected for NSFC in primiparous cows, where high-producing cows showed a reduction in NSFC as GDPR increased, whereas low-producing cows showed no relationship between GDPR and NSFC. Overall, our findings show that GDPR can be effectively used as a predictor of future reproductive performance, reaffirming the potential benefits of applying early genomic predictions for making accurate early selection decisions.

Associations between maternal characteristics and health, survival, and performance of dairy heifers from birth through first lactation.

The objective of this study was to investigate whether health, survival, and performance of dairy heifers from birth through first lactation are associated with parity and health status of their dams. Holstein heifers (n = 1,811) derived from artificial insemination were categorized as (1) daughters of primiparous cows that, consequently, were nonlactating heifers during gestation (Prim-NoL; n = 787); (2) daughters of multiparous cows that did not have any clinical diseases in the previous lactation (Mult-NoCD; n = 638); and (3) daughters of multiparous cows that had at least one clinical disease in the previous lactation (Mult-CD; n = 386). Clinical diseases of the multiparous dams included retained placenta, metritis, mastitis, lameness, and digestive and respiratory problems. Data collected for evaluation of daughters included genotypic and phenotypic characteristics at birth, morbidity, reproductive performance, and culling from birth through 305 d in milk of first lactation. Orthogonal contrasts were used to evaluate the effect of the parity of the dam (Prim-NoL vs. Mult-NoCD + Mult-CD) and the effect of clinical disease occurrence in the previous lactation among multiparous dams (Mult-NoCD vs. Mult-CD). Compared with daughters of multiparous cows, daughters of Prim-NoL were lighter at birth (36 vs. 41 kg), had greater genetic merit for production traits (e.g., genomic estimated breeding value for milk yield: 875 vs. 746 kg), were less likely to leave the herd (17 vs. 28%) and to lose pregnancy as a heifer (9 vs. 14%), calved earlier (703 vs. 711 d old), were less likely to have clinical diseases as a first lactation cow (30 vs. 37%), and had reduced performance in the first lactation when considering their genetic merit (e.g., 305-d yield of energy-corrected milk: 11,270 vs. 11,539 kg). Compared with daughters of Mult-NoCD, daughters of Mult-CD were less likely to have digestive problems as a heifer (17 vs. 27%) and clinical disease as a first lactation cow (32 vs. 42%), but were also more likely to leave the herd as a heifer (32 vs. 25%) even though genetic merit for production traits were similar (e.g., genomic estimated breeding value for milk: 744 vs. 749 kg). In conclusion, both parity and health status of the dam in the previous lactation were associated with morbidity, survival, and performance of their daughters from birth through 305 d in milk of the first lactation and might represent factors affecting developmental programming of dairy heifers in utero.

Long-term effects of postpartum clinical disease on milk production, reproduction, and culling of dairy cows.

Two retrospective studies examining data of 7,500 lactating cows from a single herd were performed with the objective of evaluating the long-term effects of clinical disease during the early postpartum period on milk production, reproduction, and culling of dairy cows through 305 days in milk (DIM). In the first study, data regarding health, milk production, reproduction, and culling of 5,085 cows were summarized. Cows were classified according to incidence of clinical problem (metritis, mastitis, lameness, digestive problem, or respiratory problem) during the first 21 DIM (ClinD21). During 305 d of lactation, cows that had ClinD21 produced, on average, 410 kg less milk, 17 kg less fat, and 12 kg less protein compared with cows that did not have ClinD21 (NoClinD21). Although the interval to first breeding was not different between groups of interest, pregnancy rate through 305 DIM was lower in cows that had ClinD21 [adjusted hazard ratio (AHR) = 0.81]. When individual breedings were analyzed, cows that had ClinD21 presented lower rates of pregnancy per breeding for breedings performed before 150 DIM, reduced numbers of calving per breeding for breedings performed before 200 DIM, and greater number of pregnancy losses for all breedings performed through 305 DIM. The rate of culling from calving through 305 DIM was higher in cows that had a single ClinD21 (AHR = 1.79) and in cows that had multiple ClinD21 (AHR = 3.06), which resulted in a greater proportion of cows leaving the herd by 305 DIM (NoClinD21 = 22.6%; single ClinD21 = 35.7%; multiple ClinD21 = 53.8%). In the second study, data regarding postpartum health and 305-d yields of milk, fat, and protein were collected from 2,415 primiparous cows that had genomic testing information. Genomic estimated breeding values (EBV) were used to predict 305-d yields of milk, fat, and protein. Genomic EBV and predicted yields of milk, fat, and protein did not differ between cows that had ClinD21 and those that did not have ClinD21. In contrast, the observed 305-d yields of milk, fat, and protein were reduced by 345, 10, and 10 kg, respectively, in cows that had ClinD21 compared with cows that did not have ClinD21. We conclude that clinical disease diagnosed and treated during the first 21 DIM has long-term effects on lactation performance, reproduction, and culling of dairy cows, which contribute to detrimental consequences of health problems on sustainability of dairy herds. Replication of our studies in multiple herds will be important to confirm our findings in a larger population.

Genetic dissection of bull fertility in US Jersey dairy cattle.

The service sire has been recognized as an important factor affecting herd fertility in dairy cattle. Recent studies suggest that genetic factors explain part of the difference in fertility among Holstein sires. The main objective of this study was to dissect the genetic architecture of sire fertility in US Jersey cattle. The dataset included 1.5 K Jersey bulls with sire conception rate (SCR) records and 96 K single nucleotide polymorphism (SNP) markers spanning the whole genome. The analysis included whole-genome scans for both additive and non-additive effects and subsequent functional enrichment analyses using KEGG Pathway, Gene Ontology (GO) and Medical Subject Headings (MeSH) databases. Ten genomic regions located on eight different chromosomes explained more than 0.5% of the additive genetic variance for SCR. These regions harbor genes, such as PKDREJ, EPB41L2, PDGFD, STX2, SLC25A20 and IP6K1, that are directly implicated in testis development and spermatogenesis, sperm motility and the acrosome reaction. In addition, the genomic scan for non-additive effects identified two regions on BTA11 and BTA25 with marked recessive effects. These regions harbor three genes-FER1L5, CNNM4 and DNAH3-with known roles in sperm biology. Moreover, the gene-set analysis revealed terms associated with calcium regulation and signaling, membrane fusion, sperm cell energy metabolism, GTPase activity and MAPK signaling. These gene sets are directly implicated in sperm physiology and male fertility. Overall, this integrative genomic study unravels genetic variants and pathways affecting Jersey bull fertility. These findings may contribute to the development of novel genomic strategies for improving sire fertility in Jersey cattle.

Genetic parameter estimation for long endurance trials in the Uruguayan Criollo horse.

The aim of this study was to estimate the genetic parameters of performance in a 750-km, 15-day ride in Criollo horses. Heritability (h2 ) and maternal lineage effects (mt2 ) were obtained for rank, a relative placing measure of performance. Additive genetic and maternal lineage (rmt) correlations among five medium-to-high intensity phase ranks (pRK) and final rank (RK) were also estimated. Individual records from 1,236 Criollo horses from 1979 to 2012 were used. A multivariate threshold animal model was applied to the pRK and RK. Heritability was moderate to low (0.156-0.275). Estimates of mt2 were consistently low (0.04-0.06). Additive genetic correlations between individual pRK and RK were high (0.801-0.924), and the genetic correlations between individual pRKs ranged from 0.763 to 0.847. The pRK heritabilities revealed that some phases were explained by a greater additive component, whereas others showed stronger genetic relationships with RK. Thus, not all pRK may be considered as similar measures of performance in competition.

Modelling female fertility traits in beef cattle using linear and non-linear models.

Female fertility traits are key components of the profitability of beef cattle production. However, these traits are difficult and expensive to measure, particularly under extensive pastoral conditions, and consequently, fertility records are in general scarce and somehow incomplete. Moreover, fertility traits are usually dominated by the effects of herd-year environment, and it is generally assumed that relatively small margins are kept for genetic improvement. New ways of modelling genetic variation in these traits are needed. Inspired in the methodological developments made by Prof. Daniel Gianola and co-workers, we assayed linear (Gaussian), Poisson, probit (threshold), censored Poisson and censored Gaussian models to three different kinds of endpoints, namely calving success (CS), number of days from first calving (CD) and number of failed oestrus (FE). For models involving FE and CS, non-linear models overperformed their linear counterparts. For models derived from CD, linear versions displayed better adjustment than the non-linear counterparts. Non-linear models showed consistently higher estimates of heritability and repeatability in all cases (h2  < 0.08 and r < 0.13, for linear models; h2  > 0.23 and r > 0.24, for non-linear models). While additive and permanent environment effects showed highly favourable correlations between all models (>0.789), consistency in selecting the 10% best sires showed important differences, mainly amongst the considered endpoints (FE, CS and CD). In consequence, endpoints should be considered as modelling different underlying genetic effects, with linear models more appropriate to describe CD and non-linear models better for FE and CS.

Genome-wide association mapping and pathway analysis of leukosis incidence in a US Holstein cattle population.

Bovine leukosis virus is an oncogenic virus that infects B cells, causing bovine leukosis disease. This disease is known to have a negative impact on dairy cattle production and, because no treatment or vaccine is available, finding a possible genetic solution is important. Our objective was to perform a comprehensive genetic analysis of leukosis incidence in dairy cattle. Data on leukosis occurrence, pedigree and molecular information were combined into multitrait GBLUP models with milk yield (MY) and somatic cell score (SCS) to estimate genetic parameters and to perform whole-genome scans and pathway analysis. Leukosis data were available for 11 554 Holsteins daughters of 3002 sires from 112 herds in 16 US states. Genotypes from a 60K SNP panel were available for 961 of those bulls as well as for 2039 additional bulls. Heritability for leukosis incidence was estimated at about 8%, and the genetic correlations of leukosis disease incidence with MY and SCS were moderate at 0.18 and 0.20 respectively. The genome-wide scan indicated that leukosis is a complex trait, possibly modulated by many genes. The gene set analysis identified many functional terms that showed significant enrichment of genes associated with leukosis. Many of these terms, such as G-Protein Coupled Receptor Signaling Pathway, Regulation of Nucleotide Metabolic Process and different calcium-related processes, are known to be related to retrovirus infection. Overall, our findings contribute to a better understanding of the genetic architecture of this complex disease. The functional categories associated with leukosis may be useful in future studies on fine mapping of genes and development of dairy cattle breeding strategies.