Genetic parameters of ovarian and uterine reproductive traits in dairy cows

Genomic Prediction for Abortion in Lactating Holstein Dairy Cows

Abortion in dairy cattle causes great economic losses due to reduced animal health, increase in culling rates, reduction in calf production, and milk yield, among others. Although the etiology of abortions can be of various origins, previous research has shown a genetic component. The objectives of this study were to (1) describe the development of the genomic prediction for cow abortions in lactating Holstein dairy cattle based on producer-recorded data and ssGBLUP methodology and (2) evaluate the efficacy of genomic predictions for cow abortions in commercial herds of US Holstein cows using data from herds that do not contribute phenotypic information to the evaluation. We hypothesized that cows with greater genomic predictions for cow abortions (Z_Abort STA) would have a reduced incidence of abortion. Phenotypic data on abortions, pedigree, and genotypes were collected directly from commercial dairy producers upon obtaining their permission. Abortion was defined as the loss of a confirmed pregnancy after 42 and prior to 260 days of gestation, treated as a binary outcome (0, 1), and analyzed using a threshold model. Data from a different subset of animals were used to test the efficacy of the prediction. The additive genetic variance for the cow abortion trait (Z_Abort) was 0.1235 and heritability was 0.0773. For all animals with genotypes (n = 1,662,251), mean reliability was 42%, and genomic predicted transmitting abilities (gPTAs) ranged from −8.8 to 12.4. Z_Abort had a positive correlation with cow and calf health traits and reproductive traits, and a negative correlation with production traits. Z_Abort effectively identified cows with a greater or lesser risk of abortion (16.6% vs. 11.0% for the worst and best genomics groups, respectively; p < 0.0001). The inclusion of cow abortion genomic predictions in a multi-trait selection index would allow dairy producers and consultants to reduce the incidence of abortion and to select high-producing, healthier, and more profitable cows.

Genes and pathways associated with pregnancy loss in dairy cattle

Pregnancy loss directly impairs reproductive performance in dairy cattle. Here, we investigated genetic factors associated with pregnancy loss following detection of a viable embryo around 42 days of gestation. The objectives of this study were to perform whole-genome scans and subsequent gene-set analyses for identifying candidate genes, functional gene-sets and gene signaling pathways implicated in pregnancy loss in US Holstein cows. Data consisted of about 58,000 pregnancy/abortion records distributed over nulliparous, primiparous, and multiparous cows. Threshold models were used to assess the binary response of pregnancy loss. Whole‐genome scans identified at least seven genomic regions on BTA2, BTA10, BTA14, BTA16, BTA21, BTA24 and BTA29 associated with pregnancy loss in heifers and lactating cows. These regions harbor several candidate genes that are directly implicated in pregnancy maintenance and fetal growth, such as CHST14, IGF1R, IGF2, PSEN2, SLC2A5 and WNT4. Moreover, the enrichment analysis revealed at least seven significantly enriched processes, containing genes associated with pregnancy loss, including calcium signaling, cell–cell attachment, cellular proliferation, fetal development, immunity, membrane permeability, and steroid metabolism. Additionally, the pathway analysis revealed a number of significant gene signaling pathways that regulate placental development and fetal growth, including Wnt, Hedgehog, Notch, MAPK, Hippo, mTOR and TGFβ pathways. Overall, our findings contribute to a better understanding of the genetic and biological basis of pregnancy loss in dairy cattle and points out novel strategies for improving pregnancy maintenance via marker‐assisted breeding.

Genetic parameters for reproductive losses estimated from in-line milk progesterone profiles in Swedish dairy cattle

This study assessed the extent of reproductive losses and associated genetic parameters in dairy cattle, using in-line milk progesterone records for 14 Swedish herds collected by DeLaval's Herd Navigator. A total of 330,071 progesterone samples were linked to 10,219 inseminations (AI) from 5,238 lactations in 1,457 Swedish Red and 1,847 Swedish Holstein cows. Pregnancy loss traits were defined as early embryonic loss (1-24 d after AI), late embryonic loss (25-41 d after AI), fetal loss (42 d after AI until calving), and total pregnancy loss (from d 1 after AI until calving). The following classical fertility traits were also analyzed: interval from calving to first service, interval from calving to last service, interval between first and last service, calving interval, and number of inseminations per service period. Least squares means with standard error (LSM ± SE), heritabilities, and genetic correlations were estimated in a mixed linear model. Fixed effects included breed, parity (1, 2, ≥3), estrus cycle number when the AI took place, and a linear regression on 305-d milk yield. Herd by year and season of AI, cow, and permanent environmental effect were considered random effects. Extensive (approximately 45%) early embryonic loss was found, but with no difference between the breeds. Swedish Red was superior to Swedish Holstein in the remaining pregnancy loss traits with, respectively: late embryonic loss of 6.1 ± 1.2% compared with 13.3 ± 1.1%, fetal loss of 7.0 ± 1.2% compared with 12.3 ± 1.2%, and total pregnancy loss of 54.4 ± 1.4% compared with 60.6 ± 1.4%. Swedish Red also had shorter calving to first service and calving to last service than Swedish Holstein. Estimated heritability was 0.03, 0.06, and 0.02 for early embryonic, late embryonic, and total pregnancy loss, respectively. Milk yield was moderately genetically correlated with both early and late embryonic loss (0.52 and 0.39, respectively). The pregnancy loss traits were also correlated with several classical fertility traits (-0.46 to 0.92). In conclusion, Swedish Red cows had lower reproductive loss during late embryonic stage, fetal stage, and in total, and better fertility than Swedish Holstein cows. The heritability estimates for pregnancy loss traits were of the same order of magnitude as previously reported for classical fertility traits. These findings could be valuable in work to determine genetic variation in reproductive loss and its potential usefulness as an alternative fertility trait to be considered in genetic or genomic evaluations.

Genetic correlations between body weight, daily weight gain, and semen characteristic traits in young Norwegian Red bulls

The aim of this study was to estimate genetic parameters for body weight (BW) at 150 d (Bw_150d), and 330 d (Bw_330d) of age and average daily weight gain (Dwg), and to estimate genetic correlations between these traits and semen characteristic traits: volume; concentration (Conc); motility in fresh, 24-h, and 48-h samples (Mot0h, Mot24h, Mot48h); and sperm defects. Data were collected at the performance test station of young Norwegian Red bulls from 2002 to 2012, before selection of bulls for artificial insemination. The weight and growth data consisted of observations for 3,209 bulls, and andrology information was available for up to 2,034 of these bulls. Genetic parameters were estimated using linear animal models. Models for BW and growth traits included the group and year the bull left the station and the pen they occupied during weighing (group-year-pen) and parity of their dam as fixed effects. Models for andrology traits had group-year, age in months (11 to 15), and the interaction between ejaculate number and days since previous collection included as fixed effects. Estimated heritability was 0.14 for Bw_150d, 0.26 for Bw_330d, and 0.34 for Dwg; the estimated genetic correlations among these traits were all favorable. Both BW traits correlated favorably with all the semen characteristic traits (0.20 to 0.76), whereas Dwg was favorably correlated with volume, Mot24h, Mot48h, and sperm defects, and unfavorably correlated with Conc (-0.25) and Mot0h (-0.53). Our results indicate that the genetic correlations between weight and growth traits and semen characteristics depend on the age of the bulls. Although most genetic correlations were favorable, selection for higher daily weight gain between 150 and 330 d might explain the slight negative genetic trends observed for semen characteristics in young Norwegian Red bulls.

Genetic and genomic analysis of long insemination interval in Israeli dairy cattle as an indicator of early abortions

One of the causes of observed low fertility is embryo loss after fertilization. Previous findings suggested that more than half of fertilizations result in embryo loss before pregnancy is detected. We proposed reinsemination between 49 and 100 d after the first insemination as an indicator trait for early abortion (EA) in dairy cattle based on the mean estrus interval of 21 d. This trait was compared with conception rate from first insemination and conception status, computed as the inverse of the number of inseminations to conception. Animal model variance components were estimated by REML, including parents and grandparents of cows with records. First-parity heritability for first insemination conception rate was 3%. In the multitrait analysis of parities 1 to 3 for putative EA, heritabilities ranged from 8.9% for first parity to 10.4% for second parity. All genetic correlations were >0.9, whereas all environmental correlations were <0.12. The variance component for the service sire effect for putative EA rate was less than half the variance component for conception rate. Thus, genetic control of the 2 traits is clearly different, and analysis of EA rate by a single-trait animal model is justified. Genetic evaluation for putative EA was computed using this model, including all first- through third-parity cows with freshening dates from January 1, 1985, through December 31, 2016, that either became pregnant on first insemination or were reinseminated between 49 and 100 d after the first insemination. All known parents and grandparents of cows with records were included in the analysis. The regression of the breeding value for non-abortion rate on the cows' birth year was 0.083%/yr. The genetic correlation between first-parity EA and conception status was 0.995. The genetic correlations between first-parity EA and milk, fat, and protein production were all negative, whereas the genetic correlation between EA and herd life was 0.33. Inclusion of putative EA in the selection index instead of conception status resulted in 10 to 20% greater genetic gain for both fertility traits. In a genome-wide association study based on 1,200 dairy bulls with reliabilities >50% for abortion rate genotyped for 41,000 markers, 6 markers were found with nominal probabilities of <10^-12 to reject the null hypothesis of no effect on EA rate. The markers with the lowest probabilities for EA rate were also included among the markers with the lowest probabilities for female fertility, but not vice versa. The marker explaining the most variance for abortion rate is located within the ABCA9 gene, which is found within an ATP-binding cassette (ABC) genes cluster. The ABC family is the major class of primary active transporters in the placenta.

Cow-level risk factors for reproductive tract disease diagnosed by 2 methods in pasture-grazed dairy cattle in Ireland

The cow-side diagnosis of reproductive tract disease (RTD) involves identifying the presence of purulent vaginal discharge (PVD) and ultrasonographic endometritis (UE). The objectives of our study were to obtain prevalence estimates for RTD diagnosed by 2 methods (PVD and UE scoring) and to investigate the risk factors for increased probability of RTD if these methods are used in isolation or in combination. Our retrospective observational cohort study tested the hypothesis that RTD assessed by 2 methods would have similar risk factors, and that those would be mainly cow- and calving-related factors. We analyzed data from 5,049 pre-breeding examinations (PBE) from 2,460 spring-calved cows on 8 farms between 2014 and 2018. Cow-related details assessed were days in milk at PBE, breed, lactation number, dry period length, body condition score at calving and PBE, 305-d milk yield, predicted transmitting ability for production and fertility, the presence of a corpus luteum at PBE, and positive diagnosis the previous year. Calving details assessed were type of sire, calf sex, twinning, stillbirth, calving difficulty score, and retained fetal membranes. We conducted statistical analyses using 4 multivariable logistic regression models to identify the risk of RTD diagnosed by (1) PVD in isolation, (2) UE in isolation, (3) the presence of either PVD or UE; and (4) the presence of both PVD and UE. We accounted for herd, cow, and year as random effects in all 4 models. The overall prevalence of RTD in models 1, 2, 3, and 4 were 7.5, 6.7, 11.6, and 2.6%, respectively. Days in milk at PBE, the interaction between days in milk and retained fetal membranes, twinning, and the predicted transmitting ability for calving interval were consistently significant risk factors for positive scores in all 4 models. Considerable calving difficulty [adjusted odds ratio (AOR) = 13.64], Holstein Friesian dam breed (AOR = 2.58), first lactation (AOR = 2.39), and body condition score at PBE (AOR = 1.64) were risk factors for a positive PVD score but not for a positive UE score. Fifth lactation (AOR = 1.69), a beef-sired calf (AOR = 1.46), and the absence of a corpus luteum at PBE (AOR = 1.57) were risk factors for a positive UE score but not for a positive PVD score. These results support the hypothesis that most of the risk factors for PVD and UE are the same but some are distinctly different, implying that in some instances the 2 methods diagnose separate components of the RTD complex.

Anti-Müllerian hormone in grazing dairy cows: Identification of factors affecting plasma concentration, relationship with phenotypic fertility, and genome-wide associations

The objectives of this study were to (1) characterize the distribution and variability of plasma anti-Müllerian hormone (AMH) concentration; (2) evaluate factors associated with phenotypic variation in plasma AMH; (3) examine the associations between categories of plasma AMH and reproductive outcomes [pregnancy to first artificial insemination (P/AI), and pregnancy rates within 21, 42, and 84 d after the mating start date (MSD)]; (4) estimate pedigree and genomic heritability for plasma AMH; and (5) identify and validate SNP associated with phenotypic variation in plasma AMH. Plasma AMH concentration (pg/mL) was determined from a blood sample collected (mean ± standard deviation) 10 ± 2 d after first insemination at detected estrus (IDE) in 2,628 first- and second-parity Irish dairy cows. Overall, plasma AMH had a positively skewed distribution with mean (± standard deviation), median, minimum, and maximum concentrations of 326 ± 231, 268, 15, and 2,863 pg/mL, respectively. Plasma AMH was greatest for Jersey, followed by Holstein × Jersey, Holstein × Norwegian Red, and Holstein cows (410, 332, 284, and 257 pg/mL, respectively). Second-parity cows had greater plasma AMH than first-parity cows (333 vs. 301 pg/mL, respectively). Samples collected at 7 and 8 d after first IDE had lesser plasma AMH than those collected on d 9, 10, 11, 12, and 13 after first IDE (291 and 297 vs. 317, 319, 331, 337, and 320 pg/mL). Plasma AMH was not associated with either body condition score at first IDE or the interval from calving to MSD. Cows were categorized into low (≤150 pg/mL; n = 526; lowest 20%), intermediate (>150 to ≤461 pg/mL; n = 1,576; intermediate 60%), and high AMH (>461 pg/mL; n = 526; highest 20%) groups based on plasma AMH, and associations with reproductive outcomes were tested. Cows with high and intermediate plasma AMH had 1.42- and 1.51-times-greater odds of becoming pregnant within 84 d after the MSD than those with low plasma AMH (90.3 and 90.8 vs. 86.8%, respectively); however, P/AI and pregnancy rate within 21 and 42 d after the MSD did not differ among AMH categories. Plasma AMH was moderately heritable (pedigree heritability of 0.40 ± 0.06 and genomic heritability of 0.45 ± 0.05), and 68 SNP across Bos taurus autosomes 7 and 11 were associated with phenotypic variation in plasma AMH. Out of 68 SNP, 42 were located in a single quantitative trait locus on Bos taurus autosome 11 that harbored 6 previously identified candidate genes (NR5A1, HSPA5, CRB2, DENND1A, NDUFA8, and PTGS) linked to fertility-related phenotypes in dairy cows.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Immune-associated traits measured in milk of Holstein-Friesian cows as proxies for blood serum measurements

Previous work has highlighted that immune-associated (IA) traits measurable in blood are associated with health, productivity, and reproduction in dairy cows. The aim of the present study was to determine relationships between IA traits measured in blood serum and those simultaneously measured in milk as well as their association with disease phenotypes. All animals were Holstein-Friesian cows from the Langhill research herd (n = 546) housed at the SRUC Dairy Research Centre in Scotland. Milk and serum samples were collected on 20 separate occasions between July 2010 and March 2015 and analyzed by ELISA for haptoglobin (Hp), tumor necrosis factor-α (TNF-α), and natural antibodies binding keyhole limpet hemocyanin (NAb_KLH) and lipopolysaccharide (NAb_LPS). Data were analyzed using mixed linear models that included pedigree information. Analyses revealed positive phenotypic correlations between milk and serum NAb (0.59 ≤ r ≤ 0.77), Hp (r = 0.37), and TNF-α (r = 0.12). Milk and serum NAb were also found to have a strong genetic correlation (0.81 ≤ r ≤ 0.94) and were genetically correlated with cow lameness (0.66 and 0.79 for milk NAb_KLH and serum NAb_LPS, respectively). Clinical mastitis was found to be phenotypically correlated with both milk and serum Hp (0.09 ≤ r ≤ 0.23). Serum Hp was also strongly genetically correlated with other cellular IA traits such as percent NKp46⁺ (a natural killer cell marker; 0.35) and percent peripheral blood mononuclear cells (PBMC; -0.90). Similarly, genetic correlations were found to exist between serum TNF-α and percent NKp46⁺ (0.22), percent PBMC (0.41), and percent lymphocytes (0.47). Excluding serum Hp, all milk and serum IA traits were repeatable, ranging from 0.11 (milk Hp) to 0.43 (serum NAb_LPS). Between-animal variation was highest in milk and serum NAb (0.34-0.43) and significant estimates of heritability were also observed in milk and serum NAb (0.17-0.37). Our findings show that certain IA traits, such as NAb_KLH and NAb_LPS, found in milk and serum are strongly correlated and highlight the potential of using routinely collected milk samples as a less invasive and cost-effective source of informative data for predictive modeling of animal IA traits.

Update on Multiple Ovulations in Dairy Cattle

This review updates the causal mechanisms and risk factors for multiple ovulations (MOV) in cattle. Clearly, MOV can lead to twin pregnancies, which negatively affects the health, production, and reproduction of cows. Therefore, a better understanding of the factors causing MOV may help to reduce twinning. Multiple ovulations occur after two or more follicles deviate and achieve codominance. The MOV rate is influenced by a complex network of hormones. For example, MOV is more common during periods of low progesterone (P4), that is, in anovulatory cattle or when luteolysis coincides with the selection of the future ovulatory follicle. There is also strong evidence for the luteinizing hormone (LH) being the primary factor leading to codominance, as high P4 concentrations suppress the transient LH surges and can reduce the ovulation rate in cattle or even inhibit deviation. Rates of MOV are increased in older and higher-producing dairy cows. Increased milk production and dry matter intake (DMI) increases hormone clearance, including P4; however, the association between milk yield and MOV has not been consistent. Additional risk factors for MOV include ovarian cysts, diet, season, and genetics.

Inbreeding effects on in vitro embryo production traits in Guzerá cattle

Inbreeding has been associated with the impairment of reproductive performance in many cattle breeds. Although the usage of reproductive biotechnologies has been increasing in bovine populations, not much attention has been given to the impact of inbreeding over cow's performance on artificial reproduction. The objective of this study was to estimate the impact of inbreeding on in vitro embryo production in a Guzerá breed population. The inbreeding coefficient (F), calculated as half of the co-ancestry of the individual's parents, was used as an estimate of inbreeding. The inbreeding coefficients of the donor, sire (used on in vitro fertilization) and of the embryos were included, separately, in the proposed models either as classificatory or continuous variables (linear and quadratic effects). The percentage of non-inbred individuals (or embryos) and mean F of donors, embryos and sires were 29.38%; 35.76%; 42.86% and 1.98±2.68; 1.32±3.13; 2.08±2.79, respectively. Two different models were considered, one for oocyte production traits and other for embryo production traits. The increase of F of the donor significantly (P<0.05) impaired the number of viable oocytes (N OV), number of grade I oocytes (N GI) and number of cleaved embryos (N CLV). Moreover, the donor's F influenced the percentage of grade I oocytes (P GI), percentage of viable embryos (P EMB) and percentage of cleaved embryos that turned into embryos (P CXE). No significant (P>0.05) effects were observed for the sire (father of the embryos) inbreeding coefficient over the traits analysed. Embryo's F influenced (P<0.05) the number of viable embryos (N EMB), percentage of viable embryos (P EMB) and percentage of cleaved embryos that turn into embryos (P CXE). Results suggested that an increase in the inbreeding coefficient might impair the embryos ability to survive through challenges imposed by the in vitro environment. Submitting highly inbred Guzerá female donors to in vitro embryo production may, in the long-term, have negative implications on the number of embryos obtained per cow and increase the relative costs of the improvement programmes based on this technology. High levels of inbreeding should be avoided when selecting Guzerá female donors and planning in vitro fertilization mating.

Reproductive Systems for North American Dairy Cattle Herds

Reproductive inefficiency compromises the profitability of dairy herds and the health and longevity of individual cows. In the average dairy herd, the combination of estrus detection and ovulation synchronization protocols yields the best economic return. Genomic selection of animals is particularly profitable in situations in which little is known about their genetic potential. Biosensor systems in milking parlors may allow for the design of reproductive strategies tailored for cows according to their physiologic needs while optimizing economic return.

Milk Production and Fertility in Cattle

Evolutionary biology provides reasons for why the intensive selection for milk production reduces reproductive success rates. There is considerable exploitable genetic variation in reproductive performance in both dairy and beef cattle, and examination of national genetic trends demonstrates that genetic gain for both reproductive performance and milk production is possible in a well-structured breeding program. Reproductive failure is often postulated to be a consequence of the greater negative energy balance associated with the genetic selection for increased milk production. However, experimental results indicate that the majority of the decline in reproductive performance cannot be attributed to early lactation energy balance, per se; reproductive success will, therefore, not be greatly improved by nutritional interventions aimed at reducing the extent of negative energy balance. Modeling can aid in better pinpointing the key physiological components governing reproductive success and, also, the impact of individual improvements on overall fertility, helping to prioritize variables for inclusion in breeding programs.