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Despite the importance of the quality of semen used in artificial insemination to the reproductive success of dairy herds, few studies have estimated the extent of genetic variability in semen quality traits. Even fewer studies have quantified the correlation between semen quality traits and male fertility. In this study, records of 100,058 ejaculates collected from 2,885 Nordic Holstein bulls were used to estimate genetic parameters for semen quality traits, including pre- and postcryopreservation semen concentration, sperm motility and viability, ejaculate volume, and number of doses per ejaculate. Additionally, summary data on nonreturn rate (NRR) obtained from insemination of some of the bulls (n = 2,142) to cows in different parities (heifers and parities 1–3 or more) were used to estimate correlations between the semen quality traits and service sire NRR. In the study, low to moderate heritability (0.06–0.45) was estimated for semen quality traits, indicating the possibility of improving these traits through selective breeding. The study also showed moderate to high genetic and phenotypic correlations between service sire NRR and some of the semen quality traits, including sperm viability pre- and postcryopreservation, motility postcryopreservation, and sperm concentration precryopreservation, indicating the predictive values of these traits for service sire NRR. The positive moderate to high genetic correlations between semen quality and service sire NRR traits also indicated that selection for semen quality traits might be favorable for improving service sire NRR.
Reproductive performance is of paramount economic importance in the livestock industry, including dairy cattle production. Several studies in dairy and beef cattle have explored the genetic parameters of female fertility (
), but few have investigated the genetics of service sire fertility and its association with semen characteristics. Low semen quality and quantity have been shown to contribute to a significant percentage of reproductive failures in AI dairy cattle (
). Therefore, selective breeding to improve semen quality traits has the potential to increase conception rate, thereby lowering cost per pregnancy. Additionally, improving semen quality has the potential to increase the quality and quantity of semen produced by genetically superior sires, hence promising wide availability of semen from elite sires at a more reasonable price (
Semen quality traits are routinely recorded at AI centers for production and marketing decisions. Thus, large-scale data on these traits are available and can be an important source of correlated information to improve traditional fertility traits registered in females. Traditional female fertility traits in general tend to have low heritability in different cattle breeds (
Nonetheless, literature on the genetic parameters of semen quality traits is scarce. To our knowledge, no study so far has reported genetic correlations between semen quality measures and service sire NRR. The objectives of this study were to estimate genetic parameters of semen quality traits using large data from routine semen collection in the Nordic Holstein and to estimate genetic correlations between semen quality traits and service sire NRR based on insemination records of cows in different parities.
MATERIALS AND METHODS
Phenotypes
Data on 100,058 ejaculates that were collected between the years 2006 and 2019 from 2,885 Nordic Holstein bulls were provided by Viking Genetics (Randers, Denmark). All ejaculates were collected at Viking Genetics' semen production sites (n = 11) in Denmark, Sweden, and Finland. Semen quality was assessed by trained laboratory technicians immediately after ejaculate collection or postthaw. The analyzed semen quality traits and number of bulls with records for each of these traits are presented in Table 1. All quality traits were evaluated as described previously in
. Briefly, sperm motility was defined as the percentage of motile spermatozoa and assessed subjectively by an experienced technician using phase contrast microscopy. Sperm viability and concentration were assessed using flow cytometric analyses, where viability was defined as the percentage of live spermatozoa. Live or dead spermatozoa were identified as the ones with intact or ruptured cellular membranes, respectively, upon staining with SYBR-14 and propidium iodide. Concentration was assessed using counting beads as described previously (
Age of bulls at ejaculate collection ranged between 7 and 160 mo. Figure 1 presents the distribution of phenotypic measurements for the studied trait across the age of bulls at ejaculate collection in months. For the statistical analysis, age at ejaculate collection was categorized into 3 classes: (1) less than 12 mo, (2) between 12 and 15 mo, and (3) more than 15 mo. The age intervals chosen for classification are related to the maturation and production status of the bulls, indicating peripubertal (age up to 12 mo), pubertal (12–15 mo with the most intense production), and mature (older than 15 mo) bulls.
Figure 1Plots of phenotypic measurements in semen quality traits against age of bulls in months at ejaculate collection. Conc = concentration; Pre = precryopreservation; post = postcryopreservation; N_doses = number of doses per ejaculate.
One of the objectives of this study was to estimate the correlations between semen quality traits and service sire NRR based on NRR at 56 d after the first insemination. However, NRR data were not available at ejaculate level. Therefore, summary data were instead obtained for a total of 2,142 of the 2,885 bulls on NRR s within 56 d after the first insemination of heifers and cows at parities 1, 2, and 3 or more. The NRR data for each bull were collected from insemination of cows across different herds and countries as well as years and seasons. Therefore, the data were corrected to account for effects of herd, year, and season in the country where insemination took place (Denmark, Sweden, or Finland). Nonreturn rate observations from the 3 countries were subsequently combined into weighted average before further analyses. The NRR data were collected and precorrected by the Nordic Cattle Genetic Evaluation center (Denmark). Nonreturn rates were recorded for a bull when the number of inseminations exceeded 100. Number of bulls with NRR data in each class of inseminated cows (i.e., heifer, parity 1–3) and the mean, minimum, and maximum number of inseminations used per bull are presented in Table 2.
Table 2Number of individuals (Nind) and mean number of inseminations recorded per individual for nonreturn rate (NRR) in different parity of inseminated cows and heifers
). The whole-genome variants were selected as peaks of QTL detected from imputed whole-genome sequence data across different European breeds, functional annotations and linkage disequilibrium between SNP, and so on (
Genotype data were subjected to quality control steps, including removing variants with a minor allele frequency of less than 0.01 as well as variants with Hardy-Weinberg equilibrium P-value less than 1 × 10−7. Additionally, markers with a call rate below 85% were excluded. Ultimately, 41,546 SNP were available for the genetic analyses. Map positions were based on the UMD 3.1 reference assembly (
). The statistical model to describe observations of semen quality traits is
y = Xβ + Z1g + Z2c + e,
[1]
where y is the vector of phenotypes, β is the vector of fixed effects [i.e., age class (1–3), production site (1–11), and month and year of ejaculate collection], X is the incidence matrix relating observations with fixed effects, g is the vector of random additive genetic effects, Z1 is the incidence matrix relating observations with random genetic effects, c is the vector of permanent environmental effects, Z2 is the incidence matrix relating observations with permanent environmental effects, and e is the vector of residual effects. The random effects are assumed to be normally distributed. Thus,
where G is a genomic relationship matrix and
is the additive genetic variance;
where I is an identity matrix of dimension equal to the number of individuals with records and
is the permanent environmental variance; and
where I is an identity matrix of dimension equal to the number of records and
is the residual variance.
Univariate analyses were performed to estimate the heritability (h2), which was defined as
[2]
Repeatability (t) was defined as
[3]
Bivariate analyses were implemented to estimate correlations between the semen quality traits using Equation 1.
Correlations between the semen quality traits and NRR were estimated using weighted bivariate analyses with corrected summary phenotypes. For the semen quality traits, the summary phenotypes were calculated by summing all the random effects predicted using Equation 1 for each bull, including the average residual effect. The summary phenotypes for NRR were described above. The bivariate model, including corrected phenotypes for one of the NRR traits (NRR within 56 d after the first insemination of heifers and cows at parities 1, 2, and 3 or more) and corrected phenotypes for one of the semen quality traits, is implemented as follows:
y = 1µ + Zg + e,
[4]
where y is the vector of corrected phenotypes, 1 is the vector of ones, µ is the overall mean, g is the vector of random genetic effects, Z is the incidence matrix relating observations with random genetic effects, and e is the vector of residual effects. For the residuals,
where D is a diagonal matrix with elements
for each bull i for trait j in the bivariate analysis to account for heterogeneous residual variances due to different reliabilities of corrected phenotypes
as a result of differences between bulls in the number of records used to calculate the corrected phenotypes for the respective trait. Reliabilities of the corrected phenotypes
were calculated for each bull as
[5]
where Ni is the number of observations available for bull i for each trait in the bivariate analysis (i.e., the number of records for the semen quality trait or the number of inseminations with NRR outcomes recorded for each bull). Lambda was the ratio of residual to bull variances calculated as
and was calculated separately for each trait in the bivariate analysis using heritability values estimated as described in Equation 2 for the semen quality traits, whereas heritability for the NRR trait was approximated in a step-wise procedure based on the following single-trait analysis:
[6]
where y is the vector of summary NRR data for each bull based on insemination to cows; 1 is the vector of ones, µ is the overall mean; e is the vector of residual effects assumed to be normally distributed:
where D is a diagonal matrix with elements
where W is the number of inseminations for each bull standardized to have a mean value of 1; and Z and g are as described for Equation 4. The heritability estimated using Equation 6 based on the summary NRR data was then transformed to an approximate individual insemination-level heritability by assuming that the heritability based on the summary data is the average reliability of the summary data given the mean number of insemination used to derive the summary data as
where No is the mean number of inseminations per bull. Thus,
which was then used to approximate the individual insemination-level heritability and subsequently the reliabilities and weights of NRR for each bull.
RESULTS
Descriptive Statistics
Table 1 presents the phenotypic mean and coefficients of variation for the semen quality traits studied. The bulls had an average ejaculate volume of 4.98 mL, precryopreservation sperm concentration of 1.29 × 109/mL, sperm motility of 69.17%, and sperm viability of 82.91%. A high coefficient of variability was observed between the records for the number of doses per ejaculate (CV = 0.81), followed by ejaculate volume (CV = 0.49) and semen concentration (CV = 0.44). Phenotypic measurements for the studied semen quality traits appeared to vary across the age of bulls at ejaculate collection (Figure 1). Generally, across the traits, measurements from bulls in early ages (<15 mo) appear to be highly dispersed between the minimum and maximum observed values for the respective trait and tend to stabilize as age increases. This is best reflected in Figure 1 for precryopreservation sperm viability and sperm concentration as well as ejaculate volume. Figure 2 presents box plots of phenotypic values for the semen quality traits in the 3 age classes. Generally, higher phenotypic values were observed for most of the semen qualities, except motility post- and precryopreservation, in the third age class (>15 mo of age at semen collection), followed by the second age group.
Figure 2Box plots showing phenotypic means per age class for the studied semen quality traits. Conc = concentration; Pre = precryopreservation; post = postcryopreservation; N_doses = number of doses per ejaculate. The top and bottom of the boxes represent the upper and lower quartile, respectively; the horizontal line inside the box represents the median; whiskers indicate variability outside the upper and lower quartiles, and the dots along the whiskers indicate outlier records.
Heritability and Repeatability of Semen Quality Traits
Estimates of phenotypic variance, heritability, and repeatability in the semen quality traits are presented in Table 3. Heritability estimates in the semen quality traits were generally low to moderate (0.06–0.45), whereas repeatability estimates were generally moderate to high (0.35–0.61). Number of doses per ejaculate had the highest heritability and repeatability estimates, whereas the estimates for postcryopreservation sperm concentration were the lowest. Comparing between the pre- and postcryopreservation measurements of the same quality indicator, sperm viability had similar heritability in both pre- and postcryopreservation, whereas heritability for precryopreservation sperm motility was more than twice that of postcryopreservation sperm motility.
Table 3Phenotypic variance heritability (h2; SE in parentheses), and repeatability (t; SE in parentheses) for semen quality traits
Genetic and Phenotypic Correlations Among the Semen Quality Traits
Table 4 presents genetic (above diagonal) and phenotypic (below diagonal) correlations among the semen quality traits. High positive genetic and phenotypic correlations were observed between pre- and postcryopreservation sperm viability
in contrast to sperm motility, which had relatively low genetic correlation between the pre- and postcryopreservation measurements
. Postcryopreservation sperm motility showed strong positive genetic correlations with both precryopreservation
and postcryopreservation
sperm viability. Ejaculate volume showed moderate negative genetic correlations with precryopreservation
and postcryopreservation
sperm viability. Number of doses per ejaculate had moderate to high positive genetic correlations with precryopreservation sperm motility
and ejaculate volume
and moderate negative genetic correlations with sperm viability precryopreservation
and postcryopreservation
.
Table 4Genetic (above diagonal) and phenotypic (below diagonal) correlations (SE in parentheses) between the semen quality traits
Genetic and Phenotypic Correlations Between Semen Quality Traits and NRR
Table 5 presents genetic and phenotypic correlations between semen quality traits and service sire NRR traits according to parity of inseminated cows and heifers. Generally, the estimates of correlations between the semen quality traits and NRR varied between parities of inseminated cows and heifers. Compared with the other semen quality traits, postcryopreservation sperm motility
precryopreservation sperm viability
postcryopreservation sperm viability
and precryopreservation sperm concentration
showed relatively higher genetic and phenotypic correlations across the NRR traits defined. For most of these traits shown to have moderate to high correlation with the NRR traits, the genetic and phenotypic correlations estimated based on insemination to cows in parity 3 or more were relatively higher than those estimated based on insemination of heifers and cows in parities 1 and 2. Accordingly, the highest genetic and phenotypic correlations were the ones of postcryopreservation sperm motility
and precryopreservation sperm viability
with the NRR based on insemination of cows at parity 3.
Nonreturn rate for service sires within 56 d after the first insemination of heifers (NRR0) and cows at parities 1 (NRR1), 2 (NRR2), and 3 or more (NRR3).
2 Nonreturn rate for service sires within 56 d after the first insemination of heifers (NRR0) and cows at parities 1 (NRR1), 2 (NRR2), and 3 or more (NRR3).
Phenotypic Trends and Genetic Parameters of Semen Quality Traits
The current study was based on a data set with 100,058 ejaculates from 2,858 bulls, which was one of the largest data sets used in the genetic parameter estimation of semen quality traits in the literature. Our study indicates that measurements in semen quality traits from bulls at an early age might be highly unstable compared with measurements at later ages and that semen quality measurements tend to be higher with a bull's maturation. Bull age at ejaculate collection is known to affect semen characteristics (
Generally, the heritability values estimated for the Nordic Holstein bulls in this study were within the range of heritability estimates reported for semen quality traits in the literature (e.g.,
). Our results indicated generally low to moderate heritability estimates for the semen quality traits, ranging from 0.06 (sperm concentration postcryopreservation) to 0.45 (number of doses per ejaculate).
The lowest heritability estimate was reported for postcryopreservation sperm concentration. Postcryopreservation sperm concentration had also low genetic correlation with precryopreservation sperm concentration. Semen doses are diluted based on observations of other precryopreservation quality indicators, such as sperm viability and ejaculate volume. Therefore, management decisions underlie most of the variation in sperm concentration postcryopreservation rather than bull genetics; therefore, the observed low heritability in this trait is not unexpected.
The relatively lower heritability estimate reported in this study for fresh semen sperm concentration was comparable with the pooled mean heritability estimate reported by
based on a meta-analysis of results from 28 different studies or populations. Our heritability estimate for fresh ejaculate volume in the Nordic Holstein was also comparable with estimates reported by
Heritability estimates for motility precryopreservation in this study were among the high estimates in the literature and substantially higher than the pooled mean heritability estimate of 0.054 reported by the meta-analysis study of
. The genetic correlation between sperm motility pre- and postcryopreservation was quite low despite our expectation of moderate to high estimates. To our knowledge, no studies have reported the genetic correlation between pre- and postcryopreservation sperm motility with which we could compare our findings. Given the relatively higher standard error of the correlation estimate, the estimate could be less reliable due to the relatively small data set for precryopreservation mortality as few of the bulls (29%) have records for this trait. At Viking Genetics AI centers located in Denmark, which account for the majority of semen production, routine evaluation for motility precryopreservation started in 2018. This trait is not routinely evaluated for across all ejaculates, thus limiting the data available for this study. Therefore, all parameter estimates reported for motility precryopreservation in this study should be interpreted cautiously due to the relatively low sample size used in the analyses.
The highest heritability value was estimated for the number of doses per ejaculate followed by ejaculate volume. A very high genetic correlation (0.94) was found between these 2 traits, indicating that ejaculate volume underlies much of the variation in the number of doses possible to produce per ejaculate.
Predictive Value of the Semen Quality Traits for Service Sire NRR
Our study reports genetic correlations between semen quality traits and service sire NRR using relatively large data sets. The results showed moderate to high genetic and phenotypic correlations between NRR and some of the semen quality traits, including sperm viability pre- and postcryopreservation, motility postcryopreservation, and precryopreservation sperm concentration. The current study confirms a previous report based on analysis of phenotypic correlations by
, which suggested promising predictive abilities of pre- and postcryopreservation sperm viability as well as precryopreservation semen concentration for NRR at 56 d post-AI. Our findings of genetic and phenotypic correlation analysis indicate that, in addition to those traits suggested by
, postcryopreservation sperm motility might have promising predictive ability for service sire NRR at 56 d post-AI. Similarly, a phenotypic level study using crossbred Indonesian bulls showed significant relationships between male fertility measured as conception rate and postcryopreservation sperm viability and motility (
). Moreover, because ejaculates with low semen quality measures are not used for insemination, the NRR data are left-censored in relation to the semen quality traits, and hence the genetic and phenotypic correlation estimates in this study might underestimate the true correlations between these traits. Our results also indicate that genetic and phenotypic correlations between the semen quality traits and service sire NRR are affected by parity of inseminated cows, with a trend of higher genetic correlations between some of the semen quality traits and NRR for bulls based on insemination to cows in parity 3.
To our knowledge, this is the first time that genetic correlations between the semen quality traits and service sire NRR have been reported. Due to the current limitations on the ability to capture NRR data at the ejaculate level, our study used summary data based on a varying number of records per bull, which might affect the correlation results given potential variations in NRR between ejaculates from the same bull.
CONCLUSIONS
Based on a large data set of 100,058 ejaculates from 2,858 Nordic Holstein bulls, this study reports low to moderate heritability and moderate to high repeatability estimates for semen quality traits, including pre- and postcryopreservation semen concentration, sperm motility, sperm viability, ejaculate volume, and number of doses per ejaculate. These results indicate the possibility of implementing selective breeding to improve semen quality traits in the Nordic Holstein. Additionally, our study found moderate to high genetic and phenotypic correlations between NRR and some of the semen quality traits. The results indicate that some of the semen quality traits, specifically pre- and postcryopreservation sperm viability, postcryopreservation sperm motility, and precryopreservation sperm concentration, can be useful predictors for service sire NRR. Positive and strong genetic correlations between these semen quality traits and service sire NRR also indicate that selection for the semen quality traits might be favorable for improving service sire NRR.
ACKNOWLEDGMENTS
This work was supported by the EliteSemen project funded by the Milk Levy Foundation (Denmark). The authors declare that they have no conflicts of interest.
REFERENCES
Berry D.P.
Eivers B.
Dunne G.
McParland S.
Genetics of bull semen characteristics in a multi-breed cattle population.
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