Bayesian estimates of genetic parameters for pre-conception traits, gestation length and calving interval in beef cattle

Population Genetic Features of Calving Interval of Holstein-Friesian Cows Bred in Hungary

Calving interval (CI) data (N = 37,263) from 17,319 cows born 2008-2018 in six herds were assessed. The data were made available by the National Association of Hungarian Holstein Friesian Breeders in Hungary. The effects of some genetic and environmental factors, population genetic parameters, breeding value (BV) of sires, and phenotypic and genetic trends of the CI were estimated. The GLM method was used for studying different effects on the CI. BLUP animal model was used for heritability (h2) and BV estimation. Linear regression analyses were applied for the trend calculation. The mean of the CI was 412.2 ± 2.0 days. The h2 of the CI proved to be low (0.07 ± 0.01 and 0.08 ± 0.01). There were relatively high differences among the sires in the estimated BV. Based on the phenotypic trend calculation, the CI of cows showed decreasing direction by an average of 1.80 days per year (R2 = 0.94; p < 0.01). In the case of genetic trend calculation, the average BV of sires in the CI has decreased -4.94 and -0.31 days per year (R2 = 0.91 and 0.41; p < 0.01).

Estimation of genetic correlations and genomic prediction accuracy for reproductive and carcass traits in Hanwoo cows

This study estimated the heritabilities (h2) and genetic and phenotypic correlations between reproductive traits, including calving interval (CI), age at first calving (AFC), gestation length (GL), number of artificial inseminations per conception (NAIPC), and carcass traits, including carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) in Korean Hanwoo cows. In addition, the accuracy of genomic predictions of breeding values was evaluated by applying the genomic best linear unbiased prediction (GBLUP) and the weighted GBLUP (WGBLUP) method. The phenotypic data for reproductive and carcass traits were collected from 1,544 Hanwoo cows, and all animals were genotyped using Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The genetic parameters were estimated using a multi-trait animal model using the MTG2 program. The estimated h2 for CI, AFC, GL, NAIPC, CWT, EMA, BF, and MS were 0.10, 0.13, 0.17, 0.11, 0.37, 0.35, 0.27, and 0.45, respectively, according to the GBLUP model. The GBLUP accuracy estimates ranged from 0.51 to 0.74, while the WGBLUP accuracy estimates for the traits under study ranged from 0.51 to 0.79. Strong and favorable genetic correlations were observed between GL and NAIPC (0.61), CWT and EMA (0.60), NAIPC and CWT (0.49), AFC and CWT (0.48), CI and GL (0.36), BF and MS (0.35), NAIPC and EMA (0.35), CI and BF (0.30), EMA and MS (0.28), CI and AFC (0.26), AFC and EMA (0.24), and AFC and BF (0.21). The present study identified low to moderate positive genetic correlations between reproductive and CWT traits, suggesting that a heavier body weight may lead to a longer CI, AFC, GL, and NAIPC. The moderately positive genetic correlation between CWT and AFC, and NAIPC, with a phenotypic correlation of nearly zero, suggesting that the genotype-environment interactions are more likely to be responsible for the phenotypic manifestation of these traits. As a result, the inclusion of these traits by breeders as selection criteria may present a good opportunity for developing a selection index to increase the response to the selection and identification of candidate animals, which can result in significantly increased profitability of production systems.

Genomic Predictions in Korean Hanwoo Cows: A Comparative Analysis of Genomic BLUP and Bayesian Methods for Reproductive Traits

This study aimed to predict the accuracy of genomic estimated breeding values (GEBVs) for reproductive traits in Hanwoo cows using the GBLUP, BayesB, BayesLASSO, and BayesR methods. Accuracy estimates of GEBVs for reproductive traits were derived through fivefold cross-validation, analyzing a dataset comprising 11,348 animals and employing an Illumina Bovine 50K SNP chip. GBLUP showed an accuracy of 0.26 for AFC, while BayesB, BayesLASSO, and BayesR demonstrated values of 0.28, 0.29, and 0.29, respectively. For CI, GBLUP attained an accuracy of 0.19, whereas BayesB, BayesLASSO, and BayesR scored 0.21, 0.24, and 0.25, respectively. The accuracy for GL was uniform across GBLUP, BayesB, and BayesR at 0.31, whereas BayesLASSO showed a slightly higher accuracy of 0.33. For NAIPC, GBLUP showed an accuracy of 0.24, while BayesB, BayesLASSO, and BayesR recorded 0.22, 0.27, and 0.30, respectively. The variation in genomic prediction accuracy among methods indicated Bayesian approaches slightly outperformed GBLUP. The findings suggest that Bayesian methods, notably BayesLASSO and BayesR, offer improved predictive capabilities for reproductive traits. Future research may explore more advanced genomic approaches to enhance predictive accuracy and genetic gains in Hanwoo cattle breeding programs.

Genetic analysis of longevity and their associations with fertility traits in Holstein cattle

The increase of longevity is intended to reduce involuntary culling rates, not extend the life span, and it reflects the ability of animals to successfully cope with the environment and disease during production. Sire model, animal model and repeatability animal models were used to estimate the (co) variance components of longevity and fertility traits. Six longevity and thirteen fertility traits were analysed, including herd life (HL), productive life (PL), number of days between first calving and the end of first lactation or culling (L1); number of days between first calving and the end of the second lactation or culling (L2); number of days between first calving and the end of the third lactation or culling (L3); number of days between first calving and the end of the fourth lactation or culling (L4); age at first service, age at first calving (AFC), the interval from first to last inseminations in heifer (IFLh), conception rate of first insemination in heifer, days open (DO), calving interval, gestation length, interval from calving to first insemination (ICF), interval from first to last inseminations in cow (IFLc), conception rate of first insemination in cow, calving ease (CE), birth weight, and calf survival. The estimated heritabilities (±SE) were 0.018 (±0.003), 0.015 (±0.003), 0.049 (±0.004), 0.025 (±0.003), 0.009 (±0.002) and 0.011 (±0.002) for HL, PL, L1, L2, L3 and L4, respectively. Strong correlations were appeared in HL and PL; the genetic and phenotypic correlation coefficients were 0.998 and 0.985, respectively. There were high genetic and phenotypic correlations which were observed in L1 and L2, L2 and L3, L3 and L4, respectively. All fertility traits of heifer showed medium to high heritability, while the cow showed low heritability. All heifer fertility traits had low genetic associations with longevity traits, ranging from -0.018 (L2 and IFLh) to 0.257 (L3 and AFC). Most of the fertility traits showed negative correlations with longevity traits in different parities, and we recommend DO, ICF, IFLc and CE as indirect indicators of longevity traits in dairy cows, but we also need to take into account the differences between parities.

Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed

Simple Summary

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. We have developed a ssGWAS by backsolving the SNP effects after implementing a ssGBLUP. The results showed an apparent heterogeneity of the additive genetic variance across the genome. Some of the genomic regions explaining the most of this additive variance were shared across traits, indicating the presence of pleiotropic effects, which were reflected in their genetic correlations.

Abstract

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: NCK1, MSTN, KCNA3, LCORL, NCAPG, and RIN3.

Genetic Parameters for Age at First Calving and First Calving Interval of Beef Cattle

Simple Summary

Reproductive performance of beef cows affects the profitability of beef production systems. Heritability of fertility traits is generally low, which means that there is a great influence of the nongenetic environmental factors. Selection based on breeding value is an effective way to improve fertility traits, and the knowledge of genetic parameters is necessary for this approach. In this study, the two most common fertility traits—the age at first calving and first calving interval are evaluated. It was found that genetic parameters and genetic correlation between these two traits differ according to population structure (multi-breed population, the population of Aberdeen Angus, and Charolais breed). A breeding strategy should be developed within a breed.

Abstract

The objective of this study was to estimate genetic parameters for age at first calving (AFC) and first calving interval (FCI) for the entire beef cattle population and separately for the Charolais (CH) and Aberdeen Angus (AA) breeds in the Czech Republic. The database of performance testing between the years 1991 and 2019 was used. The total number of cows was 83,788 from 11 breeds. After editing, the data set contained 33,533 cows, including 9321 and 4419 CH and AA cows, respectively. The relationship matrix included 85,842 animals for the entire beef population and 24,248 and 11,406 animals for the CH and AA breeds, respectively. A multibreed multitrait animal model was applied. The estimated heritability was low to moderate. Genetic correlations between AFC and FCI varied depending on the breeds from positive to negative. Differences between variance components suggest that differences between breeds should be considered before selection and breeding strategy should be developed within a breed.

Genetics of heifer reproductive traits in Japanese Black cattle

Objective

The objective of this study was to identify environmental factors strongly associated with and to estimate genetic parameters of reproductive traits in Japanese Black heifers.

Methods

Data included reproduction records of Japanese Black heifers born between 2004 and 2014. First service non-return rate (NRR) to 56 days from first to successful insemination (FS), number of services per conception (IN), age at first calving (AFC) and gestation length were analyzed with the use of the general linear model. Genetic parameters were estimated with the use of the univariate animal model of the residual maximum likelihood.

Results

Averages of reproductive traits over eleven years were assessed, and the effects of farm, year, month, artificial insemination technician and interaction of farm×year on the traits were determined. Estimated heritability of FS was very low and that of AFC was higher than that of the other traits. A close genetic relation was observed among NRR, IN, and FS; however, their heritabilities were very low. AFC shows favorable genetic correlation with IN and FS.

Conclusion

Low heritabilities of most reproductive traits in Japanese Black heifers are strongly influenced by farm management practices, and that large residual variances make genetic evaluation difficult. Among the reproductive traits, AFC is potentially more useful for genetic improvement of heifer reproductive traits because it has high heritability and favorable genetic correlations with IN and FS.

Genetic analysis of female reproductive efficiency, scrotal circumference and growth traits in Nelore cattle

This study estimated the genetic variability and correlations between growth and reproductive traits in Nelore cattle. Annual genetic changes in female reproductive traits were also evaluated using repeated measures. Direct heritability was moderate for the growth traits and scrotal circumference (0.235 ± 0.015 to 0.443 ± 0.006), indicating genetic variability in these traits in the population studied. Maternal heritability was low for weaning height (0.042 ± 0.012) and weaning weight (0.112 ± 0.013). Regarding female reproductive traits, gestation length (GL) exhibited a slightly higher heritability (0.179 ± 0.006) than days to calving (DC) and calving interval (CI) (0.123 ± 0.006 and 0.105 ± 0.008, respectively). Repeatability was lower for GL (0.222 ± 0.006) compared to DC (0.318 ± 0.004) and CI (0.406 ± 0.006). Moderate and positive genetic correlations were obtained between the growth traits and scrotal circumference, ranging from 0.193 ± 0.019 to 0.519 ± 0.007. Weaning height showed low and positive genetic associations with GL (0.138 ± 0.007) and CI (0.189 ± 0.016), but was not correlated with DC (-0.016 ± 0.011). Similarly, weaning weight, yearling height or yearling weight was not associated with any of the female reproductive traits. The genetic correlations between scrotal circumference and female reproductive traits were negative and favorable, but low: -0.116 ± 0.020 (GL), -0.084 ± 0.028 (DC), and -0.054 ± 0.038 (CI). Favorable genetic associations were estimated between all female reproductive traits, ranging from 0.170 ± 0.040 to 0.442 ± 0.050. Genetic changes were favorable for GL and CI (-0.02 days/year and -0.11 days/year, respectively) and unfavorable for DC (0.16 days/year). In conclusion, selection for higher growth using the estimated breeding values for height and weight will not affect the reproductive performance of Nelore females. Nonetheless, simultaneous selection for growth and reproductive traits is possible.

Genetic parameters of reproductive traits in Tunisian Holsteins

Abstract. Multi-trait Bayesian procedure was used to estimate genetic parameters for reproductive traits in Tunisian Holstein cows. A total of 31 348 lactations of the calving years 2005 to 2012 were analyzed. Fertility traits were the calving interval (CI), days open (DO), days to first insemination (DFI), days from first insemination to conception (FIC), and number of inseminations per conception (NI). Posterior means of heritabilities of CI, DO, DFI, FIC, and NI were 0.047, 0.03, 0.025, 0.024, and 0.069, respectively. Posterior means of repeatabilities of the same respective traits were 0.106, 0.094, 0.051, 0.036, and 0.17. Genetic correlations among female fertility traits were also computed. Calving interval and DO had the highest genetic correlation estimate (0.85) because they have overlapping genetic meanings. The lowest genetic correlation estimate (−0.25) was found between DFI and NI. Genetic parameter estimates are low and are even lower than those reported in most literature, implying that more focus should be put upon improving the management of reproduction in dairy cattle herds in Tunisia.

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Assessment of inbreeding depression in a Guzerat dairy herd: effects of individual increase in inbreeding coefficients on production and reproduction

Influences of inbreeding on daily milk yield (DMY), age at first calving (AFC), and calving intervals (CI) were determined on a highly inbred zebu dairy subpopulation of the Guzerat breed. Variance components were estimated using animal models in single-trait analyses. Two approaches were employed to estimate inbreeding depression: using individual increase in inbreeding coefficients or using inbreeding coefficients as possible covariates included in the statistical models. The pedigree file included 9,915 animals, of which 9,055 were inbred, with an average inbreeding coefficient of 15.2%. The maximum inbreeding coefficient observed was 49.45%, and the average inbreeding for the females still in the herd during the analysis was 26.42%. Heritability estimates were 0.27 for DMY and 0.38 for AFC. The genetic variance ratio estimated with the random regression model for CI ranged around 0.10. Increased inbreeding caused poorer performance in DMY, AFC, and CI. However, some of the cows with the highest milk yield were among the highly inbred animals in this subpopulation. Individual increase in inbreeding used as a covariate in the statistical models accounted for inbreeding depression while avoiding overestimation that may result when fitting inbreeding coefficients.

Comparison of ovulation, fertilization and embryonic survival in low-fertility beef cows compared to fertile females

The objective was to determine physiological causes of low fertility in beef cows. Fertility was compared between low-fertility cows (34 British cows and 64 Brahman crossbred cows; cows that did not get pregnant when mated to fertile bulls in one or two previous breeding seasons); fertile cows (16 Brahman crossbreds; cows having a calf in several of the preceding breeding seasons), and virgin heifers (45 Brahman crossbreds, 2 yr of age). Females were mated to fertile bulls and killed 3 or 34 d after breeding to obtain reproductive tracts. There were no significant differences among groups in rates of ovulation or fertilization. Overall, 14% of females failed to ovulate and 24% that ovulated failed to undergo fertilization. The proportion of cows that were not detected in estrus before Day 34 of pregnancy was lower (P<0.01) for low-fertility British cows (5 of 16 cows, 31%) than for other groups, including low-fertility Brahman crossbred cows (23/32, 72%), fertile cows (8/9, 89%), and heifers (21/24, 88%). All cows that did not return to estrus by Day 34 had an identifiable conceptus. The proportion of conceptuses recovered at Day 34 that were classified as normal (weight and length) was lower (P<0.05) for cows with low fertility (British: 2/5, 40%; Brahman crossbred: 9/23, 39%) than for fertile cows (8/8, 100%) or heifers (18/21; 86%). Similarly, the proportion of cows in which a normal embryo was recovered (cows with normal embryos/number of cows mated) was lower (P<0.001) for low-fertility British cows (2/16, 13%) and low-fertility Brahman crossbred cows (9/32, 28%) than for fertile cows (8/9, 89%) and heifers (18/24, 75%). In conclusion, cows that were infertile in previous breeding seasons did not experience reduced ovulation or fertilization rates, but had greater embryonic mortality. These data highlighted the importance of ovulation and fertilization failure and embryonic mortality as important determinants of pregnancy success. Moreover, increased embryonic loss after Day 34 contributed to infertility in low-fertility cows.