Comparison between a sire model and an animal model for genetic evaluation of fertility traits in Danish Holstein population

Genetic Parameters and Genetic Trends for Johne's Disease in U.S. Holsteins: An Updated Study

Johne's disease (JD) is an infectious enteric disease in ruminants, causing substantial economic loss annually worldwide. This work aimed to estimate JD's genetic parameters and the phenotypic and genetic trends by incorporating recent data. It also explores the feasibility of a national genetic evaluation for JD susceptibility in Holstein cattle in the United States (US). The data were extracted from a Johne's disease data repository, maintained at the Council on Dairy Cattle Breeding (CDCB), and initially supplied by 2 dairy records processing centers. The data comprised 365,980 Holstein cows from 1,048 herds participating in a voluntary control program for JD. Two protocol kits, Idexx Paratuberculosis Screening Ab Test (IDX) and Parachek® 2 (PCK), were used to analyze milk samples with the Enzyme-Linked Immunosorbent Assay (ELISA) technique. Test results from the first 5 parities were considered. An animal was considered infected if it had at least one positive outcome. The overall average of JD incidence was 4.72% in these US Holstein cattle. Genotypes of 78,964 SNP markers were used for 25,000 animals randomly selected from the phenotyped population. Variance components and genetic parameters were estimated based on 3 models, namely, a pedigree-only threshold model (THR), a single-step threshold model (ssTHR), and a single-step linear model (ssLR). The posterior heritability estimates of JD susceptibility were low to moderate: 0.11 to 0.16 based on the 2 threshold models and 0.05 to 0.09 based on the linear model. The average reliability of estimated breeding values of JD susceptibility using single-step analysis for animals with or without phenotypes varied from 0.18 (THR) to 0.22 (ssLR) for IDX and from 0.14 (THR) to 0.18 (ssTHR and ssLR) for PCK. Despite no prior direct genetic selection against JD, the estimated genetic trends of JD susceptibility were negative and highly significant (P-value <0.01). The correlations of bulls' predicted transmitting abilities with economically important traits such as milk yield, milk protein, milk fat, somatic cell score, and mastitis were low, indicating a non-overlapping genetic selection process with traits in current genetic evaluations. Our results suggest the feasibility of reducing the JD incidence rate by incorporating it into the national genetic evaluation programs.

Comparison of accuracy of breeding value for cow from three methods in Hanwoo (Korean cattle) population

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.

Genetic evaluation of age at first calving and days open under different censoring scenarios in Iranian Holstein cows

The present study aimed to investigate the effect of censoring, the situations in which incomplete at the time, out of range, and/or delayed records were considered, in the estimation of genetic parameters for age at first calving (AFC) and days open (DO) in Iranian Holstein cows. The dataset included 281,772 records collected from 1991 to 2019 by the Vahdat Cooperative Company, a pioneer dairy farm in Isfahan Province, the central part of Iran. Five animal models including linear model (LM), penalty model (PM), modified penalty model (MPM), linear-threshold model (LTM), and modified linear-threshold model (MLTM) were used for genetic evaluation of the trait studied. The predictive ability of the models was assessed using cross-validation. The lowest mean square of error and highest r(y,y) were obtained under MLTM for AFC and under LTM for DO, indicating that MLTM and LTM are recommended for genetic evaluation of AFC and DO with censored records in Iranian Holstein cows, respectively. The prediction accuracy of the models for AFC was relatively similar, ranging from 0.46 (under LM) to 0.48 (under PM, LTM, and MLTM). For DO, prediction accuracy values ranged from 0.36 (under LM) to 0.47 (under PM and LTM). The posterior mean for heritability of AFC under MLTM was 0.11. There was no significant difference among posterior means for the heritability of AFC under different models. Therefore, LM is preferred for genetic evaluation of AFC in Iranian Holsteins, and taking censored records into account is unnecessary. The posterior mean for heritability of DO under LTM was 0.09. There were no statistically significant differences among the heritability estimates of DO under LTM, PM, and MLTM. But considering censored records for genetic evaluation of DO affects the estimation of heritability and improved model accuracy for this trait. Therefore, LTM is preferred and recommended for genetic evaluation of DO in Iranian Holsteins.

An Appropriate Genetic Approach for Improving Reproductive Traits in Crossbred Thai-Holstein Cattle under Heat Stress Conditions

Thailand is a tropical country affected by global climate change and has high temperatures and humidity that cause heat stress in livestock. A temperature−humidity index (THI) is required to assess and evaluate heat stress levels in livestock. One of the livestock types in Thailand experiencing heat stress due to extreme climate change is crossbred dairy cattle. Genetic evaluations of heat tolerance in dairy cattle have been carried out for reproductive traits. Heritability values for reproductive traits are generally low (<0.10) because environmental factors heavily influence them. Consequently, genetic improvement for these traits would be slow compared to production traits. Positive and negative genetic correlations were found between reproductive traits and reproductive traits and yield traits. Several selection methods for reproductive traits have been introduced, i.e., the traditional method, marker-assisted selection (MAS), and genomic selection (GS). GS is the most promising technique and provides accurate results with a high genetic gain. Single-step genomic BLUP (ssGBLUP) has higher accuracy than the multi-step equivalent for fertility traits or low-heritability traits.

Utility of first lactation fat energy corrected milk yield as a trait for genetic evaluation of Mehsana buffalo bulls using various sire evaluation methods

India being a vegetarian country, milk is the major source of dietary bio-energy, but majority of animals are routinely being evaluated on the basis of their milk producing ability. The present study was aimed to come up with a sire evaluation methodology based on first lactation Fat Energy Corrected Milk Yield (FBE) in order to obtain an accurate and unbiased estimate of breeding value of Mehsana buffalo bulls and ranking them on the basis of their daughter's performance for future herd improvement. Data for the present study included 7825 she buffaloes in their first lactations, extended over a period of 25 years (1989 to 2013), from field progeny testing programme of Dudhsagar Research and Development Association (DURDA), Dudhsagar Dairy, Mehsana, Gujarat. The data were classified into different subclasses based on period, season, cluster and age at first calving group. The average breeding values of Mehsana buffalo bulls evaluated for FBE by least squares method (LSM), best linear unbiased prediction sire model (BLUP-SM) and best linear unbiased prediction animal model (BLUP-AM) methods were 1215.89, 1185.7 and 1185.7 kcal, respectively. BLUP-AM method had lowest error variance as compared to LSM and BLUP-SM methods of sire evaluation. This indicated that BLUP-AM was most efficient method.

Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle

Exploring dominance variance and loci contributing to dominance variation is important to understand the genetic architecture behind quantitative traits. The objectives of this study were i) to estimate dominance variances, ii) to detect quantitative trait loci (QTL) with dominant effects, and iii) to evaluate the power and the precision of identifying loci with dominance effect through post-hoc simulations, with applications for female fertility in Danish Holstein cattle. The female fertility records analyzed were number of inseminations (NINS), days from calving to first insemination (ICF), and days from the first to last insemination (IFL), covering both abilities to recycle and to get pregnant in the female reproductive cycle. There were 3,040 heifers and 4,483 cows with both female fertility records and Illumina BovineSNP50 BeadChip genotypes (35,391 single nucleotide polymorphisms (SNP) after quality control). Genomic best linear unbiased prediction (BLUP) models were used to estimate additive and dominance genetic variances. Linear mixed models were used for association analyses. A post-hoc simulation study was performed using genotyped heifers’ data. In heifers, estimates of dominance genetic variances for female fertility traits were larger than additive genetic variances, but had large standard errors. The variance components for fertility traits in cows could not be estimated due to non-convergence of the statistical model. In total, five QTL located on chromosomes 9, 11 (2 QTL), 19, and 28 were identified and all of them showed both additive and dominance genetic effects. Among them, the SNP rs29018921 on chromosome 9 is close to a previously identified QTL in Nordic Holstein for interval between first and last insemination. This SNP is located in the 3’ untranslated region of gene peptidylprolyl isomerase like 4 (PPIL4), which was shown to be associated with milk production traits in US Holstein cattle but not known for fertility-related functions. Simulations indicated that the current sample size had limited power to detect QTL with dominance effects for female fertility probably due to low QTL variance. More females need to be genotyped to achieve reliable mapping of QTL with dominance effects for female fertility.

Genetic aspects of some reproductive, udder health and energy status traits in Holstein cows

The objective of this study was to estimate heritability as well as genetic and environmental relationships between days to first heat (DFH), days to first service (DFS), interval from calving to conception (ICC), calving interval (CI) and number of inseminations per conception (NIS) with mastitis (Mast), number of mastitis occurrence (NumMast), different measures of somatic cell count (SCC) and fat to protein ratio (F:P) in the first lactation of Holstein cows in Iran using linear and threshold animal and sire models. The 33851 first lactation records of Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analyzed with univariate and bivariate linear and threshold animal and sire models using Gibbs sampling methodology. Data from parity one to nine comprising 62483 records were used to conduct repeatability model analysis for reproductive traits. Heritabilities of the reproduction traits varied from 0.067 (for ICC) to 0.105 (for DFH) using linear animal models. Also, the heritabilities of udder health traits varied from 0.005 to 0.102 using different models. The repeatabilities of reproductive traits ranged from 0.110 to 0.307. In general, the genetic correlations (r_g) between reproduction traits were positive and high (with the exception of r_g between DFH-NIS). The r_g between reproduction traits with udder health traits ranged from -0.029 to 0.359 and 0.151 to 0.584 using linear-linear and threshold-linear animal models, respectively. Generally, there was favorable r_g between reproduction traits with udder health traits; therefore, selection for one set of these traits would improve the correlated traits. However, due to different (co)variance components and economic weights in each country/region, it can be recommended to investigate inclusion of both sets of these traits in breeding objectives.

Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model

Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits.

Variance components and correlations of female fertility traits in Chinese Holstein population

BACKGROUND

The objective of the present study was to estimate (co)variance components of female fertility traits in Chinese Holsteins, considering fertility traits in different parities as different traits. Data on 88,647 females with 215,632 records (parities) were collected during 2000 to 2014 from 32 herds in the Sanyuan Lvhe Dairy Cattle Center, Beijing, China. The analyzed female fertility traits included interval from calving to first insemination, interval from first to last insemination, days open, conception rate at first insemination, number of inseminations per conception and non-return rates within 56 days after first insemination.

RESULTS

The descriptive statistics showed that the average fertility of heifers was superior to that of cows. Moreover, the genetic correlations between the performances of a trait in heifers and in cows were all moderate to high but far from one, which suggested that the performances of a trait in heifers and cows should be considered as different but genetically correlated traits in genetic evaluations. On the other hand, genetic correlations between performances of a trait in different parities of cows were greater than 0.87, with only a few exceptions, but variances were not homogeneous across parities for some traits. The estimated heritabilities of female fertility traits were low; all were below 0.049 (except for interval from calving to first insemination). Additionally, the heritabilities of the heifer interval traits were lower than those of the corresponding cow interval traits. Moreover, the heritabilities of the interval traits were higher than those of the threshold traits when measuring similar fertility functions. In general, estimated genetic correlations between traits were highly consistent with the biological categories of the female fertility traits.

CONCLUSIONS

Interval from calving to first insemination, interval from first to last insemination and non-return rates within 56 days after first insemination are recommended to be included in the selection index of the Chinese Holstein population. The parameters estimated in the present study will facilitate the development of a genetic evaluation system for female fertility traits to improve the reproduction efficiency of Chinese Holsteins.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Genetic analysis of the rates of conception using a longitudinal threshold model with random regression in dairy crossbreeding within a tropical environment

This study was designed to: (i) estimate genetic parameters and breeding values for conception rates (CR) using the repeatability threshold model (RP-THM) and random regression threshold models (RR-THM); and (ii) compare covariance functions for modeling the additive genetic (AG) and permanent environmental (PE) effects in the RR-THM. The CR was defined as the outcome of an insemination. A data set of 130 592 first-lactation insemination records of 55 789 Thai dairy cows, calving between 1996 and 2011, was used in the analyses. All models included fixed effects of year × month of insemination, breed × day in milk to insemination class and age at calving. The random effects consisted of herd × year interaction, service sire, PE, AG and residual. Variance components were estimated using a Bayesian method via Gibbs sampling. Heritability estimates of CR ranged from 0.032 to 0.067, 0.037 to 0.165 and 0.045 to 0.218 for RR-THM with the second, third and fourth-order of Legendre polynomials, respectively. The heritability estimated from RP-THM was 0.056. Model comparisons based on goodness of fit, predictive abilities, predicted service results of animal, and pattern of genetic parameter estimates, indicated that the model which fit the desired outcome of insemination was the RR-THM with two regression coefficients.

Recent developments in cattle, pig, sheep and horse breeding - a review

The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep), several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome – wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

Decomposing variation in dairy profitability: the impact of output, inputs, prices, labour and management

The UK dairy sector has undergone considerable structural change in recent years, with a decrease in the number of producers accompanied by an increased average herd size and increased concentrate use and milk yields. One of the key drivers to producers remaining in the industry is the profitability of their herds. The current paper adopts a holistic approach to decomposing the variation in dairy profitability through an analysis of net margin data explained by physical input-output measures, milk price variation, labour utilization and managerial behaviours and characteristics. Data are drawn from the Farm Business Survey (FBS) for England in 2007/08 for 228 dairy enterprises. Average yields are 7100 litres/cow/yr, from a herd size of 110 cows that use 0·56 forage ha/cow/yr and 43·2 labour h/cow/yr. An average milk price of 22·57 pence per litre (ppl) produced milk output of £1602/cow/yr, which after accounting for calf sales, herd replacements and quota leasing costs, gave an average dairy output of £1516/cow/yr. After total costs of £1464/cow/yr this left an economic return of £52/cow/yr (0·73 ppl) net margin profit. There is wide variation in performance, with the most profitable (as measured by net margin per cow) quartile of producers achieving 2000 litres/cow/yr more than the least profitable quartile, returning a net margin of £335/cow/yr compared to a loss of £361/cow/yr for the least profitable. The most profitable producers operate larger, higher yielding herds and achieve a greater milk price for their output. In addition, a significantly greater number of the most profitable producers undertake financial benchmarking within their businesses and operate specialist dairy farms. When examining the full data set, the most profitable enterprises included significantly greater numbers of organic producers. The most profitable tend to have a greater reliance on independent technical advice, but this finding is not statistically significant. Decomposing the variation in net margin performance between the most and least profitable groups, an approximate ratio of 65:23:12 is observed for higher yields: lower costs: higher milk price. This result indicates that yield differentials are the key performance driver in dairy profitability. Lower costs per cow are dominated by the significantly lower cost of farmer and spouse labour per cow of the most profitable group, flowing directly from the upper quartile expending 37·7 labour h/cow/yr in comparison with 58·8 h/cow/yr for the lower quartile. The upper quartile's greater milk price is argued to be achieved through contract negotiations and higher milk quality, and this accounts for 0·12 of the variation in net margin performance. The average economic return to the sample of dairy enterprises in this survey year was less than £6000/farm/yr. However, the most profitable quartile returned an average economic return of approximately £50 000 per farm/yr. Structural change in the UK dairy sector is likely to continue with the least profitable and typically smaller dairy enterprises being replaced by a smaller number of expanding dairy production units.

Comparison of different models for genetic analysis of clinical mastitis in Austrian Fleckvieh dual-purpose cows

The performance of different models for genetic analyses of clinical mastitis in Austrian Fleckvieh dual-purpose cows was evaluated. The main objective was to compare threshold sire models (probit and logit) with linear sire and linear animal models using REML algorithm. For comparison, data were also analyzed using a Bayesian threshold sire model. The models were evaluated with respect to ranking of sires and their predictive ability in cross-validation. Only minor differences were observed in estimated variance components and heritability from Bayesian and REML probit models. Heritabilities for probit and logit models were 0.06 and 0.08, respectively, whereas heritabilities for linear sire and linear animal models were lower (0.02). Correlations among ranking of sires from threshold and linear sire models were high (>0.99), whereas correlations between any sire model (threshold or linear) and the linear animal model were slightly lower (0.96). The worst sires were ranked very similar across all models, whereas for the best sires some reranking occurred. Further, models were evaluated based on their ability to predict future data, which is one of the main concerns of animal breeders. The predictive ability of each model was determined by using 2 criteria: mean squared error and Pearson correlation between predicted and observed value. Overall, the 5 models did not differ in predictive ability. In contrast to expectations, sire models had the same predictive ability as animal models. Linear models were found to be robust toward departures from normality and performed equally well as threshold models.