Sire Model Research Articles

Macro- and micro-genetic environmental sensitivity of yearling weight in Angus beef cattle

Australian beef cattle experience variable conditions, which may give rise to genotype-by-environment interactions depending on the genotypes’ macro- and/or micro-genetic environmental sensitivity (GES). Macro-GES gives rise to genotype-by-environment interactions across definable and shared environments, while micro-GES causes heritable variation of phenotypes, e.g., the performance of progeny from one sire may be more variable than other sires. Yearling weight (YW) is a key trait in Australian Angus cattle that may be impacted by both macro- and micro-GES. Current models for genetic evaluation of YW attempt to account for macro-GES by fitting sire-by-herd interactions (S × H). Variation in micro-GES had not yet been estimated for YW in Australian Angus. The aim of this study was to estimate genetic variation due to macro- and micro-GES in YW of Australian Angus cattle. A reaction norm with contemporary group effects as the environmental covariate was fitted either as an alternative to or in combination with a random S × H effect to account for macro-GES. Double hierarchical generalised linear models (DHGLM), fitted as sire models, were used to estimate the genetic variance of the dispersion as a measure of micro-GES. Variation due to both macro- and micro-GES were found in YW. The variance of the slope of the reaction norm was 0.02–0.03 (SEs 0.00), while the S × H variance accounted for 7% of the phenotypic variance in all models. Results showed that both a random S × H effect and a reaction norm should be included to account for both macro-GES and the additional variation captured by an S × H effect. The heritability of the dispersion on the measurement scale ranged from 0.06 to 0.10 (SEs 0.00) depending on which model was used. It should therefore be possible to alter both macro- and micro-GES of YW in Australian Angus through selection. However, care should be taken to ensure an appropriate data structure when including sire-by-herd interactions in the mean part of a DHGLM; otherwise, it can cause biased estimates of micro-GES.

Evaluation of the Breeding Value of Rainbow Trout (Oncorhynchus mykkiss) for Body Development Traits Using a Linear Model

Summary The objective of this research is to assess the breeding value of male individuals and calculate heritability values for body weight and body length at 12 months of age in the rainbow trout population in the Republic of Serbia. The study utilized data on the physical development of trout obtained through the Center for Fisheries and Applied Hydrobiology “Mali Dunav”, Experimental Estate “Radmilovac” of the Faculty of Agriculture, University of Belgrade (CEFAH) Breeding Program for rainbow trout in the Republic of Serbia. The fish were raised in individual tanks under tightly controlled conditions at the CEFAH, until they reached 5 months of age. At this point, the fish were marked (with PIT tags Norway) and transferred to commercial fish farms, where monitoring of their production results continued. To estimate the breeding value for body weight and body length of rainbow trout at 12 months of age, we analyzed data collected between 2016 and 2020, which included a total of 2014 individuals. The breeding values were estimated using a sire model. The mixed model incorporated fixed effects (spawning year and sex) and a random effect for the individual sire. The heritability estimate at 12 months of age was 0.44 for body weight, and 0.45 for body length. The breeding values were estimated for 107 sires, with body weight values ranging from −37.83 to +37.83 g and body length values ranging from −14.00 to +14.00 mm. The substantial variation observed within the studied rainbow trout population suggests the potential for further genetic improvement. The high heritability values confirm that further selection can be based on the phenotype. The inclusion of high-quality and validated males in breeding programs will contribute to the enhancement of production characteristics within the existing rainbow trout population in Serbia.

Risk factors and genetic parameter estimates for preweaning survival of Fogera calves

This study utilised mortality records of 1 043 Fogera calves maintained at Andassa Livestock Research Center from 1984 to 2021 to investigate the factors that influence survival and estimate genetic parameters for the preweaning survival of Fogera calves. Survival was defined as the probability of surviving in a given length of time. Survival analysis was done using the Weibull proportional hazard model with Survival Kit version 6.1 software. Genetic variance and heritability estimates were estimated using the sire model. The proportion of right-censored calves up to 1, 4, and 8 months of age was 90.8, 87.8, and 83.5%, respectively. Around 55.8% of all deaths (16.5%) occurred up to one month of age. In addition to birth year, sex, season, and weight at birth were the most important risk factors for calf mortality. The heritability estimates for the survival of calves at 1, 4, and 8 months of age were 0.26 ± 0.14, 0.22 ± 0.13, and 0.38 ± 0.18, respectively. Moderate heritability was estimated at the age of eight months, implying that the inclusion of survival traits in the selection criteria and inclusion in the breeding goal will enhance the preweaning survival rate of calves. Similarly, higher differences in estimated breeding values of sires for survival suggest that the selection of sires with higher estimated breeding values could improve the survival potential of calves. The decreased genetic trend of 3.34% year−1 for the survival potential of Fogera calves during the study periods suggested that survival traits should be included in the breeding goal to reduce the mortality rate.

Genetic parameters and evaluation of mortality and slaughter rate in Holstein and Jersey cows

The longevity of dairy cattle has economic, animal welfare, and health implications and is influenced by the frequency of mortality on the farm and sale for slaughter. In this study cows removed from the herd due to death or slaughter during the lactation were coded 1 and cows that were not terminated were coded 0. Genetic parameters for mortality rates (MR) and slaughter rates (SR) were estimated for Holstein (H) and Jersey (J) breeds by applying both linear (LM) and threshold (TM) sire models using about 1.2 million H and 2,860,000 J cows. Estimated breeding values (EBV) for MR and SR were predicted using animal models to assess the opportunity for selection and genetic trends. Cow termination data, recorded between 1990 and 2020 on a voluntary basis by Australian dairy farmers, were analyzed. Cow MR has increased from below 1% in the 1990s to 4.1% and 3.6% in H and J cows, respectively. Most dead cows (~36%) left the herd before 120 d of lactation, while cows that were slaughtered left the herd toward the end of the lactation. Using the LM, heritability (h2) estimates for MR were lower (1%) than those for SR (2%-3.5%). When h2 were estimated using a TM, the estimates for both traits varied between 4% and 20%, suggesting that the difference in incidence level is one of the reasons for the difference in the h2 values between MR and SR. Early test-day milk yield (MY) and 305-d MY (305-d MY) have unfavorable genetic correlations (0.32-0.41) with MR in both breeds. The genetic correlations of calving interval with MR were stronger (0.54 to 0.68) than with SR (0.28-0.45) suggesting that poor fertility can serve as an early indicator of poor cow health that may lead to increased risk of death. High early test-day somatic cell count is genetically associated with increased likelihood of slaughter (0.24-0.46), but not with increased likelihood of death. In H, 305-d protein yield (PY) had the strongest genetic correlation (-0.34--0.40) with SR whereas in J, both 305-d PY and Fat yield showed high genetic (-0.64--0.70) and moderate environmental (-0.35--0.37) correlations with SR. The genetic correlation of removal from the herd due to death and slaughter was negative (-0.3) in J and zero in H. Strong selection for improved fertility and survival and less selection emphasis for MY, has led to an improvement in the genetic trend for cow MR in H and the trend in J has stabilized. Although genetic evaluations for cow MR are feasible, the reliabilities of the EBV are low and the level of cow MR in Australia are relatively low compared with similar countries. Therefore, genetic evaluation for survival based on mortality and slaughter data could be sufficient in the current selection circumstances where breeding objectives are broadly defined. Nevertheless, all Australian farmers should be encouraged to continue recording mortality and slaughter data for monitoring of the trends and for future development of genetic evaluations.

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.

Genetic evaluation of Kankrej bulls by different sire evaluation methods

The genetic evaluation of Kankrej bulls was done by using three different methods viz., BLUP, Wombat sire, andWombat animal models. First lactation 305-days yields of 348 daughters born to 9 sires and calved from 2016 to 2020 were used for the analyses. For BLUP analysis, season and year of calving were considered as fixed effects, andsire was considered as random effect. The overall average estimate of 2414.40 kg was obtained in BLUP method while 2430.29 kg was obtained in both Wombat sire and animal models. The results revealed that the Wombat animal model discriminated against the sires to the maximum extent followed by Wombat sire and BLUP models. Based on the results, two Kankrej bulls viz., K.8.32 and K.8.62 can be selected as proven bulls for nominated mating for improving the milk productivity of Kankrej cattle.

Relationship between milk urea content and important milk traits in Holstein cattle

Breeding cattle with low nitrogen emissions has been proposed as a countermeasure against eutrophication due to dairy production. Milk urea content (MU) could potentially serve as a new readily measured indicator trait for nitrogen emissions by cows. Therefore, we estimated genetic parameters related to MU and its relationship with other milk traits. We analysed 4 178 735 milk samples collected between January 2008 and June 2019 from 261 866 German Holstein dairy cows during their first, second, and third lactations. Restricted maximum likelihood estimation was conducted using univariate and bivariate random regression sire models in WOMBAT. We obtained moderate average daily heritability estimates for the daily MU of 0.24 in first lactation cows, 0.23 in second lactation cows, and 0.21 in third lactation cows with average daily genetic SDs of 25.16 mg/kg, 24.93 mg/kg, and 23.75 mg/kg, respectively. Averaged over days in milk, the repeatability estimates were low at 0.41 in first, second, and third lactation cows. A strong positive genetic correlation was found between MU and milk urea yield (MUY; 0.72 on average). In addition, 305-day heritabilities were estimated as 0.50, 0.52, and 0.50 in first, second, and third lactation cows, respectively, with genetic correlations of 0.94 or higher for MU in different lactations. By contrast, the averaged estimates of the genetic correlations between MU and other milk traits were low (−0.07 to 0.15). Moderate heritability estimates clearly allow the possible selection for MU, and the near-zero estimates of genetic correlations indicate no risk of undesired correlated selection responses in other milk traits. However, a relationship still needs to be established between MU as an indicator trait and the target trait, defined as total individual nitrogen emissions.

Improving accuracy and stability of genetic predictions for dairy cow survival

Context Cow survival is an important trait for dairy farm profitability and animal welfare, yet it is difficult to improve because of its complexity arising, in part, from varied reasons for culling and delay in getting actual culling data, which leads to low accuracy and instability of genetic predictions. Aims To explore the benefits of partitioning the cow survival trait into ‘early survival’ (survival coded as a binary trait from the first to the second lactation) and ‘late survival’ (survival from the second to later lactations) on genetic predictions in addition to predictors of culling decisions. Methods The raw phenotypic survival records for 1 619 542 Holstein and 331 996 Jersey cows were used in our study. All cows within each herd were allocated to either a reference or validation set. The accuracy and stability of genetic predictions were compared across lactations in the validation set. Further, we estimated the phenotypic and genetic correlation between overall, early or late cow survival and production, type, workability, and fertility traits using bivariate sire models. Key results The heritability of overall survival in Jerseys (0.069 ± 0.003) was higher than in Holsteins (0.044 ± 0.001). The heritability of early survival was higher than that of late survival in Holstein (0.039 ± 0.002 vs 0.036 ± 0.001) and Jersey (0.080 ± 0.006 vs 0.053 ± 0.003). The genetic correlation between early and late survival was high in both breeds (0.770 ± 0.017 in Holstein and 0.772 ± 0.028 in Jersey). Adding survival information up to the sixth lactation had a large effect on genetic predictions of overall and late survival, whereas the predictions of early survival remained the same across lactations. Milk and protein yields, somatic cell score, fertility and temperament were highly correlated with early survival in Holstein and Jersey. However, the genetic correlations between production, type or workability traits and late survival were generally weaker than those and early survival. Conclusions Early and late survival should be considered as different traits in genetic evaluations, because they are associated with different culling decisions. Implications Partitioning cow survival into early and late survival and analysing them as two correlated traits could improve the accuracy and the stability of estimated breeding values compared with analysing overall survival as a single trait.

Reaction-norm analysis of neonatal lamb mortality suggests heritability varies with cold-stress: an example in the Elsenburg Merino selection lines

Context Coping with high levels of cold stress should be beneficial to survival of lambs, given the high mortality rate associated with severe winter storms. The Elsenburg Merino selection experiment involved divergent selection for reproduction. Phenotypic results comparing the positively selected H-Lines and negatively selected L-Lines suggested that cold-stress adaption could have contributed to the favourable genetic trends for survival of H-Line lambs. However, observing the genetic merit of better adapted animals depends on the presence of cold stress at the time of recording. A genotype by environment component (G × E) could, thus, be important when assessing survival/mortality phenotypes. Aim This study proposed the genetic analysis of this possible G × E component and compared the H- and L-Lines in this regard. Methods The sire model allowed the use of progeny phenotypes for neonatal mortality recorded during different levels of cold stress, and the possible G × E could be investigated through the reaction-norm approach. Genetic parameters were evaluated as random regression components by implementing a Gibbs sampling approach. A data set of 5723 individual lamb records was analysed as the progeny of 213 sires. Results A modelled G × E component played an important role in mortality outcomes, with the mean estimate (and 95% confidence interval) for the slope ( σ s b 2 = 0.113 [ 0.0019 – 0.28 ] AN22464_IE1.gif) only marginally smaller than the corresponding estimate for the intercept ( σ s a 2 = 0.124 [ 0.003 – 0.26 ] AN22464_IE2.gif). The reaction-norm model showed a higher heritability (h2 ± posterior standard deviation) for mortality at 3 days of age during high cold-stress (0.22 ± 0.16 at ~1100 KJm−2h−1) than during mild (0.13 ± 0.10 at ~960 KJm−2h−1) conditions, suggesting a greater ability to discriminate between sires at increasing stress levels. Conclusions Failure to account for this G × E component putatively contributes to the low h2 commonly reported for survival traits. The higher h2 at increased levels of cold stress could have played an important part in the higher survival of the H-Line progeny, who were better at coping with cold, wet and windy conditions. Implications Larger studies representing a wider environmental trajectory are recommended. This should be very feasible since cold stress can be derived from commonly available weather-station data.

Comprehensive genetic analysis of linear type traits for characterization of the Sahiwal cattle in an organized herd

Sahiwal is one of the most important dairy cattle breeds of the Indian subcontinent. A holistic and balanced approach to selection and breeding strategies must be adopted to bring about desirable genetic improvement in livestock, including indigenous cattle. The inclusion of linear type traits for dairy cattle selection in any breed improvement program has not been carried out in India so far. Therefore, this study was taken up to characterize Sahiwal cattle, on the basis of linear type traits. Data was collected on adult Sahiwal cows up to their 10thparity, maintained at Institute herd of Indian Council of Agricultural Research- National Dairy Research Institute, Karnal, Haryana from 2006-2021. Data were analysed using Least Squares Maximum Likelihood (LSMLMW), considering a sire model for the present study. Parity, season and period of calving were taken as fixed effect and age at first calving as covariable. Sire or animal was considered as random variable. Least squares means of objective linear type traits viz., stature was 125.97±0.68 cm, body length 136.58±1.01 cm, chest girth 173.04±1.14 cm, body depth203.40± 1.39 cm, rump angle 14.50±0.39 cm, rump width 20.62±0.28cm, udder depth 20.87±0.41 cm, rear udder height 18.38±0.33 cm, and teat length 6.16±0.24 cm. On the other hand, least square mean scores of subjective linear type traits (1-9 scale) viz. fore teat placement was 6.32±0.46, rear teat placement was 7.27±0.35,rear leg side view was 6.26±0.26, rear leg rear view was 6.28±0.27score, foot angle 6.86±0.27, angularity 34.97±0.50-degree, central ligament 6.55± 0.39, fore udder attachment 5.91±0.32, fore teat placement 6.32±0.46, and rear teat placement was 7.27±0.35. Parity had a significant (p<0.05) effect on fore udder attachment and central ligament and teat length in Sahiwal cattle. Season of calving had the significant (p< 0.05) effect, observed in case of udder depth in Sahiwal cattle. Period of calving had a significant(p<0.05) effect on rump angle, udder depth, teat length, angularity and central ligament in Sahiwal cattle. Based on results of present study, it was observed that Sahiwal cattle establishes a balance between the scoring pattern of linear type traits, as the balance scoring of animals was desirable for better sustainability and production performance of a dairy cattle, on a longer run. Moreover, linear type traits have a better scope in selection process and genetic improvement programs that can be utilized as balanced and comprehensive approach for indigenous dairy cattle.

Genetic associations between mastitis, milk electrical conductivity, and milk flow rate in temperate dairy cows in tropics

Milk electrical conductivity and milk flow rate are potential indicators in selection targeting mastitis resistance. This study aimed to estimate the genetic parameters for clinical mastitis, average daily milk electrical conductivity (EC), milk flow rate (FR), and milk yield (MY) for the first lactation of imported Jersey and Jersey-Friesian dairy cows in Sri Lanka. Genetic parameters for mastitis traits, the prevalence of clinical mastitis in each cow, the duration of clinical mastitis treatment, and the number of episodes of mastitis were estimated using univariate sire models with permanent environmental effect of the cow added to models for prevalence of clinical mastitis in each day of milk over the whole lactation, or within the first 100-days of milk. The genetic parameters for the traits EC, FR, and MY over the whole lactation and for these traits defined for 30-day intervals were estimated using univariate animal models. For all mastitis traits, a zero heritability was estimated under both normal and logit scales. Heritabilities of EC and FR ranged from 0.02 to 0.11 and from 0.02 to 0.14, respectively. Genetic correlations between MY and EC and between MY and FR around peak milk yield were 0.25 ± 0.46 and 0.46 ± 0.29, respectively. Based on the heritability estimates for mastitis, dairy cows in this study cannot be directly selected for mastitis resistance, but indirect selection via EC and FR is feasible. Recording all cases of both sub-clinical and clinical mastitis in subsequent lactations is recommended to aid selection of dairy cows for mastitis resistance.

Targeting improved resilience in Merino sheep – Correlations between immune competence and health and fitness traits

Resilience can be defined as the ability of an animal to remain productive in the face of diverse environmental challenges. Several factors contribute to an animal’s resilience including its ability to resist disease, cope with climatic extremes and respond to stressors. Immune competence, a proxy trait for general disease resistance, is expected to contribute to an animal’s resilience. This research aimed to develop a practical method to assess immune competence in Merino sheep which would not restrict the future sale of tested animals, and to estimate genetic parameters associated with the novel trait. We also aimed to explore associations between immune competence and other industry-relevant disease resistance and fitness-related traits and to assess the ability of immune competence phenotypes to predict health outcomes. Here, the ability of Merino wethers (n = 1 339) to mount both an antibody-mediated and cell-mediated immune response was used to define their immune competence phenotype. For that purpose, antigens in a commercial vaccine were administered at the commencement of weaning and their responses were assessed. Univariate sire models were used to estimate variance components and heritabilities for immune competence and its component traits. Bivariate sire models were used to estimate genetic correlations between immune competence and a range of disease resistance and fitness-related traits. The heritability of immune competence and its component traits, antibody-mediated immune response and cell-mediated immune response were estimated at 0.49 ± 0.14, 0.52 ± 0.14 and 0.36 ± 0.11, respectively. Immune competence was favourably genetically correlated with breech flystrike incidence (−0.44 ± 0.39), worm egg count (−0.19 ± 0.23), dag score (−0.26 ± 0.31) and fitness compromise (−0.35 ± 0.24) but not fleece rot (0.17 ± 0.23). Results suggest that selection for immune competence has the potential to improve the resilience of Merino sheep; however, due to the large standard errors associated with correlation estimates reported here, further studies will be required in larger populations to validate associations between immune competence and disease resistance and fitness traits in Australian Merino sheep.

Assessing various environmental descriptors with respect to genotype x environment interaction for milk production traits in Bavarian Fleckvieh cattle.

Genotype x environment (GxE) interaction for production traits in Fleckvieh cattle was assessed by means of various environmental descriptors (EDs). It was also of particular interest to search for EDs useful for studying differing robustness or resilience of individuals which implies reasonable GxE interaction. The set of studied EDs included farm/herd environment (e.g. herd size, housing/feeding regimes, herd production level), geographical location (e.g. height above sea level), temperature humidity index and fat-to-protein ratio. Milk, fat and protein yield deviations for the first test day, the first 100 days and the 305-day-yield of the first lactation were used as phenotypes. Genetic correlations were estimated with bi- and multivariate sire models in case of categorical EDs and reaction norm sire models in case of continuous EDs. Further, rank correlations of bulls' estimated breeding values were calculated for different environmental levels/classes. Almost all estimated genetic correlations were significantly different from 1, but not <0.93. There were some exceptions for extremely different classes/levels of some EDs (e.g. average herd-year production, organic vs conventional farm systems, way of concentrated feed supply). Rank correlations were rarely below 0.95. In summary, no substantial GxE interactions for milk production traits were found with the studied EDs.

Influence of number of daughters per sire on genetic evaluation of Mehsana Buffalo bulls under field progeny testing

First lactation production records of 7,825 Mehsana buffaloes, sired by 200 sires maintained at DudhsagarResearch and Development Association, Dudhsagar Dairy, Mehsana over a period of 25 years (1989-2013), wereutilised for estimation of breeding value of the first lactation milk yield using BLUP - Univariate sire model andanimal model using WOMBAT software. The study aimed to find out the optimum number of daughters that maybe sufficient for more accurate and unbiased estimate of breeding value of Mehsana buffalo bulls. The effectivenessof different models run with different daughters per sire for sire evaluation was judged on the basis of within-sirevariance. The maximum and minimum estimated breeding values were 1924.04 l (BLUP-AM, 5 daughters/sire)and 1855.61 l (BLUP-SM, 30 daughters/sire), respectively. However, error variance estimated was highest whenfive daughters/sire were evaluated and lowest, when 30 daughters/sire were evaluated. The present study revealedthat the sire evaluation with sires having minimum 5, 10 and 15 daughters are equally efficient. However, if we doevaluation with sires having daughters more than 20, 25 or 30, additional accuracy of approximately 2.5%, 3% and5%, respectively may be obtained.

Genotype by Environment Interaction and Selection Response for Milk Yield Traits and Conformation in a Local Cattle Breed Using a Reaction Norm Approach.

Simple SummaryThis study aimed at investigating the impact of genotype by environmental interaction (GxE) in local dual-purpose cattle. Environmental conditions were based on altitude, housing, feeding system, and use of summer pasture. Genetic variability for production traits was larger in farms in plain areas, without the use of summer pasture, with loose housing and feeding of total mixed rations. On the other hand, a greater response for most conformation traits was found for mountain farms, using loose housing, hay-based feeding, and no summer pasture. This study confirms the relevance of considering GxE in local breeds reared in various environments.Local breeds are often reared in various environmental conditions (EC), suggesting that genotype by environment interaction (GxE) could influence genetic progress. This study aimed at investigating GxE and response to selection (R) in Rendena cattle under diverse EC. Traits included milk, fat, and protein yields, fat and protein percentage, and somatic cell score, three-factor scores and 24 linear type traits. The traits belonged to 11,085 cows (615 sires). Variance components were estimated in a two-step reaction norm model (RNM). A single trait animal model was run to obtain the solutions of herd-EC effect, then included in a random regression sire model. A multivariate response to selection (R) in different EC was computed for traits under selection including beef traits from a performance test. GxE accounted on average for 10% of phenotypic variance, and an average rank correlation of over 0.97 was found between bull estimated breeding values (EBVs) by either including or not including GxE, with changing top ranks. For various traits, significantly greater genetic components and R were observed in plain farms, loose housing rearing system, feeding total mixed ration, and without summer pasture. Conversely, for beef traits, a greater R was found for mountain farms, loose housing, hay-based feeding and summer pasture.

Estimation of Genetic Parameters of First Lactation and Life Time Traits Using Sire Model and Animal Model in Crossbred Cattle

Estimation of Genetic Parameters of First Lactation and Life Time Traits Using Sire Model and Animal Model in Crossbred Cattle

PSXI-3 Genome-wide association study for MIR-predicted milk fatty acids composition in Russian Holstein cattle population

Abstract Milk fatty acids (FA) derived from infrared spectra are a new type of traits that allow fast and predictability use their in dairy breeding and herd cattle management. The Holstein animals feature are the high milk yield, but milk composition traits can be different according to population or country origin. The purpose of our study was to find out genetic variation for milk FA and detect QTLs associated with Holstein sires’ EBV in Russian cattle population. For this analysis, we used an experimental dataset for 36982 milk test records from 14 breeding herds in the Moscow region. Individual milk samples per animal analyzed routinely by MilkoScan7 for different FA types: C14:0, C16:0, C18:0, C18:1, saturated, mono- and polyunsaturated, short-, medium- and long-chain. Total number of bulls consisted 778 individuals including 222 animals with genotypes (39051 SNP, Illumina 50K). For calculating EBV by Sire Model, we applied BLUPF90. Plink 1.90 performed quality check control and GWAS procedure. Heritability coefficients were 0.071–0.155 for C14:0-C18:0 levels, 0.196 for C18:1, 0.083 for SFA, 0.018 for PUFA, 0.176 for MUFA, 0.114–0.155 for SCFA-LCFA levels. GWAS revealed most significant (P &amp;lt; 0.001-0.00001) frequently QTLs associated with FA content that were cited in articles previously for BTA5 (CHST11,C18:1), BTA6 (KCNIP4,C18:1; PPRAGC1A,C18:0), BTA11 (NRXN1,LPIN1,C18:1; NBAS,C18:0), BTA26 (PCDH15,PUFA; PRKG1,C18:1). These genes were responsible for synthesis milk fat, fertility, udder conformation traits, lauric, myristic, myristoleic, palmatoleic, oleic and other types of FA. In addition, we identified several QTLs for C14:0, C16:0, SFA, MUFA, SCFA, LCFA on BTA1 (137.32 Mb), BTA10 (5.50 Mb, 9.79 Mb), BTA14 (44.35 Mb), BTA19 (17.57–17.89 Mb) and BTA22 (14.02–14.06 Mb, 20.29–20.45 Mb). Our results are the first steps toward to understanding genetic and genomic mechanisms for using FA in selection processes to improve milk quality for Holstein cattle in Russia. The study was funded by RSF (project No. 21-76-20046)

TH80. CLUSTERING OF SCHIZOPHRENIA CASES BASED ON COMMON GENETIC VARIANTS

Due to the discrepancy of the high energy demand for rapidly increasing milk production and limited feed intake in the transition period around parturition, dairy cows require considerable metabolic adaptations. We hypothesize that some cows are genetically less suited to cope with these metabolic needs than others, leading to adverse follow-up effects on longevity. To test this, we designed a reaction norm model in which functional lifetime was linked to the metabolic challenge in the beginning of the first lactation. As challenge variables, we used either the sum of milk yield or the accumulated fat-to-protein ratio of the first 3 test-days (<120 d in milk), pre-adjusted for herd-test-day variance. We defined a random regression sire model, in which a random slope was estimated for each sire to assess whether a bull had robust (neutral or positive slopes) or non-robust (negative slopes) daughters. We fitted the model to data of ∼580,000 daughters of ∼5,000 Brown Swiss bulls with suitable observations available (≥10 daughters per bull). To validate our proposed model and assess the reliability of the estimated (co)variance components, we conducted an extensive bootstrap approach. For both challenge variables, we found the sire variance for the slope of the random regression to be significantly different from zero, suggesting a genetic component for metabolic adaptability. The results of the study show that the ability to cope with metabolic stress in the transition period has a genetic component, which can be used to breed metabolically robust dairy cows.

Identification of sequence variation in the oocyte-derived bone morphogenetic protein 15 (BMP15) gene (BMP15) associated with litter size in New Zealand sheep (Ovis aries) breeds.

Advances in the study of reproductive traits indicate that functional variation in fertility genes may be useful for improving sheep fertility. The aim of this study was to search for variation in the bone morphogenetic protein 15 gene (BMP15) and ascertain any association with litter size in purebred Finnish Landrace sheep (n = 148), Finnish Landrace × Texel-cross sheep (n = 45), and composite sheep (of varying breed background; n = 58) from New Zealand (NZ). A 482bp and 312bp fragment of exon 1 and 2, respectively, of BMP15 were analysed using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP). The additive and dominance effect of BMP15 variation on litter size were estimated using animal and sire models. Two variants (A and B) were detected in exon 1; nosequence variation was detected in exon 2. Variant A had the nucleotide sequence CTT between positions c.31 and c.33, while variant B had a deletion (c.31_33del). The observed frequency for variant A in the Finnish Landrace sheep, Finnish Landrace × Texel-cross sheep and the composite sheep, was 0.77, 0.92, and 0.68, respectively while the frequency of variant B (c.31_33del) was 0.23, 0.08, and 0.32, respectively. An association between litter size and c.31_33del (P < 0.001) was observed in composite sheep. Analysis of more sheep will be required to confirm these results. Litter size did not differ significantly between sheep breeds regardless of the presence/absence of c.31_33del. Results suggested that c.31_33del might be a genetic marker for improving fecundity in some NZ sheep.

Estimation of genetic parameters for growth and egg related traits in Russian sturgeon (Acipenser gueldenstaedtii)

Russian sturgeon (Acipenser gueldenstaedtii) is one of the species of sturgeon, which has high economic value as its source of caviar. The aim of this study was to estimate genetic parameters of growth and egg related traits in Russian sturgeon. The heritability, genetic and phenotypic correlations and breeding values were estimated for body weight (BW), egg maturation (EM) and egg color (EC). In total, 3385 fish from 26 full-sib families (26 sires and 6 dams) were used for genetic analyses based on animal model (AM), sire model (SM) and sire-dam model (SDM). The results shown that the estimated heritability of BW ranged from 0.18 to 0.21 and the estimated heritability ranged from 0.32 to 0.54 and 0.33 to 0.59 for EM and EC based on three models, respectively. The Pearson and Spearman correlation coefficients among family estimated breeding value (EBV) were high (correlation coefficients ≥0.800), indicating that the predictive ability of different models for family EBVs was consistent. However, AM had a superior ability to predict EBV and SM was the best model for sire selection. The genetic and phenotypic correlations between growth and egg related traits were low, indicating that growth trait and egg related traits were relatively independent traits that could be improved respectively. Our results represent the first report of genetic parameters for growth and egg related traits in Russian sturgeon and indicate that these traits might be improved through selection breeding.