Yearling Weight Research Articles

Estimates of genetic parameters and genetic trends for growth traits in Menz sheep under community-based breeding programs

The main objectives of this study were to estimate genetic and phenotypic parameters for growth traits in Menz sheep under community-based breeding programs (CBBPs). Data used in the study were collected from five Menz CBBPs villages during 15-year period (2009–2023). Studied growth traits were birth weight (BW), weaning weight (WW), six-month weight (6 MW), yearling weight (YW), Average daily gain from birth to weaning (ADG1), average daily gain from weaning to six months (ADG2) and average daily gain from six months to yearling (ADG3). Fixed effects were estimated using the GLM procedure of SAS 9.4. Genetic parameters were estimated fitting different univariate animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure with WOMBAT software. The most appropriate model for each trait was determined applying likelihood ratio tests. Model including only direct additive genetic effect was the most appropriate model for BW, YW, ADG2 and ADG3, whereas model including direct additive and maternal additive genetic effect without taking into account covariance between them was the most appropriate for WW, 6 MW and ADG1. Based on the most appropriate models, direct heritability of BW, WW, 6 MW, YW, ADG1, ADG2 and ADG3 were 0.29 ± 0.01, 0.45 ± 0.01, 0.46 ± 0.02, 0.42 ± 0.02, 0.44 ± 0.01, 0.75 ± 0.02 and 0.21 ± 0.02, respectively. The estimated maternal heritability were 0.04 ± 0.01, 0.02 ± 0.01 and 0.02 ± 0.01 for WW, 6 MW and ADG1, respectively. Additive coefficient of variance were ranged from 9.53 % for BW to 33.02 % for ADG2. Moderate to higher estimates of direct heritability and additive coefficient of variation (CVA) in the current study indicates higher potential for genetic improvement of studied traits through direct selection. The genetic trend for the Menz sheep's six-month weight in Molale CBBPs village reveals a promising annual growth rate of 0.20 kg. Optimizing the ongoing breeding program into specializing-sire producer groups and applying intensive selection on the sub-nucleus flock could improve the efficiency of the breeding program. Genetic correlations among the studied traits were ranged from −0.50 for ADG-ADG2 to 0.98 for WW-ADG1. Genetic correlation between 6 MW and other studied traits was positive and moderate in magnitude. To achieve optimum genetic gain, the implemented selection criteria for Menz sheep (6 MW) should be continued.

Machine Learning for the Genomic Prediction of Growth Traits in a Composite Beef Cattle Population.

The adoption of genomic selection is prevalent across various plant and livestock species, yet existing models for predicting genomic breeding values often remain suboptimal. Machine learning models present a promising avenue to enhance prediction accuracy due to their ability to accommodate both linear and non-linear relationships. In this study, we evaluated four machine learning models-Random Forest, Support Vector Machine, Convolutional Neural Networks, and Multi-Layer Perceptrons-for predicting genomic values related to birth weight (BW), weaning weight (WW), and yearling weight (YW), and compared them with other conventional models-GBLUP (Genomic Best Linear Unbiased Prediction), Bayes A, and Bayes B. The results demonstrated that the GBLUP model achieved the highest prediction accuracy for both BW and YW, whereas the Random Forest model exhibited a superior prediction accuracy for WW. Furthermore, GBLUP outperformed the other models in terms of model fit, as evidenced by the lower mean square error values and regression coefficients of the corrected phenotypes on predicted values. Overall, the GBLUP model delivered a superior prediction accuracy and model fit compared to the machine learning models tested.

Preliminary outcomes on phenotypic and genetic parameter estimates for body weight of indigenous Tswana goats in Botswana

The aims of this study were to estimate the genetic and phenotypic parameters for growth traits and evaluate genetic trends on 585 indigenous Tswana goats. The population was maintained under low input production system at the Department of Agricultural Research in Lesego ranch, Botswana, from 2005 to 2008. Data included birth weight (BW), weaning weight (WW), weight at 8 months (PW), yearling weight (YW), pre-weaning average daily gain (ADG) and two post weaning average daily gains (ADG2 and ADGYW). Data was analysed using general linear model of SAS to determine non-genetic effects. Estimation of genetic and phenotypic parameters were estimated using ASREML fitting an animal model that accounted for fixed effect of parity, sex, type of birth and year of birth. Least squares means for BW, WW, PW and YW were 2.88 ± 0.03, 12.15 ± 0.17, 16.52 ± 0.28 and 21.04 ± 0.32Kg, respectively, while those for ADG, ADG2 and ADGYW were 74.52 ± 1.41, 28.78 ± 1.55 and 33.66 ± 2.28 g/day, respectively. Estimates of heritability for BW, WW, PW and YW were 0.79 ± 0.11, 0.63 ± 0.14, 0.32 ± 0.13 and 0.48 ± 0.16, respectively. The genetic correlations for all the traits studied were positive and moderate to high (0.48 to 0.82) whilst phenotypic correlations ranged from 0.21 to 0.72. Positive average genetic trends of 12.32% (WW), 13.39% (PW) and 7.38% (YW) were attained. The results have demonstrated the potential of this breed to be improved through selection.

Evaluating genotype by environment interaction for growth traits in Limousine cattle

Environmental conditions affect the growth and health of animals, making it crucial to quantify heat stress and the genetic basis of heat tolerance in animal breeding. The main objective of this study was to evaluate heat stress on beef cattle growth and investigate the genetic background of tolerance to harsh environmental conditions in the Italian Limousine beef cattle. Three growth traits were analysed: average daily gain (ADG), weaning weight (WW), and yearling weight (YW). Data were collected from animals raised between 1991 and 2022 and combined with 14 environmental covariates. Records for ADG, WW, and YW encompassed 108 205, 100 058, and 24 939 individuals, respectively, with 4 617, 4 670, and 2 048 genotyped individuals. Climatic variables were compared for inclusion in a linear mixed model using the Deviance Information Criterion. Multiple-trait models and genomic information incorporated environmental conditions with the largest impact on the studied traits Genotype by environment interaction (G × E) was detected in all the studied traits, showing substantial heterogeneity of the variance components across the different environments (Env). Heritability for WW remains constant among Env; instead, for ADG and YW decreased under uncomfortable environmental conditions. YW showed the lowest genetic correlation (0.28) between divergent conditions (Env 2 and Env 5,) for ADG and WW correlations dropped below 0.50 among Env. The values of genetic correlations indicate that growth traits are moderately to strongly affected by G × E. Eigenvalue decomposition of the additive genetic (co)variance matrix for ADG, WW, and YW indicated that three components accounted for over 0.80 of the proportion of the variance explained, suggesting different animal performances across Env. Spearman rank correlations showed potential re-ranking of genotyped sires, because ADG, WW, and YW showed correlations between Env below 0.80. The accuracy of single-step genomic EBV was higher compared to EBV for al traits. Overall, the result confirms the existence of G × E for growth traits in the Italian Limousine population. Including G × E in the model allows for more environment-aware predictions, helping breeders understand how different genetic bases respond to varying conditions. Genomic predictions incorporating G × E could accelerate genetic gains and improve response to selection for heat tolerance.

195 Effect of selection for growth and maternal influence on crossbred Angus heifer development

Abstract This multiyear experiment was designed to determine the effects of sire yearling weight (YW) and maternal influence (MILK) expected progeny differences (EPD) on production and fertility of beef replacement heifers. Sires were classified as moderate (< 50th percentile) or high for YW EPD (122 ± 29; from 79 to 172) and as low (< 50th percentile) or high for MILK EPD (27 ± 8; from 5 to 40). Fall-born (n = 214) and spring-born (n = 207) heifers were enrolled in the study. Birth weight (BW), weaning weight (WW), and YW of the heifers were measured. In addition, reproductive tract score (RTS), dry matter intake (DMI), and average daily gain (ADG) while consuming an unprocessed grass hay diet were determined in a subsample of enrolled heifers. Neogen Igenity Beef scores (NIBS) were also run on this subset. Pregnancy rate and conception rate at fixed timed artificial insemination (FTAI) were also determined. Adjusted BW, WW and YW and RTS were analyzed using the GLIMMIX procedure of SAS (9.4, SAS Institute Inc., Cary, NC), with YW and MILK EPD as fixed effects and year of birth as random effect. Effects of sire YW and MILK classification on the likelihood of pregnancy and successful FTAI were also analyzed using the GLIMMIX procedure of SAS. Pearson correlation coefficients between independent and dependent variables were obtained using the CORR procedure of SAS. Sire MILK EPD had no effect (P ≥ 0.13) on the body weight of fall- or spring-born heifers. However, fall-born heifers were 0.12 kg and 0.34 kg heavier (P = 0.06 and 0.001, respectively) per unit increase in sire YW EPD at weaning and yearling time, respectively. There was no effect of sire YW EPD on fall-born heifer DMI as percentage of body weight (DMI % BOW; P = 0.74) nor ADG (P = 0.90) while consuming the low-energy diet. Spring-born heifers had significantly greater (all, P ≤ 0.001) adjusted BW, WW, and YW (0.02, 0.23 and 0.37 kg per unit increase in sire YW EPD, respectively. Reproductive tract score was strong and negatively correlated (P ≤ 0.001) with DMI % BOW. Heifer YW NIBS were moderate and positively correlated (P < 0.001) with ADG. There was a tendency (P = 0.09) for a weak and negative correlation between residual feed intake genetic scores and DMI % BOW. Sire genetic merit for yearling growth was transmitted to replacement heifers. However, neither ADG, nor unprocessed forage DMI % BOW was influenced by genetic potential for growth during this study. Further research is needed to assess the benefits of using genomic profile of heifers for maternal, performance and carcass traits, alongside sire EPDs, when selecting and developing beef replacement heifers.

Genome-wide association study considering genotype-by-environment interaction for productive and reproductive traits using whole-genome sequencing in Nellore cattle

BackgroundThe genotype-by-environment interaction (GxE) in beef cattle can be investigated using reaction norm models to assess environmental sensitivity and, combined with genome-wide association studies (GWAS), to map genomic regions related to animal adaptation. Including genetic markers from whole-genome sequencing in reaction norm (RN) models allows us to identify high-resolution candidate genes across environmental gradients through GWAS. Hence, we performed a GWAS via the RN approach using whole-genome sequencing data, focusing on mapping candidate genes associated with the expression of reproductive and growth traits in Nellore cattle. For this purpose, we used phenotypic data for age at first calving (AFC), scrotal circumference (SC), post-weaning weight gain (PWG), and yearling weight (YW). A total of 20,000 males and 7,159 females genotyped with 770k were imputed to the whole sequence (29 M). After quality control and linkage disequilibrium (LD) pruning, there remained ∼ 2.41 M SNPs for SC, PWG, and YW and ∼ 5.06 M SNPs for AFC.ResultsSignificant SNPs were identified on Bos taurus autosomes (BTA) 10, 11, 14, 18, 19, 20, 21, 24, 25 and 27 for AFC and on BTA 4, 5 and 8 for SC. For growth traits, significant SNP markers were identified on BTA 3, 5 and 20 for YW and PWG. A total of 56 positional candidate genes were identified for AFC, 9 for SC, 3 for PWG, and 24 for YW. The significant SNPs detected for the reaction norm coefficients in Nellore cattle were found to be associated with growth, adaptative, and reproductive traits. These candidate genes are involved in biological mechanisms related to lipid metabolism, immune response, mitogen-activated protein kinase (MAPK) signaling pathway, and energy and phosphate metabolism.ConclusionsGWAS results highlighted differences in the physiological processes linked to lipid metabolism, immune response, MAPK signaling pathway, and energy and phosphate metabolism, providing insights into how different environmental conditions interact with specific genes affecting animal adaptation, productivity, and reproductive performance. The shared genomic regions between the intercept and slope are directly implicated in the regulation of growth and reproductive traits in Nellore cattle raised under different environmental conditions.

Estimation of genetic parameters as well as trends for growth traits in Harnali sheep

The current study focussed on the growth traits pertaining to Harnali sheep maintained at Sheep Farm, LUVAS, Hisar and data were recorded from pedigree sheets of 1278 animals. Growth traits considered were birth weight (BW), weaning weight (WW), six-month weight (6MW), yearling weight (YW), and pre-weaning average daily gain (PRWDG) and least-squares means for corresponding traits found to be 3.28±0.02 kg, 12.89±0.07 kg, 17.06±0.06 kg, 24.36±0.06 kg, and 106.74±0.61 g, respectively. Effect of different factors like period of birth, sex of animal and dams’ weight at lambing was studied on growth traits. Except YW, significant effect of period of birth was observed on all the growth traits. Sex had significant influence on BW only however, dams’ weight at lambing affected significantly all the considered growth traits except YW. By leveraging the sire component of variance and covariance from mixed model analysis, the paternal half-sib correlation method was used to estimate genetic as well as phenotypic parameters. Estimates of heritability for BW, WW, 6MW, YW and PRWDG were 0.28±0.07, 0.33±0.07, 0.31±0.07, 0.12±0.04 and 0.27±0.06, respectively. Genetic as well as phenotypic trends for WW and PRWDG were found to be positive. Moderate range of genetic variability at weaning weight and its positive genetic and phenotypic correlations with growth traits specially six month’s weight indicated that genetic improvement could be possible through early selection at weaning weight in Harnali sheep.

Environmental factors affecting economically important traits of Anatolian buffalo in Yozgat

The aim of the study was to investigate effects of some environmental factors on the growth, reproduction and production traits of Anatolian Buffaloes. The reproduction and production data of 1139 Anatolian buffaloes and the growth records of the calves between 2015 and 2019 in Yozgat province were used. The least-square means of the birth (BW), weaning (WW), sixth month (SMW) and yearling weights (YW) and daily gain between those traits were determined as 30.43, 97.79, 112.98, 169.40, 0.441, 0.459, 0.382 and 0.306 kgs respectively. Calving interval (CI) and service period (SP) were 470.08 and 150.08 days. Lactation milk yield (LMY), milk yield per day of lactation period (MY/LP), milk yield per day of CI (MY/CI), peak yield (PY), day at piek yield (DPY), and persistence (P) were found to be 860.40, 4.447, 1.916, 5.589 kgs, 83.34 days, and 77.35%. The effects of village and sex on BW, WW, SMW and YW were statistically significant (P

110 Effects of sire selection on puberty and reproduction of offspring selected as replacement heifers

Abstract Sire selection is important to maintain the desired genetic capability of any cattle herd; therefore, selection of economic production traits affect profitability by increasing pre- and post-weaning gain and carcass quality potential. Using heifers developed from sires selected for growth and milk traits may have long-term impact on sustainability of the cowherd by influencing mature cow size and milk production. Our objective was to determine the impacts of sires selected for high and moderate growth and high and low milk traits on growth and reproductive performance of replacement heifers. Therefore, we selected replacement heifers sired by bulls within the upper 5th and 50th percentiles of the Angus breed for yearling weight (YW) EPD as high growth (HG) moderate growth (MG), the upper 15th percentile of the Angus breed for milk EPD as high milk (HM), and the lower 15th percentile for low milk (LM) in a 2×2 factorial design resulting in 4 treatments: HG/HM, HG/LM, MG/HM, and MG/LM. Heifers (n = 46) from appropriate AI sires that were born and developed at Oklahoma State University – Range Cow Research Center – South Range Unit were selected as replacements. They were raised on a base diet of dry, dormant tall grass prairie and moderate quality grass hay following weaning and 2 kg/d of 16% crude protein concentrate supplement. Body weights and biometrics were recorded at weaning and approximately at 1-yr of age, and blood was collected at 11 and 0 d before synchronization for progesterone analysis to determine pubertal status pre-breeding. Estrus was synchronized using the 14-d CIDR-PG with timed AI method followed by a 45-d natural service breeding period. Pregnancy checks were conducted by serum collection 35-d following AI and via rectal palpation by an experienced veterinarian 112 d after removal of the bulls. Statistical analyses were performed using the mixed procedure of SAS (SAS 9.4, SAS INC., Carey, NC). Heifers from high growth sires were 28 kg heavier at weaning (P < 0.01) and 26 kg heavier as yearlings (P < 0.01) than those sired by moderate growth sires, while sire milk EPD affected neither (P ≥ 0.55). High growth and high milk sired heifers had greater hip heights, frame scores and thus greater (P ≤ 0.05) estimated mature body weight (EMBW). Despite this, sire selection had no impact on percentage of heifers pubertal before breeding, AI pregnancy, or the total pregnancy rates (P > 0.24) Based on these data, selection of sires for HG and HM leads to increased productivity of the offspring but gives rise to larger mature cows, which may pressure grazing resources in limited resource environments impacting the long-term sustainability of the cow-calf enterprise.

Evaluation of models for estimation of genetic parameters for post-weaning body measurements and their association with yearling weight in Nellore sheep.

The objective of this study was to obtain (co) variance components and genetic parameter estimates for post-weaning body measurements such as body length (BL), height at withers (HW), and chest girth (HG) recorded at six (SBL, SHW, and SHG), nine (NBL, NHW, and NHG) and twelve (YBL, YHW, and YHG) months of age along with yearling weight (YW) in Nellore sheep maintained at livestock research station, Palamaner, Andhra Pradesh, India and also the association among body measurements with YW was studied. Data on 2,076 Nellore sheep (descended from 75 sires and 522 dams) recorded between 2007 and 2016 (10 years) were utilized in the study. Lambing year, sex of lamb, season of lambing and parity of dam were included in the model as fixed effects and ewe weight was kept as a covariate. Analyses were conducted with six animal models with different combinations of direct and maternal genetic effects using restricted maximum likelihood procedure. Best model for each trait was determined based on Akaike's information criterion. Moderate estimates of direct heritability were obtained for the studied traits viz., BL (0.02 to 0.24), HW (0.31 to 0.49), and CG (0.08 to 0.35) and their corresponding maternal heritability estimates were in the range of 0.00 to 0.07 (BL), 0.13 to 0.17 (HW), and 0.07 to 0.13 (CG), respectively. Positive direct genetic and phenotypic correlations among the traits and they ranged from 0.07 (YBL-YW) to 0.99 (SBL-SHG, SHG-YW, and NBL-YBL) and 0.01 (SBL-YBL) to 0.99 (NBL-NHG), respectively. Further, the genetic correlations among all the body measurements and YW were positive and ranged from 0.07 (YW and YBL) to 0.99 (YW and SHG). There was a strong association of chest girth at six months with YW. Further, it is indicated that moderate improvement of post-weaning body measurements in Nellore sheep would be possible through selection.

Genotype-by-gestational thermal environment interaction and its impact on the future performance of tropical composite beef cattle offspring.

With global warming, there are growing challenges for raising taurine and composite beef cattle populations in tropical regions, including elevated temperatures, limited forage availability, parasite infestation, and infectious diseases. These environmental factors can trigger specific physiological responses in the developing fetus, which may have long-term implications on its performance. Therefore, the main objective of this study was to assess the influence of naturally induced thermal stress during the gestation period on the subsequent performance of tropical composite beef cattle progeny. Furthermore, we aimed to investigate the impact of genotype-by-gestational thermal environment interaction (G×Eg) on traits under selection pressure in the breeding population. A total of 157,414 animals from 58 farms located in various Brazilian states were recorded for birth weight (BW), preweaning weight gain (PWG), yearling weight (YW), hip height (HH), scrotal circumference (SC), and days to first calving (DFC). We first applied a linear regression model to the BW data, which revealed that the last 40d of gestation were suitable for calculating the mean temperature humidity index (THIg). Subsequent regression analyses revealed that for every 10-unit increase in THIg, detrimental effects of approximately 1.13% to 16.34% are expected for all traits evaluated. Genetic parameters were estimated through a reaction norm model using THIg as the environmental descriptor. The posterior means of heritability estimates (SD) were 0.35 (0.07), 0.25 (0.03), 0.31 (0.03), 0.37 (0.01), 0.29 (0.07), and 0.20 (0.09) for the direct effect of BW, PWG, YW, HH, SC, and DFC, respectively. These estimates varied along the range of THIg values, suggesting a variable response to selection depending on the thermal environment during gestation. Genetic correlation estimates between more divergent THIg values were low or negative for YW, PWG, and DFC, indicating that the best-performing individuals at low THIg values may not perform as well at high THIg values and vice versa. Overall, thermal stress during gestation impacts the future performance of beef cattle offspring. Our results indicate the need for developing effective breeding strategies that take into account G×Eg effects and the re-ranking of breeding animals along the THIg scale, particularly for traits such as DFC that are highly sensitive to thermal stress.

Detection and characterization of copy number variation in three differentially-selected Nellore cattle populations.

Introduction: Nellore cattle (Bos taurus indicus) is the main beef cattle breed raised in Brazil. This breed is well adapted to tropical conditions and, more recently, has experienced intensive genetic selection for multiple performance traits. Over the past 43years, an experimental breeding program has been developed in the Institute of Animal Science (IZ, Sertaozinho, SP, Brazil), which resulted in three differentially-selected lines known as Nellore Control (NeC), Nellore Selection (NeS), and Nellore Traditional (NeT). The primary goal of this selection experiment was to determine the response to selection for yearling weight (YW) and residual feed intake (RFI) on Nellore cattle. The main objectives of this study were to: 1) identify copy number variation (CNVs) in Nellore cattle from three selection lines; 2) identify and characterize CNV regions (CNVR) on these three lines; and 3) perform functional enrichment analyses of the CNVR identified. Results: A total of 14,914 unique CNVs and 1,884 CNVRs were identified when considering all lines as a single population. The CNVRs were non-uniformly distributed across the chromosomes of the three selection lines included in the study. The NeT line had the highest number of CNVRs (n = 1,493), followed by the NeS (n = 823) and NeC (n = 482) lines. The CNVRs covered 23,449,890 bp (0.94%), 40,175,556 bp (1.61%), and 63,212,273 bp (2.54%) of the genome of the NeC, NeS, and NeT lines, respectively. Two CNVRs were commonly identified between the three lines, and six, two, and four exclusive regions were identified for NeC, NeS, and NeT, respectively. All the exclusive regions overlap with important genes, such as SMARCD3, SLC15A1, and MAPK1. Key biological processes associated with the candidate genes were identified, including pathways related to growth and metabolism. Conclusion: This study revealed large variability in CNVs and CNVRs across three Nellore lines differentially selected for YW and RFI. Gene annotation and gene ontology analyses of the exclusive CNVRs to each line revealed specific genes and biological processes involved in the expression of growth and feed efficiency traits. These findings contribute to the understanding of the genetic mechanisms underlying the phenotypic differences among the three Nellore selection lines.

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.

Longitudinal genetic dynamics of weaning index and implications for cow-calf production efficiency

In beef cattle, the selection for higher weights at young ages has been questioned with the argument that this criterion may increase the adult weight of cows, resulting in higher costs. Therefore, selection criteria should be employed to increase weights at young ages with minimal impact on the adult weight of cows. Additionally, the relationship between measures of cow production efficiency and other well-established selection criteria in breeding programs remains poorly understood. The objective of this study was to longitudinally evaluate the relationship between the weaning index (WIndex) as a measure of efficiency and growth traits of the cows. Possible changes over time in WIndex due to selection applied for yearling weight (YW) were also investigated. The WIndex was proposed to maximize genetic response in the weaning weight of the calf while maintaining genetic gain in BW of the cow at zero. A random regression model was adopted to estimate correlations between WIndex, BW, hip height (HH), and body condition score (BCS) using records of Nelore cows from three lines. Genetic trends were calculated for the control line (NeC) and lines selected for greater YW (NeS and NeT). The age of 3 years was the most critical for the weaning efficiency of the cows. At this stage, young cows are still growing and wean lighter calves than their adult counterparts. The genetic correlation estimates between WIndex and BW (−0.58 to 0.04), HH (−0.05 to −0.34), and BCS (−0.51 to −0.17) were close to zero or negative. BW and HH were strongly correlated genetically across all ages (0.73–0.76). In general, HH exhibited a weak and negative genetic relationship with BCS. The genetic correlation between BW and BCS was stronger for advanced ages (0.45–0.68). In lines selected for YW, important increases in WIndex were observed. However, NeS has been selected since the 1980s until the present for YW, and thus, it showed a more pronounced trend of increasing BW and, consequently, a more modest trend of increasing WIndex compared to NeT. In contrast, WIndex exhibited a trend close to zero for NeC. In this context, monitoring HH and BCS can be useful to avoid losses in the weaning efficiency of cows. Furthermore, we suggest that one way to mitigate efficiency losses in calf production could involve stabilizing the BW of cows and increasing the weaning weight of calves using the WIndex.

Development of selection strategies for genetic improvement in production traits of Mecheri sheep based on a Bayesian multi trait evaluation

The progression of genetic selection techniques to enhance farm animal performance traits is guided by the present level of genetic variation and maternal impact in each trait, as well as the genetic association between traits. This study was conducted on a population of Mecheri sheep maintained from 1980 to 2018 at Mecheri Sheep Research Station, Pottaneri, India, to determine variance and covariance components, as well as genetic parameters for various production performance traits. A total of 2616 lambs, produced by 1044 dams and 226 sires, were examined in the study and the production traits of Mecheri sheep assessed include birth weight (BW), weaning weight (WW), six-month weight (SMW), nine-month weight (NMW), and yearling weight (YW). The Bayesian approach, using the Gibbs sampler, analyzed six animal models with different combinations of additive direct and maternal additive effects. Direct genetics, maternal genetics, and residual effects models were the major contributors to total phenotypic variation for all the production traits studied. Direct heritability estimates of birth weight, WW, SMW, NMW, and YW were 0.25, 0.20, 0.12, 0.14, and 0.13, respectively. The maternal heritability estimated for BW, WW, SMW, NMW, and YW were 0.17, 0.10, 0.12, 0.14, and 0.14, respectively. The maternal effects had a major impact on the pre-weaning production traits. The genetic correlations estimated between different pairs of production traits studied ranged from 0.19 to 0.93. The body weight at birth exhibited a higher genetic relationship with weaning weight than post-weaning growth characteristics, and the genetic correlation between weaning weight and post-weaning attributes was moderate to high (0.52 to 0.72). Based on the additive genetic variance in weaning weight and the correlation estimates of weaning weight with post-weaning traits, weaning weight was proposed as a selection criterion for improving growth traits in Mecheri sheep.

118 Variance Components for Age at First Calving and Yearling Weight When Accounting for Age Differences at Fixed Breeding Dates in a Contemporary Group

Abstract The ability of a heifer to calve earlier in a breeding season has implications on the economic success of heifers in a production system. Heifers that calve earlier in a calving season have increased calf performance, improved subsequent fertility, and a longer productive life in the herd. Production systems typically breed heifers during fixed breeding dates, with heifers of variable ages in the same contemporary group. The objective of this study was to determine if heifer yearling weight (YW) or age differences going into a fixed breeding period influenced the additive genetic variance of age at first calving (AFC) explained in a multi-breed population. Heifer fertility data were obtained from International Genetic Solutions. Females with exposure and calf production records were used to identify individuals calving between 630 and 810 days of age. Females with embryo transfer, multiple birth progeny, and an age differential (DIFF) greater than 100 days were excluded. Age differential was defined as the difference in days between an individual’s birth date and the earliest birth date of an animal in a defined contemporary group. Contemporary group was defined as; breeder, herd, year born, birth and yearling group. After data filtering, there were 149,350 calving records. A 3-generation pedigree file was used containing 365,637 animals, with 37,420 unique sires and 219,533 unique dams. Two bivariate multi-trait animal models for AFC and YW with random additive genetic and residual effects and fixed effects of contemporary group, breed proportion, and % retained hybrid vigor were used. The first model consisted of the aforementioned effects while the second model included DIFF as an additional fixed effect. Analyses were performed using ASReml 3.0. When DIFF was not included as a fixed effect, the additive, residual and phenotypic variances for AFC were 126.1, 456.8, and 582.9 d2, respectively, and the genetic correlation between AFC and YW was 0.36 ± 0.02. When DIFF was included as a fixed effect, the additive, residual, and phenotypic variances for AFC were 10.0, 326.0, and 336.0 d2, respectively. The genetic correlation between AFC and YW was 0.19 ± 0.04. In the absence of DIFF, the heritability estimates for AFC and YW were 0.22 ± 0.01 and 0.44 ± 0.01, respectively but were 0.03 ± 0.003 and 0.44 ± 0.01 respectively, when DIFF was included. Age differential was a significant effect on AFC at –0.86 (P < 0.0001). The low additive variance of AFC when accounting for DIFF suggests that the influence of a female's age going into a fixed breeding date explains much of the variation in AFC. The low heritability estimate for AFC and genetic correlation with YW suggests that selection for improved AFC will be difficult using this method and that producers should instead focus on improved management practices to ensure females calve earlier in a calving season.

Genetic associations between stayability to consecutive calvings and traits of economic interest in taurine and zebu breeds.

Stayability (STAY) is a way to evaluate the productive longevity of females. Measuring the STAY at each cow calving allows earlier indicators of longevity to be obtained. Our objective with this study was to verify the association between STAY and consecutive calvings and traits potentially used as selection criteria in beef cattle, such as age at first calving (AFC), days to calving (DC), weaning weight (WW), and yearling weight (YW). Data from the Nelore, Angus/Brangus, and Hereford/Braford breeds were used. The estimation of variance components and subsequent prediction of breeding values were performed for all traits. The estimated breeding values (EBV) were used to analyse the association between STAY and the other traits. The Pearson's correlation estimated between the EBV for the intercept coefficient for STAY to consecutive calvings and those of AFC, DC, WW (direct and maternal effects), and YW was favourable and of low magnitude (<0.25) depending on the breed studied. The influence of the genetic merit of AFC on the chance of selection for STAY was favourable and relevant regardless of the intensity of selection and breed. DC and WW (maternal effect) traits were favourably influenced by the chance of selection for STAY, irrespective of breed. The WW (direct effect) did not affect the chance of selection for STAY for the Nelore and Hereford/Braford breeds and negatively influenced, but to a small extent, the Angus/Brangus breed. For YW, an increase in genetic merit affected the chances of selection for STAY, depending on the breed and selection intensity evaluated. The influence of the genetic merit for AFC, DC, and WW (maternal effect) on the chance of selection for STAY to consecutive calvings was favourable and relevant regardless of the selection intensity scenario evaluated. The WW (direct effect) did not influence the chance of selection for STAY. For the scenario with high selection intensity, the selection for YW favourably influenced the chance of selection for STAY in Angus/Brangus and Hereford/Braford breeds but not in Nelore.

Including genomic information in the genetic evaluation of production and reproduction traits in South African Merino sheep.

Genomic selection (GS) has become common in sheep breeding programmes in Australia, New Zealand, France and Ireland but requires validation in South Africa (SA). This study aimed to compare the predictive ability, bias and dispersion of pedigree BLUP (ABLUP) and single-step genomic BLUP (ssGBLUP) for production and reproduction traits in South African Merinos. Animals in this study originated from five research and five commercial Merino flocks and included between 54,072 and 79,100 production records for weaning weight (WW), yearling weight (YW), fibre diameter (FD), clean fleece weight (CFW) and staple length (SL). For reproduction traits, the dataset included 58,744 repeated records from 17,268 ewes for the number of lambs born (NLB), number of lambs weaned (NLW) and the total weight weaned (TWW). The single-step relationship matrix, H, was calculated using PreGS90 software combining 2811 animals with medium density (~50 K) genotypes and the pedigree of 88,600 animals. Assessment was based on single-trait analysis using ASREML V4.2 software. The accuracy of prediction was evaluated according to the 'LR-method' by a cross-validation design. Validation candidates were assigned according to Scenario I: born after a certain time point; and Scenario II: born in a particular flock. In Scenario I, the genotyping rate for the reference population between 2006 and the 2013 cut-off point approached 7% of animals with phenotypes and 20% of their sires. For reproduction traits, about 20% of ewes born between 2006 and 2011 cut-off were genotyped, along with 15% of their sires. Genotyping rates in the validation set of Scenario I were 3.7% (production) and 11.4% (reproduction) for candidates and 35% of their sires. Sires were allowed to have progeny in both the reference and validation set. In Scenario I, ssGBLUP increased the accuracy of prediction for all traits except NLB, ranging between +8% (0.62-0.67) for FD and +44% (0.36-0.52) for WW. This showed a promising gain in accuracy despite a modestly sized reference population. In the 'across flock validation' (Scenario II), overall accuracy was lower, but with greater differences between ABLUP and ssGBLUP ranging between +17% (0.12-0.14) for TWW and +117% (0.18-0.39) for WW. There was little indication of severe bias, but some traits were prone to over dispersion and the use of genomic information did not improve this. These results were the first to validate the benefit of genomic information in South African Merinos. However, because production traits are moderately heritable and easy to measure at an early age, future research should be aimed at best exploiting GS methods towards genetic prediction of sex-limited and/or lowly heritable traits such as NLW. GS methods should be combined with dedicated efforts to increase genetic links between sectors and improved phenotyping by commercial flocks.

Genetic and environmental parameters for early growth and yearling traits of the Elsenburg South African Mutton Merino resource flock

The Elsenburg South African Mutton Merino (SAMM) resource flock has been maintained at the Elsenburg Research Farm in the Western Cape, South Africa since 1955. Early growth and lamb survival data (record numbers from 9512 for weaning weight or WW to 13101 for lamb survival LS) over the 66-year period from 1955 to 2020 and yearling weight and wool data (record numbers from 1351 the coefficient of variation of fibre diameter or CVFD to 3505 for clean yield or CY) over a 38-year period from 1983 to 2020 were used to estimate genetic and environmental parameters for the flock. The ASREML package was used to estimate fixed effects and genetic parameters. Birth year, sex, birth type and age of dam significantly (P < 0.001) influenced the weight traits and LS. The interaction between birth year and sex was evident in most early growth traits. Direct single-trait heritability estimates amounted to 0.11 ± 0.02 for birth weight (BW), 0.04 ± 0.01 for WW, 0.03 ± 0.01 for LS, 0.28 ± 0.04 for yearling weight (YW), 0.62 ± 0.04 for CY, 0.36 ± 0.04 for clean fleece weight (CFW), 0.33 ± 0.05 for staple length (SL), 0.56 ± 0.06 for CVFD, and 0.65 ± 0.04 for fibre diameter (FD). Maternal heritability estimates were 0.17 ± 0.02 for BW, and 0.06 ± 0.01 for WW. Maternal permanent environmental effects amounted to 0.08 ± 0.02 for BW, 0.04 ± 0.01 for WW, 0.04 ± 0.01, 0.07 ± 0.02 for YW and 0.05 ± 0.02 for CFW. Litter effects were 0.22 ± 0.01 for BW, 0.18 ± 0.02 for WW and 0.14 ± 0.01 for LS. Multi-trait heritability estimates compared well with the single-trait estimates. Genetic correlations for the weight traits in the three-trait analyses ranged from −0.23 ± 0.12 for BW and YW to 0.81 ± 0.09 for WW and YW. Genetic, environmental, and phenotypic correlations amongst yearling weight and wool traits in the six-trait analyses were low to moderate and mostly within the ranges from previous literature for wool breeds. It should be feasible to select for a balanced breeding objective based on economic considerations in the flock.

Feet and legs malformation in Nellore cattle: genetic analysis and prioritization of GWAS results.

Beef cattle affected by feet and legs malformations (FLM) cannot perform their productive and reproductive functions satisfactorily, resulting in significant economic losses. Accelerated weight gain in young animals due to increased fat deposition can lead to ligaments, tendon and joint strain and promote gene expression patterns that lead to changes in the normal architecture of the feet and legs. The possible correlated response in the FLM due to yearling weight (YW) selection suggest that this second trait could be used as an indirect selection criterion. Therefore, FLM breeding values and the genetic correlation between FLM and yearling weight (YW) were estimated for 295,031 Nellore animals by fitting a linear-threshold model in a Bayesian approach. A genome-wide association study was performed to identify genomic windows and positional candidate genes associated with FLM. The effects of single nucleotide polymorphisms (SNPs) on FLM phenotypes (affected or unaffected) were estimated using the weighted single-step genomic BLUP method, based on genotypes of 12,537 animals for 461,057 SNPs. Twelve non-overlapping windows of 20 adjacent SNPs explaining more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of candidate genes identified six genes (ATG7, EXT1, ITGA1, PPARD, SCUBE3, and SHOX) that may play a role in FLM expression due to their known role in skeletal muscle development, aberrant bone growth, lipid metabolism, intramuscular fat deposition and skeletogenesis. Identifying genes linked to foot and leg malformations enables selective breeding for healthier herds by reducing the occurrence of these conditions. Genetic markers can be used to develop tests that identify carriers of these mutations, assisting breeders in making informed breeding decisions to minimize the incidence of malformations in future generations, resulting in greater productivity and animal welfare.