238 Applying the algorithm for proven and young in genome-wide association studies for reproductive traits in Nellore cattle.

Identifying genomic regions associated with traits of interest and their biological processes provides valuable insights into the phenotypic variability of these traits. This study aimed to identify candidate genes and genomic regions associated with 16 traits currently evaluated by the Brazilian Association of Zebu Breeders (ABCZ). These traits include reproductive traits such as age at first calving (AFC), stayability (STAY), and scrotal circumference at 365 (SC365) and 450 days (SC450). Growth traits include birthweight (BW), expected progeny difference for weight at 120days of age (EPD120), as well as weight at 120 (W120), 210 (W210), 365 (W365), and 450 days of age (W450). Carcass traits include body conformation (BC), finishing score (FS), marbling (MARB), muscularity (MUSC), finishing precocity (FP), and ribeye area (REA). A dataset containing 304,782 Nellore cattle genotyped with 437,650 SNPs (after quality control) was used for this study. The Algorithm for Proven and Young (APY), implemented in the PREGSF90 software, was used to compute the matrix using 36,000 core animals (which explained 98% of the variance in the genomic matrix). Subsequently, the SNP solutions were estimated by back-solving the Genomic Estimated Breeding Values (GEBVs) predicted by ABCZ using the single-step GBLUP method. Genomic regions were identified using sliding windows of 175 consecutive SNPs, and the top 1% genomic windows, ranked based on their proportion of the additive genetic variance, were used to annotate positional candidate genes and genomic regions associated with each of the 16 traits. The top 1% windows for all traits explained between 2.779% (STAY) to 3.158% (FP) of the additive genetic variance, highlighting the polygenic nature of these traits. Functional analysis of the candidate genes and genomic regions provided valuable insights into the genetic architecture underlying these traits in Nellore cattle. For instance, our results revealed genes with important functions for each trait, such as SERPINA14 (plays a key role for the endometrial epithelium) identified for AFC, HSPG2 (associated with morphological development and tissue differentiation) identified for BW, among others. We identified genomic regions and candidate genes, some of which have been previously reported in the literature, while others are novel discoveries that warrant further investigation. These findings contribute to gene prioritization efforts, facilitating the identification of functional candidate genes that can enhance genomic selection strategies for economically important traits in Nellore cattle.

This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321419 (AFC), 4671 and 309486 (SC), 2681 and 319619 (STAY) and 3356 and 319108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5-fold cross-validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome-enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait-dependent, thus, a fine-tuning for this hyper-parameter in the training phase is crucial.

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.

Estimated genetic associations among reproductive traits in Nellore cattle using Bayesian analysis

Enhancing reproductive efficiency could lead to economic benefits for Nellore producers. However, several factors limit our understanding of the main genetic factors controlling reproduction traits in Nellore cattle, including genetic differences between populations and statistical limitations. A meta-analysis can assist in pinpointing the most likely functional candidate genes, quantitative trait loci, and biological processes simultaneously associated with several traits in a group. Hence, the goal of this study was to perform a meta-analysis of genomic regions previously associated with reproduction traits in Nellore cattle, to improve our comprehension of the main genetic mechanisms regulating these traits within the breed. This study incorporated a total of 549 genomic regions sourced from 21 scientific publications, published between 2014 to 2024. The reproduction traits included in this study are scrotal circumference at various ages (365, 450, and 550 d), early pregnancy (< 31 mo of age), early puberty (defined as pregnancy at 18 mo), age at first calving, antral follicle count, calving interval, calving ease, testicular hypoplasia, stayability, heifer rebreeding, gestation length, anti-mullerian hormone concentrations, preweaning calf mortality, and post-natal mortality. All genomic regions identified in the literature were updated to the ARS-UCD1.2 genome assembly, and the Gallo R package was used to identify positional candidate genes associated with each genomic region. A total of 8,441 positional candidate genes were annotated and used in an overrepresentation analysis performed in meshr. The significant genes (adjusted P-values < 0.05) identified in the overrepresentation analysis underwent prioritization analyses using the GUILDify and ToppGene software. Subsequently, enrichment analysis of the prioritized overrepresented candidate genes was performed using the ClusterProfiler R package. The 8,441 annotated genes generated 1,757 overrepresented genes, of which 17 candidate genes were prioritized (FDR P -value ≤ 10-3). The overrepresented candidate genes that were prioritized are: SERTAD2, RFWD3, C1QTNF9B, SLFN14, CATSPERE, GFRA4, ZNF408, NOP58, ADGRG3, KIZ, REM2, FSCN3, DCAF11, ACSM4, ANKRD34B, CMKLR2-AS, and TRV-AAC1-1. The functional enrichment analysis highlighted the following genes: FSCN3 (exhibits highly specific expression in testis), CATSPERE (has a vital role in cellular processes related to reproduction and is necessary for normal fertility), ANKRD34B (associated with cytoplasm found in oocytes or early embryos), and RFWD3 (regulates the transition between phases of the mitotic cell cycle). All other prioritized genes also have roles in regulating metabolic pathways or biological processes related to reproduction, such as sperm capacitation, sperm motility, cilium or flagellum-dependent cell motility, mitotic cell cycle phase transition, and RNA endonuclease activity. The enrichment of the functional candidate genes identified highlights that these genes have an important role in the expression of reproduction traits in Nellore cattle. Candidate genes identified in this study can be used as target genes in gene expression studies, which are necessary to validate our findings.

This study aimed to perform a genome-wide association analysis (GWAS) using the Random Forest (RF) approach for scanning candidate genes for age at first calving (AFC) in Nellore cattle. Additionally, potential epistatic effects were investigated using linear mixed models with pairwise interactions between all markers with high importance scores within the tree ensemble non-linear structure. Data from Nellore cattle were used, including records of animals born between 1984 and 2015 and raised in commercial herds located in different regions of Brazil. The estimated breeding values (EBV) were computed and used as the response variable in the genomic analyses. After quality control, the remaining number of animals and SNPs considered were 3,174 and 360,130, respectively. Five independent RF analyses were carried out, considering different initialization seeds. The importance score of each SNP was averaged across the independent RF analyses to rank the markers according to their predictive relevance. A total of 117 SNPs associated with AFC were identified, which spanned 10 autosomes (2, 3, 5, 10, 11, 17, 18, 21, 24, and 25). In total, 23 non-overlapping genomic regions embedded 262 candidate genes for AFC. Enrichment analysis and previous evidence in the literature revealed that many candidate genes annotated close to the lead SNPs have key roles in fertility, including embryo pre-implantation and development, embryonic viability, male germinal cell maturation, and pheromone recognition. Furthermore, some genomic regions previously associated with fertility and growth traits in Nellore cattle were also detected in the present study, reinforcing the effectiveness of RF for pre-screening candidate regions associated with complex traits. Complementary analyses revealed that many SNPs top-ranked in the RF-based GWAS did not present a strong marginal linear effect but are potentially involved in epistatic hotspots between genomic regions in different autosomes, remarkably in the BTAs 3, 5, 11, and 21. The reported results are expected to enhance the understanding of genetic mechanisms involved in the biological regulation of AFC in this cattle breed.

The aim of this study was to estimate genetic parameters for different precocious calving criteria and their relationship with reproductive, growth, carcass and feed efficiency in Nellore cattle using the single-step genomic BLUP. The reproductive traits used were probability of precocious calving (PPC) at 24 (PPC24), 26 (PPC26), 28 (PPC28) and 30 (PPC30) months of age, stayability (STAY) and scrotal circumference at 455days of age (SC455). Growth traits such as weights at 240 (W240) and 455 (W455) days of age and adult weight (AW) were used. Rib eye area (REA), subcutaneous fat thickness (SFT), rump fat thickness (RFT) and residual feed intake (RFI) were included in the analyses. The estimation of genetic parameters was performed using a bi-trait threshold model including genomic information in a single-step approach. Heritability for PPC traits was moderate to high (0.29-0.56) with highest estimates for PPC24 (0.56) and PPC26 (0.50). Genetic correlation estimates between PPC and STAY weakened as a function of calving age. Correlation with SC455, growth and carcass traits were low (0.25-0.31; -0.22 to 0.04; -0.09 to 0.18, respectively), the same occurs with RFI (-0.09 to 0.08), this suggests independence between female sexual precocity and feed efficiency traits. The results of this study encourage the use of PPC traits in Nellore cattle because the selection for such trait would not have a negative impact on reproductive, growth, carcass and feed efficiency indicator traits. Stayability for sexual precocious heifers (PPC24 and PPC26) must be redefined to avoid incorrectly phenotype assignment.

SUMMARYGenetic parameters for visual assessment traits measured at 487 days of age (body structure (BS), finishing precocity (FP) and muscling (MS)), body weight at 450 days of age (W450), age at first calving (AFC), heifer pregnancy (HP) and stayability (STAY, i.e. the probability of a cow to produce at least three calves before reaching 76 months of age) were estimated in Nellore cattle, seeking to include these traits in the selection criteria for dams. The statistical models included additive genetic and residual random effects using single- and two-trait Bayesian analyses. The average heritability estimates were equal to 0·37 for BS, 0·42 for FP, 0·37 for MS and 0·48 for W450. Age at first calving had a low average heritability estimate (0·13), while HP and STAY estimates were higher (0·36 and 0·24, respectively). The genetic correlations between AFC, HP and STAY with visual assessment traits and body weight were favourable, indicating that selecting animals with higher BS, FP, MS and W450 values will result in the indirect selection of animals with lower AFC and successful scores for HP and STAY. The selection of heifers that present an early pregnancy should anticipate AFC and improve HP in the current herd. Except for AFC, the heritability and genetic correlation estimates between the studied traits justify their inclusion in the selection criteria of the Nellore breeding programme.

Simple SummaryIn this study, we investigated the association between single nucleotide polymorphisms (SNPs) and reproductive traits in order to identify candidate genes and biological pathways associated with these traits in Nelore beef cattle. The genome-wide association analysis revealed genomic regions that could explain part of the genetic variance of the studied traits. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, being important for reproductive efficiency. The identification of candidate genes that were associated with the studied traits as well as genes enriched in the functional terms and pathways may be useful for exploring the genetic architecture underlying reproductive traits and may be used in Nelore breeding programs.The identification of genomic regions associated with reproductive traits as well as their biological processes allows a better understanding of the phenotypic variability of these traits. This information could be applied to animal breeding programs to accelerate genetic gain. The aim of this study was to evaluate the association between single nucleotide polymorphisms (SNP) with a scrotal circumference at 365 days of age (SC365) and at 450 days of age (SC450), gestation length (GL) as a calf trait, age at first calving (AFC), accumulated productivity (ACP), heifer early calving until 30 months (HC30), and stayability (STAY) traits, in order to identify candidate genes and biological pathways associated with reproductive traits in Nelore cattle. The data set consisted of pedigree, phenotypes, and genotypes of Nelore cattle from the “Associação Nacional de Criadores e Pesquisadores” (ANCP). The association analyses were performed using the Weighted Single-Step Genome-Wide Association method; the regions, consisting of 10 consecutive SNP, which explained more than 0.5% of additive genetic variance, were considered as a significant association. A total of 3, 6, 7, 5, 10, 25, and 12 windows were associated with SC355, SC450, GL, AFC, ACP, HC30, and STAY, respectively. The results revealed genes with important functions for reproductive traits, such as fertility and precocity. Some genes were associated with more than one trait, among them CAMK1D, TASP1, ACOXL, RAB11FIP5, and SFXN5. Moreover, the genes were enriched in functional terms, like negative regulation of fat cell differentiation, fatty acid alpha-oxidation, and sphingolipids signaling pathway. The identification of the genes associated with the traits, as well as genes enriched in the terms and pathway mentioned above, should contribute to future biological validation studies and may be used as candidate genes in Nelore breeding programs.

Genome-wide association study identified genomic regions and putative candidate genes affecting meat color traits in Nellore cattle

BackgroundReproductive efficiency is crucial for the long-term economic sustainability of beef cattle production. Pregnancy loss and stillbirth are complex reproductive traits that do not yet have their genomic background fully understood, especially in zebu breeds (Bos taurus indicus). Hence, this study aimed to perform a genome-wide association study (GWAS) and functional annotation for conception success (CS), pregnancy loss (PL), stillbirth (SB), and pre-weaning calf mortality (PWM) in Nellore cattle. In this study, 3,728 cows with 17,094 reproductive records and 11,785 calves were evaluated. A total of 3,351 genotyped animals and 383,739 SNP markers were considered for GWAS analyses. SNP effects were estimated using the weighted single-step GWAS (WssGWAS), which considered two iterations. The top ten genomic windows with the highest contribution to the additive genetic variance of the traits were selected for gene annotation. Candidate genes were then analyzed for Gene Ontology terms (GO) and metabolic pathways.ResultsThe top ten genomic windows that explained the largest proportion of the direct additive genetic variance () for CS, PL, SB, and PWM accounted for 17.03% (overlapping with 79 genes), 16.76% (57 genes), 11.71% (73 genes), and 12.03% (65 genes) of the total , respectively. For CS, significant GO terms included Somitogenesis (GO:0001756), Somite Development (GO:0061053), and Chromosome Segregation (GO:0007059). Considering PL, the processes annotated were the Regulation of Hormone Secretion (GO:0046883), and Hormone Transport (GO:0009914), along with the Glucagon Signaling Pathway (bta04922). Embryonic Development (GO:0045995), and Cerebellum Development (GO:0021549) were the main biological processes found in the gene enrichment analysis for SB. For PWM, the Regulation of Glucose metabolic processes (GO:0010906), Zinc Ion Homeostasis (GO:0055069), Lactation (GO:0007595), and Regulation of Insulin Secretion (GO:0050796) were the most significant GO terms observed.ConclusionsThese findings provide valuable information on genomic regions, candidate genes, biological processes, and metabolic pathways that may significantly influence the expression of complex reproductive traits in Nellore cattle, offering potential contributions to breeding strategies and future genomic selection strategies.

This study aimed to evaluate the effects of selection for post-weaning weight on reproductive traits in Nellore cattle by (i) estimating genetic parameters and trends for birth weight (BIW), body weight at selection (BW), days to calving (DC), and pregnancy rate (PR); and (ii) performing a genome-wide association study (GWAS), gene annotation, and functional enrichment analyses to uncover genomic regions, candidate genes, biological processes, and metabolic pathways underlying DC and PR. The dataset contained 12,865 Nellore animals from the experimental breeding program of the Institute of Animal Science (IZ, Sertãozinho, Brazil), including three selection lines: Nellore Control (NeC, stablishing selection for post-weaning weight), Nellore Selection (NeS, selected for higher post-weaning weight), and Nellore Traditional (NeT, selected for higher post-weaning weight and lower residual feed intake). Genomic data were available for 2,326 animals and 384,521 autosomal SNP markers after quality control. Genetic parameters were estimated using Bayesian inference under the ssGBLUP framework. Genetic trends from 1981 to 2021 were derived from linear regressions considering genomic estimated breeding values (GEBVs). The weighted single-step GWAS (WssGWAS) was used to identify genomic regions that explained more than 1.0% of the additive genetic variance for DC and PR, which were further analyzed for gene annotation and functional enrichment. Heritability estimates were high for BIW (0.46 ± 0.02) and BW (0.41 ± 0.02), and low for DC and PR (0.10 ± 0.02 for both). Moderate genetic correlations were observed between BIW and DC, especially in lines selected for higher growth (NeS: 0.38 ± 0.12; NeT: 0.56 ± 0.09), in contrast, BW showed weak genetic correlations with reproductive traits, with estimates for DC of - 0.11 ± 0.18 (NeC), 0.15 ± 0.15 (NeS), and 0.36 ± 0.14 (NeT), and for PR of 0.25 ± 0.22 (NeC), - 0.12 ± 0.17 (NeS), and - 0.44 ± 0.16 (NeT). Genetic trends indicated consistent increases in BW and BIW in NeS and NeT, while NeC showed more favorable trends for DC and PR. The GWAS identified 13 and 9 genomic windows associated with DC and PR, respectively, with pleiotropic regions on chromosome 14 influencing both traits. Key candidate genes annotated included PLAG1, MOS, MAPK13, MAPK14, and FKBP5. Functional enrichment revealed biological processes related to hormone metabolism, immune modulation, and oocyte development. Selection for increased growth does not directly impair reproductive traits; however, it indirectly influences fertility due to correlated response in BIW, which is genetically associated with DC.

BackgroundThe profitability of the beef industry is directly influenced by the fertility rate and reproductive performance of both males and females, which can be improved through selective breeding. When performing genomic analyses, genetic markers located on the X chromosome have been commonly ignored despite the X chromosome being one of the largest chromosomes in the cattle genome. Therefore, the primary objectives of this study were to: (1) estimate variance components and genetic parameters for eighteen male and five female fertility and reproductive traits in Nellore cattle including X chromosome markers in the analyses; and (2) perform genome-wide association studies and functional genomic analyses to better understand the genetic background of male and female fertility and reproductive performance traits in Nellore cattle.ResultsThe percentage of the total direct heritability (h2total) explained by the X chromosome markers (h2x) ranged from 3 to 32% (average: 16.4%) and from 9 to 67% (average: 25.61%) for female reproductive performance and male fertility traits, respectively. Among the traits related to breeding soundness evaluation, the overall bull and semen evaluation and semen quality traits accounted for the highest proportion of h2x relative to h2total with an average of 39.5% and 38.75%, respectively. The total number of significant genomic markers per trait ranged from 7 (seminal vesicle width) to 43 (total major defects). The number of significant markers located on the X chromosome ranged from zero to five. A total of 683, 252, 694, 382, 61, and 77 genes overlapped with the genomic regions identified for traits related to female reproductive performance, semen quality, semen morphology, semen defects, overall bulls’ fertility evaluation, and overall semen evaluation traits, respectively. The key candidate genes located on the X chromosome are PRR32, STK26, TMSB4X, TLR7, PRPS2, SMS, SMARCA1, UTP14A, and BCORL1. The main gene ontology terms identified are “Oocyte Meiosis”, “Progesterone Mediated Oocyte Maturation”, “Thermogenesis”, “Sperm Flagellum”, and “Innate Immune Response”.ConclusionsOur findings indicate the key role of genes located on the X chromosome on the phenotypic variability of male and female reproduction and fertility traits in Nellore cattle. Breeding programs aiming to improve these traits should consider adding the information from X chromosome markers in their genomic analyses.

We investigated genetic associations between mature cow weight (MW) and weaning weight (WW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to yearling (GWY), weaning hip height (WHH), yearling hip height (YHH), scrotal circumference (SC), and age at first calving (AFC). Data from 127,104 Nellore animals born between 1993 and 2006, belonging to Agropecuária Jacarezinho Ltda., were analyzed. (Co)variance components were obtained by the restricted maximum likelihood method, applying an animal model in a multi-traits analysis. The model included direct genetic and residual effects as random effects, the fixed effects of contemporary group, and the linear and quadratic effects of animal age at recording (except for AFC, GBW, and GWY) and age of cow at calving as covariates (except for MW). The numbers of days from birth to weaning and from weaning to yearling were included as covariates for GBW and GWY, respectively. Estimated direct heritabilities were 0.43 ± 0.02 (MW), 0.33 ± 0.01 (WW), 0.36 ± 0.01 (YW), 0.28 ± 0.02 (GBW), 0.31 ± 0.01 (GWY), 0.44 ± 0.02 (WHH), 0.48 ± 0.02 (YHH), 0.44 ± 0.01 (SC), and 0.16 ± 0.03 (AFC). Genetic correlations between MW and productive traits were positive and of medium to high magnitude (ranging from 0.47 ± 0.03 to 0.71 ± 0.01). A positive and low genetic correlation was observed between MW and SC (0.24 ± 0.04). A negative genetic correlation (-0.19 ± 0.03) was estimated between MW and AFC. Selection to increase weight or weight gains at any age, as well as hip height, will change MW in the same direction. Selection for higher SC may lead to a long-term increase in MW. The AFC can be included in selection indices to improve the reproductive performance of beef cattle without significant changes in MW.

The use of morphological traits assessed using visual scores as indirect selection criteria in cattle has the advantage of evaluating young animals regarding potential productive and reproductive performance. This enables breeders to make earlier decisions compared to later measurements, such as scrotal circumference at 450 days (SC450) and stayability (STAY). The aim of this study was to estimate the genetic parameters for visual score traits and their associations with reproductive traits: scrotal circumference at 365 days of age (SC365), SC450, STAY, probability of precocious calving (PPC30) and age at first calving (AFC) in Nellore cattle. Visual score data from 4,175 Nellore cattle, with an average age of 22 months, and reproductive data from 3,075 cattle belonging to the HoRa Genetics Provada herd were used. The morphological traits were evaluated by the MERCOS methodology. The heritability estimates obtained ranged from 0.15 to 0.28 for visual scores and 0.10 to 0.54 for reproductive traits. Genetic correlations between visual scores and reproductive traits were generally low, except between: muscularity and PPC30; structure and STAY; racial and SC450; conformation and SC365, SC450, STAY, and AFC; navel and STAY and AFC; and sacrum and SC365, STAY, and AFC, which were moderate to high. The identification of animals with flat sacral bone (not protruding or sloping) can also be an efficient characteristic in the identification for early pregnancy, and together with the musculature score, they can be related to animals with lower age at the first calving.