Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 ± 0.00, 0.42 ± 0.02, 0.49 ± 0.01, 0.11 ± 0.01 and 0.19 ± 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.     

Genetic parameters and relationships between growth traits and scrotal circumference measured at different ages in Nellore cattle

Records from 106,212 Nellore animals, born between 1998 and 2006, were used to estimate (co)variance components and genetic parameters for birth weight (BW), average weight gains from birth to weaning (GBW), average weight gains from weaning to after yearling (GWAY), weaning hip height (WHH), postweaning hip height (PHH) and scrotal circumferences at 9 (SC9), 12 (SC12) and 15 (SC15) months of age. (Co)variance components were estimated by an animal model using multi-trait analysis. Heritability estimates for BW, GBW, GWAY, WHH, PHH, SC9, SC12 and SC15 were 0.31 ± 0.01; 0.25 ± 0.02; 0.30 ± 0.04; 0.51 ± 0.04; 0.54 ± 0.04; 0.39 ± 0.01; 0.41 ± 0.01 and 0.44 ± 0.02, respectively. Genetic correlations between growth traits ranged from 0.09 ± 0.01 to 0.88 ± 0.01, thereby implying that, at any age, selection to increase average weight gains will also increase stature. Genetic correlations between BW and average weight gains with scrotal circumferences were all positive and moderate (0.15 ± 0.03 to 0.38 ± 0.01). On the other hand, positive and low genetic associations were estimated between hip height and scrotal circumference at different ages (0.09 ± 0.01 to 0.17 ± 0.02). The results of this study pointed out that selection to larger scrotal circumferences in males will promote changes in average weight gains. In order to obtain Nellore cattle with the stature and size suitable for the production system, both weight gain and hip height should be included in a selection index.     

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.     

A bivariate quantitative genetic model for a threshold trait and a survival trait

Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.     

Genetic parameters for fatty acid composition and feed efficiency traits in Japanese Black cattle

We estimated the genetic parameters related to feed intake (FI), feed efficiency traits (including feed conversion ratio (FCR) and residual feed intake (RFI) of digestible crude protein (DCP) and total digestible nutrients (TDN)), beef marbling score (BMS), melting point of fat (MP) and fatty acid composition. Fat and meat (Musculus trapezius) samples were taken from the carcasses of 863 Japanese Black steers derived from 65 sires, for determination of the MP and fatty acid composition of the total lipid in intramuscular adipose tissue. Genetic parameters were estimated using uni- and bivariate animal models. In addition, pedigree information for 4841 animals was used. Heritability estimates for BMS, MP, individual fatty acids, monounsaturated fatty acids (MUFA), the ratio of saturated fatty acids to MUFA (MUS) and the ratio of elongation (ELONG) were generally high. The FI values of TDN and DCP were also high, but FCRs and RFIs of those were low (0.09 to 0.22). Genetic correlation of BMS with MP was -0.34 (favorable) and with C18:1, MUFA, MUS and ELONG values were 0.40, 0.28, 0.29 and 0.37, respectively (favorable). Genetic correlations of MP with C18:1, MUFA, MUS and ELONG were negative (also favorable) and high (-0.85, -0.98, -1.00 (-0.996) and -0.66, respectively). The correlation estimates for feed efficiency traits of DCP were quite similar to those of TDN. Genetic correlations of BMS with FCRs and RFIs of TDN and DCP were all positive (unfavorable; 0.21 to 0.51), and in particular, the correlations with RFIs of those were high. The correlations of C18:1, MUFA, MUS and ELONG with RFIs of TDN and DCP were positive (unfavorable) but low (0.06 to 0.17), whereas the corresponding correlations with FCRs of those were all negative (favorable; -0.38 to -0.10). These results suggest that the quantity and quality of beef fat can be simultaneously improved and that the quality of beef fat (fatty acid composition) can be improved directly or indirectly with MP. Furthermore, selecting MP or fatty acid traits does not significantly affect feed efficiency.     

Identification of quantitative trait loci for growth and carcass composition in cattle

A genomic screening to detect quantitative trait loci (QTL) affecting growth, carcass composition and meat quality traits was pursued. Two hundred nineteen microsatellite markers were genotyped on 176 of 620 (28%) progeny from a Brahman x Angus sire mated to mostly MARC III dams. Selective genotyping, based on retail product yield (%) and fat yield (%), was used to select individuals to be genotyped. Traits included in the study were birth weight (kg), hot carcass weight (kg), retail product yield, fat yield, marbling score (400 = slight00 and 500 = small00), USDA yield grade, and estimated kidney, heart and pelvic fat (%). The QTL were classified as significant when the expected number of false positives (ENFP) was less than 0.05 (F-statistic greater than 17.3), and suggestive when the ENFP was <1 (F-statistic between 10.2 and 17.3). A significant QTL (F = 19; ENFP = 0.02) was detected for marbling score at centimorgan (cM) 54 on chromosome 2. Suggestive QTL were detected for fat yield at 50 cM, for retail product yield at 53 cM, and for USDA yield grade at 63 cM on chromosome 1, for marbling score at 56 cM, for retail product yield at 70 cM, and for estimated kidney, heart and pelvic fat at 79 cM on chromosome 3, for marbling score at 44 cM, for hot carcass weight at 49 cM, and for estimated kidney, heart and pelvic fat at 62 cM on chromosome 16, and for fat yield at 35 cM on chromosome 17. Two suggestive QTL for birth weight were identified, one at 12 cM on chromosome 20 and the other at 56 cM on chromosome 21. An additional suggestive QTL was detected for retail product yield, for fat yield, and for USDA yield grade at 26 cM on chromosome 26. Results presented here represent the initial search for quantitative trait loci in this family. Validation of detected QTL in other populations will be necessary.     

Heritability estimates and genetic correlations for body weight and scrotal circumference adjusted to 12 and 18 months of age for male Nellore cattle

Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12, BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 ± 0.11, 0.21 ± 0.13, 0.21 ± 0.11, -0.08 ± 0.15, 0.16 ± 0.12 and 0.89 ± 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12, suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other. The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other. Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter, it is suggested that the practice of individual selection for these traits is possible.     

Genetic relationships between carcass cut weights predicted from video image analysis and other performance traits in cattle

The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r_g(MVC) = 0.35; max r_g(VHVC) = 0.69), and animal price at both weaning (min r_g(MVC) = 0.37; max r_g(VHVC) = 0.66) and post weaning (min r_g(MVC) = 0.50; max r_g(VHVC) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r_g(HVC) = 0.34; max r_g(LVC) = 0.45), weanling quality (min r_g(MVC) = 0.12; max r_g(VHVC) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r_g(MVC) = −0.06; max r_g(VHVC) = 0.46), post weaning (hindquarter development: min r_g(MVC) = 0.23; max r_g(VHVC) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction prices and weanling quality. Total bone weight was, however, positively correlated with skeletal scores at weaning and post weaning. These results indicate that some traits collected early in life are moderate-to-strongly correlated with carcass cut weights predicted from VIA technology. This information can be used to improve the accuracy of selection for carcass cut weights in national genetic evaluations.     

Genetic diversity measures of local European beef cattle breeds for conservation purposes

This study was undertaken to determine the genetic structure, evolutionary relationships, and the genetic diversity among 18 local cattle breeds from Spain, Portugal, and France using 16 microsatellites. Heterozygosities, estimates of Fst, genetic distances, multivariate and diversity analyses, and assignment tests were performed. Heterozygosities ranged from 0.54 in the Pirenaica breed to 0.72 in the Barrosã breed. Seven percent of the total genetic variability can be attributed to differences among breeds (mean F_st = 0.07; P < 0.01). Five different genetic distances were computed and compared with no correlation found to be significantly different from 0 between distances based on the effective size of the population and those which use the size of the alleles. The Weitzman recursive approach and a multivariate analysis were used to measure the contribution of the breeds diversity. The Weitzman approach suggests that the most important breeds to be preserved are those grouped into two clusters: the cluster formed by the Mirandesa and Alistana breeds and that of the Sayaguesa and Tudanca breeds. The hypothetical extinction of one of those clusters represents a 17% loss of diversity. A correspondence analysis not only distinguished four breed groups but also confirmed results of previous studies classifying the important breeds contributing to diversity. In addition, the variation between breeds was sufficiently high so as to allow individuals to be assigned to their breed of origin with a probability of 99% for simulated samples.     

Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. II. Genetic trends

The Tiameslan line was created between 1983 and 1985 by mating Meishan × Jiaxing crossbred Chinese boars with sows from the Laconie composite male line. The Tiameslan line has been selected since then on an index combining average backfat thickness (ABT) and days from 20 to 100 kg (DT). Direct and correlated responses to 11 years of selection were estimated using BLUP methodology applied to a multiple trait animal model. A total of 11 traits were considered, i.e.: ABT, DT, body weight at 4 (W4w), 8 (W8w) and 22 (W22w) weeks of age, teat number (TEAT), number of good teats (GTEAT), total number of piglets born (TNB), born alive (NBA) and weaned (NW) per litter, and birth to weaning survival rate (SURV). Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. The models included both direct and maternal effects for ABT, W4w and W8w. Male and female performances were considered as different traits for W22w, DT and ABT. Genetic parameters estimated in another paper (Zhang et al., Genet. Sel. Evol. 32 (2000) 41-56) were used to perform the analyses. Favourable phenotypic (ΔP) and direct genetic trends (ΔG_d) were obtained for post-weaning growth traits and ABT. Trends for maternal effects were limited. Phenotypic and genetic trends were larger in females than in males for ABT (e.g. ΔG_d = -0.48 vs. -0.38 mm/year), were larger in males for W22w (ΔG_d = 0.90 vs. 0.58 kg/year) and were similar in both sexes for DT (ΔG_d = -0.54 vs. -0.55 day/year). Phenotypic and genetic trends were slightly favourable for W4w, W8w, TEAT and GTEAT and close to zero for reproductive traits.     

Genetic diversity among Angus, American Brahman, Senepol and Romosinuano cattle breeds

The objective of this study was to quantify the genetic diversity among breeds under evaluation for tropical adaptability traits that affect the performance of beef cattle at the USDA/ARS SubTropical Agricultural Research Station (STARS) near Brooksville, FL, USA. Twenty-six microsatellite loci were used to estimate parameters of genetic diversity among the breeds American Brahman, Angus, Senepol and Romosinuano; the latter was comprised of two distinct bloodlines (Costa Rican and Venezuelan). Genotypes of 47 animals from each of these STARS herds were analysed for genetic diversity and genetic distance. Using two methods, the greatest genetic distance was detected between the Costa Rican line of Romosinuano and the Senepol. Gene diversity ranged between 0.64 (Costa Rican line of Romosinuano) and 0.75 (American Brahman). The breed relationship inferences, which are based on genetic distance, provide additional tools for consideration in future crossbreeding studies and for testing the relationship between quantified breed diversity and observed heterosis.     

Genetic parameters for carcass weight,conformation and fat in five beef cattle breeds

Profitability of beef production can be increased by genetically improving carcass traits. To construct breeding value evaluations for carcass traits, breed-specific genetic parameters were estimated for carcass weight, carcass conformation and carcass fat in five beef cattle breeds in Finland (Hereford, Aberdeen Angus, Simmental, Charolais and Limousin). Conformation and fat were visually scored using the EUROP carcass classification. Each breed was separately analyzed using a multitrait animal model. A total of 6879–19 539 animals per breed had phenotypes. For the five breeds, heritabilities were moderate for carcass weight (h²=0.39 to 0.48, s.e.=0.02 to 0.04) and slightly lower for conformation (h²=0.30 to 0.44, s.e.=0.02 to 0.04) and carcass fat (h²=0.29 to 0.44, s.e.=0.02 to 0.04). The genetic correlation between carcass weight and conformation was favorable in all breeds (r_G=0.37 to 0.53, s.e.=0.04 to 0.05), heavy carcasses being genetically more conformed. The phenotypic correlation between carcass weight and carcass fat was moderately positive in all breeds (r_P=0.21 to 0.32), implying that increasing carcass weight was related to increasing fat levels. The respective genetic correlation was the strongest in Hereford (r_G=0.28, s.e.=0.05) and Angus (r_G=0.15, s.e.=0.05), the two small body-sized British breeds with the lowest conformation and the highest fat level. The correlation was weaker in the other breeds (r_G=0.08 to 0.14). For Hereford, Angus and Simmental, more conformed carcasses were phenotypically fatter (r_P=0.11 to 0.15), but the respective genetic correlations were close to zero (r_G=−0.05 to 0.04). In contrast, in the two large body-sized and muscular French breeds, the genetic correlation between conformation and fat was negative and the phenotypic correlation was close to zero or negative (Charolais: r_G=−0.18, s.e.=0.06, r_P=0.02; Limousin: r_G=−0.56, s.e.=0.04, r_P=−0.13). The results indicate genetic variation for the genetic improvement of the carcass traits, favorable correlations for the simultaneous improvement of carcass weight and conformation in all breeds, and breed differences in the correlations of carcass fat.     

Non-linear recursive models for growth traits in the Pirenaica beef cattle breed

One of the main goals of selection schemes in beef cattle populations is to increase carcass weight at slaughter. Live weights at different growth stages are frequently used as selection criteria under the hypothesis that they usually have a high and positive genetic correlation with weight at slaughter. However, the presence of compensatory growth may bias the prediction ability of early weights for selection purposes. Recursive models may represent an interesting alternative for understanding the genetic and phenotypic relationship between weight traits during growth. For the purposes of this study, the analysis was performed for three different set of data from the Pirenaica beef cattle breed: weight at 120 days (W120) and at 210 days (W210); W120 and carcass weight at slaughter at 365 days (CW365); W210 and CW365. The number of records for each analysis was 8592, 4648 and 3234, respectively. A pedigree composed of 56323 individuals was also included. The statistical model comprised sex, year-season of birth, herd and slaughterhouse, plus a non-linear recursive dependency between traits. The dependency was modeled as a polynomial up to the 4th degree and models were compared using a Logarithm of Conditional Predictive Ordinates. The results of model comparison suggest that the best models were the 3rd degree polynomial for W120-W210 and W120-CW365 and the 2nd degree polynomial for W210-CW365. The posterior mean estimates for heritabilities ranged between 0.29 and 0.44 and the posterior mean estimates of the genetic correlations were null or very low, indicating that the relationship between traits is fully captured by the recursive dependency. The results imply that the predictive ability of the performance of future growth is low if it is only based on records of early weights. The usefulness of slaughterhouse records in beef cattle breeding evaluation is confirmed.     

Genetic relationship of discrete-time survival with fertility and production in dairy cattle using bivariate models

Bivariate analyses of functional longevity in dairy cattle measured as survival to next lactation (SURV) with milk yield and fertility traits were carried out. A sequential threshold-linear censored model was implemented for the analyses of SURV. Records on 96 642 lactations from 41 170 cows were used to estimate genetic parameters, using animal models, for longevity, 305 d-standardized milk production (MY305), days open (DO) and number of inseminations to conception (INS) in the Spanish Holstein population; 31% and 30% of lactations were censored for DO and INS, respectively. Heritability estimates for SURV and MY305 were 0.11 and 0.27 respectively; while heritability estimates for fertility traits were lower (0.07 for DO and 0.03 for INS). Antagonist genetic correlations were estimated between SURV and fertility (-0.78 and -0.54 for DO and INS, respectively) or production (-0.53 for MY305), suggesting reduced functional longevity with impaired fertility and increased milk production. Longer days open seems to affect survival more than increased INS. Also, high productive cows were more problematic, less functional and more liable to being culled. The results suggest that the sequential threshold model is a method that might be considered at evaluating genetic relationship between discrete-time survival and other traits, due to its flexibility.     

Discovery of novel genetic networks associated with 19 economically important traits in beef cattle

Quantitative or complex traits are determined by the combined effects of many loci, and are affected by genetic networks or molecular pathways. In the present study, we genotyped a total of 138 mutations, mainly single nucleotide polymorphisms derived from 71 functional genes on a Wagyu x Limousin reference population. Two hundred forty six F₂ animals were measured for 5 carcass, 6 eating quality and 8 fatty acid composition traits. A total of 2,280 single marker-trait association runs with 120 tagged mutations selected based on the HAPLOVIEW analysis revealed 144 significant associations (P < 0.05), but 50 of them were removed from the analysis due to the small number of animals (≤ 9) in one genotype group or absence of one genotype among three genotypes. The remaining 94 single-trait associations were then placed into three groups of quantitative trait modes (QTMs) with additive, dominant and overdominant effects. All significant markers and their QTMs associated with each of these 19 traits were involved in a linear regression model analysis, which confirmed single-gene associations for 4 traits, but revealed two-gene networks for 8 traits and three-gene networks for 5 traits. Such genetic networks involving both genotypes and QTMs resulted in high correlations between predicted and actual values of performance, thus providing evidence that the classical Mendelian principles of inheritance can be applied in understanding genetic complexity of complex phenotypes. Our present study also indicated that carcass, eating quality and fatty acid composition traits rarely share genetic networks. Therefore, marker-assisted selection for improvement of one category of these traits would not interfere with improvement of another.     

Genetic diversity and differentiation in Portuguese cattle breeds using microsatellites

Genotype data from 30 microsatellites were used to assess genetic diversity and relationships among 10 native Portuguese cattle breeds, American Charolais and the Brazilian Caracú. Hardy–Weinberg equilibrium was observed for all loci/population combinations except for five loci in Brava de Lide and one locus in Alentejana that exhibited heterozygote deficiency. Estimates of average observed and expected heterozygosities, total number of alleles (TNA) per breed and mean number of alleles (MNA) per locus/population were obtained. A total of 390 alleles were detected. TNA among Iberian cattle ranged from 170 to 237 and MNA ranged from 5.67 to 8.07. The highest observed heterozygosities were found in the Caracú, Maronesa, Garvonesa and Arouquesa and the lowest in Brava de Lide and Mirandesa. Estimation of population subdivision using Wright's F_ST index showed that the average proportion of genetic variation explained by breed differences was 9%. Neighbour‐joining phylogenetic trees based on D_A distances showed that the genetic relationships of present‐day Portuguese native breeds are consistent with historical origins in the Brown Concave (Arouquesa, Mirandesa, Marinhoa) and Red Convex (Mertolenga, Alentejana, Garvonesa, Minhota) evolutionary groups. The Iberian Black Orthoide group, represented by Brava de Lide and Maronesa, and the Barrosã breed appeared to be more closely related to the Brown Concave group but may represent a separate lineage. The Caracú breed was not found to be closely associated with any of the native Portuguese breeds.     

Genetic characterization of Latin-American Creole cattle using microsatellite markers

Genetic diversity in and relationships among 26 Creole cattle breeds from 10 American countries were assessed using 19 microsatellites. Heterozygosities, F-statistics estimates, genetic distances, multivariate analyses and assignment tests were performed. The levels of within-breed diversity detected in Creole cattle were considerable and higher than those previously reported for European breeds, but similar to those found in other Latin American breeds. Differences among breeds accounted for 8.4% of the total genetic variability. Most breeds clustered separately when the number of pre-defined populations was 21 (the most probable K value), with the exception of some closely related breeds that shared the same cluster and others that were admixed. Despite the high genetic diversity detected, significant inbreeding was also observed within some breeds, and heterozygote excess was detected in others. These results indicate that Creoles represent important reservoirs of cattle genetic diversity and that appropriate conservation measures should be implemented for these native breeds in order to minimize inbreeding and uncontrolled crossbreeding.     

Genetic variability of the length of postpartum anoestrus in Charolais cows and its relationship with age at puberty

Fertility records (n = 1 802) were collected from 615 Charolais primiparous and multiparous cows managed in an experimental herd over an 11-year period. The objectives of the study were to describe the genetic variability of the re-establishment of postpartum reproductive activity and the relationship with body weight (BW) and body condition score (BCS) at calving and age at puberty. The length of postpartum anoestrus was estimated based on weekly blood progesterone assays and on twice daily detection of oestrus behaviour. The first oestrus behaviour was observed 69 days (± 25 days s.d.) post-calving and the first positive progesterone measurement (≥ 1 ng mL^-1) was observed at 66 days (± 22 days s.d.) for the group of easy-calving multiparous suckling cows. Estimates of heritability and repeatability were h² = 0.12 and r = 0.38 respectively, for the interval from calving to first oestrus (ICO). Corresponding values were h² = 0.35 and r = 0.60 for the interval from calving to the first positive progesterone test (ICP). The genetic correlation between both criteria was high (r_g = 0.98). The genetic relationships between postpartum intervals and BW and BCS of the female at calving were negative: the genetic aptitude to be heavier at calving and to have high body reserves was related to shorter postpartum intervals. A favourable genetic correlation between age at puberty and postpartum intervals was found (r_g between 0.45 and 0.70). The heifers which were genetically younger at puberty also had shorter postpartum intervals.     

Genome‐enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods

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 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (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.