Estimating genetic parameters of reproductive, carcass, and meat quality traits in Polled Nellore cattle.

Considering the economic and commercial efficiency of the beef production chain, the yield and quality of the meat produced must also be included in breeding programs. For the Nellore breed, including the polled herd, these aspects have not been much studied. The aim of this study was to estimate genetic parameters for scrotal circumference adjusted to 365 (SC365) and 450 (SC450) days of age, age at first calving (AFC), accumulated productivity (AP), stayability (STAY), longissimus muscle area (LMA), thickness of subcutaneous fat over the 12th-13th ribs (BF), thickness of subcutaneous fat over the rump (RF), and shear force measured by Warner-Bratzler shear force (WBSF) of polled Nellore cattle. Bayesian analyses were performed by adopting a linear animal model, whereas STAY analyses used the linear threshold model. Heritability estimates were 0.31 (SC365), 0.37 (SC450), 0.16 (AFC), 0.25 (AP), 0.16 (STAY), 0.30 (LMA), 0.13 (BF), 0.24 (RF), and 0.15 (WBSF), indicating moderate response to selection. Genetic and residual correlations between SC365 and SC450 were high (0.91 and 0.74, respectively), as well as the genetic correlations of AP with SC365, SC450, AFC, and STAY (0.61, 0.62, - 0.69, and 0.83, respectively). Genetic and residual correlations of WBSF with reproductive and carcass characteristics exhibited high standard deviations, however favorable. Based on the results, it is expected that in the medium term, animals with greater sexual precocity will also have greater accumulated productivity and longer permanence of females in the herd, along with superior carcass traits. However, due to the low heritabilities and small genetic associations with reproductive traits, fat thickness characteristics (BF and RF) will still require direct selection.

Genome-wide interaction study reveals epistatic interactions for beef lipid-related traits in Nellore cattle.

Gene-gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene-gene interactions using the empirical Hilbert-Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega-3 (OM3), omega-6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P < 10 - 8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low-density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms ( P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP-SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid-related traits and improve human health by the selection of healthier meat products.

Experimental and computational analysis of a pharmaceutical-grade shape memory polymer applied to the development of gastroretentive drug delivery systems.

The present paper aims at developing an integrated experimental/computational approach towards the design of shape memory devices fabricated by hot-processing with potential for use as gastroretentive drug delivery systems (DDSs) and for personalized therapy if 4D printing is involved. The approach was tested on a plasticized poly(vinyl alcohol) (PVA) of pharmaceutical grade, with a glass transition temperature close to that of the human body (i.e., 37 °C). A comprehensive experimental analysis was conducted in order to fully characterize the PVA thermo-mechanical response as well as to provide the necessary data to calibrate and validate the numerical predictions, based on a thermo-viscoelastic constitutive model, implemented within a finite element framework. Particularly, a thorough thermal, mechanical, and shape memory characterization under different testing conditions and on different sample geometries was first performed. Then, a prototype consisting of an S-shaped device was fabricated, deformed in a temporary compact configuration and tested. Simulation results were compared with the results obtained from shape memory experiments carried out on the prototype. The proposed approach provided useful results and recommendations for the design of PVA-based shape memory DDSs.

Genomic prediction ability for feed efficiency traits using different models and pseudo-phenotypes under several validation strategies in Nelore cattle.

There is a growing interest to improve feed efficiency (FE) traits in cattle. The genomic selection was proposed to improve these traits since they are difficult and expensive to measure. Up to date, there are scarce studies about the implementation of genomic selection for FE traits in indicine cattle under different scenarios of pseudo-phenotypes, models, and validation strategies on a commercial large scale. Thus, the aim was to evaluate the feasibility of genomic selection implementation for FE traits in Nelore cattle applying different models and pseudo-phenotypes under validation strategies. Phenotypic and genotypic information from 4 329 and 3 467 animals were used, respectively, which were tested for residual feed intake, DM intake, feed efficiency, feed conversion ratio, residual BW gain, and residual intake and BW gain. Six prediction methods were used: single-step genomic best linear unbiased prediction, Bayes A, Bayes B, Bayes Cπ, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayes R. Phenotypes adjusted for fixed effects (Y*), estimated breeding value (EBV), and EBV deregressed (DEBV) were used as pseudo-phenotypes. The validation approaches used were: (1) random: the data was randomly divided into ten subsets and the validation was done in each subset at a time; (2) age: the partition into training and testing sets was based on year of birth and testing animals were born after 2016; and (3) EBV accuracy: the data was split into two groups, being animals with accuracy above 0.45 the training set; and below 0.45 the validation set. In the analyses that used the Y* as pseudo-phenotype, prediction ability (PA) was obtained by dividing the correlation between pseudo-phenotype and genomic EBV (GEBV) by the square root of the heritability of the trait. When EBV and DEBV were used as the pseudo-phenotype, the simple correlation of this quantity with the GEBV was considered as PA. The prediction methods show similar results for PA and bias. The random cross-validation presented higher PA (0.17) than EBV accuracy (0.14) and age (0.13). The PA was higher for Y* than for EBV and DEBV (30.0 and 34.3%, respectively). Random validation presented the highest PA, being indicated for use in populations composed mainly of young animals and traits with few generations of data recording. For high heritability traits, the validation can be done by age, enabling the prediction of the next-generation genetic merit. These results would support breeders to identify genomic approaches that are more viable for genomic prediction for FE-related traits.

Ovulation and ovulation rate in ewes under grazing conditions: factors affecting the response to short-term supplementation.

The relationships between ovulation rate and nutrition remain confused, probably because of uncontrolled variation in experimental conditions. To help resolve the problem, we analyzed data from 20 experiments conducted between 2002 and 2016, in Uruguay with grazing ewes. All experiments were carried out by a single laboratory under comparable conditions of experimental design and measured variables. The studies used a total of 3 720 ewes, of purebred Corriedale, Polwarth, or East Friesian x Polwarth genotypes. In all experiments, a control group grazed native pastures and extra nutrition was provided to the treatment groups using either improved pastures or supplements. Ovulation rate was measured by counting corpora lutea using laparoscopy or rectal ultrasound or by counting foetuses at ultrasound on day 45 of gestation. For statistical analysis, data were grouped according to nutritional treatment (control or supplemented) and, within these groups, type of supplement to provide energy or protein (protected or not from rumen degradation). Across all experiments, 92-99% of the ewes ovulated and the effects of diet, length of supplementation, and initial live weight and genotype are reported. Within diets, ovulation was most affected by overall energy intake during supplementation (P < 0.01). Ewes that grazed native pastures supplemented with protein supplements had higher ovulation rates (P < 0.05) than control ewes grazing only native pastures. The addition of tannins to the protein supplement, to protect it from degradation in the rumen, did not further increase the ovulation rate. In unsupplemented ewes that had access to legume pastures, ovulation rates did not increase when the legume pasture was rich in tannins although only ewes that grazed tanniniferous legumes had marginally higher ovulation rates than the control ewes (P < 0.05). When ewes grazing native pastures were supplemented with energy, their ovulation rate did not increase above those of nonsupplemented ewes. Live weight at the start of supplementation also affected ovulation rate. We conclude that ovulation was most affected by overall energy intake, whereas the factors that affected ovulation rate during short-tern nutritional supplementation were intake of protein from highly digested supplements or dietary protein protected from ruminal degradation.

Genome-enabled prediction of meat and carcass traits using Bayesian regression, single-step genomic best linear unbiased prediction and blending methods in Nelore cattle.

Several methods have been used for genome-enabled prediction (or genomic selection) of complex traits, for example, multiple regression models describing a target trait with a linear function of a set of genetic markers. Genomic selection studies have been focused mostly on single-trait analyses. However, most profitability traits are genetically correlated, and an increase in prediction accuracy of genomic breeding values for genetically correlated traits is expected when using multiple-trait models. Thus, this study was carried out to assess the accuracy of genomic prediction for carcass and meat quality traits in Nelore cattle, using single- and multiple-trait approaches. The study considered 15 780, 15 784, 15 742 and 526 records of rib eye area (REA, cm2), back fat thickness (BF, mm), rump fat (RF, mm) and Warner-Bratzler shear force (WBSF, kg), respectively, in Nelore cattle, from the Nelore Brazil Breeding Program. Animals were genotyped with a low-density single nucleotide polymorphism (SNP) panel and subsequently imputed to arrays with 54 and 777 k SNPs. Four Bayesian specifications of genomic regression models, namely, Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression; blending methods, BLUP; and single-step genomic best linear unbiased prediction (ssGBLUP) methods were compared in terms of prediction accuracy using a fivefold cross-validation. Estimates of heritability ranged from 0.20 to 0.35 and from 0.21 to 0.46 for RF and WBSF on single- and multiple-trait analyses, respectively. Prediction accuracies for REA, BF, RF and WBSF were all similar using the different specifications of regression models. In addition, this study has shown the impact of genomic information upon genetic evaluations in beef cattle using the multiple-trait model, which was also advantageous compared to the single-trait model because it accounted for the selection process using multiple traits at the same time. The advantage of multi-trait analyses is attributed to the consideration of correlations and genetic influences between the traits, in addition to the non-random association of alleles.

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle.

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer's early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal's sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme-dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme-low EC (-3.0 and -1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28-0.56 for SC and 0.26-0.49 for HP, using RNM_H, and 0.26-0.52 for SC and 0.22-0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (-3.0) and favorable (3.0) EC levels were 0.30 for HP and -0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals' genetic merit and re-ranking of animals on different environmental conditions. SNP marker-environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.

Effect of early shearing during gestation on the productive and reproductive behavior of female sheep offspring in their first 18 months of age.

The research has shown the interesting contributions of shearing in mid-gestation on the performance of lambs from birth to weaning. Other studies have reported that shearing at early pregnancy influences the development of the placenta and lamb live weight at birth. However, there was a lack of information on the effect of early-prepartum shearing on the behavior of the offspring from weaning onward. This study evaluated the effect of shearing ewes at 50 days of gestation on the growth, reproductive behavior and response to a gastrointestinal parasite challenge in the female offspring from weaning to 18 months old. Fifty-seven Polwarth female lambs were used, 22 being singles and 35 twins born to ewes either shorn at 50 days of pregnancy (PS, n = 23) or shorn at 62 days postpartum (U, control, n = 34) resulting in four subgroups: single lambs born to PS ewes (n = 8), born to U ewes (n = 14), twin lambs born to PS ewes (n = 15) or born to U ewes (n = 20). All progeny were managed together under improved pasture with a minimum forage allowance of 6% live weight on dry basis. Body weight, body condition score and fecal eggs count were recorded every 14 days from weaning to 18 months of age. Concentrations of progesterone were measured weekly (from 4 to 10 months of age and from 14 to 18 months of age) to establish the onset of puberty. Ovulation rate at an induced and a natural heat (545 ± 1.0 and 562 ± 1.0 day old) was recorded. Prepartum shearing did not affect the age at puberty or the ovulation rate of female offspring, but those born as singles were more precocious ( P = 0.03) and heavier ( P = 0.02) at puberty than twin born lambs. Both the average value of parasite egg count ( P = 0.0 7) and the Famacha index ( P = 0.02) for the entire study period were lower in lambs born to prepartum shorn ewes than those born to postpartum shorn ewes. In conclusion, shearing at 50 days of gestation did not affect the growth or the reproductive behavior of female offspring. However, female lambs born from ewe shorn during gestation showed a better response to the parasitic challenge, and further research is required to confirm this.

Retentive device for intravesical drug delivery based on water-induced shape memory response of poly(vinyl alcohol): design concept and 4D printing feasibility.

The use of shape memory polymers exhibiting water-induced shape recovery at body temperature and water solubility was proposed for the development of indwelling devices for intravesical drug delivery. These could be administered via catheter in a suitable temporary shape, retained in the bladder for a programmed period of time by recovery of the original shape and eliminated with urine following dissolution/erosion. Hot melt extrusion and fused deposition modeling 3D printing were employed as the manufacturing techniques, the latter resulting in 4D printing because of the shape modifications undergone by the printed item over time. Pharmaceutical-grade poly(vinyl alcohol) was selected based on its hot-processability, availability in different molecular weights and on preliminary data showing water-induced shape memory behavior. Specimens having various original and temporary geometries as well as compositions, successfully obtained, were characterized by differential scanning calorimetry and dynamic-mechanical thermal analysis as well as for fluid uptake, mass loss, shape recovery and release behavior. The samples exhibited the desired ability to recover the original shape, consistent in kinetics with the relevant thermo-mechanical properties, and concomitant prolonged release of a tracer. Although preliminary in scope, this study indicated the viability of the proposed approach to the design of retentive intravesical delivery systems.

Assessment of hot-processability and performance of ethylcellulose-based materials for injection-molded prolonged-release systems: An investigational approach.

The present work focuses on application of an investigational approach to assess the hot-processability of pharmaceutical-grade polymers with a potential for use in the manufacturing of reservoir drug delivery systems via micromolding, and the performance of resulting molded barriers. An inert thermoplastic polymer, ethylcellulose (EC), widely exploited for preparation of prolonged-release systems, was employed as a model component of the release-controlling barriers. Moldability studies were performed with plasticized EC, as such or in admixture with release modifiers, by the use of disk-shaped specimens ≥ 200 µm in thickness. The disks turned out to be a suitable tool for evaluation of the dimensional stability and diffusional barrier performance of the investigated materials after demolding. The effect of the amount of triethyl citrate, used as a plasticizer, on hot-processability of EC was assessed. The rate of a model drug diffusion across the polymeric barriers was shown to be influenced by the extent of porosity from the incorporated additives. The investigational approach proposed, of simple and rapid execution, holds potential for streamlining the development of prolonged-release systems produced by micromolding in the form of drug reservoirs, with no need for molds and molding processes to be set up on a case-by-case basis.

Reaction norm for yearling weight in beef cattle using single-step genomic evaluation.

When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.

Growth, meat and feed efficiency traits of lambs born to ewes submitted to energy restriction during mid-gestation.

The objective of this study was to evaluate the effects of the energy restriction of gestation of adult ewes from day 45 to day 115 on lamb live performance parameters, carcass and meat traits. In experiment I, dietary energy was restricted at 70% of the metabolizable energy (ME) requirements, after which ewes were re-fed ad libitum until lambing. In experiment II, dietary energy was restricted at 60% of the ME requirements, and ewes were re-fed to ME requirements until lambing. All ewes grazed together from the end of the restriction periods to weaning. Lambs were weaned and lot fed until slaughter. Feed intake, weight gain and feed efficiency were recorded, and body fat thickness and ribeye area (REA) were measured in the longissimus thoracis muscle. After slaughter, carcass weight and yield, fat depth, carcass and leg length, and frenched rack and leg weights and yields were determined. Muscle fiber type composition, Warner-Bratzler shear force, pH and color were determined in the longissimus lumborum muscle. In experiment I, energy restriction followed by ad libitum feeding affected lamb birth weight (P0.05) were observed on later BW, REA, BF or carcass traits. Lambs born to non-restricted-fed ewes had higher (P<0.05) weight and yield of the frenched rack cut and their meat tended (P=0.11) to be tender compared with that of lambs from restricted ewes. The percentage of oxidative muscle fibers was lower for lambs born to non-restricted ewes (P<0.05); however, no effects of ewe treatment were observed on other muscle fiber types. For experiment II, energy restriction followed by ME requirements feeding, affected (P<0.01) pre-weaning live weight gain, weaning and final weights. Lambs from restricted ewes had higher (P<0.05) feed intake as % of leg weight and a trend to be less efficient (P=0.16) than lambs from unrestricted dams. Ribeye area and BF were not influenced by treatment. Treatment significantly affected slaughter weight, but had no effects on carcass yield and traits or on meat traits. The results obtained in both experiments indicate submitting ewes to energy restriction during gestation affects the performance of their progeny but the final outcome would depend on the ewe's re-feeding level during late gestation and the capacity of the offspring to compensate the in utero restriction after birth.

Genome-wide association study for growth traits in Nelore cattle.

The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth.

SNP detection using RNA-sequences of candidate genes associated with puberty in cattle.

Fertility traits, such as heifer pregnancy, are economically important in cattle production systems, and are therefore, used in genetic selection programs. The aim of this study was to identify single nucleotide polymorphisms (SNPs) using RNA-sequencing (RNA-Seq) data from ovary, uterus, endometrium, pituitary gland, hypothalamus, liver, longissimus dorsi muscle, and adipose tissue in 62 candidate genes associated with heifer puberty in cattle. RNA-Seq reads were assembled to the bovine reference genome (UMD 3.1.1) and analyzed in five cattle breeds; Brangus, Brahman, Nellore, Angus, and Holstein. Two approaches used the Brangus data for SNP discovery 1) pooling all samples, and 2) within each individual sample. These approaches revealed 1157 SNPs. These were compared with those identified in the pooled samples of the other breeds. Overall, 172 SNPs within 13 genes (CPNE5, FAM19A4, FOXN4, KLF1, LOC777593, MGC157266, NEBL, NRXN3, PEPT-1, PPP3CA, SCG5, TSG101, and TSHR) were concordant in the five breeds. Using Ensembl's Variant Effector Predictor, we determined that 12% of SNPs were in exons (71% synonymous, 29% nonsynonymous), 1% were in untranslated regions (UTRs), 86% were in introns, and 1% were in intergenic regions. Since these SNPs were discovered in RNA, the variants were predicted to be within exons or UTRs. Overall, 160 novel transcripts in 42 candidate genes and five novel genes overlapping five candidate genes were observed. In conclusion, 1157 SNPs were identified in 62 candidate genes associated with puberty in Brangus cattle, of which, 172 were concordant in the five cattle breeds. Novel transcripts and genes were also identified.

Genetic parameter estimates for prenatal and postnatal mortality in Nellore cattle.

The aim of this study was to estimate genetic parameters for prenatal (PRE) and postnatal (POS) mortality in Nellore cattle. A total of 13 141 (PRE) and 17 818 (POS) records from Nellore females were used. PRE and POS were recorded using binary scale scores: a score of '1' was given to calves that were born alive (PRE) and those that were alive at weaning (POS), and a score of '0' was given to calves that were not alive at or around birth (PRE), as well as to those weighed at birth but not at weaning (POS). The relationship matrix included 698 sires, 107 paternal grandsires and 69 maternal grandsires. Data were analysed using Bayesian inference and a sire-maternal grandsire threshold model, including contemporary groups as random effects, and the classes of dam age at the beginning of mating season (for PRE), and dam age at calving and birthweight (linear covariable) (for POS), as fixed effects. For both traits, the covariance between direct and maternal effects (rD,M ) was estimated (rD,M ≠ 0) or fixed at zero (rD,M  = 0). PRE and POS rates were 3.00 and 4.04%, respectively. Estimates of direct and maternal heritability were 0.07 and 0.17, respectively, for PRE, and 0.02 and 0.07, respectively, for POS, assuming rD,M  = 0. For rD,M  ≠ 0, these estimates were 0.07 and 0.12, respectively, for PRE, and 0.03 and 0.07, respectively, for POS. The correlation estimates between direct and maternal effects were -0.71 (PRE) and -0.33 (POS). PRE and POS show low genetic variability, indicating that these traits probably suffer major environmental influences. Additionally, our study shows that the maternal genetic component affects preweaning calf mortality twice as much (or more) as the direct genetic component. A large number of offspring per sire is necessary in progeny tests to genetically decrease calf mortality.

Runs of homozygosity: current knowledge and applications in livestock.

This review presents a broader approach to the implementation and study of runs of homozygosity (ROH) in animal populations, focusing on identifying and characterizing ROH and their practical implications. ROH are continuous homozygous segments that are common in individuals and populations. The ability of these homozygous segments to give insight into a population's genetic events makes them a useful tool that can provide information about the demographic evolution of a population over time. Furthermore, ROH provide useful information about the genetic relatedness among individuals, helping to minimize the inbreeding rate and also helping to expose deleterious variants in the genome. The frequency, size and distribution of ROH in the genome are influenced by factors such as natural and artificial selection, recombination, linkage disequilibrium, population structure, mutation rate and inbreeding level. Calculating the inbreeding coefficient from molecular information from ROH (FROH ) is more accurate for estimating autozygosity and for detecting both past and more recent inbreeding effects than are estimates from pedigree data (FPED ). The better results of FROH suggest that FROH can be used to infer information about the history and inbreeding levels of a population in the absence of genealogical information. The selection of superior animals has produced large phenotypic changes and has reshaped the ROH patterns in various regions of the genome. Additionally, selection increases homozygosity around the target locus, and deleterious variants are seen to occur more frequently in ROH regions. Studies involving ROH are increasingly common and provide valuable information about how the genome's architecture can disclose a population's genetic background. By revealing the molecular changes in populations over time, genome-wide information is crucial to understanding antecedent genome architecture and, therefore, to maintaining diversity and fitness in endangered livestock breeds.

Genome scan for postmortem carcass traits in Nellore cattle.

Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes ( and ) involved in the cell cycle biological process which affects many aspects of animal growth and development. The and genes, both from AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (, , , , , and ) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the . There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.

Accuracies of genomic prediction of feed efficiency traits using different prediction and validation methods in an experimental Nelore cattle population.

Animal feeding is the most important economic component of beef production systems. Selection for feed efficiency has not been effective mainly due to difficult and high costs to obtain the phenotypes. The application of genomic selection using SNP can decrease the cost of animal evaluation as well as the generation interval. The objective of this study was to compare methods for genomic evaluation of feed efficiency traits using different cross-validation layouts in an experimental beef cattle population genotyped for a high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA). After quality control, a total of 437,197 SNP genotypes were available for 761 Nelore animals from the Institute of Animal Science, Sertãozinho, São Paulo, Brazil. The studied traits were residual feed intake, feed conversion ratio, ADG, and DMI. Methods of analysis were traditional BLUP, single-step genomic BLUP (ssGBLUP), genomic BLUP (GBLUP), and a Bayesian regression method (BayesCπ). Direct genomic values (DGV) from the last 2 methods were compared directly or in an index that combines DGV with parent average. Three cross-validation approaches were used to validate the models: 1) YOUNG, in which the partition into training and testing sets was based on year of birth and testing animals were born after 2010; 2) UNREL, in which the data set was split into 3 less related subsets and the validation was done in each subset a time; and 3) RANDOM, in which the data set was randomly divided into 4 subsets (considering the contemporary groups) and the validation was done in each subset at a time. On average, the RANDOM design provided the most accurate predictions. Average accuracies ranged from 0.10 to 0.58 using BLUP, from 0.09 to 0.48 using GBLUP, from 0.06 to 0.49 using BayesCπ, and from 0.22 to 0.49 using ssGBLUP. The most accurate and consistent predictions were obtained using ssGBLUP for all analyzed traits. The ssGBLUP seems to be more suitable to obtain genomic predictions for feed efficiency traits on an experimental population of genotyped animals.

Inclusion of cytoplasmic lineage effect and direct-maternal genetic covariance for genetic evaluation of growth traits in Nellore cattle.

We evaluated the impact of cytoplasmic lineage effects (Lc) for growth traits on genetic evaluation, including the genetic covariance between direct and maternal effects (σam). Pedigree data from 496,190 Nellore animals and observations on birth weight (BW, N = 243,391), weaning weight (WW, N = 431,681), and post-weaning weight gain adjusted to 345 days (PWG, N = 172,131) were analyzed. Four univariate models were used to obtain estimates of (co)variance components using the restricted maximum likelihood method in the BLUPF90 program. Model 1 included Lc and σam. Model 2 included Lc and σam was set to zero. Model 3 did not include Lc. Model 4 did not include Lc and σam was set to zero. These models considered the effects of the Lc as random. Phenotypic variance obtained through cytoplasmic lineage effects was determined for all traits, ranging from 0.07 to 0.15, 0.15 to 0.03, and 0.05 to 0.03% for BW, WW, and PWG, respectively, for models 1 and 2. Correlations between direct and maternal genetic components were positive for WW and negative for BW and PWG. No differences were observed for genetic parameter estimates or animal ranking with the inclusion of σam. For BW, the likelihood ratio suggested that model 1 best fits the data, while model 4 was the most appropriate for WW and PWG. Thus, these models are recommended for genetic evaluations. Despite the low magnitude of cytoplasmic lineages, this effect could predict breeding value and improve the selection of animals for BW in this Nellore population.

Genetic parameter estimates for carcass traits and visual scores including or not genomic information.

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.