Search

Abstract Background The 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. Results Significant 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. Conclusions GWAS 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.

Abstract Genomic selection (GS) offers a promising opportunity for selecting more efficient animals to use consumed energy for maintenance and growth functions, impacting profitability and environmental sustainability. Here, we compared the prediction accuracy of multi-layer neural network (MLNN) and support vector regression (SVR) against single-trait (STGBLUP), multi-trait genomic best linear unbiased prediction (MTGBLUP), and Bayesian regression (BayesA, BayesB, BayesC, BRR, and BLasso) for feed efficiency (FE) traits. FE-related traits were measured in 1156 Nellore cattle from an experimental breeding program genotyped for ~ 300 K markers after quality control. Prediction accuracy (Acc) was evaluated using a forward validation splitting the dataset based on birth year, considering the phenotypes adjusted for the fixed effects and covariates as pseudo-phenotypes. The MLNN and SVR approaches were trained by randomly splitting the training population into fivefold to select the best hyperparameters. The results show that the machine learning methods (MLNN and SVR) and MTGBLUP outperformed STGBLUP and the Bayesian regression approaches, increasing the Acc by approximately 8.9%, 14.6%, and 13.7% using MLNN, SVR, and MTGBLUP, respectively. Acc for SVR and MTGBLUP were slightly different, ranging from 0.62 to 0.69 and 0.62 to 0.68, respectively, with empirically unbiased for both models (0.97 and 1.09). Our results indicated that SVR and MTGBLUBP approaches were more accurate in predicting FE-related traits than Bayesian regression and STGBLUP and seemed competitive for GS of complex phenotypes with various degrees of inheritance.

Abstract Backgrounding Stayability, which may be defined as the probability of a cow remaining in the herd until a reference age or at a specific number of calvings, is usually measured late in the animal’s life. Thus, if used as selection criteria, it will increase the generation interval and consequently might decrease the annual genetic gain. Measuring stayability at an earlier age could be a reasonable strategy to avoid this problem. In this sense, a better understanding of the genetic architecture of this trait at different ages and/or at different calvings is important. This study was conducted to identify possible regions with major effects on stayability measured considering different numbers of calvings in Nellore cattle as well as pathways that can be involved in its expression throughout the female’s productive life. Results The top 10 most important SNP windows explained, on average, 17.60% of the genetic additive variance for stayability, varying between 13.70% (at the eighth calving) and 21% (at the fifth calving). These SNP windows were located on 17 chromosomes (1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 20, 27, and 28), and they harbored a total of 176 annotated genes. The functional analyses of these genes, in general, indicate that the expression of stayability from the second to the sixth calving is mainly affected by genetic factors related to reproductive performance, and nervous and immune systems. At the seventh and eighth calvings, genes and pathways related to animal health, such as density bone and cancer, might be more relevant. Conclusion Our results indicate that part of the target genomic regions in selecting for stayability at earlier ages (from the 2th to the 6th calving) would be different than selecting for this trait at later ages (7th and 8th calvings). While the expression of stayability at earlier ages appeared to be more influenced by genetic factors linked to reproductive performance together with an overall health/immunity, at later ages genetic factors related to an overall animal health gain relevance. These results support that selecting for stayability at earlier ages (perhaps at the second calving) could be applied, having practical implications in breeding programs since it could drastically reduce the generation interval, accelerating the genetic progress.

ABSTRACT: In beef cattle breeding programs, various selection criteria have been proposed and employed with the aim of improving traits related to carcass composition and the quality of the final product, meat. However, the importance of genotype by environment interaction (G×E) for such traits is still not well understood. Our objectives were: 1) to investigate the importance of G×E on ultrasound carcass traits, growth and visual scores and 2) to estimate the genetic correlation of ultrasound carcass traits with growth and visual scores taking into account the G×E in Hereford and Braford cattle. A multiple-trait reaction norm model was fitted to the field records of 37,948 animals. With the exception of postweaning average daily weight gain (ADG), the G×E can lead to important changes in the ranking of estimated breeding values of sires across environments for all traits. Thus, models that consider heterogeneity of genetic variances along an environmental gradient may be considered more appropriate for genetic evaluations of animals reared under conditions similar to the present study. Based on estimates of genetic correlation, the quality of visual scores or ADG as indicators of carcass quality assessed by ultrasonography is dependent on the production environment.

Abstract The wide use of genomic information has enabled the identification of lethal recessive alleles that are the major genetic causes of reduced conception rates, longer calving intervals, or lower survival for live-born animals. This study was carried out to screen the Nellore cattle genome for lethal recessive haplotypes based on deviation from the expected population homozygosity, and to test SNP markers surrounding the lethal haplotypes region for association with heifer rebreeding (HR), post-natal mortality (PNM) and stayability (STAY). This approach requires genotypes only from apparently normal individuals and not from affected embryos. A total of 62,022 animals were genotyped and imputed to a high-density panel (777,962 SNP markers). Expected numbers of homozygous individuals were calculated, and the probabilities of observing 0 homozygotes was obtained. Deregressed genomic breeding values [(G)EBVs] were used in a GWAS to identify candidate genes and biological mechanisms affecting HR, STAY and PNM. In the functional analyses, genes within 100 kb down and upstream of each significant SNP marker, were researched. Thirty haplotypes had high expected frequency, while no homozygotes were observed. Most of the alleles present in these haplotypes had a negative mean effect for PNM, HR and STAY. The GWAS revealed significant SNP markers involved in different physiological mechanisms, leading to harmful effect on the three traits. The functional analysis revealed 26 genes enriched for 19 GO terms. Most of the GO terms found for biological processes, molecular functions and pathways were related to tissue development and the immune system. More phenotypes underlying these putative regions in this population could be the subject of future investigation. Tests to find putative lethal haplotype carriers could help breeders to eliminate them from the population or manage matings in order to avoid homozygous.

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

Abstract Background Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population). Results The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle. Conclusions Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches.

Abstract The increasing global demand for food, due to the continuous growth of human population, requires improvements in the efficiency and sustainability of animal production systems. In addition, several challenges facing farming of aquatic and terrestrial organisms need to be overcome to ensure food security in the upcoming decades, e.g. adaptation to climate change, reduced availability of conventional animal feed ingredients, emerging infectious and parasitic diseases, among others. Genomic technologies such as massive parallel sequencing, high‐throughput genotyping, genome selection and gene editing, combined with highly efficient computational methods can accelerate the rate of genetic progress in animal breeding. Thus, such technologies can help us meet the needs for protein sources for human consumption in the upcoming years. This Special Issue aims at presenting current advancements in the field of genomic tools applied to aquatic and terrestrial farmed animal populations.

The prenatal environment is recognized as crucial for the postnatal performance in cattle. In tropical regions, pregnant beef cows commonly experience nutritional restriction during the second half of the gestation period. Thus, the present study was designed to analyze the genotype by prenatal environment interaction (G × Epn) and to identify genomic regions associated with the level and response in growth and reproduction-related traits of beef cattle to changes in the prenatal environment. A reaction norm model was applied to data from two Nelore herds using the solutions of contemporary groups for birth weight as a descriptor variable of the gestational environment quality. A better gestational environment favored weights until weaning, scrotal circumference at yearling, and days to first calving of the offspring. The G × Epn was strong enough to result in heterogeneity of variance components and genetic parameters in addition to reranking of estimated breeding values and SNPs effects. Several genomic regions associated with the level of performance and specific responses of the animals to variations in the gestational environment were revealed, which harbor QTLs and can be exploited for selection purposes. Therefore, genetic evaluation models considering G × Epn and special management and nutrition care for pregnant cows are recommended.

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.

Abstract Background A cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes that were not originally reported in a target population of animals genotyped with single nucleotide polymorphism (SNP) panels. The feasibility of this process relies on the accuracy of the genotype imputation in that population, particularly for potential causal mutations which may be at low frequency and either within genes or regulatory regions. The objective of the present study was to investigate the imputation accuracy to the sequence level in a Nellore beef cattle population, including that for variants in annotation classes which are more likely to be functional. Methods Information of 151 key sequenced Nellore sires were used to assess the imputation accuracy from bovine HD BeadChip SNP (~ 777 k) to whole-genome sequence. The choice of the sires aimed at optimizing the imputation accuracy of a genotypic database, comprised of about 10,000 genotyped Nellore animals. Genotype imputation was performed using two computational approaches: FImpute3 and Minimac4 (after using Eagle for phasing). The accuracy of the imputation was evaluated using a fivefold cross-validation scheme and measured by the squared correlation between observed and imputed genotypes, calculated by individual and by SNP. SNPs were classified into a range of annotations, and the accuracy of imputation within each annotation classification was also evaluated. Results High average imputation accuracies per animal were achieved using both FImpute3 (0.94) and Minimac4 (0.95). On average, common variants (minor allele frequency (MAF) > 0.03) were more accurately imputed by Minimac4 and low-frequency variants (MAF ≤ 0.03) were more accurately imputed by FImpute3. The inherent Minimac4 Rsq imputation quality statistic appears to be a good indicator of the empirical Minimac4 imputation accuracy. Both software provided high average SNP-wise imputation accuracy for all classes of biological annotations. Conclusions Our results indicate that imputation to whole-genome sequence is feasible in Nellore beef cattle since high imputation accuracies per individual are expected. SNP-wise imputation accuracy is software-dependent, especially for rare variants. The accuracy of imputation appears to be relatively independent of annotation classification.

Abstract Background Pacu (Piaractus mesopotamicus) is one of the most important Neotropical aquaculture species from South America. Disease outbreaks caused by Aeromonas hydrophila infection have been considered significant contributors to the declining levels of pacu production. The current implementation of genomic selection for disease resistance has been adopted as a powerful strategy for improvement in fish species. This study aimed to investigate the genetic architecture of resistance to A. hydrophila in pacu via Genome-Wide Association Study (GWAS), the identification of suggestive Quantitative Trait Loci (QTLs) and putative genes associated with this trait. The genetic data were obtained from 381 juvenile individuals belonging to 14 full-sibling families. An experimental challenge was performed to gain access to the levels of genetic variation for resistance against the bacteria using the following trait definitions: binary test survival (TS) and time of death (TD). Results The analyses of genetic parameters estimated moderate heritability (h 2 ) for both resistance traits: 0.20 (± 0.09) for TS and 0.35 (± 0.15) for TD. A linkage map for pacu was developed to enable the GWAS, resulting in 27 linkage groups (LGs) with 17,453 mapped Single Nucleotide Polymorphisms (SNPs). The length of the LGs varied from 79.95 (LG14) to 137.01 (LG1) cM, with a total map length of 2755.60 cM. GWAS identified 22 putative QTLs associated to A. hydrophila resistance. They were distributed into 17 LGs, and were considered suggestive genomic regions explaining > 1% of the additive genetic variance (AGV) for the trait. Several candidate genes related to immune response were located close to the suggestive QTLs, such as tbk1, trim16, Il12rb2 and lyz2. Conclusion This study describes the development of the first medium density linkage map for pacu, which will be used as a framework to study relevant traits to the production of this species. In addition, the resistance to A. hydrophila was found to be moderately heritable but with a polygenic architecture suggesting that genomic selection, instead of marker assisted selection, might be useful for efficiently improving resistance to one of the most problematic diseases that affects the South American aquaculture.

Abstract Background Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance. We hypothesized that genetic factors that contribute to variation in temperament among individuals within a species will be shared between humans and cattle. Using imputed whole-genome sequence data from 9223 beef cattle from three cohorts, a series of genome-wide association studies was undertaken on cattle flight time, a temperament phenotype measured as the time taken for an animal to cover a short-fixed distance after release from an enclosure. We also investigated the association of cattle temperament with polymorphisms in bovine orthologs of risk genes for neuroticism, schizophrenia, autism spectrum disorders (ASD), and developmental delay disorders in humans. Results Variants with the strongest associations were located in the bovine orthologous region that is involved in several behavioural and cognitive disorders in humans. These variants were also partially validated in independent cattle cohorts. Genes in these regions (BARHL2, NDN, SNRPN, MAGEL2, ABCA12, KIFAP3, TOPAZ1, FZD3, UBE3A, and GABRA5) were enriched for the GO term neuron migration and were differentially expressed in brain and pituitary tissues in humans. Moreover, variants within 100 kb of ASD susceptibility genes were associated with cattle temperament and explained 6.5% of the total additive genetic variance in the largest cattle cohort. The ASD genes with the most significant associations were GABRB3 and CUL3. Using the same 100 kb window, a weak association was found with polymorphisms in schizophrenia risk genes and no association with polymorphisms in neuroticism and developmental delay disorders risk genes. Conclusions Our analysis showed that genes identified in a meta-analysis of cattle temperament contribute to neuron development functions and are differentially expressed in human brain tissues. Furthermore, some ASD susceptibility genes are associated with cattle temperament. These findings provide evidence that genetic control of temperament might be shared between humans and cattle and highlight the potential for future analyses to leverage results between species.

Abstract Most of the knowledge about genetic variants at the sequence level in cattle is for Bos primigenius taurus populations. Here, we presented a complete genomic characterization of 52 Nellore (Bos primigenius indicus) bulls, revealing specific zebu DNA variants with putative impact in tropical adaptation and productive traits. Single nucleotide polymorphisms (SNPs) and insertion/deletion (INDELs) mutations were identified using the newest bovine reference genome ARS_UCD1.2, and variant functional consequences were predicted using the Ensembl VEP software. A total of 35,753,707 SNPs and 4,492,636 INDELs were detected and annotated to their functional effects. We identified 400 genes that comprised both, a SNP and an INDEL, of high functional impact on proteins (i.e. variants that cause protein truncation, loss of function or triggering nonsense-mediated decay). Among these, we highlight the following genes: BoLA, associated with cattle immune response to infections and reproduction aspects; HSPA8, DNAJC27, and DNAJC28, involved with thermoregulatory protective mechanisms in mammals; and many olfactory signaling pathway related genes that are important genetic factors in the evolution of mammalian species. All these functional aspects are directly related to cattle adaptability to tropical environments.

This study focused on assessing the usefulness of using audio signal processing in the gaited horse industry. A total of 196 short-time audio files (4 s) were collected from video recordings of Brazilian gaited horses. These files were converted into waveform signals (196 samples by 80,000 columns) and divided into training (N = 164) and validation (N = 32) datasets. Twelve single-valued audio features were initially extracted to summarize the training data according to the gait patterns (Marcha Batida—MB and Marcha Picada—MP). After preliminary analyses, high-dimensional arrays of the Mel Frequency Cepstral Coefficients (MFCC), Onset Strength (OS), and Tempogram (TEMP) were extracted and used as input information in the classification algorithms. A principal component analysis (PCA) was performed using the 12 single-valued features set and each audio-feature dataset—AFD (MFCC, OS, and TEMP) for prior data visualization. Machine learning (random forest, RF; support vector machine, SVM) and deep learning (multilayer perceptron neural networks, MLP; convolution neural networks, CNN) algorithms were used to classify the gait types. A five-fold cross-validation scheme with 10 repetitions was employed for assessing the models' predictive performance. The classification performance across models and AFD was also validated with independent observations. The models and AFD were compared based on the classification accuracy (ACC), specificity (SPEC), sensitivity (SEN), and area under the curve (AUC). In the logistic regression analysis, five out of the 12 audio features extracted were significant (p < 0.05) between the gait types. ACC averages ranged from 0.806 to 0.932 for MFCC, from 0.758 to 0.948 for OS and, from 0.936 to 0.968 for TEMP. Overall, the TEMP dataset provided the best classification accuracies for all models. The most suitable method for audio-based horse gait pattern classification was CNN. Both cross and independent validation schemes confirmed that high values of ACC, SPEC, SEN, and AUC are expected for yet-to-be-observed labels, except for MFCC-based models, in which clear overfitting was observed. Using audio-generated data for describing gait phenotypes in Brazilian horses is a promising approach, as the two gait patterns were correctly distinguished. The highest classification performance was achieved by combining CNN and the rhythmic-descriptive AFD.

The assessment of the presence of genotype by environment interaction (GxE) in beef cattle is very important in tropical countries with diverse climatic conditions and production systems. The present study aimed to assess the presence of GxE by using different reaction norm models for eleven traits related to growth, reproduction, and visual score in Nellore cattle. We studied five reaction norm models (RNM), fitting a linear model considering homoscedastic residual variance (RNM_homo), and four models considering heteroskedasticity, being linear (RNM_hete), quadratic (RNM_quad), linear spline (RNM_l-l), and quadratic spline (RNM_q-q). There was the presence of GxE for age at first calving (AFC), scrotal circumference (SC), weaning to yearling weight gain (WYG), and yearling weight (YW). The best models were RNM_l-l for YW and RNM_q-q for AFC, SC, and WYG. The heritability estimates for RNM_l-l ranged from 0.07 to 0.20, 0.42 to 0.61, 0.24 to 0.42, and 0.47 to 0.63 for AFC, SC, WYG, and YW, respectively. The heteroskedasticity in reaction norm models improves the assessment of the presence of GxE for YW, WYG, AFC, and SC. Additionally, the trajectories of reaction norms for these traits seem to be affected by a non-linear component, and selecting robust animals for these traits is an alternative to increase production and reduce environmental sensitivity.

The inclusion of genomic information became a reality in shrimp breeding and it is expected to accelerate the genetic gain over time. The decay of linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs) is an important measure to evaluate the feasibility of implementing genomic selection. The aim of this study was to evaluate the use of a novel 50 K SNP array tool to characterize the genomic diversity, LD and effective population size (Ne) in a farmed shrimp population. A total of 96 animals (40 sires and 56 dams) were genotyped using the novel Illumina AquaArray HD (50 K) vannamei®. Quality control (QC) of genomic data was performed and three different minor allele frequency (MAF) exclusion thresholds were applied: < 0.10 (QC1), < 0.05 (QC2) and < 0.01 (QC3). After QC, 34,425, 39,091 and 42,789 SNPs were retained for QC1, QC2 and QC3, respectively, validating the high informativeness of this SNP array to this particular shrimp breeding population. The population showed a considerable high overall heterozygosity in comparison to other aquaculture species meaning that genetic diversity is stable despite selection. The principal component analysis revealed three genetically distant groups with the first two principal components explaining 27.7 % of total variation. LD decayed rapidly in the first 30Kb of distance between markers from 0.20 to 0.07 and then decreased to 0.02 in the long-range distance. These results suggest a relatively recent incorporation of animals from different populations in the broodstock. Ne size reduced from 7,871 to 301 animals in 827 generations for QC1, 8,253 to 305 animals for QC2 and 8,957 to 315 animals for QC3, both in 899 generations. Contemporary Ne was close to 86 for all QCs. The level of LD estimated suggests that genomic selection and genome-wide association studies are feasible in shrimp by using this SNP array.

Abstract Background Selection of cattle that are less sensitive to environmental variation in unfavorable environments and more adapted to harsh conditions is of primary importance for tropical beef cattle production systems. Understanding the genetic background of sensitivity to environmental variation is necessary for developing strategies and tools to increase efficiency and sustainability of beef production. We evaluated the degree of sensitivity of beef cattle performance to environmental variation, at the animal and molecular marker levels (412 K single nucleotide polymorphisms), by fitting and comparing the results of different reaction norm models (RNM), using a comprehensive dataset of Nellore cattle raised under diverse environmental conditions. Results Heteroscedastic RNM (with different residual variances for environmental level) provided better fit than homoscedastic RNM. In addition, spline and quadratic RNM outperformed linear RNM, which suggests the existence of a nonlinear genetic component affecting the performance of Nellore cattle. This nonlinearity indicates that within-animal sensitivity depends on the environmental gradient (EG) level and that animals may present different patterns of sensitivity according to the range of environmental variations. The spline RNM showed that sensitivity to environmental variation from harsh to average EG is lowly correlated with sensitivity from average to good EG, at both the animal and molecular marker levels. Although the genomic regions that affect sensitivity in harsher environments were not the same as those associated with less challenging environments, the candidate genes within those regions participate in common biological processes such as those related to inflammatory and immune response. Some plausible candidate genes were identified. Conclusions Sensitivity of tropical beef cattle to environmental variation is not continuous along the environmental gradient, which implies that animals that are less sensitive to harsher conditions are not necessarily less responsive to variations in better environmental conditions, and vice versa. The same pattern was observed at the molecular marker level, i.e. genomic regions and, consequently, candidate genes associated with sensitivity to harsh conditions were not the same as those associated with sensitivity to less challenging conditions.

Abstract Background Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. Results Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. Conclusions There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance.

Abstract Background Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness. Results The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes. Conclusions GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

ABSTRACT The objective of this study was to estimate adjustment factors of scrotal circumference for growth traits in Nellore cattle. Measurement at post-yearling of scrotal circumference from 100,107 Nellore was adjusted for six traits: age (A), body weight (BW), hip height (HH), conformation (C), precocity (P), musculature (M), and simultaneously for age and the other five traits (A-BW, A-HH, A-C, A-P, A-M), body weight and the other four traits (BW-HH, BW-C, BW-P, BW-M), and hip height and the other three traits (HH-C, HH-P, HH-M). Standard values were 500 days, 300 kg, 135 cm, and 3, for age, body weight, hip height, and visual scores, respectively. Amplitudes of adjustment factor of scrotal circumference for age, body weight, and hip height were 0.6028, 0.4869, and 0.1572, respectively. Scrotal circumference is expected to grow, on average, 8.71 cm per 100 days of age, 6.51 cm per 100 kg of body weight, and 4.81 cm per 10 cm of hip height. The results showed higher amplitude in the adjustment factor of scrotal circumference for age and body weight (0.3429) compared with age and hip height and body weight and hip height (0.1271 and 0.0443, respectively). The amplitude observed in adjustment factor of scrotal circumference for conformation, precocity, and musculature were 0.1328, 0.1175, and 0.1160, respectively. Considering different adjustment factors of scrotal circumference can be useful for identifying better selection criteria for growth and/or sexual precocity in Nellore.

Increasing productivity through continued animal genetic improvement is a crucial part of implementing sustainable livestock intensification programs. In Zebu cattle, the lack of sexual precocity is one of the main obstacles to improving beef production efficiency. Puberty-related traits are complex, but large-scale data sets from different “omics” have provided information on specific genes and biological processes with major effects on the expression of such traits, which can greatly increase animal genetic evaluation. In addition, genetic parameter estimates and genomic predictions involving sexual precocity indicator traits and productive, reproductive, and feed-efficiency related traits highlighted the feasibility and importance of direct selection for anticipating heifer reproductive life. Indeed, the case study of selection for sexual precocity in Nellore breeding programs presented here show that, in 12 years of selection for female early precocity and improved management practices, the phenotypic means of age at first calving showed a strong decreasing trend, changing from nearly 34 to less than 28 months, with a genetic trend of almost −2 days/year. In this period, the percentage of early pregnancy in the herds changed from around 10% to more than 60%, showing that the genetic improvement of heifer’s sexual precocity allows optimizing the productive cycle by reducing the number of unproductive animals in the herd. It has a direct impact on sustainability by better use of resources. Genomic selection breeding programs accounting for genotype by environment interaction represent promising tools for accelerating genetic progress for sexual precocity in tropical beef cattle.

Abstract Background In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv ≠ 0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv = 0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_ σê2 $$ {\upsigma}_{\widehat{\mathrm{e}}}^2 $$). Results The dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor > 20) with dEBVv and ln_ σê2 $$ {\upsigma}_{\widehat{\mathrm{e}}}^2 $$, respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation. Conclusions It is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it.

Abstract Background Due to the advancement in high throughput technology, single nucleotide polymorphism (SNP) is routinely being incorporated along with phenotypic information into genetic evaluation. However, this approach often cannot achieve high accuracy for some complex traits. It is possible that SNP markers are not sufficient to predict these traits due to the missing heritability caused by other genetic variations such as microsatellite and copy number variation (CNV), which have been shown to affect disease and complex traits in humans and other species. Results In this study, CNVs were included in a SNP based genomic selection framework. A Nellore cattle dataset consisting of 2230 animals genotyped on BovineHD SNP array was used, and 9 weight and carcass traits were analyzed. A total of six models were implemented and compared based on their prediction accuracy. For comparison, three models including only SNPs were implemented: 1) BayesA model, 2) Bayesian mixture model (BayesB), and 3) a GBLUP model without polygenic effects. The other three models incorporating both SNP and CNV included 4) a Bayesian model similar to BayesA (BayesA+CNV), 5) a Bayesian mixture model (BayesB+CNV), and 6) GBLUP with CNVs modeled as a covariable (GBLUP+CNV). Prediction accuracies were assessed based on Pearson’s correlation between de-regressed EBVs (dEBVs) and direct genomic values (DGVs) in the validation dataset. For BayesA, BayesB and GBLUP, accuracy ranged from 0.12 to 0.62 across the nine traits. A minimal increase in prediction accuracy for some traits was noticed when including CNVs in the model (BayesA+CNV, BayesB+CNV, GBLUP+CNV). Conclusions This study presents the first genomic prediction study integrating CNVs and SNPs in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some traits in Nellore cattle.

Salmonid rickettsial syndrome (SRS), caused by the intracellular bacterium Piscirickettsia salmonis, is one of the main diseases affecting rainbow trout (Oncorhynchus mykiss) farming. To accelerate genetic progress, genomic selection methods can be used as an effective approach to control the disease. The aims of this study were: (i) to compare the accuracy of estimated breeding values using pedigree-based best linear unbiased prediction (PBLUP) with genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), Bayes C, and Bayesian Lasso (LASSO); and (ii) to test the accuracy of genomic prediction and PBLUP using different marker densities (0.5, 3, 10, 20, and 27 K) for resistance against P. salmonis in rainbow trout. Phenotypes were recorded as number of days to death (DD) and binary survival (BS) from 2416 fish challenged with P. salmonis. A total of 1934 fish were genotyped using a 57 K single-nucleotide polymorphism (SNP) array. All genomic prediction methods achieved higher accuracies than PBLUP. The relative increase in accuracy for different genomic models ranged from 28 to 41% for both DD and BS at 27 K SNP. Between different genomic models, the highest relative increase in accuracy was obtained with Bayes C (∼40%), where 3 K SNP was enough to achieve a similar accuracy to that of the 27 K SNP for both traits. For resistance against P. salmonis in rainbow trout, we showed that genomic predictions using GBLUP, ssGBLUP, Bayes C, and LASSO can increase accuracy compared with PBLUP. Moreover, it is possible to use relatively low-density SNP panels for genomic prediction without compromising accuracy predictions for resistance against P. salmonis in rainbow trout.

Piscirickettsia salmonis is the etiologic agent of salmon rickettsial syndrome (SRS) and is responsible for considerable economic losses in salmon aquaculture. The bacterium affects coho salmon (CS; Oncorhynchus kisutch), Atlantic salmon (AS; Salmo salar), and rainbow trout (RT; Oncorhynchus mykiss) in several countries, including Norway, Canada, Scotland, Ireland, and Chile. We used Bayesian genome-wide association study analyses to investigate the genetic architecture of resistance to P. salmonis in farmed populations of these species. Resistance to SRS was defined as the number of days to death and as binary survival (BS). A total of 828 CS, 2130 RT, and 2601 AS individuals were phenotyped and then genotyped using double-digest restriction site-associated DNA sequencing and 57K and 50K Affymetrix® Axiom® single nucleotide polymorphism (SNP) panels, respectively. Both traits of SRS resistance in CS and RT appeared to be under oligogenic control. In AS, there was evidence of polygenic control of SRS resistance. To identify candidate genes associated with resistance, we applied a comparative genomics approach in which we systematically explored the complete set of genes adjacent to SNPs, which explained more than 1% of the genetic variance of resistance in each salmonid species (533 genes in total). Thus, genes were classified based on the following criteria: i) shared function of their protein domains among species, ii) shared orthology among species, iii) proximity to the SNP explaining the highest proportion of the genetic variance, and iv) presence in more than one genomic region explaining more than 1% of the genetic variance within species. Our results allowed us to identify 120 candidate genes belonging to at least one of the four criteria described above. Of these, 21 of them were part of at least two of the criteria defined above and are suggested to be strong functional candidates influencing P. salmonis resistance. These genes are related to diverse biological processes, such as kinase activity, GTP hydrolysis, helicase activity, lipid metabolism, cytoskeletal dynamics, inflammation, and innate immune response, which seem essential in the host response against P. salmonis infection. These results provide fundamental knowledge on the potential functional genes underpinning resistance against P. salmonis in three salmonid species.

Reproductive performance is a key indicator of the long-term sustainability of any livestock production system. Testicular hypoplasia (TH) is a morphological and functional reproductive disorder that affects bulls around the world and consequently causes major economic losses due to reduced fertility rates. Despite the improvements in management practices to enhance performance of affected animals, the use of hypoplastic animals for reproduction might contribute to expand the prevalence of this disorder. The aim of this study was to identify genomic regions that are associated with TH in Nellore cattle by performing a genome-wide association study (GWAS) and functional analyses. Phenotypic and pedigree data from 47,563 animals and genotypes (500,689 Single Nucleotide Polymorphism, SNPs) from 265 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. The estimated breeding values (EBVs) were calculated by fitting a single-trait threshold animal model using a Bayesian approach. The SNP effects were estimated using the Bayes C method and de-regressed EBVs for TH as the response variable (pseudo-phenotype). The top-15 ranking windows (5-adjacent SNPs) that explained the highest proportion of variance were identified for further functional and biological network analyses. The posterior mean (95% highest posterior density) of the heritability for TH was 0.16 (0.08; 0.23). The most important genomic windows were located on BTA1, BTA3, BTA4, BTA5, BTA9, BTA22, BTA23, and BTA25. These windows explained together 22.69% of the total additive genetic variance for TH. Strong candidate genes associated with metabolism and synthesis of steroids, cell survival, spermatogenesis process and sperm motility were identified, which might play an important role in the expression of TH. Our findings contribute to a better biological understanding of TH and future characterization of causal variants might enable improved genomic prediction of this trait in beef cattle.

Chilean Farmed Atlantic salmon (Salmo salar) populations were established with individuals of both European and North American origins. These populations are expected to be highly genetically differentiated due to evolutionary history and poor gene flow between ancestral populations from different continents. The extent and decay of linkage disequilibrium (LD) among single nucleotide polymorphism (SNP) impacts the implementation of genome-wide association studies and genomic selection and provides relevant information about demographic processes of fish populations. We assessed the population structure and characterized the extent and decay of LD in three Chilean commercial populations of Atlantic salmon with North American (NAM), Scottish (SCO), and Norwegian (NOR) origin. A total of 123 animals were genotyped using a 159 K SNP Axiom® myDesignTM Genotyping Array. A total of 32 K SNP markers, representing the common SNPs along the three populations after quality control were used. The principal component analysis explained 78.9% of the genetic diversity between populations, clearly discriminating between populations of North American and European origin, and also between European populations. NAM had the lowest effective population size, followed by SCO and NOR. Large differences in the LD decay were observed between populations of North American and European origin. An r2 threshold of 0.2 was estimated for marker pairs separated by 7,800, 64, and 50 kb in the NAM, SCO, and NOR populations, respectively. In this study we show that this SNP panel can be used to detect association between markers and traits of interests and also to capture high-resolution information for genome-enabled predictions. Also, we suggest the feasibility to achieve similar prediction accuracies using a smaller SNP data set for the NAM population, compared with samples with European origin which would need a higher density SNP array.

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9–48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Resumo: O objetivo deste trabalho foi avaliar estratégias de seleção simulada pela contribuição genética ótima quanto ao ganho genético, com restrição sobre a coancestria, para a característica peso aos 84 dias idade, em ovinos Santa Inês. As análises foram definidas conforme um algoritmo de evolução diferencial, que otimizou uma função-objetivo composta pelo mérito genético e a coancestria média dos animais candidatos à reprodução. A estratégia definida como ótima indicou a utilização de 19 carneiros, o que resultaria em ganho médio esperado de 1,1259 unidades de desvio-padrão, e coancestria igual a 0,0249 (estratégia 5). Em comparação à seleção com base apenas no valor genético, a estratégia ótima reduziu a coancestria em 12%, e o ganho genético, em apenas 3%. A seleção de ovinos pela contribuição genética ótima oferece diferentes níveis de ganho genético, que são atingíveis a partir de restrições sobre a coancestria. Assim, é possível minimizar a coancestria, ou restringi-la em um valor pré-definido, e maximizar o ganho genético simultaneamente com o uso da contribuição genética ótima.

Zebu cattle (Bos taurus indicus) are highly adapted to tropical regions. However, females reach puberty after taurine heifers, which affects the economic efficiency of beef cattle breeding in the tropical regions. The aims of this study were to establish associations between the haplotype alleles of the bovine genome and age at first calving (AFC) in the Nelore cattle, and to identify the genes and quantitative trait loci (QTL) related to this phenotype. A total of 2,273 Nelore cattle (995 males and 1,278 females) genotyped using the Illumina BovineHD BeadChip were used in the current study. The association analysis included females with valid first calving records as well as open heifers. Linkage disequilibrium (LD) analysis among the markers was performed using blocks of 5, 10, and 15 markers, which were determined by sliding windows shifting one marker at a time. Then, the haplotype block size to be used in the association study was chosen based on the highest r2 average among the SNPs in the block. The five HapAlleles most strongly associated with the trait (top five) were considered as significant associations. The results of the analysis revealed four genomic regions related to AFC, which overlapped with 20 QTL of the reproductive traits reported previously. Furthermore, there were 19 genes related to reproduction in those regions. In conclusion, the use of haplotypes allowed the detection of chromosomal regions associated with AFC in Nelore cattle, and provided the basis for elucidating the mechanisms underlying this trait.

Stayability, which can be defined as the probability of a cow calving at a certain age when given the opportunity, is an important reproductive trait in beef cattle because it is directly related to herd profitability. The objective of this study was to estimate genetic parameters and to identify possible genomic regions associated with the phenotypic expression of stayability in Nellore cows. The variance components were estimated by Bayesian inference using a threshold animal model that included the systematic effects of contemporary group and sexual precocity and the random effects of animal and residual. The SNP effects were estimated by the single-step genomic BLUP method using information of 2,838 animals (2,020 females and 930 sires) genotyped with the Illumina High-Density BeadChip Array (San Diego, CA, USA). The variance explained by windows formed by 200 consecutive SNPs was used to identify genomic regions of largest effect on the expression of stayability. The heritability was 0.11 ± 0.01 when A matrix (pedigree) was used and 0.14 ± 0.01 when H matrix (relationship matrix that combines pedigree information and SNP data) was used. A total of 147 candidate genes for stayability were identified on chromosomes 1, 2, 5, 6, 9 and 20 and on the X chromosome. New candidate regions for stayability were detected, most of them related to reproductive, immunological and central nervous system functions.

Reproductive traits are economically important for beef cattle production; however, these traits are still a bottleneck in indicine cattle since these animals typically reach puberty at older ages when compared to taurine breeds. In addition, reproductive traits are complex phenotypes, i.e., they are controlled by both the environment and many small-effect genes involved in different pathways. In this study, we conducted genome-wide association study (GWAS) and functional analyses to identify important genes and pathways associated with heifer rebreeding (HR) and with the number of calvings at 53 months of age (NC53) in Nellore cows. A total of 142,878 and 244,311 phenotypes for HR and NC53, respectively, and 2,925 animals genotyped with the Illumina Bovine HD panel (Illumina®, San Diego, CA, USA) were used in GWAS applying the weighted single-step GBLUP (WssGBLUP) method. Several genes associated with reproductive events were detected in the 20 most important 1Mb windows for both traits. Significant pathways for HR and NC53 were associated with lipid metabolism and immune processes, respectively. MHC class II genes, detected on chromosome 23 (window 25-26Mb) for NC53, were significantly associated with pregnancy success of Nellore cows. These genes have been proved previously to be associated with reproductive traits such as mate choice in other breeds and species. Our results suggest that genes associated with the reproductive traits HR and NC53 may be involved in embryo development in mammalian species. Furthermore, some genes associated with mate choice may affect pregnancy success in Nellore cattle.

Two complementary methods, namely Multi-Trait Meta-Analysis and Versatile Gene-Based Test for Genome-wide Association Studies (VEGAS), were used to identify putative pleiotropic genes affecting carcass traits in Bos indicus (Nellore) cattle. The genotypic data comprised over 777,000 single-nucleotide polymorphism markers scored in 995 bulls, and the phenotypic data included deregressed breeding values (dEBV) for weight measurements at birth, weaning and yearling, as well visual scores taken at weaning and yearling for carcass finishing precocity, conformation and muscling. Both analyses pointed to the pleomorphic adenoma gene 1 (PLAG1) as a major pleiotropic gene. VEGAS analysis revealed 224 additional candidates. From these, 57 participated, together with PLAG1, in a network involved in the modulation of the function and expression of IGF1 (insulin like growth factor 1), IGF2 (insulin like growth factor 2), GH1 (growth hormone 1), IGF1R (insulin like growth factor 1 receptor) and GHR (growth hormone receptor), suggesting that those pleiotropic genes operate as satellite regulators of the growth pathway.

The objective of this study was to identify genomic regions that are associated with meat quality traits in the Nellore breed. Nellore steers were finished in feedlots and slaughtered at a commercial slaughterhouse. This analysis included 1,822 phenotypic records of tenderness and 1,873 marbling records. After quality control, 1,630 animals genotyped for tenderness, 1,633 animals genotyped for marbling, and 369,722 SNPs remained. The results are reported as the proportion of variance explained by windows of 150 adjacent SNPs. Only windows with largest effects were considered. The genomic regions were located on chromosomes 5, 15, 16 and 25 for marbling and on chromosomes 5, 7, 10, 14 and 21 for tenderness. These windows explained 3,89% and 3,80% of the additive genetic variance for marbling and tenderness, respectively. The genes associated with the traits are related to growth, muscle development and lipid metabolism. The study of these genes in Nellore cattle is the first step in the identification of causal mutations that will contribute to the genetic evaluation of the breed.

The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen® and Paint® animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations.

This study aimed to compare estimates of (co)variances considering the effect of direct maternal genetic correlation (-0,50; -0,25; +0,25; +0,50); the ratios between the direct and maternal genetic variances (75:75; 50:100; 100:50) and two models which included (M2) or not (M1) the direct maternal genetic covariance. Stochastic simulation of twenty replicates of a closed and randomly mated herd of cattle was carried out for twenty years of selection. The base population was not related, nonselected and randomly sampled. (Co)variance estimates were obtained under single trait animal model using MTDFREML application. The model was not significant on estimates of maternal permanent environmental variance. The genetic direct-maternal correlation influenced all (co)variance estimates significantly (P

A program to determine optimum contribution selection using differential evolution was developed. The objective function to be optimized was composed by the expected merit of the future progeny and the coancestry among selected parents. Simulated and real datasets of populations with overlapping generations were used to validate and test the performance of the program. The program was computationally efficient and feasible for practical applications. The expected consequences of using the program, in contrast to empirical procedures to control inbreeding and/or to selection based exclusively on expected genetic merit, would be the improvement of the selection response and a more effective control of inbreeding.Um programa baseado na técnica de evolução diferencial foi desenvolvido para a definição da contribuição genética ótima na seleção de candidatos a reprodução. A função- objetivo a ser otimizada foi composta pelo mérito genético esperado da futura progênie e pela coascendência média dos animais em reprodução. Conjuntos de dados reais e simulados de populações com gerações sobrepostas foram usados para validar e testar o desempenho do programa desenvolvido. O programa se mostrou computacionalmente eficiente e viável para ser aplicado na prática e as consequências esperadas de sua aplicação, em comparação a procedimentos empíricos de controle da endogamia e/ou com a seleção baseada apenas no valor genético esperado, seriam a melhora da resposta genética futura e limitação mais efetiva da taxa de endogamia.

Desenvolveu-se um estudo de simulação estocástica com o objetivo de verificar as consequências do uso combinado de acasalamento dirigido e sêmen sexado em uma população de bovinos de corte sob seleção. Simularam-se seis gerações de seleção para três cenários de acasalamento e uso de sêmen sexado. O primeiro cenário foi caracterizado por acasalamento aleatório e uso exclusivo de sêmen convencional. O segundo cenário caracterizou-se pelo uso de acasalamento associativo positivo nas 40% melhores vacas e acasalamento associativo negativo nas demais, sem uso de sêmen sexado. O terceiro cenário seguiu o mesmo procedimento de acasalamento do segundo, combinando-o com uso de sêmen sexado nas vacas submetidas a acasalamento associativo positivo. O acasalamento associativo positivo teve maior impacto no progresso genético que o uso de sêmen sexado, apesar de ter aumentado a incidência de endogamia na população. O uso de acasalamento associativo negativo foi ineficiente em reduzir a variabilidade dos animais destinados ao abate. O uso combinado de acasalmento associativo positivo e sêmen sexado aumentou a produção de animais geneticamente superiores.Stochastic simulation was carried out to access the consequences of combined use of assortative mating and sexed semen in a beef cattle population under selection. Six generations of selection were simulated under three different scenarios of mating strategy and sexed semen use. The first was characterized by random mating and no use of sexed semen. The second was simulated using positive assortative mating (PAM) for the 40% top dams and negative assortative mating (NAM) for the remainder, with no use of sexed semen. The third followed the mating procedure of the second combined with use of sexed semen for dams under positive assortative mating. Positive assortative mating had more impact on the genetic progress than sexed semen, although it increased inbreeding incidence in the population. The combined use of negative assortative mating breeding was not efficient in reducing genetic variability of inferior offspring. The combined use of positive assortative mating and sexed semen improved production of genetically outstanding animals.

Por meio da utilização de um programa de acasalamento dirigido e de simulação de dados, foram avaliadas e comparadas estratégias alternativas de acasalamento para aumentar a probabilidade de produzir animais superiores e reduzir a variabilidade da progênie em bovinos. Simularam-se 50 populações, cada uma com 4.800 vacas, 160 touros e 4.800 produtos. Para cada vaca e touro simulados, gerou-se uma variável aleatória, seguindo distribuição normal, reproduzindo um índice composto por diferenças esperadas na progênie (DEP) de diferentes características a ser adotado como critério de seleção. As estratégias de acasalamento simuladas foram: AA - ao acaso; AP - associativo positivo; AN - associativo negativo; C20 - associativo positivo para as vacas 20% superiores e associativo negativo para as 80% restantes; C50 - associativo positivo para as vacas 50% superiores e associativo negativo para as 50% restantes. Os acasalamentos foram definidos com a utilização de um programa de acasalamentos dirigidos, calculando-se os índices esperados dos produtos e comparando as estratégias com base nestes índices. As estratégias de acasalamento alternativas, C20 e C50, apresentam probabilidades de produção de animais superiores tão altas quanto a do acasalamento associativo positivo e reduzem a probabilidade de produzir animais inferiores. O acasalamento associativo negativo é muito eficiente em produzir progênie uniforme.A simulation study was carried out to apply and compare an alternative mating strategy for increasing the probability of producing outstanding animals and reducing progeny variability, with other conventional strategies. Fifty populations were simulated, each containing 4,800 dams, 160 sires and 4,800 calves. For each dam and sire, a random variable from a normal distribution was generated, mimicking an index composed by several expected progeny differences (EPD). The mating strategies considered were: (1) random mating (RM); (2) positive assortative mating (PA); (3) negative assortative mating (NA); (4) combined, PA (assortative mating) for 20% top dams, and NA (negative assortative mating) for the remaining 80% (C20); (5) combined, PA (positive assortative mating) for 50% top dams, and NA (negative assortative mating) for the remaining 50% (C50). After applying the mating program, the expected progeny indexes were computed and the strategies were compared based on these indexes. The alternative mating strategies, C20 and C50, show probability of producing outstanding animals as great as the positive assortative mating, and reduce the probability of producing extremely inferior animals. The negative assortative mating is very efficient in producing uniform progeny.

Objetivou-se com este estudo comparar a seleção com base no ganho médio diário de peso na pré-desmama (GMD) e no número de dias para ganhar 160 kg nessa fase (D160), com e sem correção para efeitos de grupos de contemporâneos (GC), em bovinos da raça Guzerá. Utilizou-se o banco de dados de desenvolvimento ponderal da Associação Brasileira de Criadores de Zebu (ABCZ) para esta raça. A obtenção dos parâmetros e valores genéticos foi feita pelo método da máxima verossimilhança restrita utilizando-se modelo unicaracterístico com equações de modelos mistos. O modelo utilizado foi composto pelo efeito fixo de grupo genético e pelos efeitos aleatórios, genético aditivo direto e de ambiente permanente, além do erro residual. A média para D160 foi de 270,5 dias e para GMD, 642,3 g. As correlações de Spearman entre ganho médio diário e a precocidade em dias para ganhar 160 kg na pré-desmama (PD160), e GMD e PD160c (PD160 corrigido para o efeito de grupo de contemporâneo), foram iguais a 0,91 e 0,94, respectivamente. A seleção para PD160 favorece touros que produzem progênie com desempenho superior e menos variável e a padronização deste critério com base no grupo de contemporâneos melhorou sua eficiência. A classificação dos touros varia de acordo com o critério de seleção utilizado, GMD ou PD160, principalmente nos extremos, onde ocorrem seleção e descarte de reprodutores.The aim of this study was to compare the selection criteria based on the average daily gain (ADG) and days to achieve 160 kg (D160) on pre-weaning of Guzerat cattle. Database on weight gains provided by the Brazilian Association of Zebu Cattle Breeders (ABCZ) was used. The estimated genetic parameters and breeding values was obtained by the Restricted Maximum Likelihood Method, using a uni-trait animal model, with equations of mixed models. The model included the fixed effect of contemporary group, genetic additive direct and permanent environment, as random effects, beyond the residual error. The means for D160 and ADG were 270.5 days and 642.3 g, respectively. Spearman's correlations for pre-weaning ADG and D160 (D160P), and ADG and D160P corrected for contemporary group effect (D160Pc), were equal to 0.92 and 0.94, respectively. The selection for D160P would favor sires that produced superior and less variable progenies. The correction of D160 to the contemporary group effect made this trait more efficient to identify more uniform sires. Sires classification changed according to the adopted selection criterion, ADG or D160P, mainly at the end points, where animals should be selected and rejected.

The problem of multicollinearity in regression analysis was studied. Ridge regression (RR) techniques were used to estimate parameters affecting the performance of crossbred calves raised in tropical and subtropical regions by a model including additive, dominance, joint additive or "profit heterosis" and epistatic effects and their interactions with latitude in an attempt to model genotype by environment interactions. A software was developed in Fortran 77 to perform five variant types of RR: the originally proposed method; the method implemented by SAS; and three methods of weighting the RR parameter lambda. Three mathematical criteria were tested with the aim of choosing a value for the lambda coefficient: the sum and the harmonic mean of the absolute Student t-values and the value of lambda at which all variance inflation factors (VIF) became lower than 300. Prediction surfaces obtained from estimated coefficients were used to compare the five methods and three criteria. It was concluded that RR could be a good alternative to overcome multicollinearity problems. For all the methods tested, acceptable prediction surfaces could be obtained when the VIF criterion was employed. This mathematical criterion is thus recommended as an auxiliary tool for choosing lambda.

Os objetivos neste trabalho foram comparar estimativas de parâmetros genéticos obtidas por meio de dois modelos - um contendo apenas efeitos aditivos e de dominância e outro que incluiu os efeitos aditivo-conjunto (complementaridade) e epistático - e testar alternativas de critérios objetivos para determinação do coeficiente lambda na aplicação da regressão de cumeeira. Os resultados obtidos revelaram que a escolha de um critério para determinação do coeficiente lambda em regressão de cumeeira depende não apenas do conjunto de dados e do modelo utilizado, mas, sobretudo, de um conhecimento prévio acerca do fenômeno estudado e do significado prático e da interpretação dos parâmetros encontrados. Pelo uso de modelos mais completos para avaliação de efeitos genéticos em bovinos de corte, pode-se identificar a contribuição dos efeitos aditivo-conjunto e epistático, que encontram-se embutidos no efeito de heterose estimado por modelos mais simples. A regressão de cumeeira é uma ferramenta que viabiliza a obtenção dessas estimativas mesmo na presença de forte multicolinearidade.The purpose of this study was to compare estimates of genetic effects obtained using the additive-dominance model and another which included parameters for joint-additive (complementarity) and epistatic effects, as well as evaluate alternative objective criteria for choosing the lambda coefficient in ridge regression implementation. The results indicated that the criterion to be employed at the choice of lambda not only depends on the data set and the model used, but also on a previous knowledge about the phenomenon under study and the practical interpretation of estimated coefficients. When performing genetic effects evaluation, if other than additive and dominance effects are contemplated, it may be possible to identify and separate joint-additive and epistatic effects, which are usually inlaid in the heterotic effect estimated by the additive-dominance model. The use of ridge regression method can make such analyses possible even under strong multicollinearity.

Dados de 16.592 animais da raça Gir, provenientes do controle de desenvolvimento ponderal da Associação Brasileira dos Criadores de Zebu, nascidos no período de 1978 a 1994, criados em diversas condições de ambiente no Brasil, foram usados para estimar parâmetros genéticos e ambientais das características ganho médio diário do nascimento à desmama (GMD) e dias para atingir 160 kg do nascimento à desmama (D160). As estimativas dos componentes de variância e herdabilidade foram obtidas pelo método da máxima verossimilhança restrita por modelos animais uni-característica. Foram utilizados dois modelos o modelo 1, com grupo de contemporâneos (GC) como efeito fixo e com efeitos genético aditivo de animal e materno, efeito de ambiente permanente materno e erro como aleatórios; e modelo 2, com os mesmos efeitos do modelo 1, mas com covariância genética entre os efeitos direto e materno igual a zero (sigmaam=0). As estimativas de herdabilidade, utilizando-se o Modelo 1, foram iguais a 0,11; 0,04; 0,11 e 0,07 para GMD (efeito direto), GMD (efeito materno), D160 (efeito direto) e D160 (efeito materno), respectivamente. Para o Modelo 2, as estimativas de herdabilidade foram: 0,12; 0,05; 0,10 e 0,05 para GMD (efeito direto), GMD (efeito materno), D160 (efeito direto) e D160 (efeito materno). A diferença entre os modelos pela não inclusão da estrutura de covariância entre os efeitos direto e materno (sigmaam=0), neste trabalho, não foi significativa. A contribuição da variância residual (como porcentagem da variação fenotípica total) foi de 76% para GMD e de 80% para D160, para os dois modelos, indicando a necessidade da melhoria do ambiente de criação, assim como a padronização e formação de lotes de manejo, o que reflete na possibilidade de melhor definição de grupo de contemporâneos.A data set with 16,592 records from the Brazilian Zebu Breeders Association obtained from 1978 to 1994, was used to estimate genetic parameters for preweaning average daily gain (ADG) and number of days to gain 160 kg (D160) in Gyr cattle. The (co)variance components and heritabilities were estimated by the restricted maximum likelihood derivative free method. Two models were used: the first one considered contemporary group (CG) as fixed effect and additive direct and maternal genetic effects, maternal permanent environment and error as random effect. Model 2 considered the same effects of 1 but the covariance between the genetic direct and maternal effects was assumed to be zero. Estimated heritability values using model 1 were 0.11; 0.04; 0.11 and 0.07 for ADG (direct effect), ADG (maternal effect), D160 (direct effect), and D160 (maternal effect), respectivelly, and 0.12, 0.05, 0.10 and 0.05 considering Model 2 for ADG (direct effect), ADG (maternal effect), D160 (direct effect), and D160 (maternal effect), respectivelly. The likelihood ratio test was used to compare these models and were not significant. The proportional residual variances were 76 and 80% for ADG and D160, respectively for both models. The hight values determined for the residual variance indicate the need to improve the breeding environment, such as standartization of manegement groups in order to get definition of contemporary group.

A utilização de dois critérios de seleção na pré-desmama, ganho médio diário do nascimento à desmama (GMD) e dias para ganhar 160 kg do nascimento à desmama (D160), foi estudada, analisando-se informações de 16.592 animais, provenientes do controle de desenvolvimento ponderal da Associação Brasileira dos Criadores de Zebu, nascidos no período de 1978 a 1994. Foram incluídos no modelo o efeito fixo de grupo de contemporâneos e os efeitos aleatórios genético aditivo de animal e materno, de ambiente permanente materno e o erro. A covariância entre os efeitos direto e materno foi considerada igual a zero. As estimativas dos componentes de variância e herdabilidade foram obtidas pelo método da máxima verossimilhança restrita e os valores genéticos preditos (VGs), por modelos animais uni-característica. As estimativas de herdabilidade foram: 0,12; 0,05; 0,10 e 0,05 para GMD (efeito direto), GMD (efeito materno), D160 (efeito direto) e D160 (efeito materno), respectivamente. Foram estimadas a correlação genética entre GMD e D160 (efeito direto e materno) e a correlação de classificação (Spearman) entre os valores genéticos para as categorias de touros, vacas e bezerros. As estimativas de correlação genética entre GMD e D160 foram 0,86 e 0,88, para o efeito direto e materno, respectivamente. As estimativas de correlação de ";rank";, também foram altas, entretanto, nenhuma foi igual a um, resultando em alterações na classificação dos animais. A relação entre as médias aritmética (A) e harmônica (H) e o desvio-padrão (S) do GMD ajustado para efeitos ambientais e maternos (GMDc) foi verificada utilizando-se um modelo restrito, sem intercepto, mediante as regressões linear e quadrática do S do GMDc sobre a diferença entre a média aritmética e média harmônica (A-H). Os resultados evidenciaram que, semelhantemente a H, o critério D160 apresentou a propriedade de discriminar touros com progênie mais uniforme.Two different preweaning selection criteria in Gyr cattle: average daily gain from birth to weaning (ADG) and number of days to gain 160 kg from birth to weaning (D160) were evaluated in this study. Records from the Brazilian Zebu Breeders Association obtained from 1978 to 1994, were studied. (Co)variance components and heritabilities were estimated by restricted maximum likelihood derivative free method, and expected breeding values (EBV) were predicted using an single trait animal model. In the model, contemporary group was considered as fixed effect and direct and maternal genetic, permanent environment and error as random effects. The covariance between the genetic direct and maternal genetic effects was assumed to be zero. Pearson's and Spearman's correlations of direct and maternal breeding values for ADG and D160 were estimated. Estimated heritability values were 0.12, 0.05, 0.10 and 0.05 for ADG (direct effect), ADG (maternal effect), D160 (direct effect), and D160 (maternal effect), respectivelly. The genetic correlation estimates between ADG and D160 for direct (0.86) and maternal effects (0.88) showed a strong and positive association. Rank correlation estimates were also high but not the unity, so changes occured in the animals rankings according to the trait adopted as the criterion. The relationship between the harmonic mean (H), arithmetic mean (A) and standard deviation (S) of ADG preajusted for environmental and maternal effects was also studied according to linear and quadratic regression of S on the diffrence between A and H (A-H). The results indicated that similarly to H, D160 favoured sires with more homogeneous progeny.

O objetivo deste estudo foi investigar, por meio de dados simulados, o efeito da heterogeneidade de variância residual entre grupos de contemporâneos (GC) sobre as avaliações genéticas de bovinos de corte, e comparar o uso de uma avaliação genética ponderada (R¹Isigmae²) em relação à avaliação que pressupõe homogeneidade de variância (R=Isigmae²). A característica estudada foi ganho de peso pós-desmame corrigido para 345 dias, sendo esta simulada com variância fenotípica de 300 kg² e herdabilidade igual a 0,4. A estrutura de um conjunto real de dados foi utilizada para fornecer os GC e os pais referentes às observações de cada animal. Cinco níveis de heterogeneidade de variância residual foram considerados de forma que os componentes de variância fossem, na média, iguais aos da situação de homogeneidade de variância. Na medida em que níveis mais acentuados de heterogeneidade de variância residual foram considerados, os animais foram selecionados dos GC com maior variabilidade, especialmente com pressão de seleção intensa. Em relação à consistência de predição, os produtos e as vacas tiveram seus valores genéticos preditos mais afetados pela heterogeneidade de variância residual do que os touros. O fator de ponderação utilizado reduziu, mas não eliminou o efeito da heterogeneidade de variância. As avaliações genéticas ponderadas apresentaram resultados iguais ou superiores àqueles obtidos pelas avaliações que assumiram homogeneidade de variância. Mesmo quando não necessário, o uso de avaliações ponderadas produziu resultados não inferiores às avaliações que assumiram homogeneidade de variância.The objective of this study was to investigate, via simulated data, the effect of heterogeneity of residual variance among contemporary groups (CG) on genetic evaluation of beef cattle, and to compare a weighted genetic evaluation procedure (R¹Isigmae²) with one that assumes homogeneity of variances (R = Isigmae²). Different data sets of postweaning weight gain, adjusted to 345 days, were simulated with and without heterogeneity of residual variance, using a phenotypic variance of 300 kg² and a true heritability of 0.4. A real data set was used to provide the CG and parents related to each animal observation. Results showed that, when high levels of heterogeneity of residual variance were considered, animals were selected from CG with higher variability, especially with intense selection. With respect to prediction consistency, non parent animals and cows had their predicted breeding values more affected by heterogeneity of residual variance than sires. The weighed factor used reduced, but did not eliminate, the effect of heterogeneity of residual variance. The results of weighted genetic evaluations were similar or superior to those from evaluations that assumed homogeneity of variances. Even when the variances were homogeneous, the weighed genetic evaluations yielded results that were not inferior than those from the usual evaluations, which assumed homogeneity of variances.

The reproductive performance of bulls has a high impact on the beef cattle industry. Scrotal circumference (SC) is the most recorded reproductive trait in beef herds, and is used as a major selection criterion to improve precocity and fertility. The characterization of genomic regions affecting SC can contribute to the identification of diagnostic markers for reproductive performance and uncover molecular mechanisms underlying complex aspects of bovine reproductive biology. In this paper, we report a genome-wide scan for chromosome segments explaining differences in SC, using data of 861 Nellore bulls (Bos indicus) genotyped for over 777,000 single nucleotide polymorphisms. Loci that excel from the genome background were identified on chromosomes 4, 6, 7, 10, 14, 18 and 21. The majority of these regions were previously found to be associated with reproductive and body size traits in cattle. The signal on chromosome 14 replicates the pleiotropic quantitative trait locus encompassing PLAG1 that affects male fertility in cattle and stature in several species. Based on intensive literature mining, SP4, MAGEL2, SH3RF2, PDE5A and SNAI2 are proposed as novel candidate genes for SC, as they affect growth and testicular size in other animal models. These findings contribute to linking reproductive phenotypes to gene functions, and may offer new insights on the molecular biology of male fertility.