Genome-wide association study for stayability at different calvings in Nellore beef cattle.

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.

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

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.

Probabilistic reaction norm reveals family-related variation in the association between size, condition, and sexual maturation onset in Atlantic salmon (Salmo salar).

This study investigated the relationship between the size, condition, year class, family, and sexual maturity of Atlantic salmon (Salmo salar) using data collected in an aquaculture selective breeding programme. Males that were sexually mature at 2 years of age (maiden spawn) have, on average, greater fork length and condition factor (K) at 1 year of age than their immature counterparts. For every 10-mm increase in fork length or 0.1 increase in K at 1 year of age, the odds of sexual maturity at 2 years of age increased by 1.48 or 1.22 times, respectively. Females that were sexually mature at 3 years of age (maiden spawn) have, on average, greater fork length and K at 2 years of age than their immature counterparts. For every 10-mm increase in fork length or 0.1 increase in K at 2 years of age, the odds of sexual maturity at 3 years of age increased by 1.06 or 1.44 times, respectively. The family explained 34.93% of the variation in sexual maturity among 2-year-old males that was not attributable to the average effects of fork length and K at 1 year of age and year class. The proportion of variation in sexual maturity among 3-year-old females explained by the family could not be investigated. These findings suggest that the onset of sexual maturation in Atlantic salmon is conditional on performance (with respect to energy availability) surpassing a threshold, the magnitude of which can vary between families and is determined by a genetic component. This could support the application of genetic selection to promote or inhibit the onset of sexual maturation in farmed stocks.

Signatures of selection in Nelore cattle revealed by whole-genome sequencing data.

Nelore cattle breed was farmed worldwide due to its economic importance in the beef market and adaptation to the tropics. In Brazil, purebred Nelore animals (PO) receive a certificate from the breeders' association based on the animal's genealogy and morphological characterization. The top 20 to 30% of the superior animals are eligible to receive the Special Certificate of Identification and Production (CEIP), meaning animals from this category were selected and evaluated in a breeding program to improve economically important traits. We used whole-genome sequencing and approaches based on haplotype differentiation and allelic differentiation to detect regions of selection signatures in Nelore cattle by comparing animals from PO and CEIP categories. From a total of 150 animals, a hierarchical clustering analysis was performed to choose the more unrelated animals from each category (16 PO and 40 CEIP). The hapFLK statistic was performed, and extensions of hapFLK values were investigated considering continuous regions with significant q-values. The Weir and Cockerham's Fst estimator (wcFst) was computed using the GPAT++ software library. The total of 82,326 SNPs with hapFLK values passed the FDR control (q-value<0.05), and 718 segments were target as signatures of selection. A total of 1713 highly differentiated genomic regions were identified based on the segmentFst approach. The signatures of selection were spread across the genome. Annotation of overlapping selection signature regions between the two methods revealed 118 genes in common. A variant located within the 3' region of the BOLA-DRB3 gene was found as a promising candidate polymorphism. Within genomic regions that deserves attention, we found genes previously associated with adaptation to tropical environments (HELB), growth and navel size (HMGA2), fat deposition and domestication (IRAK3), and feed efficiency and postmortem carcass traits (GABRG3). The genes BOLA-DQA2, BOLA-DQB, BOLA-DQA5, BOLA-DQA1, BOLA-DRB3, ENSBTAG00000038397 on chromosome 23 are part of the Bovine Major Histocompatibility Complex (MHC) Class II gene family, representing good candidates for immune response and adaptation to tropical conditions. The BoLA family genes and the interaction of ROBO1 with SLIT genes appeared in the enrichment results. Genomic regions located in intronic regions were also identified and might play a regulatory role in traits under selection in PO and CEIP subpopulations. The regions here identified contribute to our knowledge regarding genes and variants that have an important role in complex traits selected in this breed.

Testicular hypoplasia in Nellore Cattle: Genetic analysis and functional analysis of genome-wide association study results.

Characterized by the incomplete development of the germinal epithelium of the seminiferous tubules, Testicular hypoplasia (TH) leads to decreased sperm concentration, increased morphological changes in sperm and azoospermia. Economic losses resulting from the disposal of affected bulls reduce the efficiency of meat production systems. A genome-wide association study and functional analysis were performed to identify genomic windows and the underlying positional candidate genes associated with TH in Nellore cattle. Phenotypic and pedigree data from 207,195 animals and genotypes (461,057 single nucleotide polymorphism, SNP) from 17,326 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. A possible correlated response on TH resulting from the selection for scrotal circumference was evaluated by using a two-trait analysis. Thus, estimated breeding values were calculated by fitting a linear-threshold animal model in a Bayesian approach. The SNP effects were estimated using the weighted single-step genomic BLUP method. Twelve non-overlapping windows of 20 adjacent SNP that explained more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of the candidate genes identified genes (KHDRBS3, GPX5, STAR, ERLIN2), which might play an important role in the expression of TH due to their known roles in the spermatogenesis process, synthesis of steroids and lipid metabolism.

Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits.

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.

Imputation accuracy to whole-genome sequence in Nellore cattle.

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.

Comparison of methods for predicting genomic breeding values for growth traits in Nellore cattle.

The objective of this study was to evaluate the accuracy of genomic predictions of growth traits in Nellore cattle. Data from 5064 animals belonging to farms that participate in the Conexão DeltaGen and PAINT breeding programs were used. Genotyping was performed with the Illumina BovineHD BeadChip (777,962 SNPs). After quality control of the genomic data, 412,993 SNPs were used. Deregressed EBVs (DEBVs) were calculated using the estimated breeding values (EBVs) and accuracies of birth weight (BW), weight gain from birth to weaning (GBW), postweaning weight gain (PWG), yearling height (YH), and cow weight (CW) provided by GenSys. Three models were used to estimate marker effects: genomic best linear unbiased prediction (GBLUP), BayesCπ, and improved Bayesian least absolute shrinkage and selection operator (IBLASSO). The prediction ability of genomic estimated breeding value (GEBVs) was estimated by the average Pearson correlation between DEBVs and GEBVs, predicted with the different methodologies in the validation populations. The regression coefficients of DEBVs on GEBVs in the validation population were calculated and used as indicators of prediction bias of GEBV. In general, the Bayesian methods provided slightly more accurate predictions of genomic breeding values than GBLUP. The BayesCπ and IBLASSO were similar for all traits (BW, GBW, PWG, and YH), except for CW. Thus, there does not seem to be a more suitable method for the estimation of SNP effects and genomic breeding values. Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions.

Development of a SNP linkage map and genome-wide association study for resistance to Aeromonas hydrophila in pacu (Piaractus mesopotamicus).

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 (h2) 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.

Genetic control of temperament traits across species: association of autism spectrum disorder risk genes with cattle temperament.

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.

Single-step genomic evaluation improves accuracy of breeding value predictions for resistance to infectious pancreatic necrosis virus in rainbow trout.

The aim of this study was to compare the accuracy of breeding values (EBVs) predicted using the traditional pedigree based Best Linear Unbiased Prediction (PBLUP) and the single-step genomic Best Linear Unbiased Prediction (ssGBLUP) for resistance against infectious pancreatic necrosis virus (IPNV) in rainbow trout. A total of 2278 animals were challenged against IPNV and 768 individuals were genotyped using a 57 K single nucleotide polymorphism array for rainbow trout. Accuracies for both methods were assessed using five-fold cross-validation. The heritabilities were higher for PBLUP compared to ssGBLUP. The ssGBLUP accuracies outperformed PBLUP in 7 and 11% for days to death and binary survival, respectively. The ssGBLUP could be an alternative approach to improve the accuracy of breeding values for resistance against infectious pancreatic necrosis virus in rainbow trout, using information from genotyped and non-genotyped animals.

Across-breed validation study confirms and identifies new loci associated with sexual precocity in Brahman and Nellore cattle.

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10-3 ) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10-3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review.

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0-0.86) and the heritability of residual variance is low (median = 0.01; range 0-0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.

Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning.

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.

Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle.

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.

Unraveling genetic sensitivity of beef cattle to environmental variation under tropical conditions.

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.

Accounting for population structure in selective cow genotyping strategies.

The objective of the present study was to investigate the impact of considering population structure in cow genotyping strategies over the accuracy and bias of genomic predictions. A small dairy cattle population was simulated to address these objectives. Based on four main traditional designs (random, top-yield, extreme-yield and top-accuracy cows), different numbers (1,000; 2,000 and 5,000) of cows were sampled and included in the reference population. Traditional designs were replicated considering or not population structure and compared among and with a reference population containing only bulls. The inclusion of cows increased accuracy in all scenarios compared with using only bulls. Scenarios accounting for population structure when choosing cows to the reference population slightly outperformed their traditional versions by yielding higher accuracy and lower bias in genomic predictions. Building a cow-based reference population from groups of related individuals considering the frequency of individuals from those same groups in the validation population yielded promising results with applications on selection for expensive- or difficult-to-measure traits. Methods here presented may be easily implemented in both new or already established breeding programs, as they improved prediction and reduced bias in genomic evaluations while demanding no additional costs.

Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables.

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_[Formula: see text]). 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_[Formula: see text], 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.

Genomic predictions combining SNP markers and copy number variations in Nellore cattle.

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.