Genotype-by-environment interactions for feed efficiency traits in Nellore cattle based on bi-trait reaction norm models.

BACKGROUND: Selecting animals for feed efficiency directly impacts the profitability of the beef cattle industry, which contributes to minimizing the environmental footprint of beef production. Genetic and environmental factors influence animal feed efficiency, leading to phenotypic variability when exposed to different environmental conditions (i.e., temperature and nutritional level). Thus, our aim was to assess potential genotype-by-environment (G × E) interactions for dry matter intake (DMI) and residual feed intake (RFI) in Nellore cattle (Bos taurus indicus) based on bi-trait reaction norm models (RN) and evaluate the genetic association between RFI and DMI across different environmental gradient (EG) levels. For this, we used phenotypic information on 12,958 animals (young bulls and heifers) for DMI and RFI recorded during 158 feed efficiency trials. RESULTS: The heritability estimates for DMI and RFI across EG ranged from 0.26 to 0.54 and from 0.07 to 0.41, respectively. The average genetic correlations (± standard deviation) across EG for DMI and RFI were 0.83 ± 0.19 and 0.81 ± 0.21, respectively, with the lowest genetic correlation estimates observed between extreme EG levels (low vs. high) i.e. 0.22 for RFI and 0.26 for DMI, indicating the presence of G × E interactions. The genetic correlation between RFI and DMI across EG levels decreased as the EG became more favorable and ranged from 0.79 (lowest EG) to 0.52 (highest EG). Based on the estimated breeding values from extreme EG levels (low vs. high), we observed a moderate Spearman correlation of 0.61 (RFI) and 0.55 (DMI) and a selection coincidence of 53.3% and 40.0% for RFI and DMI, respectively. CONCLUSIONS: Our results show evidence of G × E interactions on feed efficiency traits in Nellore cattle, especially in feeding trials with an average daily gain (ADG) that is far from the expected of 1 kg/day, thus increasing reranking of animals.

Assessment of copy number variants in three Brazilian locally adapted cattle breeds using whole-genome re-sequencing data.

Further characterization of genetic structural variations should strongly focus on small and endangered local breeds given their role in unraveling genes and structural variants underlying selective pressures and phenotype variation. A comprehensive genome-wide assessment of copy number variations (CNVs) based on whole-genome re-sequencing data was performed on three Brazilian locally adapted cattle breeds (Caracu Caldeano, Crioulo Lageano, and Pantaneiro) using the ARS-UCD1.2 genome assembly. Data from 36 individuals with an average coverage depth of 14.07× per individual was used. A total of 24 945 CNVs were identified distributed among the breeds (Caracu Caldeano = 7285, Crioulo Lageano = 7297, and Pantaneiro = 10 363). Deletion events were 1.75-2.07-fold higher than duplications, and the total length of CNVs is composed mostly of a high number of segments between 10 and 30 kb. CNV regions (CNVRs) are not uniformly scattered throughout the genomes (n = 463), and 105 CNVRs were found overlapping among the studied breeds. Functional annotation of the CNVRs revealed variants with high consequence on protein sequence harboring relevant genes, in which we highlighted the BOLA-DQB, BOLA-DQA5, CD1A, ß-defensins, PRG3, and ULBP21 genes. Enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p < 0.01) strongly associated with immunity and cattle resilience to harsh environments. Additionally, QTL associated with body conformation and dairy-related traits were also unveiled within the CNVRs. These results provide better understanding of the selective forces shaping the genome of such cattle breeds and identify traces of natural selection pressures by which these populations have been exposed to challenging environmental conditions.

Genomic evaluation of commercial herds with different pedigree structures using the single-step genomic BLUP in Nelore cattle.

The aim of this work was to evaluate the impact of applying genomic information in pedigree uncertainty situations on genetic evaluations for growth- and cow productivity-related traits in Nelore commercial herds. Records for accumulated cow productivity (ACP) and adjusted weight at 450 days of age (W450) were used, as well as genotypes of registered and commercial herd animals, genotyped with the Clarifide Nelore 3.1 panel (~29,000 SNPs). The genetic values for commercial and registered populations were estimated using different approaches that included (ssGBLUP) or did not include genomic information (BLUP), with different pedigree structures. Different scenarios were tested, varying the proportion of young animals with unknown sires (0, 25, 50, 75, and 100%), and unknown maternal grandsires (0, 25, 50, 75, and 100%). The prediction accuracies and abilities were calculated. The estimated breeding value accuracies decreased as the proportion of unknown sires and maternal grandsires increased. The genomic estimated breeding value accuracy using the ssGBLUP was higher in scenarios with a lower proportion of known pedigree when compared to the BLUP methodology. The results obtained with the ssGBLUP showed that it is possible to obtain reliable direct and indirect predictions for young animals from commercial herds without pedigree structure.

Estimates of genetic and phenotypic parameters for feeding behaviour and feed efficiency-related traits in Nelore cattle.

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n = 4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5 ± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n = 8) animal model. The heritability estimates for RFI (0.23 ± 0.02), DMI (0.31 ± 0.02), MF (0.65 ± 0.02), AMD (0.29 ± 0.02), ACM (0.24 ± 0.02), MD (0.41 ± 0.02), MC (0.48 ± 0.02), and CR (0.42 ± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73 ± 0.03), CR and AMD (-0.68 ± 0.04), and RFI and DMI (0.81 ± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77 ± 0.02), and DMI and RFI (0.77 ± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.

Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle.

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFIpop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI.

Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle.

BACKGROUND: Potential functional variants (PFVs) can be defined as genetic variants responsible for a given phenotype. Ultimately, these are the best DNA markers for animal breeding and selection, especially for polygenic and complex phenotypes. Herein, we described the identification of PFVs for complex phenotypes (in this case, Feed Efficiency in beef cattle) using a systems-biology driven approach based on RNA-seq data from physiologically relevant organs. RESULTS: The systems-biology coupled with deep molecular phenotyping by RNA-seq of liver, muscle, hypothalamus, pituitary, and adrenal glands of animals with high and low feed efficiency (FE) measured by residual feed intake (RFI) identified 2,000,936 uniquely variants. Among them, 9986 variants were significantly associated with FE and only 78 had a high impact on protein expression and were considered as PFVs. A set of 169 significant uniquely variants were expressed in all five organs, however, only 27 variants had a moderate impact and none of them a had high impact on protein expression. These results provide evidence of tissue-specific effects of high-impact PFVs. The PFVs were enriched (FDR < 0.05) for processing and presentation of MHC Class I and II mediated antigens, which are an important part of the adaptive immune response. The experimental validation of these PFVs was demonstrated by the increased prediction accuracy for RFI using the weighted G matrix (ssGBLUP+wG; Acc = 0.10 and b = 0.48) obtained in the ssGWAS in comparison to the unweighted G matrix (ssGBLUP; Acc = 0.29 and b = 1.10). CONCLUSION: Here we identified PFVs for FE in beef cattle using a strategy based on systems-biology and deep molecular phenotyping. This approach has great potential to be used in genetic prediction programs, especially for polygenic phenotypes.

Heritability and genetic correlations between marbling in longissimus dorsi muscle and conventional economic traits in Nellore beef cattle.

In Nellore beef cattle, studies addressing genetic correlations between ultrasound marbling content and other economically important traits are still incipient. Therefore, this work aimed to estimate heritability and genetic correlations between ultrasound marbling content in the longissimus dorsi muscle (MARB) and growth, reproductive, feed efficiency, and carcass-related traits in a Nellore beef cattle population from Brazil. Phenotypic records of 614,395 Nellore animals were used and included adjusted weight at 210 (W210) and 450 (W450) days of age, adult cow weight (AW), early heifer pregnancy (EH), stayability (STAY), adjusted scrotal circumference at 365 days of age (SC365), ribeye area (REA), subcutaneous backfat thickness (BF), rump fat thickness (RF), and marbling (MARB). The genetic parameters for all traits but EH and STAY were estimated considering a linear animal model, whereas for those two nonlinear traits, a threshold animal model was used. The direct and correlated response to selection for MARB versus the other traits, and the relative efficiency of selection, were also calculated. The heritability estimate for MARB was 0.31 and for the other conventional evaluated traits was low to moderate, with values ranging from 0.14 to 0.41. The genetic correlations between MARB and growth, reproductive, feed efficiency, and carcass-related trait were very low, with values close to zero, with similar correlated responses. The MARB displayed adequate genetic variability to respond to selection and crossbreeding programs looking forward to higher meat quality and differential market standards for the Nellore beef. The selection for growth, reproductive, feed efficiency, and carcass-related traits would not affect MARB in Nellore beef cattle and vice versa. Therefore, this trait should be included as a selection criterion in the Nellore breeding program.

Integration analyses of structural variations and differential gene expression associated with beef fatty acid profile in Nellore cattle.

This study aimed to integrate analyses of structural variations and differentially expressed genes (DEGs) associated with the beef fatty acid (FA) profile in Nellore cattle. Copy numbers variation (CNV) detection was performed using the penncnv algorithm and CNVRuler software in 3794 genotyped animals through the High-Density Bovine BeadChip. In order to perform the genomic wide association study (GWAS), a total of 963 genotyped animals were selected to obtain the intramuscular lipid concentration and quantify the beef FA profile. A total of 48 animals belonging to the same farm and management lot were extracted from the 963 genotyped and phenotyped animals to carry out the transcriptomic and differentially expressed gene analyses. The GWAS with extreme groups of FA profiles was performed using a logistic model. A total of 43, 42, 66 and 35 significant CNV regions (p < 0.05) for saturated, monounsaturated, polyunsaturated and omega 3 and 6 fatty acids were identified respectively. The paired-end sequencing of 48 samples was performed using the Illumina HiSeq2500 platform. Real-time quantitative PCR was used to validate the DEGs identified by RNA-seq analysis. The results showed several DEGs associated with the FA profile of Longissimus thoracis, such as BSCL2 and SAMD8. Enriched terms as the cellular response to corticosteroid (GO:0071384) and glucocorticoid stimulus (GO:0071385) could be highlighted. The identification of structural variations harboring candidate genes for beef FA must contribute to the elucidation of the genetic basis that determines the beef FA composition of intramuscular fat in Nellore cattle. Our results will contribute to the identification of potential biomarkers for complex phenotypes, such as the FA profile, to improve the reliability of the genomic predictions including pre-selected variants using differentiated weighting in the genomic models.

Transcriptome Profile Reveals Genetic and Metabolic Mechanisms Related to Essential Fatty Acid Content of Intramuscular Longissimus thoracis in Nellore Cattle.

Beef is a source of essential fatty acids (EFA), linoleic (LA) and alpha-linolenic (ALA) acids, which protect against inflammatory and cardiovascular diseases in humans. However, the intramuscular EFA profile in cattle is a complex and polygenic trait. Thus, this study aimed to identify potential regulatory genes of the essential fatty acid profile in Longissimus thoracis of Nellore cattle finished in feedlot. Forty-four young bulls clustered in four groups of fifteen animals with extreme values for each FA were evaluated through differentially expressed genes (DEG) analysis and two co-expression methodologies (WGCNA and PCIT). We highlight the ECHS1, IVD, ASB5, and ERLIN1 genes and the TF NFIA, indicated in both FA. Moreover, we associate the NFYA, NFYB, PPARG, FASN, and FADS2 genes with LA, and the RORA and ELOVL5 genes with ALA. Furthermore, the functional enrichment analysis points out several terms related to FA metabolism. These findings contribute to our understanding of the genetic mechanisms underlying the beef EFA profile in Nellore cattle finished in feedlot.

Transcriptomic profile of longissimus thoracis associated with fatty acid content in Nellore beef cattle.

The beef fatty acid (FA) profile has the potential to impact human health, and displays polygenic and complex features. This study aimed to identify the transcriptomic FA profile in the longissimus thoracis muscle in Nellore beef cattle finished in feedlot. Forty-four young bulls were sampled to assess the beef FA profile by considering 14 phenotypes and including differentially expressed genes (DEG), co-expressed (COE), and differentially co-expressed genes (DCO) analyses. All samples (n = 44) were used for COE analysis, whereas 30 samples with extreme phenotypes for the beef FA profile were used for DEG and DCO. A total of 912 DEG were identified, and the polyunsaturated (n = 563) and unsaturated ω-3 (n = 346) FA sums groups were the most frequently observed. The COE analyses identified three modules, of which the blue module (n = 1776) was correlated with eight of 14 FA phenotypes. Also, 759 DCO genes were listed, and the oleic acid (n = 358) and monounsaturated fatty acids sum (n = 120) were the most frequent. Furthermore, 243 and 13, 319 and seven, and 173 and 12 gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways were enriched respectively for the DEG, COE, and DCO analyses. Combining the results, we highlight the unexplored GIPC2, ASB5, and PPP5C genes in cattle. Besides LIPE and INSIG2 genes in COE modules, the ACSL3, ECI1, DECR2, FITM1, and SDHB genes were signaled in at least two analyses. These findings contribute to understand the genetic mechanisms underlying the beef FA profile in Nellore beef cattle finished in feedlot.

Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP.

This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.

Accuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information.

The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP effects are derived from ssGBLUP with a reference population with known sires. The ssGBLUP could be applied in situations of uncertain paternity, especially when selecting young animals. This methodology is shown to be accurate, mainly in scenarios with a high percentage of MS.

Differentially expressed genes identified through RNA-seq with extreme values of principal components for beef fatty acid in Nelore cattle.

The aim of this study was to identify differentially expressed genes (DEG) in the Longissimus thoracis muscle of Nelore cattle related to fatty acid (FA) profile through RNA sequencing and principal component analysis (PCA). Two groups of 10 animals each were selected containing PC1 and PC2 extreme DEG values (HIGH × LOW) for each FA group. The intramuscular fat (IMF) was compared between cluster groups by ANOVA, and only the sum of monounsaturated FA (MUFA) and ω3 showed significant differences (p < .05). Interestingly, the highest percentage (95%) of phenotypic variation explained by the sum of the first two PC was observed for ω3, which also displayed the lowest number of DEG (n = 1). The lowest percentage (59%) was observed for MUFA, which also revealed the largest number of DEG (n = 66). Since only MUFA and ω3 exhibited significant differences between cluster groups, we can conclude that the differences observed for the remaining groups are not due to the percentage of IMF. Several genes that have been previously associated with meat quality and FA traits were identified as DEG in this study. The functional analysis revealed one KEGG pathway and eight GO terms as significant (p < .05), in which we highlighted the purine metabolism, glycolytic process, adenosine triphosphate binding and bone development. These results strongly contribute to the knowledge of the biological mechanisms involved in meat FA profile of Nelore cattle.

Genome-wide detection of signatures of selection in indicine and Brazilian locally adapted taurine cattle breeds using whole-genome re-sequencing data.

BACKGROUND: The cattle introduced by European conquerors during the Brazilian colonization period were exposed to a process of natural selection in different types of biomes throughout the country, leading to the development of locally adapted cattle breeds. In this study, whole-genome re-sequencing data from indicine and Brazilian locally adapted taurine cattle breeds were used to detect genomic regions under selective pressure. Within-population and cross-population statistics were combined separately in a single score using the de-correlated composite of multiple signals (DCMS) method. Putative sweep regions were revealed by assessing the top 1% of the empirical distribution generated by the DCMS statistics. RESULTS: A total of 33,328,447 biallelic SNPs with an average read depth of 12.4X passed the hard filtering process and were used to access putative sweep regions. Admixture has occurred in some locally adapted taurine populations due to the introgression of exotic breeds. The genomic inbreeding coefficient based on runs of homozygosity (ROH) concurred with the populations' historical background. Signatures of selection retrieved from the DCMS statistics provided a comprehensive set of putative candidate genes and revealed QTLs disclosing cattle production traits and adaptation to the challenging environments. Additionally, several candidate regions overlapped with previous regions under selection described in the literature for other cattle breeds. CONCLUSION: The current study reported putative sweep regions that can provide important insights to better understand the selective forces shaping the genome of the indicine and Brazilian locally adapted taurine cattle breeds. Such regions likely harbor traces of natural selection pressures by which these populations have been exposed and may elucidate footprints for adaptation to the challenging climatic conditions.

Genome-wide scan for runs of homozygosity in the composite Montana Tropical® beef cattle.

The aim of this study was to assess the distribution of runs of homozygosity (ROH) and autozygosity islands in the composite Montana Tropical® beef cattle to explore hotspot regions which could better characterize the different biological types within the composite breed. Montana animals (n = 1,436) were genotyped with the GGP-LD BeadChip (~30,000 markers). ROH was identified in every individual using the plink v1.90 software. Medium and long ROH prevailed in the genome, which accounted for approximately 74% of all ROH detected. On an average, 2.0% of the genome was within ROH, agreeing with the pedigree-based inbreeding coefficient. The Montana cattle with a higher proportion of productive breed types showed the highest number of autozygosity islands (n = 17), followed by those with a higher proportion of breeds adapted to tropical environments (n = 15). Enriched terms (p < .05) associated with the immune and inflammatory response, homeostasis, reproduction, mineral absorption, and lipid metabolism were described within the autozygosity islands. In this regard, over-represented GO terms and KEGG pathways described in this population may play a key role in providing information to explore the genetic and biological mechanisms together with the genomic regions underlying each biological type that favoured their optimal performance ability in tropical and subtropical regions.

Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle.

The aim of this study was to evaluate the genomic predictions using the single-step genomic best linear unbiased predictor (ssGBLUP) method based on SNPs and haplotype markers associated with beef fatty acids (FAs) profile in Nelore cattle. The data set contained records from 963 Nelore bulls finished in feedlot (±90 days) and slaughtered with approximately 24 months of age. Meat samples from the Longissimus dorsi muscle were taken for FAs profile measurement. FAs were quantified by gas chromatography using a SP-2560 capillary column. Animals were genotyped with the high-density SNP panel (BovineHD BeadChip assay) containing 777,962 markers. SNPs with a minor allele frequency and a call rate lower than 0.05 and 0.90, respectively, monomorphic, located on sex chromosomes, and with unknown position were removed from the data set. After genomic quality control, a total of 469,981 SNPs and 892 samples were available for subsequent analyses. Missing genotypes were imputed and phased using the FImpute software. Haplotype blocks were defined based on linkage disequilibrium using the Haploview software. The model to estimate variance components and genetic parameters and to predict the genomic values included the random genetic additive effects, fixed effects of the contemporary group and the age at slaughter as a linear covariate. Accuracies using the haplotype-based approach ranged from 0.07 to 0.31, and those SNP-based ranged from 0.06 to 0.33. Regression coefficients ranged from 0.07 to 0.74 and from 0.08 to 1.45 using the haplotype- and SNP-based approaches, respectively. Despite the low to moderate accuracies for the genomic values, it is possible to obtain genetic progress trough selection using genomic information based either on SNPs or haplotype markers. The SNP-based approach allows less biased genomic evaluations, and it is more feasible when taking into account the computational and operational cost underlying the haplotypes inference.

The metabolic characteristics of susceptibility to wooden breast disease in chickens with high feed efficiency.

This study was conducted to characterize metabolic differences between high feed efficiency (HFE) and low feed efficiency (LFE) chickens to investigate why feed efficient chickens are more susceptible to muscle abnormalities such as wooden breast disease. Gene expression profiles were generated by RNA sequencing of pectoralis major muscle samples from 10 HFE and 13 LFE broiler chickens selected from a modern broiler population. Metabolism-associated differentially expressed genes were identified and interpreted by Ingenuity Pathway Analysis and literature mining. Our RNA-seq data indicate decreased glycolytic capacity, increased fatty acid uptake, mitochondrial oxidation of fatty acids, and several other metabolic alterations in the pectoralis major muscle of HFE chickens. We also quantified glycogen content of the pectoralis major muscle and found that the HFE chickens had a significantly (P ≤ 0.05) lower glycogen content. Collectively, this study indicates extensive metabolic differences in the pectoralis major muscle between HFE and LFE chickens and helps identify metabolic features of susceptibility to muscle disorders in modern broiler chickens.

Genetic association between different criteria to define sexual precocious heifers with growth, carcass, reproductive and feed efficiency indicator traits in Nellore cattle using genomic information.

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

Genomic regions and enrichment analyses associated with carcass composition indicator traits in Nellore cattle.

The aim of this study was to estimate genetic parameters and identify genomic regions associated with carcass traits obtained by ultrasound and visual scores in Nellore cattle. Data from ~66,000 animals from the National Association of Breeders and Researchers (ANCP) were used. The variance components for backfat thickness, rump fat thickness and Longissimus muscle area (LMA) were estimated considering a linear model whereas a threshold model for body structure (BS), finishing precocity (FP) and musculature (MS) traits. The SNP solutions were estimated using the ssGBLUP approach by considering windows of 10 consecutive SNPs. Regions that accounted for more than 1.0% of the additive genetic variance were used. Genes identified within the significant windows, such as FOXA3, AP2S1, FKRP, NPASI and ATP6V1G1, were found to be related with MS, while OMA1 and FFGY with BS and FP traits. The PLTP, TNNC2 and GPAT2 genes were found in the regions associated with LMA, as well as TKT, FNDC5 and CHRND can strongly be related with fat deposition. Gene enrichment analysis revealed processes that might be directly influenced the organism growth and development. These results should help to better understand the genetic and physiological mechanisms regulating growth and body composition, muscle tissue development and subcutaneous fat expression, and this information might be useful for future genomic studies in Nellore cattle.

Autozygosity islands and ROH patterns in Nellore lineages: evidence of selection for functionally important traits.

BACKGROUND: The aim of this study was to assess genome-wide autozygosity in a Nellore cattle population and to characterize ROH patterns and autozygosity islands that may have occurred due to selection within its lineages. It attempts also to compare estimates of inbreeding calculated from ROH (FROH), genomic relationship matrix (FGRM), and pedigree-based coefficient (FPED). RESULTS: The average number of ROH per animal was 55.15 ± 13.01 with an average size of 3.24 Mb. The Nellore genome is composed mostly by a high number of shorter segments accounting for 78% of all ROH, although the proportion of the genome covered by them was relatively small. The genome autozygosity proportion indicates moderate to high inbreeding levels for classical standards, with an average value of 7.15% (178.70 Mb). The average of FPED and FROH, and their correlations (- 0.05 to 0.26) were low. Estimates of correlation between FGRM-FPED was zero, while the correlation (- 0.01 to - 0.07) between FGRM-FROH decreased as a function of ROH length, except for FROH > 8Mb (- 0.03). Overall, inbreeding coefficients were not high for the genotyped animals. Autozygosity islands were evident across the genome (n = 62) and their genomic location did not largely differ within lineages. Enriched terms (p < 0.01) associated with defense response to bacteria (GO:0042742), immune complex reaction (GO:0045647), pregnancy-associated glycoproteins genes (GO:0030163), and organism growth (GO:0040014) were described within the autozygotic islands. CONCLUSIONS: Low FPED-FROH correlation estimates indicate that FPED is not the most suitable method for capturing ancient inbreeding when the pedigree does not extend back many generations and FROH should be used instead. Enriched terms (p < 0.01) suggest a strong selection for immune response. Non-overlapping islands within the lineages greatly explain the mechanism underlying selection for functionally important traits in Nellore cattle.