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.

A network-based approach to understanding gene-biological processes affecting economically important traits of Nelore cattle.

This study aimed to build gene-biological process networks with differentially expressed genes associated with economically important traits of Nelore cattle from 17 previous studies. The genes were clustered into three groups by evaluated traits: group 1, production traits; group 2, carcass traits; and group 3, meat quality traits. For each group, a gene-biological process network analysis was performed with the differentially expressed genes in common. For production traits, 37 genes were found in common, of which 13 genes were enriched for six Gene Ontology (GO) terms; these terms were not functionally grouped. However, the enriched GO terms were related to homeostasis, the development of muscles and the immune system. For carcass traits, four genes were found in common. Thus, it was not possible to functionally group these genes into a network. For meat quality traits, the analysis revealed 222 genes in common. CSRP3 was the only gene differentially expressed in all three groups. Non-redundant biological terms for clusters of genes were functionally grouped networks, reflecting the cross-talk between all biological processes and genes involved. Many biological processes and pathways related to muscles, the immune system and lipid metabolism were enriched, such as striated muscle cell development and triglyceride metabolic processes. This study provides insights into the genetic mechanisms of production, carcass and meat quality traits of Nelore cattle. This information is fundamental for a better understanding of the complex traits and could help in planning strategies for the production and selection systems of Nelore cattle.

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.

Estimation of genetic parameters for the tick and hemoparasite burden in Angus cattle.

The study was conducted with the objective of estimating genetic and phenotypic parameters for tick (CRM) and Babesia bigemina (IBBi), Babesia bovis (IBBo), and Anaplasma marginale (IAM) burden in Angus female breed in Brazil. The sample group was composed of Angus females raised in herds located in a region of endemic instability for cattle tick fever in the state of Rio Grande Sul (RS), Brazil. The variance components were estimated using Bayesian inference and Gibbs sampling algorithm, considering a multi-trait animal model. Heritability estimates showed values of low magnitude, ranging from 0.03 (IBBo) to 0.16 (CRM), while repeatability estimates ranged between 0.07 (IBBo) and 0.21 (CRM). Regarding the genetic correlation estimates, the values showed low (-0.01 for IBBo × IAM) to moderate (0.55 between IBBi × IAM) magnitudes. The results indicate that it is possible to use tick count and hemoparasite infection levels as selection criteria, with small genetic gains.

Small genetic variation affecting mRNA isoforms associated with marbling and meat color in beef cattle.

The aim of this study was to identify mRNA isoforms and small genetic variants that may be affecting marbling and beef color in Nellore cattle. Longissimus thoracis muscle samples from 20 bulls with different phenotypes (out of 80 bulls set) for marbling (moderate (n = 10) and low (n = 10) groups) and beef color (desirable (n = 10) and undesirable (n = 9) group) traits were used to perform transcriptomic analysis using RNA sequencing. Fourteen and 15 mRNA isoforms were detected as differentially expressed (DE) (P-value ≤ 0.001) between divergent groups for marbling and meat color traits, respectively. Some of those DE mRNA isoforms have shown sites of splicing modified by small structural variants as single nucleotide variant (SNV), insertion, and/or deletion. Enrichment analysis identified metabolic pathways, such as O2/CO2 exchange in erythrocytes, tyrosine biosynthesis, and phenylalanine degradation. The results obtained suggest potential key regulatory genes associated with these economically important traits for the beef industry and for the consumer.

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.

Analysis of residual feed intake in Nellore bulls of different ages, rib eye area, and backfat thickness.

The aim of the present study was to use different models that include body composition phenotypes for the evaluation of residual feed intake (RFI) in Nellore bulls of different ages. Phenotypic and genotypic data of bulls that had participated in feed efficiency tests of a commercial (COM) and an experimental (EXP) herd between 2007 and 2019 were used. The mean entry age in the two herds was 645 and 279 days, respectively. The phenotypes were evaluated: rib eye area (REA), backfat thickness (BFT), residual feed intake (RFIKOCH), RFI adjusted for REA (RFIREA), RFI adjusted for BFT (RFIBFT), and RFI adjusted for REA and BFT (RFIREA BFT). The (co)variance components and prediction of genomic estimated breeding values (GEBV) were obtained by REML using ssGBLUP in single and two-trait analyses. Spearman's correlations were calculated based on the GEBV for RFIKOCH. The RFI phenotypes exhibited moderate heritability estimates in both herds (0.17 ± 0.03 to 0.27 ± 0.04). The genetic correlation between phenotypes was positive and high (0.99) in the two herds, a fact that permitted the creation of a single database (SDB). The heritability estimates of the SDB were also of moderate magnitude for the different definitions of RFI (0.19 ± 0.04 to 0.21 ± 0.04). The genetic correlations were positive and high between RFI traits 0.97 ± 0.01 to 0.99 ± 0.01), and positive and low/moderate between REA and BFT (0.01 ± 0.10 to 0.31 ± 0.12). The selection of animals based on the GEBV for RFIKOCH did not alter the ranking of individuals selected for RFIREA, RFIBFT, and RFIREA BFT. The results of the present study suggest that records of Nellore bulls of different ages and with different body compositions can be combined in a SDB for RFI calculation. Therefore, young animals can be evaluated in feed efficiency tests in order to reduce costs and the generation interval and possibly to obtain a higher response to selection.

The effect of mitochondrial DNA polymorphisms on cattle reproduction.

The aim of this study was to identify SNPs located in mitochondrial DNA that are associated with reproductive traits in beef cows. A total of 1999 Nelore females genotyped with the high-density Illumina BovineHD BeadChip (Illumina Inc., San Diego, CA, USA) were used to study the association of mitochondrial DNA variants with reproductive traits using a single-step procedure. In a preliminary analysis, the present results indicate a small participation of the mitogenome in the expression of reproductive traits in beef cattle. However, possible difficulties related to the biological characteristics of mitochondrial DNA and its inheritance, genotyping, and annotation of the phenotypes studied may also explain the results.

Gene expression profiling and identification of hub genes in Nellore cattle with different marbling score levels.

The marbling rate evaluation is difficult and expensive, requiring slaughter of the animal or ultrasound measurement. Thus, this trait is generally not included in animal breeding programs. The use of molecular techniques to elucidate intramuscular fat deposition may help improve this trait. In this respect, transcriptome studies and differential gene expression analysis by RNA-Seq can contribute to advances in this area. The objective of this study was to use RNA-Seq to identify differentially expressed genes (DEGs) in muscle tissue (longissimus thoracis) of Nellore cattle divergently ranked on marbling, in order to increase our understanding of genes involved in the expression of this trait. The results revealed 49 DEGs and three hub genes (CISH, UFM1, TSHZ1), all of them involved in insulin and diabetes mellitus metabolism. These results indicating key genes and pathways, which may help to develop strategies designed to select animals with greater marbling.

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.

Investigating the accuracy of imputing autosomal variants in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome.

BACKGROUND: Imputation accuracy among other things depends on the size of the reference panel, the marker's minor allele frequency (MAF), and the correct placement of single nucleotide polymorphism (SNP) on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50 K to 777 K SNP density using Minimac3, when map positions were determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to the empirical imputation accuracy. RESULTS: The overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R2dose) was almost identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R2dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy increased from 0.903 to 0.913, and the marker density in the imputed data increased from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals. The model-based imputation quality scores from Minimac3 (Rsq) were systematically higher than empirically estimated accuracies. However, both metrics were positively correlated and the correlation increased with the size of the reference panel and MAF of imputed variants. CONCLUSIONS: Accurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel and MAF of the imputed variants.

Use of gene expression profile to identify potentially relevant transcripts to myofibrillar fragmentation index trait.

The myofibrillar fragmentation index (MFI) is an indicative trait for meat tenderness. Longissimus thoracis muscle samples from the 20 most extreme bulls (out of 80 bulls set) for MFI (high (n = 10) and low (n = 10) groups) trait were used to perform transcriptomic analysis, using RNA Sequencing (RNA-Seq). An average of 24.616 genes was expressed in the Nellore muscle transcriptome analysis. A total of 96 genes were differentially expressed (p value ≤ 0.001) between the two groups of divergent bulls for MFI. The HEBP2 and BDH1 genes were overexpressed in animals with high MFI. The MYBPH and MYL6, myosin encoders, were identified. The differentially expressed genes were related to increase mitochondria efficiency, especially in cells under oxidative stress conditions, and these also were related to zinc and calcium binding, membrane transport, and muscle constituent proteins, such as actin and myosin. Most of those genes were involved in metabolic pathways of oxidation-reduction, transport of lactate in the plasma membrane, and muscle contraction. This is the first study applying MFI phenotypes in transcriptomic studies to identify and understand differentially expressed genes for beef tenderness. These results suggest that differences detected in gene expression between high and low MFI animals are related to reactive mechanisms and structural components of oxidative fibers under the condition of cellular stress. Some genes may be selected as positional candidate genes to beef tenderness, MYL6, MYBPH, TRIM63, TRIM55, TRIOBP, and CHRNG genes. The use of MFI phenotypes could enhance results of meat tenderness studies.

Mapping genomic regions for reproductive traits in beef cattle: Inclusion of the X chromosome.

Although the second largest chromosome of the genome, the X chromosome is usually excluded from genome-wide association studies (GWAS). Considering the presence and importance of genes on this chromosome that are involved in reproduction, the aim of this study was to evaluate the effect of its inclusion in GWAS on reproductive traits (scrotal circumference [SC], early pregnancy [P16] and age at first calving [AFC]) in a Nelore herd. Genotype data from 3,263 animals with the above-mentioned phenotypes were used. The results showed an increase in the variances explained by the autosomal markers for all traits when the X chromosome was not included. For SC, there was an increase of more than 10% for the windows on chromosomes 2 and 6. For P16, the effect was increased by almost 20% for windows on chromosome 5. The same pattern was found for AFC, with an increase of more than 10% for the most important windows. The results indicate that the noninclusion of the X chromosome can overestimate the effects of autosomes on SC, P16 and AFC not only because of the additive effect of the X chromosome itself but also because of its epistatic effect on autosomal genes.

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.

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.

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.

Prediction of hub genes associated with intramuscular fat content in Nelore cattle.

BACKGROUND: The aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content. RESULTS: A total of 30 transcriptomics datasets (RNA-Seq) obtained from longissimus thoracis muscle were selected based on the phenotypic value of divergent intramuscular fat content: 15 with the highest intramuscular fat content (HIF) and 15 with the lowest intramuscular fat content (LIF). The transcriptomics datasets were aligned with a reference genome and 65 differentially expressed genes (DEGs) were identified, including 21 upregulated and 44 downregulated genes in HIF animals. The normalized count data from DEGs was then used for co-expression network construction. From the co-expression network, four modules were identified. The topological properties of the network were analyzed; those genes engaging in the most interactions (maximal clique centrality method) with other DEGs were predicted to be hub genes (PDE4D, KLHL30 and IL1RAP), which consequently may play a role in cellular and/or systemic lipid biology in Nelore cattle. Top modules screened from the gene co-expression network were identify. The two candidate modules had clear associated biological pathways related to fat development, cell adhesion, and muscle differentiation, immune system, among others. The hub genes belonged in top modules and were downregulated in HIF animals. PDE4D and IL1RAP have known effects on lipid metabolism and the immune system through the regulation of cAMP signaling. Given that cAMP is known to play a role in lipid systems, PDE4D and IL1RAP downregulation may contribute to increased levels of intracellular cAMP and thus may have effects on IF content differences in Nelore cattle. KLHL30 may have effects on muscle metabolism. Klhl protein families play a role in protein degradation. However, the downregulation of this gene and its role in lipid metabolism has not yet been clarified. CONCLUSIONS: The results reported in this study indicate candidate genes and molecular mechanisms involved in IF content difference in Nelore cattle.

Genome-wide scan reveals population stratification and footprints of recent selection in Nelore cattle.

BACKGROUND: This study aimed at (1) assessing the genomic stratification of experimental lines of Nelore cattle that have experienced different selection regimes for growth traits, and (2) identifying genomic regions that have undergone recent selection. We used a sample of 763 animals genotyped with the Illumina BovineHD BeadChip, among which 674 animals originated from two lines that are maintained under directional selection for increased yearling body weight and 89 animals from a control line that is maintained under stabilizing selection. RESULTS: Multidimensional analysis of the genomic dissimilarity matrix and admixture analysis revealed a substantial level of population stratification between the directional selection lines and the stabilizing selection control line. Two of the three tests used to detect selection signatures (FST, XP-EHH and iHS) revealed six candidate regions with indications of selection, which strongly indicates truly positive signals. The set of identified candidate genes included several genes with roles that are functionally related to growth metabolism, such as COL14A1, CPT1C, CRH, TBC1D1, and XKR4. CONCLUSIONS: The current study identified genetic stratification that resulted from almost four decades of divergent selection in an experimental Nelore population, and highlighted autosomal genomic regions that present patterns of recent selection. Our findings provide a basis for a better understanding of the metabolic mechanism that underlies the growth traits, which are modified by selection for yearling body weight.

Expression of genes related to mitochondrial function in Nellore cattle divergently ranked on residual feed intake.

Several measures have been proposed to investigate and improve feed efficiency in cattle. One of the most commonly used measure of feed efficiency is residual feed intake (RFI), which is estimated as the difference between actual feed intake and expected feed intake based on the animal's average live weight. This measure permits to identify and select the most efficient animals without selecting for higher mature weight. Mitochondrial function has been indicated as a major factor that influences RFI. The analysis of genes involved in mitochondrial function is therefore an alternative to identify molecular markers associated with higher feed efficiency. This study analyzed the expression of PGC1α, TFAM, UCP2 and UCP3 genes by quantitative real-time PCR in liver and muscle tissues of two groups of Nellore cattle divergently ranked on RFI values in order to evaluate the relationship of these genes with RFI. In liver tissue, higher expression of TFAM and UCP2 genes was observed in the negative RFI group. Expression of PGC1α gene did not differ significantly between the two groups, whereas UCP3 gene was not expressed in liver tissue. In muscle tissue, higher expression of TFAM gene was observed in the positive RFI group. Expression of PGC1α, UCP2 and UCP3 genes did not differ significantly between the two groups. These results suggest the use of TFAM and UCP2 as possible candidate gene markers in breeding programs designed to increase the feed efficiency of Nellore cattle.