Selective signatures in composite MONTANA TROPICAL beef cattle reveal potential genomic regions for tropical adaptation.

Genomic regions related to tropical adaptability are of paramount importance for animal breeding nowadays, especially in the context of global climate change. Moreover, understanding the genomic architecture of these regions may be very relevant for aiding breeding programs in choosing the best selection scheme for tropical adaptation and/or implementing a crossbreeding scheme. The composite MONTANA TROPICAL® population was developed by crossing cattle of four different biological types to improve production in harsh environments. Pedigree and genotype data (51962 SNPs) from 3215 MONTANA TROPICAL® cattle were used to i) characterize the population structure; ii) identify signatures of selection with complementary approaches, i.e. Integrated Haplotype Score (iHS) and Runs of Homozygosity (ROH); and iii) understand genes and traits related to each selected region. The population structure based on principal components had a weak relationship with the genetic contribution of the different biological types. Clustering analyses (ADMIXTURE) showed different clusters according to the number of generations within the composite population. Considering results of both selection signatures approaches, we identified only one consensus region on chromosome 20 (35399405-40329703 bp). Genes in this region are related to immune function, regulation of epithelial cell differentiation, and cell response to ionizing radiation. This region harbors the slick locus which is related to slick hair and epidermis anatomy, both of which are related to heat stress adaptation. Also, QTLs in this region were related to feed intake, milk yield, mastitis, reproduction, and slick hair coat. The signatures of selection detected here arose in a few generations after crossbreeding between contrasting breeds. Therefore, it shows how important this genomic region may be for these animals to thrive in tropical conditions. Further investigations on sequencing this region can identify candidate genes for animal breeding and/or gene editing to tackle the challenges of climate change.

Fetal Programming Influence on Microbiome Diversity and Ruminal and Cecal Epithelium in Beef Cattle.

We explored the influence of maternal nutritional strategies on the development of the rumen and cecum in offspring. Additionally, we investigated the potential repercussions of prenatal nutrition on the rumen and fecal microbiota composition, utilizing metagenomic 16S techniques, to understand the effects of fetal programming (FP) in Nellore cattle. A total of 63 bulls submitted to different prenatal nutrition strategies, namely, non-programming (NP), partial programming (PP), and complete programming (CP), were evaluated. The rumen epithelium was methodically evaluated based on the presence of rumenitis and structural irregularities. The assessment of cecum lesions was conducted post-evisceration, whereby all thoroughly cleaned ceca were methodically evaluated. Samples from 15 animals of rumen fluid at slaughter and feces during the finishing phase were collected, respectively. All DNA extraction were carried out using the Macherey Nagel NucleoSpin Tissue®, and 16S sequencing was conducted using the V4 primers on the MiSeq platform. Within the ruminal ecosystem, an estimated range of 90 to 130 distinct amplicon sequence variants was discerned, as distributed across 45,000 to 70,000 sequencing reads. Our metagenomic exploration unveils microbial communities that distinctly mirror gastrointestinal tract microenvironments and dietary influences. In sum, this comprehensive study advances our comprehension of FP, highlighting the interplay of maternal nutrition, gastrointestinal development, and microbial communities, contributing significantly to the fields of animal science.

An Exploratory Data Analysis from Ovine and Bovine RNA-Seq Identifies Pathways and Key Genes Related to Cervical Dilatation.

The present study developed a review and exploration of data in public and already validated repositories. The main objective was to identify the pathways involved in ruminants' cervical dilatation, which are conserved between cattle and sheep in the follicular and luteal phases of the reproductive cycle. In cattle, 1961 genes were more differentially expressed in the follicular phase and 1560 in the luteal phase. An amount of 24 genes were considered exclusively expressed from these. A total of 18 genes were in the follicular phase and 6 genes were in the luteal phase. In sheep, 2126 genes were more differentially expressed in the follicular phase and 2469 genes were more differentially expressed in the luteal phase. Hoxb genes were identified in both species and are correlated with the PI3K/Akt pathway. PI3K/Akt was also found in both cattle and sheep, appearing prominently in the follicular and luteal phases of both species. Our analyses have pointed out that the PI3K/Akt pathway and the Hoxb genes appear in prominence in modulating mechanisms that involve estrus alterations in the cervix. PI3K/Akt appears to be an important pathway in the cervical relaxation process.

Weighted genomic prediction for growth and carcass-related traits in Nelore cattle.

This study aimed to assess the impact of differential weighting in genomic regions harboring candidate causal loci on the genomic prediction accuracy and dispersion for growth and carcass-related traits in Nelore cattle. The dataset contained 168 793 phenotypic records for adjusted weight at 450 days of age (W450), 83 624 for rib eye area (REA), 24 480 for marbling (MAR) and 82 981 for subcutaneous backfat thickness (BFT) and rump fat thickness (RFT). The pedigree harbored information from 244 254 animals born between 1977 and 2016, including 6283 sires and 50 742 dams. Animals (n = 7769) were genotyped with the low-density panel (Clarifide® Nelore 3.0), and the genotypes were imputed to a panel containing 735 044 markers. A linear animal model was applied to estimate the genetic parameters and to perform the weighted single-step genome-wide association study (WssGWAS). A total of seven models for genomic prediction were evaluated combining the SNP weights obtained in the iterations of the WssGWAS and the candidate QTL. The heritability estimated for W450 (0.35) was moderate, and for carcass-related traits, the estimates were moderate for REA (0.27), MAR (0.28) and RFT (0.28), and low for BFT (0.18). The prediction accuracy for W450 incorporating reported QTL previously described in the literature along with different SNPs weights was like those described for the default ssGBLUP model. The use of the ssGWAS to weight the SNP effects displayed limited advantages for the REA prediction accuracy. Comparing the ssGBLUP with the BLUP model, a meaningful improvement in the prediction accuracy from 0.09 to 0.63 (700%) was observed for MAR. The highest prediction accuracy was obtained for BFT and RFT in all evaluated models. The application of information obtained from the WssGWAS is an alternative to reduce the genomic prediction dispersion for growth and carcass-related traits, except for MAR. Furthermore, the results obtained herein pointed out that is possible to improve the prediction accuracy and reduce the genomic prediction dispersion for growth and carcass-related traits in young animals.

Impacts of Different Prenatal Supplementation Strategies on the Plasma Metabolome of Bulls in the Rearing and Finishing Phase.

This study investigated the effects of maternal nutrition on the plasma metabolome of Nellore bulls in the rearing and finishing phases, and metabolic differences between these phases. For this study, three nutritional approaches were used in 126 cows during pregnancy: NP-(control) mineral supplementation; PP-protein-energy supplementation in the final third; and FP-protein-energy supplementation during the entire pregnancy. We collected blood samples from male offspring in the rearing (450 ± 28 days old) and finishing phases (660 ± 28 days old). The blood was processed, and from plasma samples, we performed the targeted metabolome analysis (AbsoluteIDQ® p180 Kit). Multiple linear regression, principal component analysis (PCA), repeated measures analysis over time, and an enrichment analysis were performed. PCA showed an overlap of treatments and time clusters in the analyses. We identified significant metabolites among the treatments (rearing phase = six metabolites; finishing phase = three metabolites) and over time (21 metabolites). No significant metabolic pathways were found in the finishing phase, however, we found significant pathways in the rearing phase (Arginine biosynthesis and Histidine metabolism). Thus, prenatal nutrition impacted on plasma metabolome of bulls during the rearing and finishing phase and the different production stages showed an effect on the metabolic levels of bulls.

Metabolomics Changes in Meat and Subcutaneous Fat of Male Cattle Submitted to Fetal Programming.

This study investigated changes in meat and subcutaneous fat metabolomes and possible metabolic pathways related to prenatal nutrition in beef cattle. For this purpose, 18 Nellore bulls were used for meat sampling and 15 for fat sampling. The nutritional treatments during the gestation were: NP-not programmed or control, without protein-energy supplementation; PP-partially programmed, with protein-energy supplementation (0.3% of body weight (BW)) only in the final third of pregnancy; and FP-full programming, with protein-energy supplementation (0.3% of BW) during the entire pregnancy. The meat and fat samples were collected individually 24 h after slaughter, and the metabolites were extracted using a combination of chemical reagents and mechanical processes and subsequently quantified using liquid chromatography or flow injection coupled to mass spectrometry. The data obtained were submitted to principal component analysis (PCA), analysis of variance (ANOVA), and functional enrichment analysis, with a significance level of 5%. The PCA showed an overlap between the treatments for both meat and fat. In meat, 25 metabolites were statistically different between treatments (p ≤ 0.05), belonging to four classes (glycerophospholipids, amino acids, sphingolipids, and biogenic amine). In fat, 10 significant metabolites (p ≤ 0.05) were obtained in two classes (phosphatidylcholine and lysophosphatidylcholine). The functional enrichment analysis showed alterations in the aminoacyl-tRNA pathway in meat (p = 0.030); however, there was no pathway enriched for fat. Fetal programming influenced the meat and fat metabolomes and the aminoacyl-tRNA metabolic pathway, which is an important candidate for the biological process linked to meat quality and related to fetal programming in beef cattle.

Genome-Wide Association (GWAS) Applied to Carcass and Meat Traits of Nellore Cattle.

The meat market has enormous importance for the world economy, and the quality of the product offered to the consumer is fundamental for the success of the sector. In this study, we analyzed a database which contained information on 2470 animals from a commercial farm in the state of São Paulo, Brazil. Of this total, 2181 animals were genotyped, using 777,962 single-nucleotide polymorphisms (SNPs). After quality control analysis, 468,321 SNPs provided information on the number of genotyped animals. Genome-wide association analyses (GWAS) were performed for the characteristics of the rib eye area (REA), subcutaneous fat thickness (SFT), shear force at 7 days' ageing (SF7), and intramuscular fat (IMF), with the aid of the single-step genomic best linear unbiased prediction (ssGBLUP) method, with the purpose of identifying possible genomic windows (~1 Mb) responsible for explaining at least 0.5% of the genetic variance of the traits under analysis (≥0.5%). These genomic regions were used in a gene search and enrichment analyses using MeSH terms. The distributed heritability coefficients were 0.14, 0.20, 0.18, and 0.21 for REA, SFT, SF7, and IMF, respectively. The GWAS results indicated significant genomic windows for the traits of interest in a total of 17 chromosomes. Enrichment analyses showed the following significant terms (FDR ≤ 0.05) associated with the characteristics under study: for the REA, heat stress disorders and life cycle stages; for SFT, insulin and nonesterified fatty acids; for SF7, apoptosis and heat shock proteins (HSP27); and for IMF, metalloproteinase 2. In addition, KEGG (Kyoto encyclopedia of genes and genomes) enrichment analysis allowed us to highlight important metabolic pathways related to the studied phenotypes, such as the growth hormone synthesis, insulin-signaling, fatty acid metabolism, and ABC transporter pathways. The results obtained provide a better understanding of the molecular processes involved in the expression of the studied characteristics and may contribute to the design of selection strategies and future studies aimed at improving the productivity of Nellore cattle.

Differential Allele-Specific Expression Revealed Functional Variants and Candidate Genes Related to Meat Quality Traits in B. indicus Muscle.

Traditional transcriptomics approaches have been used to identify candidate genes affecting economically important livestock traits. Regulatory variants affecting these traits, however, remain under covered. Genomic regions showing allele-specific expression (ASE) are under the effect of cis-regulatory variants, being useful for improving the accuracy of genomic selection models. Taking advantage of the better of these two methods, we investigated single nucleotide polymorphisms (SNPs) in regions showing differential ASE (DASE SNPs) between contrasting groups for beef quality traits. For these analyses, we used RNA sequencing data, imputed genotypes and genomic estimated breeding values of muscle-related traits from 190 Nelore (Bos indicus) steers. We selected 40 contrasting unrelated samples for the analysis (N = 20 animals per contrasting group) and used a beta-binomial model to identify ASE SNPs in only one group (i.e., DASE SNPs). We found 1479 DASE SNPs (FDR ≤ 0.05) associated with 55 beef-quality traits. Most DASE genes were involved with tenderness and muscle homeostasis, presenting a co-expression module enriched for the protein ubiquitination process. The results overlapped with epigenetics and phenotype-associated data, suggesting that DASE SNPs are potentially linked to cis-regulatory variants affecting simultaneously the transcription and phenotype through chromatin state modulation.

Variability of the ß-casein gene polymorphism in Curraleiro Pé-Duro cattle: a geographical genetics approach.

This study purposes to examine the distribution of A2A2 alleles in herds of Curraleiro Pé-Duro (CPD) cattle and test association patterns with geographical and municipal development data. Eight CPD herds were selected from the municipalities of Tocantins State, Brazil. The frequency of the A1 and A2 allele was 40.0 and 60.0%, and the frequencies of genotypes A1A1, A1A2, and A2A2 were 20.0, 39.0, and 41.0%, respectively. Correlation estimates supported that the preferred genotype (A2A2) was mostly present in the relatively higher developed mesoregion (West) (P < 0.05). However, genotypic frequencies varied at random according to human population of municipalities and human development index (P > 0.05). The evaluation of the variability of the ß-casein gene polymorphism, coupled with spatially explicit methods (spatial autocorrelation, mantel test, and interpolation procedures), revealed some level of spatial dependency. The results suggest that the production of A2A2 milk in indigenous CPD cattle is feasible. This will depend on the adoption of selection schemes.

Allele-specific expression reveals functional SNPs affecting muscle-related genes in bovine.

Single nucleotide polymorphisms showing allele-specific expression (ASE SNPs) are useful for cis-regulatory variants discovery. Despite this potential, there are expensive costs involved in genome-level ASE analysis for large sample sizes. If different data resolutions are available, genotype imputation can be used to mitigate this limitation. Aiming to increase the power to detect regulatory variants, we used a large dataset (>4 million) of imputed SNP genotypes and RNA-Seq data from 190 Nelore steers. Differences between major and minor allele expressions in muscle were tested with a Binomial Test. We identified 38,177 ASE SNPs (FDR ≤ 0.05) within 7304 linkage disequilibrium blocks. After that, we searched for aseQTLs (i.e., neighboring SNPs potentially regulating the ASE SNPs' allelic expression) by comparing the ASE of heterozygous to homozygous sample groups under a Wilcoxon Rank Sum test. We identified 21,543 aseQTLs potentially regulating 430 ASE SNPs (FDR ≤ 0.05). A total of 3333 cis-eQTLs (being 2098 ASE SNPs and 1075 aseQTLs) were associated with the expression of 758 transcripts (FDR ≤ 0.05), demonstrating the cis-regulatory effect of these ASE SNPs and aseQTLs. Data integration showed reproducibility with previous studies in bovine ASE and genomic imprinting. Furthermore, we identified 36,756 novel ASE regions due to the imputation approach. Comparisons with epigenetics data from Functional Annotation of Animal Genomes (FAANG) suggest a regulatory potential of the ASE-related SNPs. The affected genes were enriched in metabolic pathways essential for muscle homeostasis. These findings reinforce the potential of using ASE for discovering cis-regulatory SNPs that may affect muscle-related traits.

Genomic integration to identify molecular biomarkers associated with indicator traits of gastrointestinal nematode resistance in sheep.

This study aimed to integrate GWAS and structural variants to propose possible molecular biomarkers related to gastrointestinal nematode resistance traits in Santa Inês sheep. The phenotypic records FAMACHA, haematocrit, white blood cell count, red blood cell count, haemoglobin, platelets and egg counts per gram of faeces were collected from 700 naturally infected animals, belonging to four Brazilian flocks. A total of 576 animals were genotyped using the Ovine SNP12k BeadChip and were imputed using a reference population with Ovine SNP50 BeadChip. The GWAS approaches were based on SNPs, haplotypes, CNVs and ROH. The overlapping between the significant genomic regions detected from all approaches was investigated, and the results were integrated using a network analysis. Genes related to the immune system were found, such as ABCB1, IL6, WNT5A and IRF5. Genomic regions containing candidate genes and metabolic pathways involved in immune responses, inflammatory processes and immune cells affecting parasite resistance traits were identified. The genomic regions, biological processes and candidate genes uncovered could lead to biomarkers for selecting more resilient sheep and improving herd welfare and productivity. The results obtained are the start point to identify molecular biomarkers related to indicator traits of gastrointestinal nematode resistance in Santa Inês sheep.

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals.

BACKGROUND: A decline in the level of genetic diversity in livestock can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, various metrics have been proposed to assess the level of genetic diversity in selected populations. Therefore, the main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses. RESULTS: A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four ROH islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (FHOM), uniting of gametes (FUNI), and genotype additive variance (FGRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (FROH). For the HER, 3576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system, indicating potential balancing selection. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data. CONCLUSIONS: The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes.

Searching for causal relationships among latent variables concerning performance, carcass, and meat quality traits in broilers.

In causal relationship studies, the latent variables may summarize the phenotypes in theoretical traits according to their phenotypic correlations, improving the understanding of causal relationships between broilers phenotypes. In this study, we aimed to investigate potential causal relationships among latent variables in broilers using a structural equation model in the context of genetic analysis. The data used in this study comprised 14 traits in broilers with 2,017 records each, and 104,154 animals in pedigree. Four latent variables (WEIGHT, LOSSES, COLOUR, and VISCERA) were defined and validated using Bayesian Confirmatory Factor Analysis. Subsequently, a search for causal linkage structures was performed, obtaining a single causal link structure between the latent variables. Then, this information was used to fit the structural equation model (SEM). The results from the SEM indicated positive causal effects of the variables WEIGHT and LOSSES on the variables VISCERA and COLOUR, respectively, with structural coefficient estimates of 1.006 and 0.040, respectively. On the other hand, an antagonist causal effect of the variable WEIGHT on the variable LOSSES was verified, with a structural coefficient estimate of -4.333. These results highlight the causal relationship between performance and meat quality traits, which may be associated with the natural processes involved in the conversion of muscle into meat and the structural changes in muscle tissues due to intense selection for high growth rates in broilers.

Reduced rank analysis of morphometric and functional traits in Campolina horses.

Multitrait models can increase the accuracy of breeding value prediction and reduce bias due to selection by using traits measured before and after it has occurred. However, as the number of traits grows, a similar trend is expected for the number of parameters to be estimated, which directly affects the computing power and the amount of data required. The aim of the present study was to apply reduced rank (principal components model-PCM) and factor analytical models (FAM), to estimate (co)variance components for nineteen traits, jointly evaluated in a single analysis in Campolina horses. A total of 18 morphometric traits (MT) and one gait visual score (GtS), along with genealogical records of 48,806 horses, were analysed under a restricted maximum likelihood framework. Nine PCM, nine FAM and one standard multitrait model (MTM) were fitted to the data and compared to find the best suitable model. Based on Bayesian information criterion, the best model was the FAM option, considering five common factors (FAM5). After performing an intraclass analysis, none of MT were genetically negatively correlated, whereas GtS was negatively related to all MT, except for the genetic correlations among GtS and BLL, and between GtS and BLLBL (0.01 and 0.10 respectively). From all MT, two traits were derived computing ratios involving other traits, those had negative correlations with others MT, but all favourable for selection. Similar patterns were observed between the genetic parameters obtained from MTM and FAM5 respectively. The heritability estimates ranged from 0.09 (head width) to 0.47 (height at withers). Our results indicated that FAM was efficient to reduce the multitrait analysis dimensionality, and therefore, traits can be combined based on the first three eigenvectors from the additive genetic (co)variance matrix. In addition, there was sufficient genetic variation for selection, benefiting its potential implementation in a breeding program.

Metafounders May Reduce Bias in Composite Cattle Genomic Predictions.

Metafounders are pseudo-individuals that act as proxies for animals in base populations. When metafounders are used, individuals from different breeds can be related through pedigree, improving the compatibility between genomic and pedigree relationships. The aim of this study was to investigate the use of metafounders and unknown parent groups (UPGs) for the genomic evaluation of a composite beef cattle population. Phenotypes were available for scrotal circumference at 14 months of age (SC14), post weaning gain (PWG), weaning weight (WW), and birth weight (BW). The pedigree included 680,551 animals, of which 1,899 were genotyped for or imputed to around 30,000 single-nucleotide polymorphisms (SNPs). Evaluations were performed based on pedigree (BLUP), pedigree with UPGs (BLUP_UPG), pedigree with metafounders (BLUP_MF), single-step genomic BLUP (ssGBLUP), ssGBLUP with UPGs for genomic and pedigree relationship matrices (ssGBLUP_UPG) or only for the pedigree relationship matrix (ssGBLUP_UPGA), and ssGBLUP with metafounders (ssGBLUP_MF). Each evaluation considered either four or 10 groups that were assigned based on breed of founders and intermediate crosses. To evaluate model performance, we used a validation method based on linear regression statistics to obtain accuracy, stability, dispersion, and bias of (genomic) estimated breeding value [(G)EBV]. Overall, relationships within and among metafounders were stronger in the scenario with 10 metafounders. Accuracy was greater for models with genomic information than for BLUP. Also, the stability of (G)EBVs was greater when genomic information was taken into account. Overall, pedigree-based methods showed lower inflation/deflation (regression coefficients close to 1.0) for SC14, WWM, and BWD traits. The level of inflation/deflation for genomic models was small and trait-dependent. Compared with regular ssGBLUP, ssGBLUP_MF4 displayed regression coefficient closer to one SC14, PWG, WWM, and BWD. Genomic models with metafounders seemed to be slightly more stable than models with UPGs based on higher similarity of results with different numbers of groups. Further, metafounders can help to reduce bias in genomic evaluations of composite beef cattle populations without reducing the stability of GEBVs.

Random-effect meta-analysis of genetic parameter estimates for carcass and meat quality traits in beef cattle.

Considerable variability of genetic parameter estimates is observed among different studies for the same trait, which is associated with the distinct effects included in the statistical model, population breed, and sample sizes. The random-effect meta-analysis summarizes genetic parameters considering the heterogeneity among studies. Therefore, the aim of this study was to perform a random-effect meta-analysis of heritability and genetic correlation estimates for carcass and meat quality traits in beef cattle. A total of 152 estimates of heritability and 83 genetic correlations for longissimus muscle area (LMA), back fat thickness (BFT), and marbling score (MRB) were used. High heterogeneity among published studies was observed for all traits, indicating the need of a random-effects model to perform the analysis. Estimates of heritability through the meta-analysis using the random-effects model were high (0.30 to 0.34), indicating that fast genetic progress can be obtained for these traits. However, genetic correlations had low magnitude (lower than 0.25), which suggested that all three traits should be included in the selection scheme.

Genetic parameters associated with meat quality of Nellore cattle at different anatomical points of longissimus: Brazilian standards.

The present study estimated genetic parameters and evaluated the genetic and phenotypic correlations between meat quality characteristics of Nellore cattle evaluated at different anatomical points of the longissimus. Data from 1329 Nellore young bulls were used to evaluate, in the 5th and 12th ribs, marbling score (MAR), shear force (SF), cooking weight losses (CWL) and intramuscular fat (IMF). In addition, the subcutaneous fat thickness was measured at the 12th rib (SFT12) and between the last lumbar and the first sacral vertebrae (SFTLR), in the separation of loin and round. Results yielded moderate heritability coefficients for evaluated characteristics, except CWL. High genetic correlations (0.61) were found between measurements of SFT12 and SFTLR. MAR, IMF and SF were evaluated at the 5th and 12th rib. Meat quality and subcutaneous fat thickness measured at different anatomical points of the longissimus are genetically correlated and can be used in genetic selection programs to improve meat quality characteristics in Nellore cattle.

Genetic Parameters and Genome-Wide Association Studies for Anti-Müllerian Hormone Levels and Antral Follicle Populations Measured After Estrus Synchronization in Nellore Cattle.

Reproductive efficiency plays a major role in the long-term sustainability of livestock industries and can be improved through genetic and genomic selection. This study aimed to estimate genetic parameters (heritability and genetic correlation) and identify genomic regions and candidate genes associated with anti-Müllerian hormone levels (AMH) and antral follicle populations measured after estrous synchronization (AFP) in Nellore cattle. The datasets included phenotypic records for 1099 and 289 Nellore females for AFP and AMH, respectively, high-density single nucleotide polymorphism (SNP) genotypes for 944 animals, and 4129 individuals in the pedigree. The heritability estimates for AMH and AFP were 0.28 ± 0.07 and 0.30 ± 0.09, and the traits were highly and positively genetically correlated (rG = 0.81 ± 0.02). These findings indicated that these traits can be improved through selective breeding, and substantial indirect genetic gains are expected by selecting for only one of the two traits. A total of 31 genomic regions were shown to be associated with AMH or AFP, and two genomic regions located on BTA1 (64.9-65.0 Mb and 109.1-109.2 Mb) overlapped between the traits. Various candidate genes were identified to be potentially linked to important biological processes such as ovulation, tissue remodeling, and the immune system. Our findings support the use of AMH and AFP as indicator traits to genetically improve fertility rates in Nellore cattle and identify better oocyte donors.

Predicting the shear value and intramuscular fat in meat from Nellore cattle using Vis-NIR spectroscopy.

Visible and near-infrared spectroscopy (Vis-NIRS) was tested for its effectiveness in predicting intramuscular fat (IMF) and WBSF in Nellore steers. Beef samples from longissimus thoracis, aged for either 2 or 7 days, had their spectra collected for wavelengths ranging from 400 to 1395 nm. Partial least squares regression models were developed for each trait. Determination coefficients of calibration models for WBSF ranged from 0.17 to 0.53. Considering WBSF in samples aged for 2 days, Vis-NIR correctly classified 100% of tough samples (>45 N), but wrongly classified all tender samples (≤45 N) as tough. Determination coefficients of calibration models for IMF ranged from 0.12 to 0.14. Vis-NIRS is a useful tool for identifying tough beef, but it is less effective in predicting tender samples and IMF. Additional studies are necessary to generate more robust models for the prediction of intramuscular fat in intact meat samples of Nellore cattle.

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.