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.

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.

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.

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.

Genomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes.

The aim of the present study was to compare the predictive ability of SNP-BLUP model using different pseudo-phenotypes such as phenotype adjusted for fixed effects, estimated breeding value, and genomic estimated breeding value, using simulated and real data for beef FA profile of Nelore cattle finished in feedlot. A pedigree with phenotypes and genotypes of 10,000 animals were simulated, considering 50% of multiple sires in the pedigree. Regarding to phenotypes, two traits were simulated, one with high heritability (0.58), another with low heritability (0.13). Ten replicates were performed for each trait and results were averaged among replicates. A historical population was created from generation zero to 2020, with a constant size of 2000 animals (from generation zero to 1000) to produce different levels of linkage disequilibrium (LD). Therefore, there was a gradual reduction in the number of animals (from 2000 to 600), producing a "bottleneck effect" and consequently, genetic drift and LD starting in the generation 1001 to 2020. A total of 335,000 markers (with MAF greater or equal to 0.02) and 1000 QTL were randomly selected from the last generation of the historical population to generate genotypic data for the test population. The phenotypes were computed as the sum of the QTL effects and an error term sampled from a normal distribution with zero mean and variance equal to 0.88. For simulated data, 4000 animals of the generations 7, 8, and 9 (with genotype and phenotype) were used as training population, and 1000 animals of the last generation (10) were used as validation population. A total of 937 Nelore bulls with phenotype for fatty acid profiles (Sum of saturated, monounsaturated, omega 3, omega 6, ratio of polyunsaturated and saturated and polyunsaturated fatty acid profile) were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. To compare the accuracy and bias of direct genomic value (DGV) for different pseudo-phenotypes, the correlation between true breeding value (TBV) or DGV with pseudo-phenotypes and linear regression coefficient of the pseudo-phenotypes on TBV for simulated data or DGV for real data, respectively. For simulated data, the correlations between DGV and TBV for high heritability traits were higher than obtained with low heritability traits. For simulated and real data, the prediction ability was higher for GEBV than for Yc and EBV. For simulated data, the regression coefficient estimates (b(Yc,DGV)), were on average lower than 1 for high and low heritability traits, being inflated. The results were more biased for Yc and EBV than for GEBV. For real data, the GEBV displayed less biased results compared to Yc and EBV for SFA, MUFA, n-3, n-6, and PUFA/SFA. Despite the less biased results for PUFA using the EBV as pseudo-phenotype, the b(Yi,DGV estimates obtained for the different pseudo-phenotypes (Yc, EBV and GEBV) were very close. Genomic information can assist in improving beef fatty acid profile in Zebu cattle, since the use of genomic information yielded genomic values for fatty acid profile with accuracies ranging from low to moderate. Considering both simulated and real data, the ssGBLUP model is an appropriate alternative to obtain more reliable and less biased GEBVs as pseudo-phenotype in situations of missing pedigree, due to high proportion of multiple sires, being more adequate than EBV and Yc to predict direct genomic value for beef fatty acid profile.

Association study between copy number variation and beef fatty acid profile of Nellore cattle.

The aim of this study was to analyze the association between the copy number variation regions (CNVRs) and fatty acid profile phenotypes for saturated (SFA), monosaturated (MUFA), polyunsaturated (PUFA), ω6 and ω3 fatty acids, PUFA/SFA and ω6/ω3 ratios, as well as for their sums, in Nellore cattle (Bos primigenius indicus). A total of 963 males were finished in feedlot and slaughtered with approximately 2 years of age. Animals were genotyped with the BovineHD BeadChip (Illumina Inc., San Diego, CA, USA). The copy number variation (CNV) detection was performed using the PennCNV algorithm. Log R ratio (LRR) and allele B frequency (BAF) were used to estimate the CNVs. The association analyses were done using the CNVRuler software and applying a logistic regression model. The phenotype was adjusted using a linear model considering the fixed effects of contemporary group and the animal age at slaughter. The fatty acid profile was analyzed on samples of longissimus thoracis muscle using gas chromatography with a 100-m capillary column. For the association analysis, the adjusted phenotypic values were considered for the traits, while the data was adjusted for the effects of the farm and year of birth, management groups at birth, weaning, and superannuation. A total of 186 CNVRs were significant for SFA (43), MUFA (42), PUFA (66), and omega fatty acid (35) groups, totaling 278 known genes. On the basis of the results, several genes were associated with several fatty acids of different saturations. Olfactory receptor genes were associated with C12:0, C14:0, and C18:0 fatty acids. The SAMD8 and BSCL2 genes, both related to lipid metabolic process, were associated with C12:0. The RAPGEF6 gene was found to be associated with C18:2 cis-9 cis-12 n-6, and its function is related to regulation of GTPase activity. Among the results, we highlighted the olfactory receptor activity (GO:0004984), G-protein-coupled receptor activity (GO:0004930), potassium:proton antiporter activity (GO:0015386), sodium:proton antiporter activity (GO:0015385), and odorant-binding (GO:0005549) molecular functions. A large number of genes associated with fatty acid profile within the CNVRs were identified in this study. These findings must contribute to better elucidate the genetic mechanism underlying the fatty acid profile of intramuscular fat in Nellore cattle.

Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data.

The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty.

Genomic regions and pathways associated with gastrointestinal parasites resistance in Santa Inês breed adapted to tropical climate.

BACKGROUND: The aim of this study was to estimate variance components and to identify genomic regions and pathways associated with resistance to gastrointestinal parasites, particularly Haemonchus contortus, in a breed of sheep adapted to tropical climate. Phenotypes evaluations were performed to verify resistance to gastrointestinal parasites, and were divided into two categories: i) farm phenotypes, assessing body condition score (BCS), degree of anemia assessed by the famacha chart (FAM), fur score (FS) and feces consistency (FC); and ii) lab phenotypes, comprising blood analyses for hematocrit (HCT), white blood cell count (WBC), red blood cell count (RBC), hemoglobin (HGB), platelets (PLT) and transformed (log10) egg per gram of feces (EPGlog). A total of 576 animals were genotyped with the Ovine SNP12k BeadChip (Illumina, Inc.), that contains 12,785 bialleleic SNP markers. The variance components were estimated using a single trait model by single step genomic BLUP procedure. RESULTS: The overall linkage disequilibrium (LD) mean between pairs of markers measured by r2 was 0.23. The overall LD mean between markers considering windows up to 10 Mb was 0.07. The mean LD between adjacent SNPs across autosomes ranged from 0.02 to 0.10. Heritability estimates were low for EPGlog (0.11), moderate for RBC (0.18), PLT (0.17) HCT (0.20), HGB (0.16) and WBC (0.22), and high for FAM (0.35). A total of 22, 21, 23, 20, 26, 25 and 23 windows for EPGlog for FAM, WBC, RBC, PLT, HCT and HGB traits were identified, respectively. Among the associated windows, 10 were shown to be common to HCT and HGB traits on OAR1, OAR2, OAR3, OAR5, OAR8 and OAR15. CONCLUSION: The traits indicating gastrointestinal parasites resistance presented an adequate genetic variability to respond to selection in Santa Inês breed, and it is expected a higher genetic gain for FAM trait when compared to the others. The level of LD estimated for markers separated by less than 1 Mb indicated that the Ovine SNP12k BeadChip might be a suitable tool for identifying genomic regions associated with traits related to gastrointestinal parasite resistance. Several candidate genes related to immune system development and activation, inflammatory response, regulation of lymphocytes and leukocytes proliferation were found. These genes may help in the selection of animals with higher resistance to parasites.

Physical and chemical characteristics of the longissimus dorsi from swine reared in climate-controlled and uncontrolled environments.

The aim of this study was to evaluate the effect of ambient temperature on the physical and chemical characteristics of the longissimus dorsi muscle by comparing the quality of meat from pigs reared in a controlled and in an uncontrolled environment, the latter provided with a shallow pool. Twenty castrated male pigs of the Topigs line were randomly allotted to two treatments: a controlled environment, with constant temperature (22 °C) and relative humidity (70%); and an uncontrolled environment in a conventional shed for rearing pigs equipped with a shallow pool, where pigs were subject to climatic variations. Meat from pigs kept in the controlled environment showed a greater capacity to retain intracellular water, higher tenderness, and lower cholesterol levels than meat from pigs reared in the uncontrolled environment, but displayed higher lipid oxidation and a lower concentration of DHA. Treatments had no effect on color, pH, chemical composition, or fatty acid profile (except DHA concentration). Rearing pigs in sheds equipped with a shallow pool minimizes the effects of environmental heat on meat quality, allowing the production of high-quality meat in warm climate regions without expensive investments. Animals reared in an uncontrolled environment equipped with a shallow pool are able to produce meat with characteristics within the quality standards and with similar quality to that of meat from animals raised in controlled environment.

Genomic prediction for beef fatty acid profile in Nellore cattle.

The objective of this study was to compare SNP-BLUP, BayesCπ, BayesC and Bayesian Lasso methodologies to predict the direct genomic value for saturated, monounsaturated, and polyunsaturated fatty acid profile, omega 3 and 6 in the Longissimus thoracis muscle of Nellore cattle finished in feedlot. A total of 963 Nellore bulls with phenotype for fatty acid profiles, were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. The predictive ability was evaluated using cross validation. To compare the methodologies, the correlation between DGV and pseudo-phenotypes was calculated. The accuracy varied from -0.40 to 0.62. Our results indicate that none of the methods excelled in terms of accuracy, however, the SNP-BLUP method allows obtaining less biased genomic evaluations, thereby; this method is more feasible when taking into account the analyses' operating cost. Despite the lowest bias observed for EBV, the adjusted phenotype is the preferred pseudophenotype considering the genomic prediction accuracies regarding the context of the present study.

Genetic correlation estimates between beef fatty acid profile with meat and carcass traits in Nellore cattle finished in feedlot.

The objective of this study was to estimate the genetic-quantitative relationships between the beef fatty acid profile with the carcass and meat traits of Nellore cattle. A total of 1826 bulls finished in feedlot conditions and slaughtered at 24 months of age on average were used. The following carcass and meat traits were analysed: subcutaneous fat thickness (BF), shear force (SF) and total intramuscular fat (IMF). The fatty acid (FA) profile of the Longissimus thoracis samples was determined. Twenty-five FAs (18 individuals and seven groups of FAs) were selected due to their importance for human health. The animals were genotyped with the BovineHD BeadChip and, after quality control for single nucleotide polymorphisms (SNPs), only 470,007 SNPs from 1556 samples remained. The model included the random genetic additive direct effect, the fixed effect of the contemporary group and the animal's slaughter age as a covariable. The (co)variances and genetic parameters were estimated using the REML method, considering an animal model (single-step GBLUP). A total of 25 multi-trait analyses, with four traits, were performed considering SF, BF and IMF plus each individual FA. The heritability estimates for individual saturated fatty acids (SFA) varied from 0.06 to 0.65, for monounsaturated fatty acids (MUFA) it varied from 0.02 to 0.14 and for polyunsaturated fatty acids (PUFA) it ranged from 0.05 to 0.68. The heritability estimates for Omega 3, Omega 6, SFA, MUFA and PUFA sum were low to moderate, varying from 0.09 to 0.20. The carcass and meat traits, SF (0.06) and IMF (0.07), had low heritability estimates, while BF (0.17) was moderate. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with BF were 0.04, 0.64 and -0.41, respectively. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with SF were 0.29, -0.06 and -0.04, respectively. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with IMF were 0.24, 0.90 and -0.67, respectively. The selection to improve meat tenderness in Nellore cattle should not change the fatty acid composition in beef, so it is possible to improve this attribute without affecting the nutritional beef quality in zebu breeds. However, selection for increased deposition of subcutaneous fat thickness and especially the percentage of intramuscular fat should lead to changes in the fat composition, highlighting a genetic antagonism between meat nutritional value and acceptability by the consumer.

Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure.

BACKGROUND: Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method. RESULTS: The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9, C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio. CONCLUSIONS: The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health.

Genetic analysis on accumulated productivity and calving intervals in Nelore cattle.

The aim of this study was to estimate genetic parameters for accumulated productivity (ACP), first calving interval (CI1), second calving interval (CI2), and mean calving interval (MCI) in Nelore beef cattle. The ACP trait is a reproduction index and comprises the total number of calves born per dam, weight of weaned calves, and age of the dam at calving. Genetic parameters were estimated by the average information restricted maximum likelihood method in two-trait analyses. The average heritability estimate for ACP was 0.17 (0.03). For CI1, CI2, and MCI, the heritability estimates were 0.02, 0.02, and 0.06, respectively. Genetic correlations between ACP with CI1, CI2, and MCI were -0.16 ± 0.47, -0.29 ± 0.53, and -0.40 ± 0.27, respectively. Despite of the low heritability estimates obtained in our study, reproduction traits should be further studied and their inclusion in the selection criteria must be evaluated in order to improve the performance of females because these traits are of great economic importance in beef cattle. Accumulated productivity could contribute to decrease the mean calving interval in Nelore cattle.

Growing-finishing performance and carcass yield of pigs reared in a climate-controlled and uncontrolled environment.

The objective of this study was to evaluate the effect of temperature on the performance and carcass yield of pigs housed in different environments. Twenty castrated male pigs of the Topigs line were assigned to two treatments: T1, controlled environment, and T2, uncontrolled environment containing a shallow pool. A completely randomized design consisting of two treatments and ten repetitions each was used. The data were submitted to analysis of variance, and means were compared by the Tukey test at a level of significance of 5 % using the SAS 9.2 program (SAS Institute, Inc., NC, USA). The results showed that rearing pigs in an uncontrolled environment during the growing and finishing phases reduced daily feed intake (1.722 and 3.164 kg, respectively) and improved feed conversion (2.15 and 2.70 kg, respectively), but did not influence the carcass yield of the animals. In conclusion, rearing pigs under different environmental conditions during the growing and finishing phases influenced animal performance without interfering with carcass yield.