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.

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.

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

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

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.

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.