Lenise Freitas Mueller

Gene expression profile of intramuscular muscle in Nellore cattle with extreme values of fatty acid

BackgroundFatty acid type in beef can be detrimental to human health and has received considerable attention in recent years. The aim of this study was to identify differentially expressed genes in longissimus thoracis muscle of 48 Nellore young bulls with extreme phenotypes for fatty acid composition of intramuscular fat by RNA-seq technique.ResultsDifferential expression analyses between animals with extreme phenotype for fatty acid composition showed a total of 13 differentially expressed genes for myristic (C14:0), 35 for palmitic (C16:0), 187 for stearic (C18:0), 371 for oleic (C18:1, cis-9), 24 for conjugated linoleic (C18:2 cis-9, trans11, CLA), 89 for linoleic (C18:2 cis-9,12 n6), and 110 genes for α-linolenic (C18:3 n3) fatty acids. For the respective sums of the individual fatty acids, 51 differentially expressed genes for saturated fatty acids (SFA), 336 for monounsaturated (MUFA), 131 for polyunsaturated (PUFA), 92 for PUFA/SFA ratio, 55 for ω3, 627 for ω6, and 22 for ω6/ω3 ratio were identified. Functional annotation analyses identified several genes associated with fatty acid metabolism, such as those involved in intra and extra-cellular transport of fatty acid synthesis precursors in intramuscular fat of longissimus thoracis muscle. Some of them must be highlighted, such as: ACSM3 and ACSS1 genes, which work as a precursor in fatty acid synthesis; DGAT2 gene that acts in the deposition of saturated fat in the adipose tissue; GPP and LPL genes that support the synthesis of insulin, stimulating both the glucose synthesis and the amino acids entry into the cells; and the BDH1 gene, which is responsible for the synthesis and degradation of ketone bodies used in the synthesis of ATP.ConclusionSeveral genes related to lipid metabolism and fatty acid composition were identified. These findings must contribute to the elucidation of the genetic basis to improve Nellore meat quality traits, with emphasis on human health. Additionally, it can also contribute to improve the knowledge of fatty acid biosynthesis and the selection of animals with better nutritional quality.

Genetic parameters for fatty acids in intramuscular fat from feedlot-finished Nelore carcasses

The aim of the present study was to estimate covariance components and genetic parameters for beef fatty acid (FA) composition of intramuscular fat in the longissimus thoracis muscle in Nelore bulls finished in feedlot. Twenty-two FAs were selected. The heritability estimates for individual FAs ranged from 0.01 to 0.35. The heritability estimates for myristic (0.25 ± 0.09), palmitic (0.18 ± 0.07), oleic (0.28 ± 0.09), linoleic (0.16 ± 0.06) and α-linolenic (0.35 ± 0.10) FAs were moderate. Stearic, elaidic, palmitoleic, vaccenic, conjugated linoleic acid, docosahexanoic, eicosatrienoic and arachidonic FAs had heritability estimates below 0.15. The genetic-correlation estimates between the individual saturated FAs (SFAs) were low and negative between myristic and stearic FAs (–0.22 ± 0.84), moderate between palmitic and myristic FAs (0.58 ± 0.56) and negative between palmitic and stearic FAs (–0.69 ± 0.45). The genetic correlations between the individual long-chain polyunsaturated FAs (PUFAs) were positive and moderate (>0.30). However, the genetic-correlation estimates between long-chain PUFAs and α-linolenic acid were low (<0.30), except for the correlation between arachidonic and α-linolenic acids. The genetic correlation estimates of the sums of SFAs with monounsaturated fatty acids and omega 6 FAs were low (0.25 ± 0.59 and –0.02 ± 0.51 respectively), high with PUFAs and omega 9 FAs (–0.85 ± 0.15 and 0.86 ± 0.17 respectively) and moderate with omega 3FAs (–0.67 ± 0.26). The present study demonstrated the existence of genetic variation and, hence, the possibility to increase the proportion of healthy and favourable beef FAs through selection. The results obtained in the study have provided knowledge to elucidate the additive genetic influence on FA composition of intramuscular fat. In addition, genetic-relationship estimates of intramuscular FA profile help seek strategies for genetic selection or genetic-based diet management to enhance the FA profile in Zebu cattle.

Whole cottonseed, vitamin E and finishing period affect the fatty acid profile and sensory traits of meat products from Nellore cattle

This study investigated how different finishing periods and the inclusion of whole cottonseed and vitamin E in diets fed to feedlot cattle affect meat lipid composition and sensory traits of fresh beef and hamburgers. Fifty-four Nellore bulls were fed 3 different diets (C: control; WCS: 30% whole cottonseed; WCSE: 30% whole cottonseed plus vitamin E) during finishing periods of 83, 104, and 111days. The inclusion of cottonseed did not affect saturated fatty acid levels (SFA), but increased the levels of certain polyunsaturated fatty acids (PUFA) in meat. The SFA levels and n-6/n-3 ratio increased over the length of finishing period. In general, meat products from animals fed the WCS and WCSE diets were more tender and juicier (P<0.05); however, an off-flavor was detected by the panelists (P<0.05). The sensory difference test results showed that the WCS hamburger flavor was not significantly different for the studied lengths of finishing period. Addition of 30% DM cottonseed in diets for cattle did not promote changes likely to affect human health, and it provided a more tender and juiciness meat, however differences in the off flavor were perceived only by panelist.

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.