Fábio Luiz Buranelo Toral
Other affiliations: Universidade Federal de Mato Grosso, Universidade Federal de Viçosa, Sao Paulo State University ...read more
Bio: Fábio Luiz Buranelo Toral is an academic researcher from Universidade Federal de Minas Gerais. The author has contributed to research in topics: Heritability & Beef cattle. The author has an hindex of 13, co-authored 65 publications receiving 491 citations. Previous affiliations of Fábio Luiz Buranelo Toral include Universidade Federal de Mato Grosso & Universidade Federal de Viçosa.
Papers published on a yearly basis
TL;DR: Evidence of genotype x environment interaction is shown, and that regional genetic evaluations, when available, can be more useful than a state evaluation, is shown.
Abstract: The effect of genotype x environment interaction on body weight at birth (BW), weaning (W205), 12 (W365) and 18 (W550) months of age of Nellore cattle raised in the regions of Alto Taquari, Campo Grande and Pantanal, MS, Brazil, was studied. The data were analyzed for each region separately and for all regions together. Variance and covariance components and genetic parameters were estimated by the restricted maximum likelihood method, using an animal model that included the random additive direct effect, and the fixed effects of sex and contemporary group (herd, year, season and region of birth), and sires were ranked based on their breeding values (BV). The results showed that the additive direct and residual variances were different among regions. The heritability estimates ranged from 0.16 to 0.66 (BW), 0.36 to 0.59 (W205), 0.35 to 0.49 (W365) and 0.30 to 0.45 (W550), depending on the region. Pearson's correlation coefficients between BVs of sires, obtained for each pair of regions, showed means equal to 0.11 (BW), 0.38 (W205), 0.38 (W365) and 0.39 (W550). When the correlations were for the BVs obtained for each region with the BVs obtained for all regions together, the estimates were higher showing means equal to 0.80 (BW), 0.88 (W205), 0.88 (W365) and 0.87 (W550). Despite the high values of these last ones, the results show evidence of genotype x environment interaction, and that regional genetic evaluations, when available, can be more useful than a state evaluation.
TL;DR: There is ample indication that meat quality and immune response could be improved by dietary vitamin E supplementation, and there seemed to be no relationship between dietaryitamin E supplementation and growth performance.
Abstract: The effect of vitamin E supplementation on the growth performance, carcass traits, meat quality, and immune response of male broiler chickens was studied using a meta-analysis. The database was consisted of 51 scientific papers published in peer-reviewed journals. The dependent variables for meta-analysis included final body weight, average daily gain, daily feed intake, feed conversion ratio, vitamin E concentration in the muscle, tissue polyunsaturated fatty acid concentration, lipid peroxidation value, post mortem pH, heterophil to lymphocyte ratio, and total immunoglobulins. Linear mixed models were used to analyze the data. Vitamin E supplementation did not influence growth performance, as the estimated slopes were not different from zero, with P-values equal to 0.92 for final body weight, 0.81 for average daily gain, 0.31 for daily feed intake, and 0.83 for feed conversion ratio. Dietary vitamin E supplementation increased the vitamin E content in the muscle (P = 0.001), did not change the polyunsaturated fatty acid concentration, and decreased the lipid peroxidation (P = 0.01). The immune response was improved, the heterophil to lymphocyte ratio was constant, and the total immunoglobulins were increased (P = 0.037) by dietary vitamin E supplementation. With regard to broiler chicken performance, there seemed to be no relationship between dietary vitamin E supplementation and growth performance. There is ample indication that meat quality and immune response could be improved by dietary vitamin E supplementation.
TL;DR: SC growth in Guzerat bulls was characterized by an accelerated growth phase, followed by decreased growth; this was best represented by the Logistic model, which best estimated SC in the early phase.
Abstract: The objective was to use various nonlinear models to describe scrotal circumference (SC) growth in Guzerat bulls on three farms in the state of Minas Gerais, Brazil. The nonlinear models were: Brody, Logistic, Gompertz, Richards, Von Bertalanffy, and Tanaka, where parameter A is the estimated testis size at maturity, B is the integration constant, k is a maturating index and, for the Richards and Tanaka models, m determines the inflection point. In Tanaka, A is an indefinite size of the testis, and B and k adjust the shape and inclination of the curve. A total of 7410 SC records were obtained every 3 months from 1034 bulls with ages varying between 2 and 69 months ( 731 days = 3652 SC measurements). Goodness of fit was evaluated by coefficients of determination (R2), error sum of squares, average prediction error (APE), and mean absolute deviation. The Richards model did not reach the convergence criterion. The R2 were similar for all models (0.68–0.69). The error sum of squares was lowest for the Tanaka model. All models fit the SC data poorly in the early and late periods. Logistic was the model which best estimated SC in the early phase (based on APE and mean absolute deviation). The Tanaka and Logistic models had the lowest APE between 300 and 1600 days of age. The Logistic model was chosen for analysis of the environmental influence on parameters A and k. Based on absolute growth rate, SC increased from 0.019 cm/d, peaking at 0.025 cm/d between 318 and 435 days of age. Farm, year, and season of birth significantly affected size of adult SC and SC growth rate. An increase in SC adult size (parameter A) was accompanied by decreased SC growth rate (parameter k). In conclusion, SC growth in Guzerat bulls was characterized by an accelerated growth phase, followed by decreased growth; this was best represented by the Logistic model. The inflection point occurred at approximately 376 days of age (mean SC of 17.9 cm). We inferred that early selection of testicular size might result in smaller testes at maturity.
TL;DR: It is shown that it is possible to include up to 20% of canola meal without damages on broiler performance and in the digestive tract and there was increase in crypt depth in accordance of increasing levels ofCanola meal.
Abstract: A trial was carried to verify the effect of increasing levels (0, 10, 20, 30 and 40%) of canola meal in diets of broiler chickens, on performance and mucous morphology, during the starting period (1 - 21 days). 1,000 male chicks one-day-old were used, distributed in a randomized experimental assay, with five treatments, four replicates and 50 birds per experimental unit. At the 1 st , 21 st and 41 st days, the birds and the rations were weighed and at the 21 st day two birds of each experimental unit were sacrificed for collection of a duodenum segment for evaluation of intestinal morphometry. The results demonstrated that increasing levels of canola meal induced to a linear reduction in weight gain, weight and feed intake and worst feed conversion. During the growing period (21 to 41 days), in which all of the birds received similar diet, a decrease was observed in the weight and weight gain, with the increase of the levels of canola meal, while parameters feed conversion and feed intake were similar. Data regarding mucous morphology, submitted to the regression analysis, demonstrated that there was increase in crypt depth in accordance of increasing levels of canola meal. It is possible to include up to 20% of canola meal without damages on broiler performance and in the digestive tract.
TL;DR: Genetic parameters for body weights at weaning, 12 months old and adult age, culling age, and other production traits suggest that selection of females based on weaning and 12-month body weights will not affect productivity, however, it may be decreased by increasing female adult body weight.
Abstract: The objective of this study was to estimate genetic parameters for body weights at weaning (PD), 12 months old (P12) and adult age (PAD), culling age (TPR, days in herd), number (ND10) and kilograms (QD10) of calves weaned up to ten years of age, total number (NDT) and total kilograms (QDT) of calves weaned during herd life, and kilograms of calves weaned per year in herd (QTPR) of Canchim (5/8 Charolais + 3/8 Zebu) females from one herd. Data consisted of 3,249, 3,111, 1,138, 1,340, 1,362, 1,362, 1,340, 1,340 and 1,340 records of PD, P12, PAD, TPR, ND10, QD10, NDT, QDT and QTPR, respectively. Variance and covariance components were estimated by bivariate analyses between PD, P12 and PAD and other production traits using Bayesian inference. The models included the additive direct, permanent environmental and residual random effects and the fixed effects year and month of birth or calving, calving age and age of the animal, depending on the trait. QD10, QDT and QTPR of each female were obtained by adjusting the weaning weights of calves for year and month of birth, sex and age of cow. Average of heritability estimates were 0.38 (PD), 0.40 (P12), 0.54 (PAD), 0.22 (TPR), 0.22 (ND10), 0.24 (QD10), 0.23 (NDT), 0.23 (QDT) and 0.32 (QTPR), indicating genetic variability to obtain response by selection. Genetic correlations between TPR (-0.02, 0.26 and -0.12), ND10 (0.04, 0.10 and -0.29), QD10 (0.37, 0.39 and -0.13), NDT (-0.03, 0.14 and -0.25), QDT (0.20, 0.33 and -0.16), QTPR (0.21, 0.28 and -0.19) and body weights (PD, P12 and PAD) suggest that selection of females based on weaning and 12-month body weights will not affect productivity. However, it may be decreased by increasing female adult body weight.
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
TL;DR: The following tables highlight daily diet dry matter and nutrient density requirements for diffferent classes of cattle at various stages of production based on the National Research Council’s Nutrient Requirements of Beef Cattle.
Abstract: Understanding beef cattle nutrient requirements is a critical step in developing a nutritional management strategy for the herd. Nutritional decision making is a key factor determining beef cattle production and profitability. Adequate nutrition is required for growth, maintenance, lactation, and reproduction. The following tables highlight daily diet dry matter and nutrient density requirements for diffferent classes of cattle at various stages of production based on the National Research Council’s Nutrient Requirements of Beef Cattle:
TL;DR: An excellent review of life history theory, which integrates this well with results from the empirical literature, and gives an invaluable route into the literature, with a bibliography of 1600 or so items.
Abstract: Life history biology sits on the interface between genetics and ecology, and both have made important theoretical and empirical contributions to our understanding. However, the connections between the disciplines have not always been as close as they might have been and this book takes some useful steps towards remedying this. It gives an excellent review of life history theory, and integrates this well with results from the empirical literature. After an 11-page introduction, Roff sets out ‘a framework for analysis’ in which he covers the necessary elements of quantitative and population genetics. This includes clear definitions of fitness in a range of circumstances, from density independent populations in constant environments through to the more complex situations of density and frequency dependence and environments that are spatially or temporally stochastic. Trade-offs are then examined, including a valuable analysis of potential pitfalls in studying them and ways that these can be avoided. The author then deals in turn with evolution in constant environments; stochastic environments and ‘predictable environments’. The last of these covers situations where there is environmental variation, but at least some information is available to allow individuals to make an adaptive response. The final chapter identifies 20 topics for future study. Some will find the book too dominated by theory. Others (but probably not readers of Heredity!) will find it contains too much genetics. But Roff does an excellent job of making the theory accessible, covering the essential issues and pointing to original sources for the details. Theory is related to a significant number of empirical studies, although there is room for another book reviewing the empirical literature on life histories in detail, and Roff’s book would provide a robust skeleton on which to hang this. To make my own assessment, I examined in detail Roff’s discussion of the question of fitness measures for density dependent populations in stochastic environments – an area in which I have been involved. I could not fault him – all the key references were there and the issues were made very clear without the more esoteric mathematics. I also examined some areas that I was less familiar with, and again the text was clear and easy to read. My only real criticism of the book would be that its very long chapters (more than 130 pages in one case) makes it difficult to find things. It would have been simple to address this by including the section headings on the contents pages. A minor personal quibble would be that the book usually expresses problems in terms of the intrinsic rate of increase, r, and the characteristic (Lotka) equation. A matrix formulation is often more tractable and is easier to generalise to density dependent populations and stochastic environments, so expanding on the relationship between the two would have been useful. But overall this is an excellent book. It brings together the key theory in a single place. It gives an invaluable route into the literature, with a bibliography of 1600 or so items. These features, and its identification of topics that need further study should make an important contribution to moving the field forward.
01 Jan 2016
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TL;DR: Genes inside ROH islands suggest a strong selection for dairy traits and enrichment for Gyr cattle environmental adaptation and the existence of a moderate correlation between larger ROH indicates that FROH can be used as an alternative to inbreeding estimates in the absence of pedigree records.
Abstract: Runs of homozygosity (ROH) are continuous homozygous segments of the DNA sequence. They have been applied to quantify individual autozygosity and used as a potential inbreeding measure in livestock species. The aim of the present study was (i) to investigate genome-wide autozygosity to identify and characterize ROH patterns in Gyr dairy cattle genome; (ii) identify ROH islands for gene content and enrichment in segments shared by more than 50% of the samples, and (iii) compare estimates of molecular inbreeding calculated from ROH (FROH), genomic relationship matrix approach (FGRM) and based on the observed versus expected number of homozygous genotypes (FHOM), and from pedigree-based coefficient (FPED). ROH were identified in all animals, with an average number of 55.12 ± 10.37 segments and a mean length of 3.17 Mb. Short segments (ROH1–2 Mb) were abundant through the genomes, which accounted for 60% of all segments identified, even though the proportion of the genome covered by them was relatively small. The findings obtained in this study suggest that on average 7.01% (175.28 Mb) of the genome of this population is autozygous. Overlapping ROH were evident across the genomes and 14 regions were identified with ROH frequencies exceeding 50% of the whole population. Genes associated with lactation (TRAPPC9), milk yield and composition (IRS2 and ANG), and heat adaptation (HSF1, HSPB1, and HSPE1), were identified. Inbreeding coefficients were estimated through the application of FROH, FGRM, FHOM, and FPED approaches. FPED estimates ranged from 0.00 to 0.327 and FROH from 0.001 to 0.201. Low to moderate correlations were observed between FPED-FROH and FGRM-FROH, with values ranging from −0.11 to 0.51. Low to high correlations were observed between FROH-FHOM and moderate between FPED-FHOM and FGRM-FHOM. Correlations between FROH from different lengths and FPED gradually increased with ROH length. Genes inside ROH islands suggest a strong selection for dairy traits and enrichment for Gyr cattle environmental adaptation. Furthermore, low FPED-FROH correlations for small segments indicate that FPED estimates are not the most suitable method to capture ancient inbreeding. The existence of a moderate correlation between larger ROH indicates that FROH can be used as an alternative to inbreeding estimates in the absence of pedigree records.