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1.
J Anim Sci ; 94(9): 3613-3623, 2016 Sep.
Article in English | MEDLINE | ID: mdl-27898889

ABSTRACT

Animal feeding is the most important economic component of beef production systems. Selection for feed efficiency has not been effective mainly due to difficult and high costs to obtain the phenotypes. The application of genomic selection using SNP can decrease the cost of animal evaluation as well as the generation interval. The objective of this study was to compare methods for genomic evaluation of feed efficiency traits using different cross-validation layouts in an experimental beef cattle population genotyped for a high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA). After quality control, a total of 437,197 SNP genotypes were available for 761 Nelore animals from the Institute of Animal Science, Sertãozinho, São Paulo, Brazil. The studied traits were residual feed intake, feed conversion ratio, ADG, and DMI. Methods of analysis were traditional BLUP, single-step genomic BLUP (ssGBLUP), genomic BLUP (GBLUP), and a Bayesian regression method (BayesCπ). Direct genomic values (DGV) from the last 2 methods were compared directly or in an index that combines DGV with parent average. Three cross-validation approaches were used to validate the models: 1) YOUNG, in which the partition into training and testing sets was based on year of birth and testing animals were born after 2010; 2) UNREL, in which the data set was split into 3 less related subsets and the validation was done in each subset a time; and 3) RANDOM, in which the data set was randomly divided into 4 subsets (considering the contemporary groups) and the validation was done in each subset at a time. On average, the RANDOM design provided the most accurate predictions. Average accuracies ranged from 0.10 to 0.58 using BLUP, from 0.09 to 0.48 using GBLUP, from 0.06 to 0.49 using BayesCπ, and from 0.22 to 0.49 using ssGBLUP. The most accurate and consistent predictions were obtained using ssGBLUP for all analyzed traits. The ssGBLUP seems to be more suitable to obtain genomic predictions for feed efficiency traits on an experimental population of genotyped animals.


Subject(s)
Cattle/genetics , Genomics/methods , Models, Genetic , Polymorphism, Single Nucleotide , Animal Feed , Animals , Bayes Theorem , Brazil , Breeding , Cattle/metabolism , Eating/genetics , Eating/physiology , Genome , Genotype , Male , Software
2.
Animal ; 8(3): 370-8, 2014 Mar.
Article in English | MEDLINE | ID: mdl-24405717

ABSTRACT

The use of polynomial functions to describe the average growth trajectory and covariance functions of Nellore and MA (21/32 Charolais+11/32 Nellore) young bulls in performance tests was studied. The average growth trajectories and additive genetic and permanent environmental covariance functions were fit with Legendre (linear through quintic) and quadratic B-spline (with two to four intervals) polynomials. In general, the Legendre and quadratic B-spline models that included more covariance parameters provided a better fit with the data. When comparing models with the same number of parameters, the quadratic B-spline provided a better fit than the Legendre polynomials. The quadratic B-spline with four intervals provided the best fit for the Nellore and MA groups. The fitting of random regression models with different types of polynomials (Legendre polynomials or B-spline) affected neither the genetic parameters estimates nor the ranking of the Nellore young bulls. However, fitting different type of polynomials affected the genetic parameters estimates and the ranking of the MA young bulls. Parsimonious Legendre or quadratic B-spline models could be used for genetic evaluation of body weight of Nellore young bulls in performance tests, whereas these parsimonious models were less efficient for animals of the MA genetic group owing to limited data at the extreme ages.


Subject(s)
Cattle/growth & development , Cattle/genetics , Models, Biological , Algorithms , Animals , Body Weight , Female , Male , Regression Analysis
3.
Food Chem ; 127(2): 404-11, 2011 Jul 15.
Article in English | MEDLINE | ID: mdl-23140679

ABSTRACT

In this study, we investigated the effects of the flavonoid rutin (3,3',4',5,7-pentahydroxyflavone-3-rutinoside) on glioma cells, using the highly proliferative human cell line GL-15 as a model. We observed that rutin (50-100µM) reduced proliferation and viability of GL-15 cells, leading to decreased levels of ERK1/2 phosphorylation (P-ERK1/2) and accumulation of cells in the G2 phase of the cell cycle. On the other hand, 87.4% of GL-15 cells exposed to 100µM rutin entered apoptosis, as revealed by flow cytometry after AnnexinV/PI staining. Nuclear condensation and DNA fragmentation were also observed, further confirming that apoptosis had occurred. Moreover, the remaining cells that were treated with 50µM rutin presented a morphological pattern of astroglial differentiation in culture, characterised by a condensed cell body and thin processes with overexpression of GFAP. Because of its capacity to induce differentiation and apoptosis in cultured human glioblastoma cells, rutin could be considered as a potential candidate for malignant gliomas treatment.

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