Marcos Vin'icius G. Barbosa da Silva

Avaliação genética de bovinos da raça holandesa usando a produção de leite no dia do controle

153,963 test day milk yield records and 13,273 first lactations of Holstein cows calving between 1989 and 1998, were used with the objective of estimating genetic, phenotypic and environmental parameters for test day milk yield (PLDC) and 305 day milk yield (P305) and to study the convenience of using test day yields in genetic evaluations to replace P305. Four models were used. Models 1 and 2 differed according contemporary grouping and monthly milk records were considered as repeated measures. In model 1 (PLDCM01) records were grouped by herd-year-season of test day yield and in model 2 (PLDCM02) by herd-year-season of calving. In a third (model 3), monthly yield records were analyzed as individual traits (C01 to C10); and the fourth (model 4) was the traditional 305-day model. Restricted Maximum Likelihood methodology was used with the MTDFREML system. The estimates of heritability for PLDC, using model 1, model 2 and for P305 were 0.27, 0.15 and 0.25, respectively. Heritabilities for monthly milk records ranged from 0.11+0.02 (C01) to 0.21+0.03 (C08), with the largest values occurring beginning in the fourth month. Genetic correlation estimates between monthly records and P305 ranged from 0.76 to 1.00, with the highest correlations occurring in the middle lactation. It was concluded that using test day milk yield is promising and that selecting for middle lactation records could have advantages over 305-day milk yield.

Efeito da endogamia sobre características produtivas e reprodutivas de bovinos do ecótipo Mantiqueira

Genealogies of 2070 animals and records from the first five lactations of 1406 cows of the Mantiqueira type cattle, daughters of 113 sires, were analyzed to estimate the frequency of inbred animals, the inbreeding average per generation and the possible effect of inbreeding increase on reproductive and productive traits. The evaluated traits were age at first calving (IPP), calving intervals (IDP), total milk production (PL) and lactation period (DL). Models for PL, IDP and DL included the fixed effects of year-season of calving were used, linear and quadratic effects of the age of the cow as covariate and the random animal effects, permanent environment and error. The fixed effect of lactation period was included also in the PL analysis. Year-season of calving as fixed, and animal and error as random were fit in the mode for IPP. Restricted maximum likelihood methodology was used in the analyses. Trends of inbreeding were estimated by generation. Significant increases of inbred animals and average levels of inbreeding coefficient were observed with the latter varying between 0.33 and 7.34% and increasing up to the last generation. Linear effects of inbreeding on breeding values for PL and IPP and quadratic effect for IDP and DL were found. Inbreeding influenced negatively the breeding values for all traits being responsible for reductions in PL and DL and increases in IPP and IDP. Poor efficient breeding programs and the fact that the herd is closed are important factors for the continuous increase in the level of inbreeding and number of inbred animals.

Mesh Mapping Exploration for Coarse-Grained Reconfigurable Array Architectures

Coarse-grained reconfigurable array architectures are currently focus of intensive research. They have already proven performance improvements and energy savings over traditional architectures. However, coarse-grained arrays vary widely in the number and characteristics of the processing elements and routing topologies used. This work presents a flexible mapping environment for design space exploration of coarse-grained, data-driven, reconfigurable array architectures. The mapping included in the environment presented in this paper takes advantage of Java and XML technologies to enable an efficient architectural tradeoff analysis. This approach does not focus on neither a specific mapping algorithm nor a specific architecture, but on an open environment where users can add their own mapping algorithms and architecture patterns. A genetic algorithm for placement is presented. A number of DSP benchmarks are used to explore a range of mesh architectures and to validate the approach. The experiments show a fast, scalable and flexible mapping environment to explore new mesh array patterns, homogeneous and heterogeneous architectures

Correlated responses in the reproductive traits in the breeding program of Mantiqueira cattle for milk production

The objective of this work was to estimate the genetic parameters, product-moment and rank correlations between breeding values, and also correlated responses for reproductive traits using bivariate analysis of total milk production (PL) and the age at the first calving (IPP), or calving intervals (IDP), or days open (PSERV). Records from the NPZGJRA/IZ/APTA/SAA-SSP breeding program of the first five lactations of 1406 cows of Mantiqueira ecotype; daughters of 113 sires, with calvings from 1952 to 1997 were used. The MTDFREML system was used in the analyses with models for the PL, IDP, and PSERV traits which included the fixed effects of year-season of calving, linear and quadratic terms of calving age as covariate and the random animal effects; environment permanent and error. In the PL analysis, the fixed effect of lactation period was also included. The model for IPP consisted of the year-season fixed effects of calving and the random effects of animal and error. Genetic correlations of PL with IPP, IDP and PSERV were -0.63, -0.41 and -0.37, respectively, representing favorable associations of milk yield and reproductive traits. Direct, correlated responses and efficiency of the indirect selection were, respectively, -0.8904, 1.0165 and -0.8759, for IPP; -3.3520, 2.4561 and 1.3598, for IDP and -3.0120, 2.4544 and -1.2272, for PSERV. These values suggest that the direct response for IPP would be more effective than the indirect, being the opposite for IDP and PSERV. Product-moment and rank correlations of PL with the reproductive traits were high, indicating linear and favorable association between predicted breeding values.

Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population

Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.

Sistema Fuzzy Aplicado À Bioinformática Na Tomada De Decisão Para Identificação De SNPs

Research involving the discovery of single nucleotide polymorphisms (SNPs) requires bioinformatics tools to be applied to different cases, with the ability to analyze “reads” from different sources, levels of coverage and to establish reliable measures. These tools work with different methodologies on different attributes, however, it is expected similar results, even when dealing with a same data set, but it’s not unusual to provide different results, which leads to uncertainty in decision making, when the results are discordant. This papes shows a fuzzy inference system that implements a fuzzy inference model decision support applied to bioinformatics, specifically, in the identification of SNPs, based on results from two other SNPs discovery tools