Random regression models with different residual variance structures for describing litter size in swine

Objetivou-se comparar modelos de regressão aleatória com diferentes estruturas de variância residual, a fim de se buscar a melhor modelagem para a característica tamanho da leitegada ao nascer (TLN). Utilizaram-se 1.701 registros de TLN, que foram analisados por meio de modelo animal, unicaracterística, de regressão aleatória. As regressões fixa e aleatórias foram representadas por funções contínuas sobre a ordem de parto, ajustadas por polinômios ortogonais de Legendre de ordem 3. Para averiguar a melhor modelagem para a variância residual, considerou-se a heterogeneidade de variância por meio de 1 a 7 classes de variância residual. O modelo geral de análise incluiu grupo de contemporâneo como efeito fixo; os coeficientes de regressão fixa para modelar a trajetória média da população; os coeficientes de regressão aleatória do efeito genético aditivo-direto, do comumde-leitegada e do de ambiente permanente de animal; e o efeito aleatório residual. O teste da razão de verossimilhança, o critério de informação de Akaike e o critério de informação bayesiano de Schwarz apontaram o modelo que considerou homogeneidade de variância como o que proporcionou melhor ajuste aos dados utilizados. As herdabilidades obtidas foram próximas a zero (0,002 a 0,006). O efeito de ambiente permanente foi crescente da 1a (0,06) à 5a (0,28) ordem, mas decrescente desse ponto até a 7a ordem (0,18). O comum-de-leitegada apresentou valores baixos (0,01 a 0,02). A utilização de homogeneidade de variância residual foi mais adequada para modelar as variâncias associadas à característica tamanho da leitegada ao nascer nesse conjunto de dado.The objective of this work was to compare random regression models with different residual variance structures, so as to obtain the best modeling for the trait litter size at birth (LSB) in swine. One thousand, seven hundred and one records of LSB were analyzed. LSB was analyzed by means of a random-regression, single-characteristic animal model. The fixed and random regressions were represented by continuous functions over the farrowing order, adjusted by third-order Legendre’s orthogonal polynomials. To obtain the best modeling for the residual variance, variance heterogeneity was assumed by means of 1 to 7 classes of residual variance. The general analysis model included a contemporary group; the fixed regression coefficients for modeling the population’s average trajectory; the random regression coefficients of the direct additive genetic effects both of the litter and of the animal’s permanent environment; and the residual random effect. The likelihood-ratio test, Akaike’s information criterion, and Schwarz’s Bayesian information criterion appointed the model that considered variance homogeneity as being the one that provided the best adjustment to the data used. Overall, the heritabilities obtained were close to zero (0.002 to 0.006). Regarding the permanent environment proportion, different magnitudes were observed for the farrowing order: increasing from the 1st (0.06) to the 5th (0.28) orders and decreasing from there to the 7th order (0.18). The common litter effect presented low values (from 0.01 to 0.02). The use of residual variance homogeneity was more suitable for modeling variances associated to the trait litter size at birth in this data set.publishe

Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle

Abstract\ud \ud Background\ud Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.\ud \ud \ud Results\ud Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches.\ud \ud \ud Conclusions\ud The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.This study was conducted with funding from EMBRAPA (Macroprograma1,\ud 01/2005) and FAPESP (process number 2012/23638-8). GBM, LLC, LCAR and\ud MMA were granted CNPq fellowships. We thank Sean McWilliam, Marina R. S.\ud Fortes, Edilson Guimaraes, Robson Rodrigues Santiago, Roselito F. da Silva,\ud Fernando F. Cardoso, Flavia Aline Bressani, Wilson Malago Jr., Avelardo U. C.\ud Ferreira, Michel E. B. Yamaguishi and Fabio D. Vieira for the help and\ud technical assistance. The authors would like to acknowledge the\ud collaborative efforts among EMBRAPA, University of Sao Paulo and CSIRO

UTILIZAÇÃO DE DIFERENTES ESTRUTURAS DE VARIÂNCIA RESIDUAL EM MODELOS DE REGRESSÃO ALEATÓRIA PARA DESCRIÇÃO DA CURVA DE CRESCIMENTO DE PERDIZES (Rhynchotus rufescens) CRIADAS EM CATIVEIRO

Random regression models (RRM) allows considering heterogeneous residual variances to describe the growth for each age. However, this feature increases the number of parameters to be estimated in the maximization likelihood function process. Searching for more parsimonious RRM, several approaches have been suggested. One of them is the use of different structures of residual variances modelled through step function in different classes with similar variance or through variance functions. A total of 7,369 records of body weight of partridges, measured from birth to 210 days of partridges born from 2000 to 2004 were used in this research. The random regression models applied to the data set considered different structures of residual variances and were performed by the restricted maximum likelihood method. The residual variances were modeled using classes of 210 (R210) and 30 (R30) ages and variance functions with orders ranging from quadratic (VF2) to nine (VF9). The R30 considered birds weighted in the same week. The random effects included were the genetic additive direct and the permanent environment effects of the animal. It was not possible to include the maternal effects in the models. All random effects were modelled by sixth order regression on Legendre polynomials. The models were compared by the likelihood ratio test, the Akaike's information criterion and the Schwarz's Bayesian information criterion. Best results were showed by the models R210 and VF5. In conclusion, the most parsimonious model was VF5 and should be applied to fit growth records of partridges

ESTIMATIVAS DE PARÂMETROS GENÉTICOS PARA PESOS CORPORAIS EM PERDIZES (Rhynchotus rufescens) CRIADAS EM CATIVEIRO

Currently, the concern on different poultry market has increased and among several native species, partridge, (Rhynchotus rufescens) is good option as source of avian protein, showing excellent carcass performance. The aims of this paper were to study environmental and genetic factors those affect body weight on different ages in partridges, raised in captivity. Data were collected in the Wild Animal Section of Departamento de Zootecnia, located at Faculdade de Ciências Agrárias e Veterinárias (UNESP), at Jaboticabal - SP. Partridges were raised in a commercial avian barn and families were kept using 1 sire to 2 or 5 dams. Mattings were through natural ride. Eggs were collected daily, weighted, measured and identified by box and sire for pedigree control. Chick were identified and weighted at birth and weekly til get 30 weeks of age. Data set had 13,164 weights taken from 2000 to 2004. The statistical analyses were performed by least squares method and heritability estimated y the Maximum likelihood method. The overall means of 3(W3), 7 (W7), 14 (W14), 21 (W21), 28(W28), 35 (W35), 42 (W42), 49 (W49), 56 (W56), 63(W63), 70(W70), 77 (W77), 84 (W84), 91 (W91), 98 (W98), 105 (W105), 112 (W112), 119 (W119), 126 (W126), 133 (W133), 140 (W140), 147 (W147), 154 (W154), 161 (W161), 168 (W168), 175 (W175), 182 (W182), 189 (W189), 196 (W196), 203 (W203) and 210 (W210) days weight were 38.92g, 52.23g, 76.40g, 105.61g, 137.79g, 208.38g, 208.56g, 249.99g, 293.71g, 335.45g, 373.86g, 408.53g, 440.83g, 467.92g, 503.29g, 522.36g, 548.70g, 564.21g, 582.71g, 593.59g, 603.69g, 613.85g, 629.08g, 642.44g, 637.03g, 646.91g, 637.81g, 653.86g, 662.63, 663.19g and 667.385, respectively. The estimates of heritability to egg weight and weight at birth showed large genetic variability among birds and selection for weight at these ages could be done. The genetic and environmental effects are difficult to estimate in old ages and require more information to provide best estimates

REDUCING COMPETITION IN AGROFORESTRY BY PRUNING NATIVE TREES

ABSTRACT The degree to which pruning helps reestablish balance in agroforestry was assessed in a system established in São Carlos, São Paulo, Brazil, in 2008. Seven native tree species were planted at a density of 600 trees/ha in five strips of three rows each, and annual crops were cultivated in the 17-m crop strips between the tree strips. Competition was established after 35 months, decreasing the aboveground biomass production of corn planted close to the trees. An assessment of black oats in the dry season following tree pruning showed that the proximity of trees caused reductions in plant and panicle density, aboveground biomass production, number of grains per panicle and grain weight. Because pruning was not sufficient to maintain crop yields, tree thinning is recommended in order to minimize competition and restore conditions for adequate crop production

Genetic and environmental effects on scores of conformation, precocity and muscling in long yearling Nellore cattle

Os escores visuais de conformação (C), precocidade (P) e musculosidade (M) são usados para acessar indiretamente características relacionadas à terminação e composição de carcaça. Neste estudo, objetivou-se analisar como a idade da vaca ao parto (AC), idade (YA) e peso do animal ao sobreano (YW) influenciam os escores de bovinos da raça Nelore, além de estimar suas herdabilidades. Foram estimadas funções de regressão dos efeitos de AC, YA e YW sobre os escores C, P e M, após a absorção do efeito de grupo de contemporâneos (CG). As herdabilidades foram estimadas por máxima verossimilhança restrita, considerando-se quatro diferentes modelos que incluíram o efeito genético aditivo de animal como aleatório, e diferentes covariáveis (AC, YA e YW) como efeitos fixos. Nas análises de regressão, as covariáveis, tanto linear como quadrática, influenciaram significativamente os escores C, P e M. Os coeficientes de determinação dos modelos para YA e AC foram de pequena magnitude, provavelmente devido à absorção do efeito de CG. As estimativas de herdabilidade para os escores variaram de 0,13 a 0,36 para C, de 0,32 a 0,36 para P, e de 0,35 a 0,38 para M, considerando todos os modelos utilizados, indicando que C, P e M respondem à seleção direta. A classificação dos animais de acordo com seus valores genéticos, principalmente em relação a C, variou de acordo com os efeitos de ambiente incluídos nos modelos.s.The visual scores for conformation (C), precocity (P) and muscle (M) are used to indirectly assess traits related to termination and carcass composition. This study analyzes how age of dam at calving (AC), long yearling age (YA) and long yearling weight (YW) of the animal affect the scores of Nellore cattle, and estimates their heritability. Regression functions were estimated to determine the AC, YA and YW effects on C, P and M scores after the contemporary group (CG) effect being absorbed. The heritabilities were estimated by restricted maximum likelihood using four different models that included animal additive genetic effect as random and different covariates (AC, YA and YW) as fixed effects. The regression analysis showed that the covariates, either linear or quadratic, significantly influenced the scores of C, P and M. The determination coefficients of the models for YA and AC were small, probably due to the CG bias removal. The heritability estimates for the scores ranged from 0.13 to 0.36 for C; 0.32 to 0.36 for P; and, 0.35 to 0.38 for M, for all models, indicating that C, P and M respond to direct selection. The classification of animals according to their breeding values, especially in relation to C, varied according to the environmental effects included in the models

Modelos de regressão aleatória com diferentes estruturas de variância residual para descrever o tamanho da leitegada Random regression models with different residual variance structures for describing litter size in swine

Objetivou-se comparar modelos de regressão aleatória com diferentes estruturas de variância residual, a fim de se buscar a melhor modelagem para a característica tamanho da leitegada ao nascer (TLN). Utilizaram-se 1.701 registros de TLN, que foram analisados por meio de modelo animal, unicaracterística, de regressão aleatória. As regressões fixa e aleatórias foram representadas por funções contínuas sobre a ordem de parto, ajustadas por polinômios ortogonais de Legendre de ordem 3. Para averiguar a melhor modelagem para a variância residual, considerou-se a heterogeneidade de variância por meio de 1 a 7 classes de variância residual. O modelo geral de análise incluiu grupo de contemporâneo como efeito fixo; os coeficientes de regressão fixa para modelar a trajetória média da população; os coeficientes de regressão aleatória do efeito genético aditivo-direto, do comum-de-leitegada e do de ambiente permanente de animal; e o efeito aleatório residual. O teste da razão de verossimilhança, o critério de informação de Akaike e o critério de informação bayesiano de Schwarz apontaram o modelo que considerou homogeneidade de variância como o que proporcionou melhor ajuste aos dados utilizados. As herdabilidades obtidas foram próximas a zero (0,002 a 0,006). O efeito de ambiente permanente foi crescente da 1ª (0,06) à 5ª (0,28) ordem, mas decrescente desse ponto até a 7ª ordem (0,18). O comum-de-leitegada apresentou valores baixos (0,01 a 0,02). A utilização de homogeneidade de variância residual foi mais adequada para modelar as variâncias associadas à característica tamanho da leitegada ao nascer nesse conjunto de dado.<br>The objective of this work was to compare random regression models with different residual variance structures, so as to obtain the best modeling for the trait litter size at birth (LSB) in swine. One thousand, seven hundred and one records of LSB were analyzed. LSB was analyzed by means of a random-regression, single-characteristic animal model. The fixed and random regressions were represented by continuous functions over the farrowing order, adjusted by third-order Legendre's orthogonal polynomials. To obtain the best modeling for the residual variance, variance heterogeneity was assumed by means of 1 to 7 classes of residual variance. The general analysis model included a contemporary group; the fixed regression coefficients for modeling the population's average trajectory; the random regression coefficients of the direct additive genetic effects both of the litter and of the animal's permanent environment; and the residual random effect. The likelihood-ratio test, Akaike's information criterion, and Schwarz's Bayesian information criterion appointed the model that considered variance homogeneity as being the one that provided the best adjustment to the data used. Overall, the heritabilities obtained were close to zero (0.002 to 0.006). Regarding the permanent environment proportion, different magnitudes were observed for the farrowing order: increasing from the 1st (0.06) to the 5th (0.28) orders and decreasing from there to the 7th order (0.18). The common litter effect presented low values (from 0.01 to 0.02). The use of residual variance homogeneity was more suitable for modeling variances associated to the trait litter size at birth in this data set