José Marcelo Soriano Viana

Genetic parameters relating isoflavone and protein content in soybean seeds

Isoflavones are a class of compounds present in high amounts in soybean seeds, which can be used for prevention and treatment of several chronic diseases. Proteins present in soybean seeds are the basis for the high nutritional value and versatility of this leguminous species in animal and human feeding. The main goals of this work were to estimate heritabilities for isoflavone contents in soybean seeds and the correlation between isoflavone and protein contents. Commercial variety IAC-100 (high isoflavone and normal protein contents) and the line BARC-8 (low isoflavone and high protein contents) were crossed, and one single F1 plant derived 97 F2 seeds, which were used to obtain F3 seeds. A sample of F3 seeds from each F2 plant was used for isoflavone determination by HPLC and protein by the Kjeldahl method. Six isoflavone forms were detected: daidzin, genistin, glycitin, malonyldaidzin, malonylgenistin and malonylglycitin. Total isoflavone contents ranged from 427.92 to 965.89 μg per gram of dry seed and the protein content ranged from 45.17 to 34.95% in BARC-8 and IAC-100, respectively. Our results indicate that it is possible to select for high isoflavone content in early breeding generations because the broad sense heritabilities for the contents of the various isoflavone forms were higher than 90%. In addition, high correlation values among the contents of the individual isoflavone forms were observed (between 0.80 and 0.98). However, negative correlation values were obtained between isoflavone and protein contents, ranging from −0.51 to −0.37 for the different isoflavone forms. The correlation value of −0.47 between total isoflavone and protein contents confirmed the negative correlation between these two parameters, as reported by other authors.

Theory and analysis of partial diallel crosses

This study presents theory and analysis of partial diallel crosses based on Haymans methods. This genetic design consists of crosses among two parental groups. It should be used when there are two groups of parents, for example, dent and flint maize inbred lines, and the breeder is not interested in the assessment of crosses between parents of the same group. Analyses are carried out using data from the parents and their F1 hybrids allowing a detailed characterization of the polygenic systems under study and the choice of parents for hybridization. Diallel analysis allows the estimation of genetic and non-genetic components of variation and genetic parameters and to assess the following: genetic variability in each group; genotypic differences between parents of distinct groups; if a parent has a common or a rare genotype in the group to which it does not belong; if there is dominance; if dominant genes increase or decrease trait expression (direction of dominance); average degree of dominance in each group; the relative importance of mean effects of genes and dominance in determining a trait; if, in each group, the allelic genes have the same frequency; if genes are equally frequent in the two groups; the group with the greatest frequency of favorable genes; the group in which dominant genes are most frequent; the relative number of dominant and recessive genes in each parent; if a parent has a common or a rare genotype in the group to which it belongs, and the genotypic differences between parents of the same group. An example with common bean varieties is considered.

Analysis of general and specific combining abilities of popcorn populations, including selfed parents

Estimation of general and specific combining ability effects in a diallel analysis of cross-pollinating populations, including the selfed parents, is presented in this work. The restrictions considered satisfy the parametric values of the GCA and SCA effects. The method is extended to self-pollinating populations (suitable for other species, without the selfed parents). The analysis of changes in population means due to inbreeding (sensitivity to inbreeding) also permits to assess the predominant direction of dominance deviations and the relative genetic variability in each parent population. The methodology was used to select popcorn populations for intra- and inter-population breeding programs and for hybrid production, developed at the Federal University of Vicosa, MG, Brazil. Two yellow pearl grain popcorn populations were selected.

The parametric restrictions of the Griffing diallel analysis model: combining ability analysis

It was studied the parametric restrictions of the diallel analysis model of Griffing, method 2 (parents and F1 generations) and model 1 (fixed), in order to address the questions: i) does the statistical model need to be restricted? ii) do the restrictions satisfy the genetic parameter values? and iii) do they make the analysis and interpretation easier? Objectively, these questions can be answered as: i) yes, ii) not all of them, and iii) the analysis is easier, but the interpretation is the same as in the model with restrictions that satisfy the parameter values. The main conclusions were that: the statistical models for combining ability analysis are necessarily restricted; in the Griffing model (method 2, model 1), the restrictions relative to the specific combining ability (SCA) effects, and for all j, do not satisfy the parametric values, and the same inferences should be established from the analyses using the model with restrictions that satisfy the parametric values of SCA effects and that suggested by Griffing. A consequence of the restrictions of the Griffing model is to allow the definition of formulas for estimating the effects, their variances and the variances of contrasts of effects, as well as for calculating orthogonal sums of squares.

Ridge, Lasso and Bayesian additive-dominance genomic models

BackgroundA complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes).ResultsG-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close.ConclusionsAmongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (−2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Dominance, epistasis, heritabilities and expected genetic gains

Although epistasis is common in gene systems that determine quantitative traits, it is usually not possible to estimate the epistatic components of genotypic variance because experiments in breeding programs include only one type of progeny. As the study of this phenomenon is complex, there is a lack of theoretical knowledge on the contribution of the epistatic variances when predicting gains from selection and on the bias in estimating genetic parameters when fitting the additive-dominant model. The objective of this paper is to discuss these aspects. Regarding a non-inbred population, the genetic value due to dominance and the epistatic components of the genotypic value are not indicators of the number of favorable genes present in an individual. Thus, the efficiency of a selection process should be based on the narrow-sense heritability, a function only of additive variance. If there is no epistasis, generally it is satisfactory to assess the selection efficiency and to predict gain based on the broad-sense heritability. Regardless of the selection unit or type of epistasis, the bias in the estimate of the additive variance when assuming the additive-dominant model is considerable. This implies overestimation of the heritabilities at half sib family mean, plant within family and plant levels, and underestimation if the selection units are full sib progenies. The predicted gains will have a bias proportional to that of the heritability.

Eficiências relativas dos processos de seleção entre e dentro de famílias de meios-irmãos em população de milho-pipoca

Selecao entre e dentro de familias de meios-irmaos e o metodo de melhoramento intrapopulacional de milho mais utilizado, por ser simples, rapido e eficiente. Programas de melhoramento de populacoes de milho-pipoca sao necessarios para o desenvolvimento dessa cultura no pais. Alem de ser importador de graos, poucas populacoes melhoradas, inclusive hibridos, estao disponiveis aos produtores. Objetivou-se com este trabalho elevar a capacidade de expansao (CE) e a produtividade de uma populacao de milho-pipoca em um programa de melhoramento intrapopulacional recorrente com base em progenies de meios-irmaos, e obter informacoes sobre as eficiencias dos processos de selecao entre e dentro, com um ciclo anual. Foi verificada variabilidade genetica para CE, peso de cem graos e producao. A selecao entre com base em CE e producao e a selecao no lote de recombinacao com base em CE elevaram a qualidade da populacao, mas nao a produtividade. Embora a analise dos ganhos preditos em CE e producao tenha evidenciado maior eficiencia da selecao entre, 89,5% do ganho realizado em CE foram devidos a selecao massal no lote. Portanto, pode-se praticar selecao com base em qualidade no lote de recombinacao cultivado fora da estacao.

Testes de capacidade de expansão em programas de melhoramento de milho pipoca

Quality, normally expressed by the relation volume of popcorn/weight of grains (volume expansion), is an important characteristic in popcorn breeding. Different systems of assessing popcorn expansion should be used in individual and family selections, since they are common to consumers. The purpose of this work was to evaluate two systems for popping expansion determination in breeding programs. The first was a hot air popcorn pumper and the second was a microwave oven. For the first one an experiment was installed in a completely randomized design, with three treatments and nine levels of kernel weight, and five replications. For the second one, aiming to define an alternative packaging, an experiment was installed also in a completely randomized design, following a factorial scheme, with three replications, involving two times and five packagings. Another experiment was achieved to verify the microwave oven quality for volume expansion determination with a little kernel quantity and the best time to be used. The hot air popcorn pumper is an efficient system, in which 10 g of kernel can be used to evaluate plants and up to 90 g of kernel can be used to evaluate families in the experiments. The microwave oven is equivalent to the hot air popcorn pumper. Kraft paper bags can be used in the microwave oven. For plant evaluation 10 g of kernel with 140 seconds are recommended. To evaluate progenies 30 g to 90 g of kernel with 220 seconds can be used.

Genomic growth curves of an outbred pig population

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

BLUP for genetic evaluation of plants in non-inbred families of annual crops

Best Linear Unbiased Prediction (BLUP) has become the most widely used method for genetic assessment of animal and perennial species, and it is potentially relevant for annual crops. The objective of this study was to assess this method for selection within non-inbred families in recurrent breeding programs. The ‘animal model’ was fitted. The data were expansion volume (EV) and grain yield of plants in recombination plots of two to three selection cycles in the popcorn population Viçosa, with half- and full-sib progenies. The ASReml program was used to perform the analyses. For both EV and yield the breeding values predicted from the additive and additive-dominant models were highly correlated. Multi-generation BLUP was, in general, more accurate than single-generation analysis. These two methods resulted in highly correlated predicted breeding values. The dominance genetic values predicted from the single- and multi-generation analysis were also highly correlated. The pedigree information reduced the percentage of coincidences among the selected individuals relative to phenotypic selection mainly in the population structured in half-sib families. Based on breeding values predicted by BLUP analysis, the most efficient selection procedure was mass selection.