Alternativas de análise para experimentos G × E multiatributo

Geralmente, nos experimentos genótipo por ambiente (G × E) é comum observar o comportamento dos genótipos em relação a distintos atributos nos ambientes considerados. A análise deste tipo de experimentos tem sido abordada amplamente para o caso de um único atributo. Nesta tese são apresentadas algumas alternativas de análise considerando genótipos, ambientes e atributos simultaneamente. A primeira, é baseada no método de mistura de máxima verossimilhança de agrupamento - Mixclus e a análise de componentes principais de 3 modos - 3MPCA, que permitem a análise de tabelas de tripla entrada, estes dois métodos têm sido muito usados na área da psicologia e da química, mas pouco na agricultura. A segunda, é uma metodologia que combina, o modelo de efeitos aditivos com interação multiplicativa - AMMI, modelo eficiente para a análise de experimentos (G × E) com um atributo e a análise de procrustes generalizada, que permite comparar configurações de pontos e proporcionar uma medida numérica de quanto elas diferem. Finalmente, é apresentada uma alternativa para realizar imputação de dados nos experimentos (G × E), pois, uma situação muito frequente nestes experimentos, é a presença de dados faltantes. Conclui-se que as metodologias propostas constituem ferramentas úteis para a análise de experimentos (G × E) multiatributo.

The effects of density on the growth and survival of different families of juvenile Penaeus japonicus Bate

Variations in the growth and survival of six families of juvenile (initial mean weight = 4.16 g) Penaeus japonicus were examined at two densities (48 and 144 individuals m(-2)) in a controlled laboratory experiment. Survival was very high throughout the experiment (95.4%), but differed significantly between densities and rearing tanks. Family, sex and family x density interaction did not significantly affect survival. Mean specific growth rate (SGR) of the shrimp was 18% faster at the low density (1.93 +/- 0.05% day(-1)) than at high density (1.64 +/- 0.03% day(-1)). However, there was a small but significant interaction between family and density indicating that growth of the families was not consistent at both densities. The inconsistent growth of the families across the two densities resulted in a change in the relative performance (ranking) of families at each density. Sex, rearing tank and rearing cage also affected growth of the shrimp. Mean SGR of the females (1.79 +/- 0.03% day(-1)) was 5% faster than males (1.70 +/- 0.03% day(-1)) when averaged across both densities. Shrimp grew significantly faster in rearing tank 3 than rearing tank 1 or 2 at both densities. Results of the present study suggest that family x density interaction could affect the efficiency of selection for growth if shrimp stocks produced from shrimp breeding programs are to be grown across a wide range of densities. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

The influence of gene environment interaction on the risk of cognitive impairment: Reducing sexual risk behaviors and alcohol use in HIV-infected adults

Memory deficits and executive dysfunction are highly prevalent among HIV-infected adults. These conditions can affect their quality of life, antiretroviral adherence, and HIV risk behaviors. Several factors have been suggested including the role of genetics in relation to HIV disease progression. This dissertation aimed to determine whether genetic differences in HIV-infected individuals were correlated with impaired memory, cognitive flexibility and executive function and whether cognitive decline moderated alcohol use and sexual transmission risk behaviors among HIV-infected alcohol abusers participating in an NIH-funded clinical trial comparing the efficacy of the adapted Holistic Health Recovery Program (HHRP-A) intervention to a Health Promotion Control (HPC) condition in reducing risk behaviors. ^ A total of 267 individuals were genotyped for polymorphisms in the dopamine and serotonin gene systems. Results yielded significant associations for TPH2, GALM, DRD2 and DRD4 genetic variants with impaired executive function, cognitive flexibility and memory. SNPs TPH2 rs4570625 and DRD2 rs6277 showed a risk association with executive function (odds ratio = 2.5, p = .02; 3.6, p = .001). GALM rs6741892 was associated with impaired memory (odds ratio = 1.9, p = .006). At the six-month follow-up, HHRP-A participants were less likely to report trading sex for food, drugs and money (20.0%) and unprotected insertive or receptive oral (11.6%) or vaginal and/or anal sex (3.2%) than HPC participants (49.4%, p^

Host genotype and age shape the leaf and root microbiomes of a wild perennial plant.

Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome is evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.

The Influence of Gene Environment Interaction on the Risk of Cognitive Impairment: Reducing Sexual Risk Behaviors and Alcohol Use in HIV-infected Adults

Memory deficits and executive dysfunction are highly prevalent among HIV-infected adults. These conditions can affect their quality of life, antiretroviral adherence, and HIV risk behaviors. Several factors have been suggested including the role of genetics in relation to HIV disease progression. This dissertation aimed to determine whether genetic differences in HIV-infected individuals were correlated with impaired memory, cognitive flexibility and executive function and whether cognitive decline moderated alcohol use and sexual transmission risk behaviors among HIV-infected alcohol abusers participating in an NIH-funded clinical trial comparing the efficacy of the adapted Holistic Health Recovery Program (HHRP-A) intervention to a Health Promotion Control (HPC) condition in reducing risk behaviors. A total of 267 individuals were genotyped for polymorphisms in the dopamine and serotonin gene systems. Results yielded significant associations for TPH2, GALM, DRD2 and DRD4 genetic variants with impaired executive function, cognitive flexibility and memory. SNPs TPH2 rs4570625 and DRD2 rs6277 showed a risk association with executive function (odds ratio = 2.5, p = .02; 3.6, p = .001). GALM rs6741892 was associated with impaired memory (odds ratio = 1.9, p = .006). At the six-month follow-up, HHRP-A participants were less likely to report trading sex for food, drugs and money (20.0%) and unprotected insertive or receptive oral (11.6%) or vaginal and/or anal sex (3.2%) than HPC participants (49.4%, p

Docking of HIV-1 Vpr to the nuclear envelope is mediated by the interaction with the nucleoporin hCG1

The HIV-1 genome contains several genes coding for auxiliary proteins, including the small Vpr protein. Vpr affects the integrity of the nuclear envelope and participates in the nuclear translocation of the preintegration complex containing the viral DNA. Here, we show by photobleaching experiments performed on living cells expressing a Vpr-green fluorescent protein fusion that the protein shuttles between the nucleus and the cytoplasm, but a significant fraction is concentrated at the nuclear envelope, supporting the hypothesis that Vpr interacts with components of the nuclear pore complex. An interaction between HIV-1 Vpr and the human nucleoporin CG1 (hCG1) was revealed in the yeast two-hybrid system, and then confirmed both in vitro and in transfected cells. This interaction does not involve the FG repeat domain of hCG1 but rather the N-terminal region of the protein. Using a nuclear import assay based on digitonin-permeabilized cells, we demonstrate that hCG1 participates in the docking of Vpr at the nuclear envelope. This association of Vpr with a component of the nuclear pore complex may contribute to the disruption of the nuclear envelope and to the nuclear import of the viral DNA.

Adaptabilidade e estabilidade de progênies de meios-irmãos de pinhão-manso em diferentes regiões do Brasil.

RESUMO: Programas de melhoramento do pinhão-manso (Jatropha curcas L.) intensificaram-se nos últimos cinco anos, tendo sido selecionadas, localmente, plantas em diversas regiões do Brasil. O objetivo deste trabalho foi quantificar a interação genótipos x ambientes da produção de grãos de pinhão-manso, avaliada em três regiões brasileiras, e o progresso genético obtido com a seleção. A partir de progênies de meios-irmãos, selecionadas pela Embrapa Semiárido e pela EPAMIG, foram instalados, no ano de 2008, três testes de progênies, nos municípios de Planaltina, DF, Nova Porteirinha, MG e Pelotas, RS, utilizando-se delineamento de blocos ao acaso, com três repetições e cinco plantas por parcela. Como testemunhas foram utilizadas sementes de plantas não selecionadas e um dos materiais genéticos comercializados no Brasil. A interação genótipo x ambiente foi significativa. Foram identificadas oito progênies de adaptabilidade geral, três progênies de baixa adaptabilidade, duas progênies de adaptabilidade específica a ambientes favoráveis e duas progênies de adaptabilidade específica a ambientes desfavoráveis, em diferentes regiões do Brasil. As estimativas de progresso genético indicam eficiência da seleção massal, com ganhos de 28, 76 e 177%, nos municípios de Planaltina, DF, de Nova Porteirinha, MG, e de Pelota, RS, respectivamente. Observa-se que os ganhos de seleção obtidos pelo método centroide são mais equilibrados entre ambientes e, por isso, preferíveis. As novas médias, estimadas com o plantio das progênies selecionadas, em toneladas por hectare, são de 2,34 ton.ha-1, em Planaltina, DF; de 2,37 ton.ha-1, em Nova Porteirinha, MG, e de 2,09 ton.ha-1 , em Pelotas, RS. ABSTRACT: Physic nut (Jatropha curcas L.) breeding programs have intensified in the past five years, locally selecting plants from various Brazilian regions. The objective of this study was to quantify the genotype x environment interaction of the physic nut grain production and the genetic progress obtained with the selection. From Half-sib progenies selected by Embrapa and EPAMIG, in 2008, three progeny trials were installed in the cities of Planaltina-DF, Nova Porteirinha-MG and Pelotas-RS, using a randomized block design with three replications of five plants per plot. Non-selected plant seeds and genetic material commercialized in Brazil were used as control. The genotype x environment interaction was significant for the J. curcas grain yield expression. We identified eight progenies of broad adaptability, three progenies of low adaptability, two progenies of specific adaptability to favorable environments and two progenies of specific adaptability to unfavorable environments of different Brazilian regions. Estimates of genetic progress indicate mass selection efficiency, with genetic gains of 28%, 76% and 177% in the Planaltina-DF, New Porteirinha-MG and Pelotas-RS, respectively. The genetic gains obtained by the centroid method were more balanced among environments, and therefore, preferable. The new means estimated with the cultivating of the selected progenies are: 2.34 ton.ha-1 in Planaltina-DF, 2.37 ton.ha-1 in Nova Porteirinha- MG and 2.09 ton.ha-1 in Pelotas-RS.

Environmental effect on sunflower oil quality.

Sunflower is one of the most important oilseed crops and produces a high-quality edible oil. Balance of fatty acids in standard sunflower oil shows preponderance of linoleic rather than oleic acid, and conditions during seed development, such as temperature, changes the oleic/linoleic ratio of the oil. This work aimed to evaluate the environmental effect on fatty acid profile in a group of standard and high oleic varieties and hybrids. Seeds were produced during regular season crop and during off-season crop featuring different temperatures from anthesis to maturity. Fatty acid composition was determined by gas chromatography. Levels of oleic acid, in standard oil genotypes, raised as the crop developed in warmer environment while levels of linoleic acid decreased, and the opposite was observed when the crop was grown under lower temperature. High oleic genotypes were less sensitive to environment switching and showed lower variation on fatty acid composition.

Breeding for low input conditions and consequences for participatory plant breeding: Examples from tropical maize and wheat

Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.

Yield response of rice (Oryza sativa L.) genotypes to different types of drought under rainfed lowlands - Part 1. Grain yield and yield components

Responses of rice genotypes to drought stress may be different when characteristics of the drought stress environments differ. The performance of 128 genotypes was examined under irrigation and four different types of drought stress, to determine genotypic consistency in yield and factors determining yields under different drought stress conditions. The different drought conditions were mild drought during grain filling, short and severe drought at flowering, prolonged severe drought during the reproductive to grain filling, and prolonged mild drought during vegetative and grain filling. Genotypic grain yield under mild stress conditions was associated with yield under irrigated conditions, indicating the importance of potential yield in environments where the yield reduction was less than 50%. However, yields under irrigated conditions differed over time and locations. Under prolonged or severe drought conditions, flowering time was an important determinant of grain yield. Earlier flowering genotypes escaped the severe stress and had higher grain yields indicating large genotype by environment (G x E) interactions which have implications for plant breeding even for mild stress. It is suggested that variations in flowering time, potential yields and drought patterns need to be considered for development of drought-resistant cultivars using specific physiological traits. (C) 2002 Elsevier Science B.V. All rights reserved.

Yield response of rice (Oryza sativa L.) genotypes to different types of drought under rainfed lowlands - Part 2. Selection of drought resistant genotypes

Drought frequently reduces grain yield of rainfed lowland rice. A series of experiments were conducted in drought-prone northeast Thailand to study the magnitude and consistency of yield responses of diverse, rainfed lowland rice genotypes to drought stress environments and to examine ways to identify genotypes that confer drought resistance. One hundred and twenty-eight genotypes were grown under non-stress and four different types of drought stress conditions. The relationship of genotypic variation in yield under drought conditions to genetic yield potential, flowering time and flowering delay, and to a drought response index (DRI) that removed the effect of potential yield and flowering time on yield under stress was examined. Drought stress that developed prior to flowering generally delayed the time of flowering of genotypes, and the delay in flowering was negatively associated with grain yield, fertile panicle percentage and filled grain percentage. Genotypes with a longer delay in flowering time had extracted more water during the early drought period, and as a consequence, had higher water deficits. They were consistently associated with a larger yield reduction under drought and in one experiment with a smaller DRI. Genotypes, however, responded differently to the different drought stress conditions and there was no consistency in the DRI estimates for the different genotypes across the drought stress experiments. The results indicate that with the use of irrigated-control and drought test environments, genotypes with drought resistance can be identified by using DRI or delay in flowering. However, selections will differ depending on the type of drought condition. The inconsistency of the estimates in DRI and flowering delay across different drought conditions reflects the nature of the large genotype-by-environment interactions observed for grain yield under various types of drought in rainfed lowland conditions. (C), 2002 Elsevier Science B.V. All rights reserved.

Development of a generic crop model template in the cropping system model APSIM

The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

A major challenge faced by today's white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic diversity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic diversity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological/physiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.

The GP problem: quantifying gene-to-phenotype relationships

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.