Izabela R. C. Oliveira

Bio: Izabela R. C. Oliveira is an academic researcher from University of Hasselt. The author has contributed to research in topics: Overdispersion & Generalized linear mixed model. The author has an hindex of 3, co-authored 4 publications receiving 37 citations.

Inheritance of type IV glandular trichome density and its association with whitefly resistance from Solanum galapagense accession LA1401

Abstract: Tomato is affected by a large number of arthropod pests, among which the whitefly (Bemisia tabaci) is considered to be one of the most destructive. Several accessions of the wild species of Solanum galapagense, including accession LA1401, are considered resistant to whitefly (B. tabaci). This resistance has been associated with the presence of type IV glandular trichomes on the leaf surface. Our research aimed to study the inheritance of type IV glandular trichome density and its association with resistance to whitefly (B. tabaci biotype B) in populations derived from the interspecific cross Solanum lycopersicum × S. galapagense ‘LA1401.’ High estimates for both broad-sense and narrow-sense heritabilities of type IV glandular trichome densities suggest that inheritance of this trait is not complex. Whitefly resistance was associated with high density of type IV glandular trichomes. F2 (S. galapagense × S. lycopersicum) population plants selected for the highest densities of type IV glandular trichomes showed similar levels of resistance to those found in the donor of resistance LA1401.

Quantifying intraclass correlations for count and time‐to‐event data

Abstract: The intraclass correlation is commonly used with clustered data. It is often estimated based on fitting a model to hierarchical data and it leads, in turn, to several concepts such as reliability, heritability, inter-rater agreement, etc. For data where linear models can be used, such measures can be defined as ratios of variance components. Matters are more difficult for non-Gaussian outcomes. The focus here is on count and time-to-event outcomes where so-called combined models are used, extending generalized linear mixed models, to describe the data. These models combine normal and gamma random effects to allow for both correlation due to data hierarchies as well as for overdispersion. Furthermore, because the models admit closed-form expressions for the means, variances, higher moments, and even the joint marginal distribution, it is demonstrated that closed forms of intraclass correlations exist. The proposed methodology is illustrated using data from agricultural and livestock studies.

Negative variance components for non-negative hierarchical data with correlation, over-, and/or underdispersion

Abstract: The concept of negative variance components in linear mixed-effects models, while confusing at first sight, has received considerable attention in the literature, for well over half a century, following the early work of Chernoff [7] and Nelder [21]. Broadly, negative variance components in linear mixed models are allowable if inferences are restricted to the implied marginal model. When a hierarchical view-point is adopted, in the sense that outcomes are specified conditionally upon random effects, the variance–covariance matrix of the random effects must be positive-definite (positive-semi-definite is also possible, but raises issues of degenerate distributions). Many contemporary software packages allow for this distinction. Less work has been done for generalized linear mixed models. Here, we study such models, with extension to allow for overdispersion, for non-negative outcomes (counts). Using a study of trichomes counts on tomato plants, it is illustrated how such negative variance componen...

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Review of Recent Methodological Developments in Group-Randomized Trials: Part 2--Analysis.

Abstract: In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have updated that review with developments in analysis of the past 13 years, with a companion article to focus on developments in design.We discuss developments in the topics of the earlier review (e.g., methods for parallel-arm GRTs, individually randomized group-treatment trials, and missing data) and in new topics, including methods to account for multiple-level clustering and alternative estimation methods (e.g., augmented generalized estimating equations, targeted maximum likelihood, and quadratic inference functions).In addition, we describe developments in analysis of alternative group designs (including stepped-wedge GRTs, network-randomized trials, and pseudocluster randomized trials), which require clustering to be accounted for in their design and analysis.

Resistance to tomato yellow leaf curl virus in tomato germplasm

Abstract: Tomato yellow leaf curl virus (TYLCV) is a virus species causing epidemics in tomato (Solanum lycopersicum) worldwide. Many efforts have been focused on identification of resistance sources by screening wild tomato species. In many cases, the accession numbers were either not provided in publications or not provided in a consistent manner, which led to redundant screenings. In the current study, we summarized efforts on the screenings of wild tomato species for TYLCV resistance from various publications. In addition, we screened 708 accessions from 13 wild tomato species using different inoculation assays (i.e., whitefly natural infection and Agrobacterium-mediated inoculation) from which 138 accessions exhibited no tomato yellow leaf curl disease (TYLCD) symptoms. These symptomless accessions include 14 accessions from S. arcanum, 43 from S. chilense, 1 from S. chmielewskii, 28 from S. corneliomulleri, 5 from S. habrochaites, 4 from S. huaylasense, 2 from S. neorickii, 1 from S. pennellii, 39 from S. peruvianum, and 1 from S. pimpinellifolium. Most of the screened S. chilense accessions remained symptomless. Many symptomless accessions were also identified in S. arcanum, S. corneliomulleri, and S. peruvianum. A large number of S. pimpinellifolium accessions were screened. However, almost all of the tested accessions showed TYLCD symptoms. Further, we studied allelic variation of the Ty-1/Ty-3 gene in few S. chilense accessions by applying virus-induced gene silencing and allele mining, leading to identification of a number of allele-specific polymorphisms. Taken together, we present a comprehensive overview on TYLCV resistance and susceptibility in wild tomato germplasm, and demonstrate how to study allelic variants of the cloned Ty-genes in TYLCV-resistant accessions.

Quantitative trait loci associated with trichomes in the Solanum galapagense accession LA1401

Abstract: Pest resistance in Solanum galapagense has been associated with the presence of type IV glandular trichomes and allelochemicals. Knowledge of the genetic factors involved in determining the presence and type of trichomes may assist in the process of gene introgression for development of pest resistant tomato cultivars. In this study, we sought to identify QTLs associated with the presence of type IV trichomes in an F2 population derived from the interspecific cross of Solanum lycopersicum TOM-684 × S. galapagense accession LA1401. Two QTLs contributing to type IV trichome occurrence and density were detected, one major QTL (gal.IV-2), responsible for 35.22% of phenotypic variation, was located on chromosome 2. The other QTL (gal.IV-3) was located on chromosome 3, and explained 23.35% of the phenotypic variation in the F2 population. These QTLs were responsible for 26.44 and 3.37% of the variation observed in a progeny derived from a backcross to TOM-684. The same QTLs were also associated with type II + III non-glandular trichomes, whose densities were negatively correlated to those of type IV trichomes, suggesting that the loci found may have pleiotropic effects for high type IV/low type II + III trichome densities. Our results indicate that the inheritance for type IV trichomes can be explained by a few genetic factors affecting the presence of a gland and the density of trichomes. These results further suggest a revision to trichome classification used for tomato may be appropriate.

Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data.

Abstract: Background: Describing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data. Methods: We analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data. Results: We reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip-oral cavity-pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer. Conclusion: The methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.