Título: Statistical challenges in genotype by environment interactions and QTL by environment interactions

Palestrante: Paulo Canas Rodrigues (UFBA).
Data: 07/10/2020.
Horário: 15:30.
Local: Transmissão online.

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Resumo: When analyzing two-way data tables, with genotypes in the rows and environments in the columns, it is frequent to observe differential responses of genotypes across environments. This phenomenon is known as genotype by environment interaction (GEI) and can be defined by the change of genetic ranking of genotypes with the environment (e.g. in plant sciences, a genotype that is superior at well-watered conditions may yield poorly under dry conditions). The GEI can be expressed either as crossovers, when two different genotypes change in rank order of performance when evaluated in different environments, or inconsistent responses of some genotypes across environments without changes in rank order. One step further from the GEI can be made by considering the whole genetic information and analyze the QTL (quantitative trait loci) by environment interaction (QEI). To structure and better understand these interactions, the use of modern statistical methods is required. In this talk, I will present generalizations of two fixed effects models: the additive main effects and multiplicative interaction (AMMI) model, and the genotype plus genotype by environment interaction (GGE) model. These generalizations are the robust AMMI and robust GGE models, which outperform their classical counterparts when outlying observations are present in the data. I will present model performance and comparison in terms of QTL detection and QEI interpretation, by considering applications to simulated and real data sets.

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