Statistical approaches for QTL mapping and genomic prediction of multiple correlated traits across varying environmental conditions: case studies in pepper

Promovendus mr. NA (Nurudeen Adeniyi) Alimi
Promotor dr. FA (Fred) van Eeuwijk
Copromotor dr ir MCAM Bink
Organisatie Wageningen University, Leerstoelgroep Wiskundige en statistische methoden

di 1 november 2016 13:30 tot 15:00

Locatie Aula, gebouwnummer 362


Breeders aim at selecting genotypes that show a superior performance for target traits, often complex, in a target population of environments. In this research, we present the results of a number of statistical techniques that were used to describe and understand the genetics of yield in pepper as an example of a complex trait measured under different environmental conditions. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits. In addition, in statistical network reconstruction approaches yield was confirmed to be downstream to its component traits, indicating that yield can be studied and predicted from its component traits. Genetic improvements for yield could benefit from improvements on yield components. Finally, complex trait prediction can be enhanced by a full integration of multi-trait, crop growth and network models, in which both multivariate QTL mapping and whole genome prediction models have a role.