Thursday 10 october 2019 at 2PM
Room 108 (heart school) at 2pm
(Center for Computational and Theoretical Biology, University Würzburg, 97074 Würzburg, Germany)
Natural Variation of Gene Regulatory Networks
Understanding the causal relationship between genotype and phenotype is a major objective in biology. A default tool to illuminate these relationships are genome-wide association studies (GWAS). Here the goal is to identfy genetic loci that associate with the trait of interest. Genomic prediction (GP), on the other hand, aims to predict the phenotype from the genome. Both methods have been successfully used in many different species to elucidate trait architecture or prognose plant response. However, most studies concentrate on marginal marker effects and ignore epistatic and gene-environment interactions. These interactions are problematic to account for, but are likely to make major contributions to many phenotypes that are not regulated by independent genetic effects, but by more sophisticated gene-regulatory networks. A further complication arises from the fact that these networks vary in different natural accessions. Still, understanding the differences of gene regulatory networks and gene-gene interactions is crucial to conceive trait architecture and predict phenotypes.
I will present data on statistical aproaches to tackle these challenges and present examples – using data from the Arabidopsis 1001 Genomes Project – of gene regulatory networks that have been realized differntly in different natural accessions.
contact : firstname.lastname@example.org