Using large SNP datasets to understand the genetic mechanisms of complex traits in Arabidopsis thaliana

Arabidopsis thaliana, as a model species, has been widely genotyped and sequenced. Many studies have been done to understand the kinship and population structure of the species. This data and information is beneficial for understanding the genetic mechanisms of complex traits. In this thesis, we first used genotyped data for 5,967 accessions to study the occurrence of tetraploidy in the species. We found that tetraploidy is a transient character state, and the species is a diploid species. Secondly, we used 211K and 1.6M SNPs for 440 accessions to run genome-wide analyses (GWA) for four traits: glufosinate tolerance, hybrid incompatibilities, seed size, and secondary metabolites. We used two different statistical methods, EMMAX and MLMM, to calculate the associations between SNP and phenotype. Putative gene lists for each trait from each statistical model are available for the general public to find candidate genes that are involved in these traits.