Ontology highlight
ABSTRACT: Premise
The explosion of available genomic data poses significant opportunities and challenges for genome-wide association studies. Current approaches via linear mixed models (LMM) are straightforward but prevent flexible assumptions of an a priori genomic architecture, while Bayesian sparse LMMs (BSLMMs) allow this flexibility. Complex traits, such as specialized metabolites, are subject to various hierarchical effects, including gene regulation, enzyme efficiency, and the availability of reactants.Methods
To identify alternative genetic architectures, we examined the genetic architecture underlying the carotenoid content of an association mapping panel of Helianthus annuus individuals using multiple BSLMM and LMM frameworks.Results
The LMMs of genome-wide s
SUBMITTER: Dowell JA
PROVIDER: S-EPMC10719882 | biostudies-literature | 2023 Nov-Dec
REPOSITORIES: biostudies-literature