Floral Genetic Architecture: An Examination of QTL Architecture Underlying Floral (Co)Variation Across Environments.
Summary of "Floral Genetic Architecture: An Examination of QTL Architecture Underlying Floral (Co)Variation Across Environments."
Genetic correlations are expected to be high among functionally related traits, and lower between groups of traits with distinct functions (e.g., reproductive vs. resource-acquisition traits). Here, we explore the quantitative-genetic and QTL architecture of floral organ sizes, vegetative traits, and life-history in a set of Brassica rapa recombinant inbred lines within and across field and greenhouse environments. Floral organ lengths were strongly positively correlated within both environments, and analysis of standardized G-matrices indicates that the structure of genetic correlations is ~80% conserved across environments. Consistent with these correlations, we detected a total of 19 and 21 additive-effect floral QTL in the field and greenhouse, respectively, and individual QTL typically affected multiple organ types. Interestingly, QTL x QTL epistasis also appeared to contribute to observed genetic correlations, i.e., interactions between two QTL had similar effects on filament length and two estimates of petal size. Although floral and non-floral traits are hypothesized to be genetically decoupled, correlations between floral organ size and both vegetative and life-history traits were highly significant in the greenhouse; G-matrices of floral and vegetative traits as well as floral and life-history traits differed across environments. Correspondingly, many QTL (45% of those mapped in the greenhouse) showed environmental interactions, including approximately even numbers of floral and non-floral QTL. Most instances of QTL x QTL epistasis for floral traits were environment-dependent.
Affiliation
University of Wyoming.
Journal Details
This article was published in the following journal.
Name: Genetics
ISSN: 1943-2631
Pages:
Links
- PubMed Source: http://www.ncbi.nlm.nih.gov/pubmed/20837996
- DOI: http://dx.doi.org/10.1534/genetics.110.119982
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