Date Thesis Awarded

5-2017

Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)

Department

Biology

Advisor

Joshua Puzey

Committee Member

Jordan Walk

Committee Member

Matthias Leu

Committee Member

Helen Murphy

Abstract

Color patterns are found in a plethora of organisms, from vertebrates to flowering plants. While many studies have examined the mechanisms that produce these diverse patterns in animals, little research has investigated the mechanisms by which plants create color patterns. The conclusions drawn from animal studies may not accurately translate to plants due to early divergence in the evolution of life. Characterization of plant patterning mechanisms would have widespread impacts on developmental and evolutionary biology. To unravel the mystery behind pattern formation, we suggest an experimental framework to understand pattern evolution and development at a phenotypic, genotypic, and quantitative level, creating a holistic model for the evolution of complex traits and phenotypic diversity. Here, we provide a novel protocol for the quantification of pattern morphology, and demonstrate its efficacy in a segregating F2 population of the model organism Mimulus luteus . By co-opting ArcGIS and FragStats, two landscape ecology softwares, to map petal patterns, we developed a high throughput method for objective phenotype characterization. This protocol is useful for preliminary work in a bulk segregant analysis by separating a population in discrete groups based on morphology. We used this protocol to demonstrate that patterns are distinct between petals within the same flower depending on petal location, and that there is a genetic basis for pattern formation in flowers. Minor tweaks to the genes guiding pattern formation may be responsible for the rapid evolution of angiosperm flower diversity. Future work is required to identify the genes responsible for pattern formation, and to develop a method for modeling these genes to predict how minor mutations would impact phenotypic traits.

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