A role for AtGLR3.3 in buffering root responses to gravity detected computationally within a multi-dimensional behavior space.

摘要

A major goal of genomics studies in model organisms is to determine functional roles for the genes that make up the organism. These studies rely on the use of genomic tools to systematically create sequence-index libraries of genetic mutations. In Arabidopsis, this approach has led to significant progress in describing gene function at the organismal level; however the huge majority of the genome remains to be functionally described. The detection of effects of a single mutation in one of 25,000+ genes within a complex environmental and developmental landscape has become a challenge for genomics studies research. This thesis describes an experimental approach that incorporates influences of environment, development, and parental environment on gene function. It was found that parental environment directly and indirectly through seed size affects growth and development throughout the Arabidopsis life cycle and over generations. Multi-dimensional characterization of a well-studied stimulus-response, root gravitropism, was enabled using a machine vision approach. A dataset of over a thousand individual root responses was compiled. Root gravitropism was found to vary with environment, development, and seed size. Observing the response of roots throughout this space uncovered aspects of the behavior that have not been well characterized, such as classification of root behavior into different response types, detailing the relationship between growth rate and tip angle, and describing relationships between gravitropic bending and autotropic straightening during tip angle progression. This detailed description of gravity responses within a non-genetic framework allowed for the careful characterization of a gene known to play a key role in electrical signaling in the root, but having no apparent effect on the organism when mutated. This gene, AtGLR3.3, was found to have a subtle effect on overall tip angle development which required the construction of computational tools with the resolution to uncover its function during the gravitropic response. An optimization approach in tandem with wavelet analysis uncovered a role for AtGLR3.3 in buffering root responses to gravity that was persistent across conditions and over generations. The approach described here is applicable to functional genomics studies of other areas of plant development and in other model organisms.