Biomedical subjects

Andrew Bangham

Publications and source records attributed to Andrew Bangham.

3 recordsLinked to original sources

PubMed2006

Evolutionary paths underlying flower color variation in Antirrhinum.

To understand evolutionary paths connecting diverse biological forms, we defined a three-dimensional genotypic space separating two flower color morphs of Antirrhinum. A hybrid zone between morphs showed a steep cline specifically at genes controlling flower color differences, indicating that these loci are under selection. Antirrhinum species with diverse floral phenotypes formed a U-shaped cloud within the genotypic space. We propose that this cloud defines an evolutionary path that allows flower color to evolve while circumventing less-adaptive regions. Hybridization between morphs located in different arms of the U-shaped path yields low-fitness genotypes, accounting for the observed steep clines at hybrid zones.

Adaptation, Biological↗

PubMed2006

Visualizing plant development and gene expression in three dimensions using optical projection tomography.

A deeper understanding of the mechanisms that underlie plant growth and development requires quantitative data on three-dimensional (3D) morphology and gene activity at a variety of stages and scales. To address this, we have explored the use of optical projection tomography (OPT) as a method for capturing 3D data from plant specimens. We show that OPT can be conveniently applied to a wide variety of plant material at a range of scales, including seedlings, leaves, flowers, roots, seeds, embryos, and meristems. At the highest resolution, large individual cells can be seen in the context of the surrounding plant structure. For naturally semitransparent structures, such as roots, live 3D imaging using OPT is also possible. 3D domains of gene expression can be visualized using either marker genes, such as beta-glucuronidase, or more directly by whole-mount in situ hybridization. We also describe tools and software that allow the 3D data to be readily quantified and visualized interactively in different ways.

Flowers↗

PubMed2005

Evolution through genetically controlled allometry space.

Understanding evolutionary change requires phenotypic differences between organisms to be placed in a genetic context. However, there are few cases where it has been possible to define an appropriate genotypic space for a range of species. Here we address this problem by defining a genetically controlled space that captures variation in shape and size between closely related species of Antirrhinum. The axes of the space are based on an allometric model of leaves from an F2 of an interspecific cross between Antirrhinum majus and Antirrhinum charidemi. Three principal components were found to capture most of the genetic variation in shape and size, allowing a three-dimensional allometric space to be defined. The contribution of individual genetic loci was determined from QTL analysis, allowing each locus to be represented as a vector in the allometric space. Leaf shapes and sizes of 18 different Antirrhinum taxa, encompassing a broad range of leaf morphologies, could be accurately represented as clouds within the space. Most taxa overlapped with, or were near to, at least one other species in the space, so that together they defined a largely interconnected domain of viable forms. It is likely that the pattern of evolution within this domain reflects a combination of directional selection and evolutionary tradeoffs within a high dimensional space.

Antirrhinum↗