Plasticity of Arabidopsis Root Gravitropism throughout a Multidimensional Condition Space Quantified by Automated Image Analysis    

Abstract

Plant development is genetically determined but it is also plastic, a fundamental duality that can be investigated provided large number of measurements can be made in various conditions. Plasticity of gravitropism in wild-type Arabidopsis (Arabidopsis thaliana) seedling roots was investigated using automated image acquisition and analysis. A bank of computer-controlled charge-coupled device cameras acquired images with high spatiotemporal resolution. Custom image analysis algorithms extracted time course measurements of tip angle and growth rate. Twenty-two discrete conditions defined by seedling age (2, 3, or 4 d), seed size (extra small, small, medium, or large), and growth medium composition (simple or rich) formed the condition space sampled with 1,216 trials. Computational analyses including dimension reduction by principal components analysis, classification by k-means clustering, and differentiation by wavelet convolution showed distinct response patterns within the condition space, i.e. response plasticity. For example, 2-d-old roots (regardless of seed size) displayed a response time course similar to those of roots from large seeds (regardless of age). Enriching the growth medium with nutrients suppressed response plasticity along the seed size and age axes, possibly by ameliorating a mineral deficiency, although analysis of seeds did not identify any elements with low levels on a per weight basis. Characterizing relationships between growth rate and tip swing rate as a function of condition cast gravitropism in a multidimensional response space that provides new mechanistic insights as well as conceptually setting the stage for mutational analysis of plasticity in general and root gravitropism in particular.

Detection of a Gravitropism Phenotype inglutamate receptor-like 3.3Mutants ofArabidopsis thalianaUsing Machine Vision and Computation

“…The wavelet analysis demonstrated that GLR3.3 promoted curvature development after the tip angle reached 40°. Previous research demonstrated that maximum swing rate occurs at a tip angle of $30°, regardless of condition or overall response time course (Durham Brooks et al 2010). Following this maximum, tip angle rapidly decelerates as part of autotropic straightening, which counteracts gravitropic signaling so that the reoriented portion of the root begins to grow straight (Stankovic et al 1998).…”

“…Superimposed on this time course are step functions showing where first-order (red) or second-order (blue) Gaussian derivative wavelets significantly separated both mutant allele populations from the wild type (P , 0.05). In other words, glr3.3 mutations (both alleles) affected the first derivative, or swing rate (Durham Brooks et al 2010), when the red line steps up. The second derivative, or acceleration of the tip angle, differed in glr3.3 mutants when the blue line steps down.…”

“…The size of the seed from which the seedling emerged and postgermination age significantly affected response trajectory when measured with high resolution at 2-min intervals over a 10-hr period (Durham Brooks et al 2010). Therefore, seed size (small or large) and seedling age (2 days or 4 days) created a 2 3 2 condition grid in which a gravity response phenotype was sought in two T-DNA insertion (mutant) alleles of GLR3.3 (At1g42540).…”

“…A bank of seven CCD cameras each equipped with a close-focus zoom lens formed the front end of a computer-controlled image acquisition and analysis platform that was used in a previous study to investigate the plasticity of wild-type root gravitropism (Durham Brooks et al 2010). The size of the seed from which the seedling emerged and postgermination age significantly affected response trajectory when measured with high resolution at 2-min intervals over a 10-hr period (Durham Brooks et al 2010).…”

“…Either such phenotypes do not exist in glr3.3 mutants or some nonstandard methods for finding them were necessary. Here, a highly automated process for quantifying dynamic root growth and behavior involving image processing and mathematical analysis was employed to search for a root growth behavior phenotype (Miller et al 2007;Durham Brooks et al 2010). The results demonstrate a function for GLR3.3 in root gravitropism and provide an example of how a single-gene phenotype can be isolated by applying appropriate technology.…”