Growth Chambers
Seasonal flowering time response in different geographic regions
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The collection of 384 accessions will be made of up a majority of world wide collections and some population specific collections. They will be measured for quantitative variation in two well studied traits, seedling elongation light response and flowering time (Fankhauser and Staiger 2002; Komeda 2004). The environments under which to study these traits will represent two seasons and two geographic locations. Winter annual accessions of A. thaliana germinate in the fall and over-winter as a rosette, then transition to flowering in the spring. Summer annual accessions in contrast germinate in the spring and more quickly set seeds in the summer. At southern latitudes, such as the possible glacial refugia in the Iberian Peninsula (Sharbel et al. 2000), summer annual accessions may undergo two generations per year. In Northern latitudes likely only a single cycle is permitted. To capture the seasonal and geographic environmental variation under which A. thaliana has adapted, growth chamber settings will reflect mean light quality, light intensity, day length, and temperature. Daily chamber settings are programmed to vary according to the changing season; either entering winter followed by spring for the fall planting, or spring conditions entering summer for the spring planting. Temperate, light quality and light intensity will cycle appropriately with changing day length regimes. Northern latitudes will be more extreme for seasonal variation while southern latitudes transition more gradually. The two seasonal planting times corresponding to fall and spring and the two geographic regions represent Spain and Sweden. These combinations create four environments that capture a variety of exogenous cues to signal flowering and seedling elongation (Koornneef et al. 2004; Maloof et al. 2000). Importantly, these settings capture the major environmental conditions in the field without the random noise that accompanies actual field conditions. These predictable seasonal changes are likely what plants can quickly adapt to, as compared to the more unpredictable disease and pest pressure, rain fall, or frost. Removing the unpredictable components in the environment reduces much of the noise in the experiment allowing one to focus on the genetic basis of adaptation to seasonal and geographic cues.
Molecular biologists may feel these enviroments are too complex and it would be difficult to dissect the genetic basis of variation under these conditions. That may be true, but I would argue that studying flowering time under constant day length, light quantity, and light quality, and temperature does not make ecological sense. These are far from the conditions under which flowing time and seedling elongation responses have evolved. It may be more appropriate to look at natural variation under conditions similar to field conditions. In this case loci identified are much more likely to be ecologically relevant. Natural selection at these loci may have shaped patterns of variation. Thus starting from environments that mimic wild conditions and perturbing them by season and geographic location may reveal a previously hidden genetic basis for differences in life history, such as winter annual vs. summer annual and/or differences along latitudinal gradients.
A Plant’s Diet
This proposal to measure controlled but realistic environments for association studies can be compared to studying the effect of diet when looking for genetic causes of obesity or diabetes in humans. As with plants grown in the field there is a huge variation in the diets people eat. Trying to dissect the human genotype by diet interactions causing disease is a very difficult task. Forcing everyone in the study group to eat nothing but rice or nothing but sausage all day every day from birth to death would help reduce the diet complexity tremendously and give much more power to see how people respond differently to different diets. If successful however we could only conclude the genetic basis for a difference in response to two completely artificial diets. Would these genetic differences be relevant to determining what different types of people should eat to avoid disease, or would it just highlight our gross metabolic variation? In principal this is analogous to studying flowering time two constant conditions. An alternative design would be to have everyone eat either of two “balanced” diets that cover the range of human food habits. This could be strict vegan vs only McDonalds. The interpretation here is more relevant. Aside from the overall effect of diet on disease, we could determine why some people are especially sensitive or resistant to the only McDonalds diet relative to the vegan diet. From both a science and policy perspective, it would be interesting to determine the variance explained by genetics, diet, and the interaction between them. Studying flowering time and light response under controlled yet relevant environmental conditions is a powerful way to determine the genetic basis to environmental response. This is an important study design test case with potentially broad impact. Concept based on Supersize Me
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growth chambers
