Plants are dependent on light for their photosynthetic growth. In order to optimize their growth, plants have evolved a sophisticated set of photoreceptors and light responses that are used to interpret and respond to their light environment1 . At the seedling stage, light triggers the switch from heterotrophic to photoautotrophic growth at soil emergence. Later in life, light is used to determine season (and hence flowering2) and neighbor proximity; close neighbors can trigger a shade avoidance response3. Interestingly, the correct response to a specific light cue depends on the environmental context. Thus, plants native to different light environments have evolved different adaptive responses. One clear example is that of shade avoidance. Light that is transmitted through or reflected from neighboring plants is reduced in its red to far-red (R/FR) ratio, because chlorophyll absorbs red but not far-red light. The phytochrome photoreceptors detect this change in light quality and trigger a suite of responses that increase light competiveness, including stem and petiole elongation and early reproduction3 (figure 1).
Plants native to sunny environments are very sensitive to shade from their neighbors and show robust shade avoidance responses, allowing them to compete for sunlight. In contrast, shade avoidance is much reduced in plants native to constitutively shady environments such as forest understory. Such changes in shade avoidance response are adaptive and are due to heritable genetic differences4-6. Although mutational studies have defined a number of genes involved in phytochrome signaling7,8, the genes and molecular changes responsible for adaptive changes in light response remain unknown.
Until very recently, most studies of population or species differences have been descriptive rather than mechanistic. Recent developments in genomics are changing the level at which questions about adaptation and evolution can be asked. We are taking a molecular-genetic approach to the study of plant light adaptation and are interested in determining which genes are responsible for adaptive changes in light response, the mechanisms by which changes in these genes affect light signaling, and the evolutionary forces that have acted on these genes. Because of the fundamental importance of light perception to plant growth, the genomics tools and information available in the "model" plant Arabidopsis thaliana, and the long history of light signaling research, this is an ideal system in which to study the molecular basis of adaptive responses. Our general approach is to study natural variation in Arabidopsis thaliana light signaling to find genes important for variation in light response. Once genes causing natural variation in shade avoidance have been defined, these genes (and changes in them) can be studied at mechanistic, evolutionary, and ecological levels. These studies can provide insight into the molecular basis of quantitative variation and adaptation. In addition, this work could be helpful for crop improvement since shade avoidance reduces crop yield under crowded conditions
To determine if A. thaliana is an appropriate organism for study of light adaptation, we characterized the extent of light response variation in 140 A. thaliana accessions using a simple response, seedling emergence9. A wide range of heritable differences in light response was found (figure 2).
Interestingly, there was a significant inverse correlation between latitude and light sensitivity, suggesting adaptation to an environmental factor that varies over latitudinal clines (perhaps light itself). Some accessions had novel response patterns whereas others had patterns suggesting changes in known pathways. One accession, Lm-2, was insensitive to far-red light, similar to phytochromeA (phyA) mutants. We found that Lm-2 fails to complement phyA due to a single amino acid change and that this change causes production of a protein that is less sensitive to light. Biochemical characterization of Lm-2 phytochrome demonstrated that it has reduced kinase activity and altered spectral properties. We used Quantitative Trait Loci (QTL) mapping to identify loci involved in light-response variation for seedling emergence between two other strains, Ler and Cvi (figure 3-4), and identified an average of four loci per light condition examined10.
Some loci map to regions with no known photomorphogenic mutants, suggesting that new genes involved in light response have been identified. In contrast, one QTL maps near PHYTOCHROMEB (PHYB), known to be important for response to red light. We created a near-isogenic line (NIL) that confirmed that this region is important for light response, and preliminary results from transgenic plants suggest that PHYB may indeed be the QTL. Strikingly, association testing suggests that the PHYB region is an important determinant of light response across many A. thaliana accessions. Furthermore, sequence comparison between A. thaliana and Arabidopsis lyrata show that PHYB is evolving in a non-neutral fashion. Combined, these studies demonstrate that Arabidopsis is an excellent organism for studying the molecular basis of natural variation in light response, and suggest that some changes in light response in Arabidopsis and its relatives is adaptive.
QTL mapping of shade avoidance traits
We are continuing to use QTL mapping to find genes important for variation in light response. Our preliminary studies focused on seedling emergence. We are now studying shade avoidance responses, because of the clear adaptive value of variation in shade avoidance responses4-6 and possible benefit to agriculture. To separate phytochrome-mediated responses from those caused by reduced irradiance we are growing plants in three light conditions: high R/FR, low R/FR (simulating shade), and high R/FR but with photosynthetically active radiation (PAR ) reduced to match that in the low R/FR environment. Preliminary results on one Recombinant Inbred Line (RIL) population demonstrates that there is substantial genetic variance in R/FR response (figure 5; p < 0.0001).
In each environment we are measuring a variety of shade avoidance characters, including hypocotyl, stem, and petiole elongation, leaf angle, leaf shape, and flowering time. This work is part of an NSF funded collaboration with Cynthia Weinig at the University of Minnesota who is examining these lines under low and high competitive conditions in the field to study group versus individual selection.
Expression Profiling and eQTL mapping
Recent reports demonstrate that EST or oligo microarrays can be used to detect significant natural variation in the transcriptome among strains of yeast, flies, fish, maize, mice, and humans11-14. In several of these studies, the expression levels were used as traits for linkage or QTL analysis. Notably, about one third of the transcripts with expression differences in yeast and mice are closely linked to loci or expression QTL (eQTL) predicted to control their expression differences11-14 . For these genes it is likely that the differences in expression are caused by changes in the regulatory sequences or the transcript itself, meaning that a strong candidate gene for the eQTL has been identified.
To better understand the mechanisms underlying variation in Arabidopsis shade avoidance traits, we are coupling expression profiling with the classical QTL mapping experiments described above. We hypothesize that eQTL that control expression differences in low and high R/FR and that co-localize with QTL for shade avoidance traits are likely to be causal for those traits. Thus we can learn about the molecular effects of particular QTL by examining the types of genes that it regulates. For example, a QTL affecting expression primarily of cell wall enzymes likely acts downstream in the shade avoidance pathway, whereas a QTL controlling expression of transcription factors may be more upstream. Comparing genes affected by eQTL with those controlled by known shade avoidance regulators will further help define the mechanisms of QTL action.
QTL maps typically resolve the involved loci into regions that contain hundreds of genes. However a number of QTL have been recently cloned, demonstrating that it is possible to identify the causative genes. The full genome sequence, abundant genetic markers, and nearly saturating gene knock-out collection make Arabidopsis perhaps the premier multi-cellular organism for QTL cloning15 . To better understand the molecular basis of quantitative genetic variation and to find the genes controlling variation in shade-avoidance, the full suite of Arabidopsis molecular genetic tools is being used to clone QTL identified in the lab.
Functional molecular evolution
Recently developed likelihood models of codon based nucleotide substitution greatly increase the ability to detect positive selection and allow prediction of particular codons that have been subject to positive selection16-18. Thus, evolutionary data can be used to predict functionally interesting amino acid residues. PHYB is an ideal candidate for the application of these methods. While selective pressure on R/FR sensitivity could affect any gene in the PHYB pathway, there is evidence that PHYB itself is under selection. First, phys are evolving more rapidly than average plant genes19; second, we found that PHYB co-localizes with a quantitative trait locus (QTL) affecting response to white and red light in Arabidopsis10; and last, our unpublished analysis of A. thaliana and A. lyrata PHYB sequences suggests positive selection using the McDonald-Krietman test20. Codon based substitution models will be used to analyze PHYB sequence across the brassicaceae. Site-directed mutagenesis of interesting residues will be used to test the functional consequence of amino acid substitution using transgenic Arabidopsis and in vitro tests. This work is part of a HFSP funded collaboration with Ulrich Genick and Christian Fankhauser to explore variation in Phy structure and function.