The genomics of buffering and canalization in Arabidopsis

Making sense of natural variation remains one of the greatest challenges in biology. Understanding how genetic variation translates into phenotypic variation, and how this translation depends on the environment is fundamental to our understanding of evolution, and has enormous practical implications for medicine, agriculture and energy production. There has been much speculation about the existence of buffering, or "canalizing" effect that serve to mask the phenotypic effects of genetic variation under "normal" environmental conditions (i.e. conditions to which the organisms is adapted), but reveals it under abnormal conditions. For example, it has been suggested that many human diseases are due to genetic variants that were buffered under the conditions under which humans evolved, but which have been revealed under the, evolutionarily speaking, extreme conditions of modern life: modern humans eat much more than our ancestors did, and are also exposed to a broad range of environmental pollution. To truly understand the genotype-phenotype map, it is ultimately necessary to understand these kinds of buffering effects. However, they are difficult to study, and our understanding of the genetic mechanisms that could lead to buffering is thus very incomplete, despite their importance. Buffering is perhaps best viewed as an emergent property of a very complicated network comprising hundreds of genes depending on gene-by-gene (G x G) and gene-by-environment (G x E) interactions. To understand of buffering, it is necessary to break down this network into pathways, determine causality, and discover the mechanisms that stabilize development at the molecular level. Here I propose a systematic approach that will leverage rich genomic data from natural inbred lines of A. thaliana in order to provide an unbiased picture of buffering effects. A. thaliana is an ideal model for this study due to availability of large numbers of inbred line as well as other genomic resources. In particular, I will use genome- wide association studies (GWAS) to identify candidate genes for buffering (based on G x G and G x E interactions), and statistically predict the buffering network. A number of promising candidates will be verified using a variety of experiment approaches. Dr. Nordborg`s hosting laboratory provides an outstanding environment for developing the required statistical methods, and is also generating unprecedented multi-layer biological data comprising detailed phenotypic data, as well as levels of gene expression, DNA methylation, histone methylation, and small RNA, in two different environments for 200 fully sequenced Arabidopsis lines. The confluence of all these factors provides perhaps our best chance to date of gaining insight into the regulation of cryptic genetic variation to date.

In the life cycle of flowering plants, the transition from vegetative to reproductive growth is a key developmental step, and the timing of this switch is tightly coordinated by genetic and environmental influences. The interaction between genetics and the environment is believed to play a crucial role in plant evolution and adaptation, in particular buffering mechanisms that regulate robustness of trait in the face of environmental perturbations. For an example, buffering may make the timing of germination or flowering uniform regardless of genetic differences under the condition the plant is adapted to, but not under other conditions. Understanding the molecular mechanisms that underlie such buffering is a central question of genetics with broad implications for agriculture and ecology. In this project, we focused on temperature-dependent variation of flowering time (the period from germination to flower) in natural isolates of Arabidopsis thaliana. We collected flowering time data for more than 150 Swedish isolates under two temperature conditions (cool and warm; 10, 16C). Under warm conditions the flowering time across isolates was highly variable in comparison to cool condition, suggesting that genetic differences expressed under warm conditions were buffered under cool conditions. We found that these isolates could be classified into three groups based on their reaction to warm conditions: accelerated, delayed, unaltered flowering. To identify genes regulating the temperature-dependent variation of flowering time, we screened several million known genetic variants for thus statistically associated with flowering time variation. We identified a major flowering suppressor gene, FLOWERING LOCUS C (FLC), as a key regulator of the variation. In addition to FLC, we identified strong effects of VERNALIZATION INSENSITIVE 3 (VIN3) and FIONA1 (FIO1). VIN3 is a known suppressor of FLC, but the function of FIO1 is unknown. The flowering time of each isolate under the two conditions could be predicted by the combination of genetic variants in those three genes with high accuracy. Thus, our result demonstrated that the gene network centering on FLC plays a major role of temperature-dependent variation of flowering time in A. thaliana. Climate change is expected to shift the life cycle of species. The molecular mechanisms underlying those changes have not been elucidated. Our approach to dissecting the regulation of flowering provides insight into this, and may help predict the influence of climate change on the ecosystem.