With the rapid advances in sequencing technologies and bioinformatics, we are now able to take up the challenge of discovering genetic basis of trait evolution not only in model organisms but also in other ecologically important species. Accordingly, the current project I am working on, funded by National Science Foundation within the framework of Dimensions of Biodiversity Program, is focused on a South African shrub species, Protea repens (sugar bush), expanding a wide range of climate gradients in the highly diverse Cape Floristic Region. Functional trait variation that different populations display, across strong gradients in precipitation, temperature, fire frequency, makes this species a great system for exploring evolutionary mechanisms leading to local adaptation. In this project, I am using three complementary approaches. First, I have analyzed population level gene expression patterns that correlate with environmental variation and how these relationships are reflected in trait expression. Second, by using experimental physiology and transcriptomics, I am studying responses of different populations to important environmental stresses. And lastly, by using population genomics approaches, I will try to reveal signatures of natural selection acting on gene sequence variation by using population level genotype and trait data.
- Population level transcriptomics
Phenotypic variation can be shaped either by gene sequence diversity or plasticity in expression patterns, or a combination of both. Recently, there have been many studies looking at population level sequence variation to detect signatures of natural selection, however gene expression variation is often not explored. This is mainly because gene expression is a readily changing and plastic process influenced by many external factors, which makes sample collection challenging. Nevertheless, common garden experiments enable us to minimize this excess variation and to detect biologically relevant responses of plants to various environments. For this purpose, we set up a common garden consisting of seedlings from Protea repens populations in order to study correlations between trait phenotypes, source population site climate variables and gene expression patterns of the seedlings. By analyzing common garden transcriptome-wide expression data, I identified gene networks correlated with temperature-related environmental variables of the source populations. The expression patterns of the same gene networks, which are involved in growth, cell wall and carbohydrate metabolism, correlates also with growth related traits. This study shows that, environmental variables of source sites are explanatory factors for gene and trait expression variation in a common garden, indicative of local adaptations in sugar bush. This work is published in New Phytologist, full text is here!
- Experimental physiology and transcriptomics
Another line of my research is to conduct experimental physiology and transcriptomics studies to detect genes that are differentially regulated between populations when plants are under drought and temperature stress, and detect effect of the climate in shaping this plastic response. Accordingly, in a collaborative project with Dr. Jane Carlson of Nicholls State University, we are performing stress experiments in a green house for select populations of Protea repens. Our aim with this work is to complement the results from our population level transcriptomics project by detecting differential gene regulation patterns of these populations to strong, well-controlled environmental contrasts. We will be testing if similar genes or gene pathways, as detected in our common garden experiments, are regulated in different populations under drought and temperature stress and if we can detect population specific responses shaped by source site climates. This work is very close to completion, so stay tuned!
- Population genomics
Apart from the gene expression variation, I am also interested in how the evolutionary processes shape gene sequence variation and allele frequencies in distinct populations. For this part of the project, I am analyzing sequence data from twenty Protea repens populations across the environmental and geographic range of the species in order to detect outlier loci as an indicative of selection. Additionally, by using genotype and the trait data, I will conduct a genome wide association study to find loci controlling functional trait variation observed in the common garden. Both of these analyses will complement to the population level transcriptome and experimental physiology projects to reveal genetic basis of local adaptations in Protea repens, which can later be translated to other species adapted to Mediterranean climates.