Genetics of adaptation to toxic environments

SUMMARY Resistance to toxins often evolves via major effect mutations in the target protein. Theory predicts that these major effect mutations carry fitness costs, which are subsequently resolved or ameliorated via compensatory mutations. Yet, characterization of compensatory mutations has remained elusive because their testing has

been hampered by a lack of tools. With the advent of genome sequencing and genome engineering, we can now identify candidate compensatory mutations and rigorously test them in vivo. Here, I propose to use Drosophila subobscura as a new model system to fully characterize compensatory mutations ameliorating

neuronal costs of toxin resistance mutations in ATPα (α-subunit of the Na+, K+-ATPase). I will adopt both a candidate-based and an unbiased genome-wide approach to characterize compensatory mutations, which should allow me gain a complete view of compensatory evolution in Drosophila subobscura. During the K99

phase (first and second aims), I will adopt the candidate-based approach to explore compensatory mutations within the resistant ATPα alleles of D. subobscura. Under the first aim, I will employ a population genomic approach to identify candidate compensatory mutations within the resistant ATPα alleles. Under the second

aim, I will employ a genome engineering approach to characterize the candidate compensatory mutations from the first aim by editing them together with the resistance mutations in the sensitive ATPα allele of D. melanogaster. During the R00 phase (third and fourth aims), I will adopt the unbiased genome-wide approach

to explore compensatory mutations outside the resistant ATPα alleles of D. subobscura (“modifier locus”). Under the third aim, I will employ a genome engineering approach to introduce the resistant ATPα alleles of D. subobscura in a sensitive D. subobscura background to first validate the presence of a “modifier locus”. Under

the fourth aim, I will use gene mapping to characterize the modifier locus. The collective results of this project will provide a detailed picture where in the genome compensatory mutations evolve and in which order they evolve relative to the the resistance mutations. A K99 Award would allow me to receive training in population genomics and sequencing technologies and

provide time to extend my expertise in genome engineering and theory on the genetics of adaptation to toxic environments. The training phase of this proposal will be performed in the laboratory of Dr. Dmitri Petrov, which is ideal for exchanging exciting idea and learning population genomics as he is a leader in the

Drosophila population genomics of adaptation. Stanford and the the Department of Biology provide an excellent environment and facilities for the proposed work. My long term career goal is to establish my independent academic research laboratory where I will study the genetics of adaptation to toxic environments.