Elevational adaptation in Maize/Teosinte
I have recently started a new postdoc in Jeffrey Ross-Ibarra’s lab at UC-Davis. My primary focus will be on characterizing adaptive genomic changes in high elevation populations of Maize and it’s non-domesticated relatives teosinte. This project will allow me to investigate new questions about how evolution operates upon quantitative trait variation (as opposed to Mendelian; see below) in populations that are repeatedly undergoing similar adaptive pressures. The project will also weave in other interesting evolutionary elements regarding the role of large highly pleiotropic genomic changes (i.e. chromosomal inversions) on the evolution of correlated phenotypic changes and how introgression/hybridization opposes or promotes shifts in adaptive phenotypic changes.
Bulk segregant RNA-sequencing reveals insights into the genetic basis for the loss of anthocyanin pigmentation in Iochroma loxense
Constraint is a widely documented and powerful evolutionary force. At the genetic level, constraint is typically invoked when changes that lead to adaptive phenotypes may have other pleiotropic costs. In plant floral evolution, these costs may be substantial enough to drive the evolution of gene duplicates through sub or neofunctionalization or to drive predictable genetic mechanisms of independently derived phenotypes. To understand better how constraint shapes evolutionary dynamics I have characterized the genetic basis of a relatively recently duplicated repressor of floral pigmentation in the plant species Iochroma loxense. Currently I am using a combination of bioinformatics, genomics, phylogenetics, and functional assays to better understand the patterns and evolutionary dynamics that have resulted in the numerous changes of function and expression required to go from tandem gene duplicate to novel a novel repressor of floral pigmentation.
Defining the optimal tipset leads to greater support in the Iochrominae species tree
The current applications of high throughput sequencing (HTS) preparation for species phylogeny datasets represent a trade-off between the phylogenetic power and the ease of data collection. This tradeoff has lead to an active discussion in how to choose the best overall dataset in the face of substantial imbalance across loci and individuals. I am currently characterizing the history of the plant subtribe Iochrominae (Solanaceae) using custom target capture Illumina sequence data. The data I have collected so far is quite noisy and serves as an excellent example of how to let natural characteristics of phylogenetic datasets inform downstream processes to maximally leverage phylogenetic signal while reducing error and background noise.