Abstract
Artemisia tridentata (big sagebrush) is a landscape-dominating foundational shrub in the western United States which occupies distinct ecological niches, exhibiting diploid and tetraploid cytotypes. Tetraploids have a large impact on the species' landscape dominance as they occupy a preponderance of the arid spectrum of the A. tridentata range. Three distinct subspecies are recognized, which co-occur in ecotones - the transition zone between two or more distinct ecological niches - allowing for hybridization and introgression.In Chapter 1, I assess the genomic distinctiveness and extent of hybridization among subspecies at different ploidies under both contemporary and predicted future climates. I sampled five transects throughout the western United States where subspecies-specific climate niche models predicted a subspecies overlap. Along each transect, I sampled multiple plots representing the parental and the potential hybrid habitats. I performed reduced representation sequencing and processed the data using a ploidy-informed genotyping approach. Population genomic analyses revealed distinct diploid subspecies and at least two distinct tetraploid gene pools, indicating independent origins of the tetraploid populations. I detected low levels of hybridization (2.5%) between the diploid subspecies, while we found evidence for increased admixture between ploidy levels (18%), indicating hybridization has an important role in the formation of tetraploids.
In Chapter 2, I re-utilize the same data set to develop markers for a genotyping-in-thousands sequencing (GT-seq) panel to facilitate a rapid and cost-efficient subspecies, hybrid, and ploidy identification. I identify 389 genomic variants, design primers for these variants and validate the final variant set for their statistical power to distinguish between subspecies and ploidy. I apply Bayesian methods, multivariate methods, and machine learning algorithms at those variant sites. The results of the Bayesian and multivariate methods agree with previous findings for both, subspecies, and hybrid identification as well as recovery of comparable ancestry proportions. The machine learning algorithms classify most of the subspecies (99.5%) and ploidy (99.5%) correctly. My findings suggest that a select number of genomic markers is highly suitable for a GT-seq panel which may find application in big sagebrush research, land management and restoration.
In Chapter 3, I cultivate seeds of diploid individuals from a common garden experiment and a triploid individual from the natural environment, aiming to identify pathways of WGD in A. tridentata. I utilized flow cytometric genome size estimation coupled with chromosome counts, and provide evidence for both, “one-step” tetraploid formation as well as the “triploid-bridge”. I show that progeny of a triploid exhibit variable chromosome numbers – ranging from near diploid to near tetraploid. Applying ddRAD-sequencing on the cultivated individuals as well as their close and distant relatives, I find evidence for autopolyploidy, originating from each diploid subspecies, respectively. My results indicate that different pathways to WGD may be frequently occurring in A. tridentata across the landscape, and I suggest that future studies investigating fine-scale environmental gradients to assess frequency of and pathways to ploidy variation may be warranted.