Matching Items (2)
192525-Thumbnail Image.png
Description
The ecological niche of a species can shift due to changing environmental conditions and lead to the species to undergo selective pressures to adapt to them. Ecological niche models are used to predict a species’ distribution based on its ecological niche. Ecological niche models can be integrated with a geographic

The ecological niche of a species can shift due to changing environmental conditions and lead to the species to undergo selective pressures to adapt to them. Ecological niche models are used to predict a species’ distribution based on its ecological niche. Ecological niche models can be integrated with a geographic information system to predict a species’ geographic distribution based on environmental variables. In this project, two reptile species that inhabit wide and variable geographic ranges, Uta stansburiana and Gopherus berlandieri, had their ecological niches predicted and mapped based off population data and climactic data. These ecological niche maps were then compared to sample populations of each species to infer and predict whether certain populations of each species were possibly under increased selective pressures. Based off these maps and comparisons, this study infers that the two species differ in which environmental variables are the most relevant to their suitability. This study also predicts that populations of U. stansburiana experiencing extremes in their most relevant values for temperature and precipitation could be under greater selective pressures, while populations of G. berlandieri experiencing lower values for their relevant temperature and precipitation variables could be under greater selective pressures. Furthermore, it can be inferred from this study that differences in these variables across each species’ range could be influencing genetic variation among their populations, in line with previous studies. Further genomic study of each species can be used to test these inferences.
ContributorsLukasik-Drescher, Zachary (Author) / Kusumi, Kenro (Thesis director) / Araya-Donoso, Raúl (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2024-05
Description

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on dee

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on deep transcriptome sequences of adult skeletal muscle, lung, brain, and blood. The draft genome assembly for G. agassizii has a scaffold N50 length of 252 kbp and a total length of 2.4 Gbp. Genome annotation reveals 20,172 protein-coding genes in the G. agassizii assembly, and that gene structure is more similar to chicken than other turtles. We provide a series of comparative analyses demonstrating (1) that turtles are among the slowest-evolving genome-enabled reptiles, (2) amino acid changes in genes controlling desert tortoise traits such as shell development, longevity and osmoregulation, and (3) fixed variants across the Gopherus species complex in genes related to desert adaptations, including circadian rhythm and innate immune response. This G. agassizii genome reference and annotation is the first such resource for any tortoise, and will serve as a foundation for future analysis of the genetic basis of adaptations to the desert environment, allow for investigation into genomic factors affecting tortoise health, disease and longevity, and serve as a valuable resource for additional studies in this species complex.

Data Availability: All genomic and transcriptomic sequence files are available from the NIH-NCBI BioProject database (accession numbers PRJNA352725, PRJNA352726, and PRJNA281763). All genome assembly, transcriptome assembly, predicted protein, transcript, genome annotation, repeatmasker, phylogenetic trees, .vcf and GO enrichment files are available on Harvard Dataverse (doi:10.7910/DVN/EH2S9K).

ContributorsTollis, Marc (Author) / DeNardo, Dale F (Author) / Cornelius, John A (Author) / Dolby, Greer A (Author) / Edwards, Taylor (Author) / Henen, Brian T. (Author) / Karl, Alice E. (Author) / Murphy, Robert W. (Author) / Kusumi, Kenro (Author)
Created2017-05-31