ORCID Identifier(s)

0000-0002-0879-8366

Graduation Semester and Year

2022

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Quantitative Biology

Department

Biology

First Advisor

Matthew Fujita

Abstract

The continual reduction of the cost of high-throughput sequencing is now making it feasible to sequence large genomic and transcriptomic datasets for non-model organisms. Many of these under study non-model organisms have no available molecular data available. Yet, many of these organisms are of interest for their usefulness in addressing long-standing unanswered questions in the field of evolutionary biology or of conservational concern and need immediate intervention. Now we can quickly generate large datasets for these organisms, and here we generate two large datasets for lizards that are both of in interest in the genus Holbrookia and Aspidoscelis. In chapter 1 we sequence the transcriptome for three lizard species in the genus Holbrookia who are of conservation interest as their populations are in decline. We aimed to generate the needed molecular needed for further conservation studies and identify adaptive loci. In chapter 2 we generated an extensive whole mitochondrial genome dataset for multiple lizards in the genus Aspidoscelis, whose genus contains multiple asexual and sexual reproducing lizards. In this chapter, we examined how the absence of sex influences the mitochondrial genome by comparing the asexual lizards' mitochondrial genomes to their sexual reproducing counterpart. In chapter 3 we begin developing further resources beyond only shot-gun sequencing genomes but develop a protocol to culture fibroblast cells from the tail tissues of lizards successfully. With additional resources beyond shot-gun sequence data, we can better address questions found in chapters 1 and 2.

Keywords

Genome, Evolution, Mutations, Natural Selection, Squamates, DNA

Disciplines

Biology | Life Sciences

Comments

Degree granted by The University of Texas at Arlington

30959-2.zip (2671 kB)

Included in

Biology Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.