McGhie, Megan
Comparative Transcriptomics of Patagonian Lizards (Liolaemus) and
Central-American Casque-headed Lizards (Corytophanidae)
Faculty Mentor: Jack Sites, Jr., Department of Biology

Introduction
This project aimed help identify some of the genomic basis of various phenotypic-genotypic
relationships among reptiles. These include the genetic basis of adaption in the following aims:
(1) the evolution of hemoglobin subunits and its relationship to high altitudes/hypoxia and (2)
comparative analyses on parity modes (oviparity, viviparity, and parthenogenesis). For these
purposes, we analyzed published data versus the new data form two charismatic groups of
lizards: (1) four species of the temperate Patagonian genus Liolaemus and (2) one species from
each of the Neotropical genera Corytophanes and Basiliscus (family: Corytophanidae). Both
clades have relative limited or no genomic/transcriptomic data, despite the interesting biological
questions surrounding the evolution of phenotypic adaptations and genetic basis of such
phenotypes. My research planned to focus on some of the basic issues on the phenotype–
genotype relationships in these two groups, specifically in tracing some of the details of genomic
changes associated with the evolution of these novel parity modes.

Methodology
I started by cleaning the raw sequence reads as they are generated in the BYU Genomic Center.
This process required running SnoWhite, a cleaning program for raw sequenced reads, for each
forward and reverse reads. Then, I proceeded to assembled the transcriptomes without a
reference genome (i.e., de novo) using Trinity after reduction of the data complexity by in silico normalization. I focused on transcriptomes of specific tissues that included organs with high
transcriptomic activity such as brain, liver, kidney, and gonads. After assembly, I annotated these
transcriptomes using BLASTx similar algorithms against curated databases (e.g., UNIPROT)
and the Anolis genome consortium database through the cluster facilities at the BYU
Supercomputer Facility. In parallel, I also performed the functional annotation using
InterProScan to identify the corresponding gene ontologies as well as a better characterization of
the genes expressed. The last step involved planned is the quantification of gene expression per
individual tissue sample, and then a comparison between species with contrasting parity modes
within and between the two study groups (Liolaemus and Corytophanidae). Additionally, I will
be performing the phylogenetic regression analyses that will relate the evolution protein primary
structure and life history traits. Both last steps have not been completed as of yet, and will be
performed in early 2017.

Results and Discussion
I have done four tissue samples (brain, liver, gonad, and eye) for Liolaemus crepuscularis. I also
did 8 different tissues for Project 7. I am working on 7 different tissues for Project 9. For each of
these tissues, I cleaned the raw reads, assembled de novo transcriptomes, and identified
corresponding gene ontologies. We plan to quantify gene expression and do phylogenetic
regression analyses for the tissues as well. For each step I have written scripts using bash and
python to run the programs needed, do pre- and post-processing, and other computational needs.
These scripts can be used for future work in the lab. I have learned much running the programs
needed, writing scripts, and understanding results. I ran into many problems that ultimately
brought me to learn and grow. These problems included lack of computational needs, figuring
out to run a program that didn’t have necessary documentation to understand easily, and being
able to analyze large files in general. Overcoming these problems helped me grow as a biologist
as well as a computer scientist. In order to do the comparison between parity modes, at the level
of transcriptomes, we need to make sure that the de novo assemblies are optimal. This will be
done in the coming months and the comparisons at the level of expression and gene homology
will follow. In the future, I would like to be able to optimize the processes needed for these
analyses. In order to best clean raw reads, pair sequences, and build transcriptomes a lot could be
improved.

Conclusion
Understanding phenotypic-genotypic relationships among reptiles can further evolutionary,
phylogenetic, and developmental research. Our method of building transcriptomes is a more
affordable option to ultimately open many options for understanding many biological features of
not only reptiles but any groups of interest. We hope to publish the transcriptomic data (target
journal: Genome Biology and Evolution). We also hope to complete parity comparative analyses
and publish (target journal: Molecular Biology and Evolution or a multidisciplinary journal—
PNAS or PLoSBiology).