Genomic and transcriptomic reference assemblies and analyses with sequencing datasets from multiple non-traditional model species

High-throughput nucleic acid “Next-Generation” sequencing (NGS) methods have revolutionized the biological sciences over the past decade by facilitating research and discoveries at the whole-genome level. However, generating high-quality genome and transcriptome references and navigating downstream analyses still remain challenging and computationally-intensive endeavors, especially for non-model species. This dissertation focused on automating bioinformatics methods for two different projects with multiple non-model species: the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP) and differential expression analysis of gill epithelium from Fundulus North American killifish following salinity challenge. With these two projects, I sought to generate high quality de novo transcriptomes and genomes in a uniform and automated way. Three aims were addressed: how the re-analysis of old data with new tools affects the outcome of the reference assemblies, how to generate data and draft de novo assemblies for several high-quality reference genomes from nonmodel species in a cost-efficient manner, and how to generate high quality species-specific de novo transcriptomes and annotations using annotations from a closely-related model species reference. Furthermore, I used these de novo transcriptomes and annotations to examine gene expression responses of multiple species of Fundulus killifish to a common salinity challenge experiment.