Date Published: April 5, 2017
Publisher: Public Library of Science
Author(s): David E. Carlson, Marshal Hedin, Matjaž Kuntner.
Next-generation sequencing technology is rapidly transforming the landscape of evolutionary biology, and has become a cost-effective and efficient means of collecting exome information for non-model organisms. Due to their taxonomic diversity, production of interesting venom and silk proteins, and the relative scarcity of existing genomic resources, spiders in particular are excellent targets for next-generation sequencing (NGS) methods. In this study, the transcriptomes of six entelegyne spider species from three genera (Cicurina travisae, C. vibora, Habronattus signatus, H. ustulatus, Nesticus bishopi, and N. cooperi) were sequenced and de novo assembled. Each assembly was assessed for quality and completeness and functionally annotated using gene ontology information. Approximately 100 transcripts with evidence of homology to venom proteins were discovered. After identifying more than 3,000 putatively orthologous genes across all six taxa, we used comparative analyses to identify 24 instances of positively selected genes. In addition, between ~ 550 and 1,100 unique orphan genes were found in each genus. These unique, uncharacterized genes exhibited elevated rates of amino acid substitution, potentially consistent with lineage-specific adaptive evolution. The data generated for this study represent a valuable resource for future phylogenetic and molecular evolutionary research, and our results provide new insight into the forces driving genome evolution in taxa that span the root of entelegyne spider phylogeny.
The rise of high throughput sequencing technologies (also known as next-generation sequencing, hereafter NGS) has created new research opportunities in many fields of biology, including evolutionary biology and systematics (e.g., [1,2]). For non-model organisms, shotgun sequencing of a transcriptome can be a useful and cost-effective means of gaining insight into genome-wide biological processes (). One way that transcriptomic data have been used to study molecular and organismal evolution is through comparative analyses of sequences from multiple taxa. Comparative transcriptomics has been used, for example, to detect positive selection in genomes ([4,5]), estimate transcriptome-wide rates of molecular evolution (), and resolve difficult phylogenetic questions (e.g., [2,7–9]).