Abstract
The continual loss of threatened biodiversity is occurring at an accelerated pace. High-throughput sequencing technologies are now providing opportunities to address this issue by aiding in the generation of molecular data for many understudied species of high conservation interest. Our overall goal of this study was to begin building the genomic resources to continue investigations and conservation of the Spot-Tailed Earless lizard. Here we leverage the power of high-throughput sequencing to generate the liver transcriptome for the Northern Spot-Tailed Earless Lizard (Holbrookia lacerata) and Southern Spot-Tailed Earless Lizard (Holbrookia subcaudalis), which have declined in abundance in the past decades, and their sister species, the Common Lesser Earless Lizard (Holbrookia maculata). Our efforts produced high quality and robust transcriptome assemblies validated by 1) quantifying the number of processed reads represented in the transcriptome assembly and 2) quantifying the number of highly conserved single-copy orthologs that are present in our transcript set using the BUSCO pipeline. We found 1,361 1-to-1 orthologs among the three Holbrookia species, Anolis carolinensis, and Sceloporus undulatus. We carried out dN/dS selection tests using a branch-sites model and identified a dozen genes that experienced positive selection in the Holbrookia lineage with functions in development, immunity, and metabolism. Our single-copy orthologous sequences additionally revealed significant pairwise sequence divergence (~.73%) between the Northern H. lacerata and Southern H. subcaudalis that further supports the recent elevation of the Southern Spot-Tailed Earless Lizard to full species.
Highlights
The continuing reduction of per-base costs of high-throughput sequencing (HTS) methodologies has provided new opportunities to generate large-scale genomic and transcriptomic resources
With hundreds to thousands of variable sites, HTS datasets can be beneficial for species management by providing high resolution and accurate inferences of important parameters such as genetic diversity, inbreeding depression, effective population size [9,10], as well as historical demography and local adaptations
By using millions of short reads generated by massive parallel sequencing of complementary DNA (cDNA) libraries and robust assembly methods [15,16], one can generate a high coverage de novo transcriptome assembly without the need for a reference genome
Summary
The continuing reduction of per-base costs of high-throughput sequencing (HTS) methodologies has provided new opportunities to generate large-scale genomic and transcriptomic resources. With the low cost of HTS, it is possible to rapidly generate hundreds to thousands of genetic markers from multiple individuals and populations to assay genetic diversity for virtually any species [7] These larger datasets can overcome some of the limitations of traditional methods used in conservation genetics that yield only a few variable loci [8]. With hundreds to thousands of variable sites, HTS datasets can be beneficial for species management by providing high resolution and accurate inferences of important parameters such as genetic diversity, inbreeding depression, effective population size [9,10], as well as historical demography and local adaptations. The usage of gene expression data for conservation biology is an emerging field that will significantly benefit wildlife management [19]
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