CaveCrawler: An Interactive Analysis Suite for Cavefish Bioinformatics
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Date
2022-04-13
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Abstract
The growing use of genomics data in diverse animal models enables researchers to identify genomic and transcriptional differences between species and experimental groups. Genetics databases have played critical roles in establishing the most widely recognized genetic model organisms, such as fruit flies and mice, but most emerging model species for evolutionary biology research lack such databases. One such emerging model organism is the Mexican tetra, Astyanax mexicanus. This fish species exists as eyed surface populations and at least 30 cave populations, providing a system to study convergent evolution. Further, since the surface and cave morphs differ in phenotypes with clinical relevance, the Mexican tetra is an emerging model system for human disease. Though researchers are increasingly using genomic, transcriptional, and functional genetic approaches to study disease and evolution using this species, there currently exists no centralized database for accessing Mexican tetra genetics data and comparing results from across studies. We generated a web-based analysis suite which integrates datasets from different studies, then demonstrated the utility of our tool by identifying genes whose transcription and markers of selection differ between populations and across experimental contexts. Results of diverse studies can be analyzed in conjunction with each other and with other genetic data, such as Gene Ontology (GO) information, to enable biological inferences from across studies and identify future avenues of research. Furthermore, the framework that we have built for A. mexicanus can be adjusted for use in other emerging model systems, enabling research which is only possible in species not traditionally used in genetic analyses.
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evolution, genetics, Mexican tetra, astyanax mexicanus, model organisms, data repositories, R, shiny, next-generation sequencing, sleep