Subterranean Fishes of the World

5618

2022

AIM 2022

25

Now published in G3

In recent years, non-traditional model organisms have become increasingly important for health and evolutionary research (Russel et al. 2017). These model organisms are necessary for some forms of research, as some diseases and evolutionary mechanisms can be studied only in specific species (Dutrillaux & Dutrillaux 2017; Aalkjaer & Wang 2021; Russel et al. 2017). The Mexican tetra is one such non-traditional model organism (McGaugh et al. 2020). This species consists of two morphs, a surface-dwelling and a cave-dwelling morph, which differ in key phenotypic features such as sleep, metabolism, and anxiety (McGaugh et al. 2020; Chin et al. 2018). Due to the homology between human and Mexican tetra genomes, these morphs are naturally occurring control and experimental groups with which to study the genetic basis of human disorders of sleep, metabolism, anxiety, and much more (Atukorala et al. 2019; Chin et al. 2018; Marandel et al. 2020; Jaggard 2020). Though Mexican tetra genetics research has proliferated in recent years, this surplus of data presents a challenge for researchers. There currently exists no central location in which to access Mexican tetra genetics data and no easy way to compare data from across studies and experimental contexts. To address this need, we created CaveCrawler, a web-based genetics inference tool which combines Mexican tetra genetics data from many studies to enable cross-study comparisons and identification of yet-to-be-answered research questions. CaveCrawler enables rapid parsing and comparison of transcription, statistical, and genome architecture data in the Mexican tetra, and new data can easily be integrated into this analysis tool. In addition to advancing research in the Mexican tetra, CaveCrawler’s open-source code can be adapted to incorporate data from other species, enabling researchers to create webbased genetics inference tools for their own non-traditional model organisms.

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