RT Journal Article SR Electronic T1 STAGdb: a 30K SNP genotyping array and Science Gateway for Acropora corals and their dinoflagellate symbionts JF bioRxiv FD Cold Spring Harbor Laboratory SP 2020.01.21.914424 DO 10.1101/2020.01.21.914424 A1 S.A. Kitchen A1 G. Von Kuster A1 K.L. Vasquez Kuntz A1 H.G. Reich A1 W. Miller A1 S. Griffin A1 Nicole D. Fogarty A1 I.B. Baums YR 2020 UL http://biorxiv.org/content/early/2020/01/23/2020.01.21.914424.abstract AB Standardized identification of genotypes is necessary in animals that reproduce asexually and form large clonal populations such as coral. We developed a high-resolution hybridization-based genotype array coupled with an analysis workflow and database for the most speciose genus of coral, Acropora, and their symbionts. We designed the array to co-analyze host and symbionts based on bi-allelic single nucleotide polymorphisms (SNP) markers identified from genomic data of the two Caribbean Acropora species as well as their dominant dinoflagellate symbiont, Symbiodinium ‘fitti’. SNPs were selected to resolve multi-locus genotypes of host (called genets) and symbionts (called strains), distinguish host populations and determine ancestry of the coral hybrids in Caribbean acroporids. Pacific acroporids can also be genotyped using a subset of the SNP loci and additional markers enable the detection of symbionts belonging to the genera Breviolum, Cladocopium, and Durusdinium. Analytic tools to produce multi-locus genotypes of hosts based on these SNP markers were combined in a workflow called the Standard Tools for Acroporid Genotyping (STAG). In the workflow the user’s data is compared to the database of previously genotyped samples and generates a report of genet identification. The STAG workflow and database are contained within a customized Galaxy environment (https://coralsnp.science.psu.edu/galaxy/), which allows for consistent identification of host genet and symbiont strains and serves as a template for the development of arrays for additional coral genera. STAG data can be used to track temporal and spatial changes of sampled genets necessary for restoration planning as well as be applied to downstream genomic analyses.