RT Journal Article
SR Electronic
T1 Development of an integrated genomic map for a threatened Caribbean coral (<em>Orbicella faveolata</em>)
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 183467
DO 10.1101/183467
A1 Jacob Snelling
A1 Katherine Dziedzic
A1 Sarah Guermond
A1 Eli Meyer
YR 2017
UL http://biorxiv.org/content/early/2017/10/03/183467.abstract
AB Genomic methods are powerful tools for studying evolutionary responses to selection, but the application of these tools in non-model systems threatened by climate change has been limited by the availability of genomic resources in those systems. High-throughput DNA sequencing has enabled development of genome and transcriptome assemblies in non-model systems including reef-building corals, but the fragmented nature of early draft assemblies often obscures the relative positions of genes and genetic markers, and limits the functional interpretation of genomic studies in these systems. To address this limitation and improve genomic resources for the study of adaptation to ocean warming in corals, we’ve developed a genetic linkage map for the mountainous star coral, Orbicella faveolata. We analyzed genetic linkage among multilocus SNP genotypes to infer the relative positions of markers, transcripts, and genomic scaffolds in an integrated genomic map. To illustrate the utility of this resource, we tested for genetic associations with bleaching responses and fluorescence phenotypes, and estimated genome-wide patterns of population differentiation. Mapping the significant markers identified from these analyses in the integrated genomic resource identified hundreds of genes linked to significant markers, highlighting the utility of this resource for genomic studies of corals. The functional interpretations drawn from genomic studies are often limited by the availability of genomic resources linking genes to genetic markers. The resource developed in this study provides a framework for comparing genetic studies of O. faveolata across genotyping methods or references, and illustrates an approach for integrating genomic resources that may be broadly useful in other non-model systems.