Repository series · ncbi-prjna613076

Population genomic analyses of the sea urchin, Echinometra sp. EZ, across an extreme environmental gradient

The study of genetic diversity and population structure in marine organisms is fundamental to our understanding of how species have evolved and diversified. Extreme environmental gradients represent excellent study systems to better understand the variables that mediate patterns of genomic variation between populations, and allow for more accurate predictions of how environmental change might affect marine species. The Persian/Arabian Gulf is extreme in both temperature and salinity while the adjacent Gulf of Oman has conditions more typical of tropical oceans. The sea urchin Echinometra sp. EZ inhabits both of these seas and plays a critical role in coral reef health as a grazer and bioeroder, but, to date, there have been no population genomic studies on urchins in this unique region. More broadly, there have been no regional studies investigating marine invertebrate species with similar life histories, such as long-lived, planktotrophic larvae, large population sizes, and large reproductive clutches. These traits, in theory, should homogenize populations, unless non-neutral processes are occurring. To this end, we generated a draft genome and a restriction-site associated DNA sequencing dataset from seven populations along an environmental gradient across the Persian/Arabian Gulf and the Gulf of Oman. Population structure analyses revealed a high degree of admixture between all sites, although there was population differentiation and significant pairwise FST values between the two seas. Preliminary results suggest migration is bidirectional between the seas and nine candidate loci were identified as being under putative natural selection, including one collagen gene. This study is the first to investigate the population genomics of a sea urchin from this extreme environmental gradient and is an important contribution to our understanding of the complex spatial patterns that drive genomic divergence.