Description from NSF award abstract:
The first explicit model of population differentiation and speciation in the deep-sea fauna, the depth-differentiation hypothesis, was formulated in the early 1990s. According to this theory, the potential for population differentiation decreases with depth because the bathyal zone (200- 4000 m) has stronger selective gradients and more opportunity for geographic isolation to impede gene flow than does the more extensive and environmentally uniform abyssal plain (>4000 m). To determine whether depth-related variation is genetic, and therefore a consequence of evolutionary change, the PI has developed new methods to extract and sequence mitochondrial DNA from archived deep-sea molluscan species collected in earlier expeditions that had been fixed in formalin and preserved in alcohol. These preliminary studies supported the depth-differentiation hypothesis. They also revealed the limitations of using preserved material. For this project, the PI describes 2 hypotheses about evolution in the deep sea that emerged from the previous work: 1) The depth differentiation hypothesis suggests population divergence decreases with depth; and 2) A strong break in population structure at 3300 m might represent an unrecognized phylogeographic barrier.
The PI will test each of these hypotheses with multiple independent loci using deep-sea protobranch bivalves and recently developed statistical phylogeographic and phylogenetic models. The aforementioned work relied on formalin-fixed tissues, restricting analyses to a single locus (mtDNA). Nuclear loci are essential as independent measures of population structure, gene flow and historical influences, but are also critical to establish whether some of the remarkable divergences the PI documented represent cryptic species. The new material collected during the previous round of funding allowed the PI to develop the necessary nuclear loci and assess their utility for this work. The primary focus of this proposal is to use these new markers to test each of these hypotheses and distinguish intra- versus inter-specific variation.
The deep-sea supports one of the most diverse and unique marine communities, the evolutionary and historical development of which is virtually unknown. The proposed research will contribute very significantly to answering the two most basic questions about evolutionary diversification in this vast and remote environment: Where does it occur, and how? Analysis of the strong bathymetric divergence in Deminucula atacellana will provide the first detailed investigation of potential incipient speciation in a deep-sea organism (apart from reducing environments) and possibly identify the scales and mechanisms involved. It will also create a solid conceptual and methodological context for future evolutionary studies in the deep sea and lay the groundwork for understanding bathymetric and geographic variation at much larger scales (e.g., among ocean basins or pan-Atlantic).
Related Publications:
Baco, AR, RJ Etter, PA Ribeiro, S von der Heyden, P Beerli, BP Kinlan. 2016. A synthesis of genetic connectivity in deep-sea fauna and implications for connectivity and marine reserve design. Molecular Ecology 25:3276-3298. doi:10.1111/mec.13689
Etter, R.J., and A.S. Bower. 2015. Dispersal and population connectivity in the deep North Atlantic estimated from physical transport processes. Deep Sea Research I 104:159-172. doi:10.1016/j.dsr.2015.06.009
Glazier, AE, and RJ Etter. 2017. Genetic divergence across an oxygen minimum zone. Marine Ecology Progress Series 577: 79–91. doi:10.3354/meps12239
Dataset | Latest Version Date | Current State |
---|---|---|
GenBank accession numbers for sequences from deep-sea protobranch bivalves collected on R/V Endeavor cruise EN447 in the Western North Atlantic (34-39N, 68-70W) in 2008 (Ev Deep Sea Molluscs II project) | 2016-09-23 | Final no updates expected |
Principal Investigator: Ron J. Etter
University of Massachusetts Boston (UMass Boston)
Contact: Ron J. Etter
University of Massachusetts Boston (UMass Boston)
Data Management Plan received by BCO-DMO on 01 Dec 2014. (35.67 KB)
12/02/2014