Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

During the June peak of seasonal flowering in 2019, divers on SCUBA collected a single vegetative shoot at each node within each sampling grid for genetic analysis (n=15 ramets per grid, 45 per depth, 90 per site). At approximately alternating nodes (i.e., 5-7 of the 15 nodes in each grid, depending on the location of bare patches), divers also harvested all shoots from within a 25 × 25 centimeter (cm) quadrat (n = 15-21 per depth) to estimate shoot density and canopy characteristics. Samples were returned to the lab on ice for processing. The second and third leaves of each genetic sample were preserved in silica.

After the flowering season and once seeds had dropped (September 2019; von Staats et al. 2021), we returned to each sampling grid to collect dispersed seeds. Sediment cores (10 cm in diameter and 10 cm in depth) were taken at three locations within each grid at Curlew Beach and at four locations within each grid at the other three field sites (n=9 or 12 cores per depth). Sediment cores were bagged and kept cold (4 degrees Celsius (°C)) until they could be processed; each core was hand-sieved for intact seeds within 3 days of collection. We counted all intact seeds encountered and assessed viability by firmness (the squeeze test; Marion and Orth 2010). Seeds deemed viable were individually weighed and stored in microfuge tubes and frozen at -80°C until DNA extraction.

Leaf samples (2 to 4 milligrams (mg) of dried tissue from the middle third of the leaf) were ground with a Retsch mixer mill MM400; seeds were ground by hand with a micropestle after removing the seed coat. DNA extraction was done with the Omega Bio-Tek E-Z 96 Tissue DNA kit, and samples were stored at -20°C. We prepared one genomic library of 464 individuals (359 adults, 105 seeds) by following the ddRADseq protocol of Parchman et al. (2012) and sequenced the library using two lanes of Illumina Novaseq. We digested gDNA with two restriction enzymes, EcoRI and MseI, and ligated adaptors containing unique 8-10bp barcodes to the digested DNA of each individual. The products were then PCR-amplified in two independent reactions with standard Illumina primers. All amplicons were pooled and shipped to the University of Texas Genomic Sequencing and Analysis Facility, which used Blue Pippen Prep to isolate the 300-450bp fraction. This fraction was then single-read-sequenced (approximately 100bp) with both lanes of an Illumina Novaseq machine. We used custom scripts to demultiplex into sample-specific FASTQ- formatted files.

These are the raw sequences from the Illumina sequencer after the demultiplex step (see methods above).

- Imported original file "BioSampleObjects_wLatLon_final.csv" into the BCO-DMO system.
- Renamed fields to comply with BCO-DMO naming conventions.
- Saved final file as "958698_v1_z_marina_genbank_accessions.csv".

NSF Award Abstract:
Understanding how species cope with spatial variation in their environment (e.g. gradients in light and temperature) is necessary for informed management as well as for predicting how they may respond to change. This project will examine how key traits vary with depth in common eelgrass (Zostera marina), one of the most important foundation species in temperate nearshore ecosystems worldwide. The investigators will use a combination of experiments in the field and lab, paired with fine-scale molecular analyses, to determine the genetic and environmental components of seagrass trait variation. This work will provide important information on the microevolutionary mechanisms that allow a foundation species to persist in a variable environment, and thus to drive the ecological function of whole nearshore communities. The Northeastern University graduate and Keene State College (KSC) undergraduate students supported by this project will receive training in state-of-the-art molecular techniques, as well as mentorship and experience in scientific communication and outreach. A significant portion of KSC students are from groups under-represented in science. Key findings of the research will be incorporated into undergraduate courses and outreach programs for high school students from under-represented groups, and presented at local and national meetings of scientists and stakeholders.

Local adaptation, the superior performance of "home" versus "foreign" genotypes in a local environment, is a powerful demonstration of how natural selection can overcome gene flow and drift to shape phenotypes to match their environment. The classic test for local adaptation is a reciprocal transplant. However, such experiments often fail to capture critical aspects of the immigration process that may mediate realized gene flow in natural systems. For example, reciprocal transplant experiments typically test local and non-local phenotypes at the same (often adult) life history stage, and at the same abundance or density, which does not mirror how dispersal actually occurs for most species. In real populations, migrants (non-local) often arrive at low numbers compared to residents (local), and relative frequency itself can impact fitness. In particular, rare phenotypes may experience reduced competition for resources, or relative release from specialized pathogens. Such negative frequency dependent selection can reduce fitness differences between migrants and residents due to local adaptation, and magnify effective gene flow, thus maintaining greater within-population genetic diversity. The investigators will combine spatially paired sampling and fine-scale molecular analyses to link seed/seedling trait variation across the depth gradient at six meadows to key factors that may drive these patterns: local environmental conditions, population demography, and gene flow across depths. The team will then experimentally test the outcome of cross-gradient dispersal in an ecologically relevant context, by reciprocally out-planting seeds from different depths and manipulating relative frequency in relation to both adults and other seedling lineages. The possible interaction between local adaptation and frequency-dependence is particularly relevant for Zostera marina, which represents one of the best documented examples of the ecological effects of genetic diversity and identity. Further, a better understanding of seagrass trait differentiation is not simply a matter of academic interest, but critical to successful seagrass restoration and conservation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF abstract:

During the 20th century, the Pacific oyster Crassostrea gigas was deliberately introduced from its native range of coastal Asia to the estuaries of six continents. While the introduced Pacific oysters are widely aquacultured and thus can generate local economic wealth, they sometimes outcompete native oysters, and can carry microbial, animal and plant hitchhikers that negatively impact local economies and the ecological functioning of local estuaries. This study comprehensively assesses the pathways and sources of Pacific oyster introductions using a worldwide, population genetic survey. Simultaneously, the study also assesses the pathways and source of one hitchhiking protist (Haplosporidium nelsoni) that causes the disease MSX (multinucleated sphere X) in the Virginia oyster (Crassostrea virginica) along the eastern seaboard of the United States. One goal of this research is to generate management strategies that combat the negative impacts of the Pacific oyster and its associated invaders, and minimize future invasions. A second goal is to minimize some uncertainty about the population biology of the devastating Haplosporidium parasite, and thus, increase confidence of policy makers who are managing shellfish health, restoration and commerce. By quantifying the pathways and sources of C. gigas, this project may inform strategies to combat negative impacts of C. gigas and its associated invaders, as well as minimize future invasions. Moreover, quantifying dispersal within and among populations of H. nelsoni along the US East Coast will provide perspective on the effectiveness of regional biosecurity measures in preventing the ongoing dispersal of this destructive pathogen via aquaculture. In addition, the project lends itself well to programs that foster critical thinking and research experience among both undergraduate and K-12 students. The project provides opportunities for 6-9 undergraduates to perform research, includes a 2-day workshop on bioinformatics for the wider undergraduate community, and facilitates ongoing opportunities for K-12 students to participate in citizen-science research.

There is a wealth of information on the source, pathways and vectors of C. gigas based largely on historical documents but no study has comprehensively tested whether these historical accounts are correct using a worldwide, population genetic survey. Using >14K single-nucleotide polymorphisms (SNPs) from 41 populations across five continents a high level of spatial genetic differentiation was found within the native range and differences in source populations among non-native regions. Preliminary genetic data indicated that the parasitic protist, Haplosporidium nelsoni arrived with C. gigas imports to the US Atlantic coastline and then infected the native C. virginica, however the native source populations, the pathways and vector from which H. nelsoni arrived remain unknown. This project couples high-throughput sequencing technologies and Approximate Bayesian Computing (ABC)-based models to answer the following: What are the population genomic patterns among C. gigas from native and non-native regions? What are the population genomic patterns of Haplosporidium nelsoni among Asian and North American Crassostrea gigas and eastern North American C. virginica? What were the source populations and invasion pathways of C. gigas and H. nelsoni? Identifying source locations, pathways and vectors of introduction of C. gigas will provide researchers with a null-model of invasion history for dozens of other non-native species that were transported with C. gigas. Currently, there are no verified 'vector maps' for historical shipments of C. gigas that are similar to those generated from modern-day or historical shipping records.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.