‘Omics in the Northeast
We use genomic science to study an organism’s entire DNA. We identify species, estimate age, define population, and determine stock size using DNA markers.
Genomic science examines an animal’s or plant’s DNA directly, changing how we monitor marine ecosystems. While traditional genetics focuses on single genes, genomics allows us to study the entire genetic blueprint of organisms and their interactions with the environment. This advanced technology provides new lines of evidence-based fishery assessment and management. At the Northeast Fisheries Science Center, we use this technology to:
- Identify species using DNA in the environment
- Estimate animal ages with markers that attach to the DNA
- Define populations based on their genomic profile
- Use the DNA as a tag to estimate population size
Environmental DNA: the Ocean’s Genetic Footprint
Using water samples to detect and quantify marine life without physically capturing the animals.
Marine Communities & Biodiversity
By analyzing "fingerprints" left in the water, we can identify a wide array of species, from microbes to marine mammals. This is particularly useful for monitoring elusive species or those in hard-to-reach habitats like deep-sea corals and seamounts.
Predator-Prey & Food Webs
Environmental DNA allows for highly precise identification of prey items in stomach contents, such as for longfin and shortfin squid, providing new insights into the North Atlantic food web.
Methodological Innovation
We are leading the way in standardizing eDNA workflows, including the use of Smith-Root eDNA samplers and developing bioinformatics pipelines like ePlacer, which uses deep learning and biogeography to improve species identification accuracy.
Explore our comprehensive guide to Environmental DNA Research in the Northeast.
Epigenetic Ageing: a New Biological Clock
Revolutionizing stock assessments through DNA-based age determination.
In a critical collaboration with the Gloucester Marine Genomics Institute , we are developing an "epigenetic clock" for fish. This method uses DNA methylation patterns (chemical tags on the genome) to predict the age of fish like haddock and Atlantic cod.
Traditional aging requires the removal of ear bones (otoliths), which is time-intensive and lethal. Epigenetic ageing offers a potentially non-lethal,high-throughput alternative that can be applied to species where traditional ageing is difficult or impossible, ensuring more accurate data for sustainable fisheries management.
This work was recently highlighted in the NOAA 'Omics Strategy Report for its success in correlating genetic markers with validated otolith ages.
Population Genetics & Stock Identification
Understanding the "hidden" boundaries of fish stocks.
Resolving Management Units
Using advanced genomic techniques, we can distinguish between separate subpopulations and identify "cryptic" species that appear identical but are genetically distinct
Strategic Applications
Current studies on silver hake and monkfish are using these tools to evaluate whether existing management boundaries align with biological reality, helping to prevent overfishing of unique genetic groups
Close-Kin Mark-Recapture
Using genetic "family trees" to estimate population size.
By identifying related individuals (e.g., parent-offspring pairs) within a population, scientists can use statistical models to estimate the total abundance of a stock without the need for physical tagging.
We are preparing to apply close-kin mark-recapture to species like bluefin tuna, using larval samples collected from the Slope Sea to refine our understanding of this highly migratory and valuable stock.
AI & Bioinformatics: Powering ‘Omics
Developing the digital tools to process massive genetic datasets.
Cloud-Based Pipelines
We are migrating our analysis to the NOAA Google Cloud Platform to standardize how eDNA data is processed, ensuring it is findable, accessible, interoperable, and reusable.
Deep Learning
Our collaboration with the URI Institute for AI & Computational Research is building next-generation software to automate the classification of millions of eDNA sequences, significantly reducing the time between data collection and management advice.