Programme Thesis
The NIH ancient DNA for Modern Genomics (aDMG) Research Projects (U01) programme funds interdisciplinary research that uses ancient DNA (aDNA) to address fundamental questions in human evolution, population history, and the genetic basis of modern diseases. It exists to leverage the unique temporal perspective of aDNA to uncover genetic variants and evolutionary pressures that influence present-day health and disease susceptibility.
Selection Criteria
- Scientific merit and innovation of the proposed research (scored on significance, investigator, innovation, approach, environment)
- Relevance to the aDMG mission: must use ancient DNA to inform modern human biology or disease
- Feasibility of aDNA extraction, sequencing, and analysis methods
- Strength of the multidisciplinary team (e.g., archaeologists, geneticists, clinicians)
- Data sharing and resource dissemination plan
- Budget justification and resource allocation
- Letters of support from collaborators and institutional commitment
Past Winners / Cohort Profiles
Past winners typically include established research teams at major universities or institutes (e.g., Harvard, UC Berkeley, Max Planck) with a track record in aDNA, population genetics, and bioinformatics. Archetypes are senior PIs with multi-PI consortia, often combining aDNA wet-lab expertise with computational genomics. Named examples are not listed on the page but common NIH U01 awardees include groups like David Reich's lab or Pontus Skoglund's team.
Ideal Candidate Fingerprint
The platonic ideal applicant is a mid-to-senior career researcher (PhD or MD/PhD) with a strong publication record in aDNA, population genetics, or evolutionary genomics, leading a multi-institutional team that includes archaeologists, ancient DNA specialists, and clinicians. They have access to unique ancient samples, established wet-lab protocols, and computational infrastructure for large-scale genomic analysis.
Recommended Framing
Eniola should frame their application around using ancient DNA to study the evolutionary history of addiction-related genes (e.g., dopamine receptors, opioid pathways) and how selective pressures in African populations may influence modern addiction vulnerability. Their CCT model and computational skills (TDA, Bayesian methods) can be positioned as a novel analytical framework to integrate aDNA data with modern pharmacogenomics, leveraging their Nigerian heritage and access to understudied African ancient genomes. The provisional patent and collaborations with Berridge/Gershman add credibility, but the proposal must pivot from pharmacology to evolutionary genomics.
Watch Out
Eniola is an independent researcher without a PhD or institutional affiliation, which is a major disadvantage for a U01 grant that typically requires a PI with a doctoral degree and a host institution. The programme explicitly requires a U01 mechanism, which is designed for established investigators with significant research infrastructure. Additionally, Eniola's background in pharmacology and computational neuroscience does not directly align with aDNA wet-lab work, and the proposal would need strong co-investigators with aDNA expertise. The deadline is not listed, but if it is imminent, Eniola lacks the team and sample access to compete.