David E Reich
Harvard University, MA·Genetics
DNA recovered from ancient human remains lets researchers watch genetic change happen over thousands of years, instead of inferring it from people alive today. These changes reflect migrations and population mixing, which shape the gene variants people inherit and their disease risk.
- Fields
Genetics
Ecology & Evolution
Computer Science
- Topics
ancient DNA
aDNA
population genetics
- Grants
- 2 known grants, through Feb 2030
What they work on
- Assemble an ancient DNA time series of 34,000 West Eurasians, enough to measure natural selection coefficients as small as about 0.25%, and release it as a public resource before publication.
- Combine selection estimates over time with genome-wide association study (GWAS) variants to model the "selection architecture" of diverse complex traits.
- Carry out the first ancient DNA selection studies outside West Eurasia, analyzing about 1,000 individuals each from Brazil, the Andes and Mesoamerica spanning 10,000 years.
- Build an unbiased pipeline for processing ancient DNA, use it to reprocess the world's ancient DNA data, and extend admixture graphs and other software for inferring population history.
More about the research
They also reflect natural selection on traits. Two projects use ancient DNA this way. One builds better tools for reconstructing population history. The other uses very large ancient datasets to measure how selection shaped complex traits.
Why it matters
Knowing how history and natural selection shaped gene variants can help explain why disease risk differs between populations. It can also help geneticists find disease genes in mixed or founder populations. Public ancient DNA datasets and software, with data from the Americas as well as Europe, could make findings on complex traits and disease risk apply to more people.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Maanasa Raghavan
University of Chicago, IL·Genetics
Reconstruct the last ~8,000 years of South Asian population history, including migrations and admixture (the mixing of separate populations), by jointly generating and analyzing ancient and modern human genome datasets.
Mateus Gouveia
Morehouse School of Medicine, GA·Genetics·Early-career
Map subcontinental ancestries across Africa, the Americas, and Europe by assembling genome-wide data on roughly 75,000 ancestrally diverse individuals and applying current population genomics methods.
Xinjun Zhang
University of Michigan, MI·Genetics
Develop machine learning methods to detect archaic introgression from unknown 'ghost' archaic humans in East Asian genomes.
The school
Harvard University: 42 labs on PI Pages, $1.5B a year on research, 712 research doctorates a year.
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