The 84th Annual Meeting of the American Association of Physical Anthropologists (2015)


Phenotypic inference from ancient DNA

IAIN MATHIESON1, WOLFGANG HAAK4, NICK PATTERSON1,2, SWAPAN MALLICK1, BASTIEN LLAMAS4, NADIN ROHLAND1, EADAOIN HARNEY1, SUZANNE NORDENFELDT1, KRISTIN STEWARDSON1, IOSIF LAZARIDIS1, JOSEPH PICKRELL9, ALAN COOPER4, GUIDO BRANDT5, NICOLE NICKLISCH5,6, HARALD MELLER6, KURT W. ALT5,6,7,8 and DAVID REICH1,2,3.

1Department of Genetics, Harvard Medical School, 2Broad Institute, 3Howard Hughes Medical Institute, Harvard Medical School, 4Australian Centre for Ancient DNA, University of Adelaide, 5Institute of Anthropology, Johannes Gutenberg University of Mainz, 6State Office for Heritage Management and Archaeology Saxony-Anhalt and State Heritage Museum Halle, 7Institute for Prehistory and Archaeological Science, University of Basel, 8Danube Private University, 9New York Genome Center

March 26, 2015 , Gateway Ballroom 2 Add to calendar

One of the most exciting consequences of recent developments in ancient DNA technology is that we have the ability to infer the phenotypes of ancient samples for traits that cannot be reliably inferred from skeletal remains. Important examples include pigmentation traits, dietary traits like lactase persistence and amylase copy number, and disease resistance mutations. These have relatively simple genetic architectures, but by using information from genome-wide association studies, and by genotyping many more sites, we can also predict the values of polygenic traits that are controlled by many loci, for example height, weight, and complex disease susceptibility. By investigating how they change through time, we can disentangle the effects of natural selection and population turnover in the evolution of these traits.

In this study, we present genetic data from a series of samples from seven archaeologically defined cultures in central Europe, ranging from 8000BCE to present. We have genotyped these samples at 390,000 genomic loci, including 30,000 which have known phenotypic effects. We then use this data to distinguish between traits that have changed consistently with population turnovers, traits that have changed apparently neutrally, and traits that have changed dramatically due to recent natural selection. Finally, we investigate whether we can detect selection in polygenic traits like height or weight.

These data demonstrate a powerful new source of information about ancient samples, and have the potential to teach us both about the specific traits of these populations, and also about the general mechanisms of evolution and adaptation in human history.