The goal of this project is to compare patterns of functional variation in the genomes of ancient and modern human populations. DNA from at least 50 ancient human individuals from a range of time periods (6300 BC- 400 BCE, with at least 10 individuals from each time period) and locations in Bulgaria will be extracted from teeth and sequenced using a recently developed method for targeted whole-genome capture followed by whole-genome sequencing. This will be the first study to obtain genome sequences from populations of ancient individuals from a range of time periods. The results will be analyzed to determine the genetic relationships of these individuals to other ancient individuals and to modern populations. In addition, functional variation in these genomes will be examined to test the hypothesis that variation, including the load of deleterious mutations, has increased over the last 10,000 years as a result of the human population explosion produced by the invention of agriculture. This hypothesis, predicted by population genetic theory, can be most directly tested using ancient DNA. I will accomplish these goals through three specific aims: First, I will sequence ancient DNA from the teeth of 50 individuals from different geographical areas and time periods in Bulgaria. The extracted DNA will first be subjected to targeted whole-genome capture to enrich for endogenous sequences, and the resulting library will be sequenced at low coverage using Illumina technology to assess the levels of human DNA in the samples. DNA from at least 50 samples that pass strict quality control criteria will then be sequenced to higher levels of coverage. Secondly, I will use autosomal, mitochondrial, and Y-chromosomal variation to trace population identities and movements over time. I will determine the mitochondrial and Y-chromosomal haplogroups of the ancient individuals and compare them to those of modern populations. In addition, I will use the whole-genome sequencing data to analyze autosomal variation in these ancient genomes by comparing to reference panels including 1,000 Genomes, the Population Reference Sample (POPRES), and the Human Genome Diversity Panel (HGDP). Finally, I will compare patterns of functional variation in ancient and modern human genomes. I will categorize variation in ancient and modern genomes using three criteria: impact on the amino acid sequence;functional prediction by computational methods based on evolutionary conservation and effect on protein structure;and presence in databases of human disease mutations. I will then compare the relative frequency of putatively damaging vs. putatively neutral variants in the ancient vs. modern genomes to assess whether, as predicted by theory, modern-day populations have accumulated a disproportionate number of deleterious variants. The results of these analyses could shed light on the demographic processes that determined the spectrum of functional variation in modern and ancient human populations. !

Public Health Relevance

Recent studies have found that rare and de novo mutations play an important role in the etiology of complex diseases such as type II diabetes and autism. Population genetic analyses suggest that the levels of this type of variation in the genome have increased over the past 10,000 years of human population growth;however, this theory can only be directly tested by comparisons with ancient human genomes. This study will be the first to compare ancient and modern human genomes in order to illuminate the demographic processes that generated the spectrum of variation, including disease-causing mutations, present in populations today. !

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32HG007342-02
Application #
8657386
Study Section
Special Emphasis Panel (ZRG1-F08-Q (20))
Program Officer
Junkins, Heather
Project Start
2013-05-01
Project End
2016-04-30
Budget Start
2014-05-01
Budget End
2015-04-30
Support Year
2
Fiscal Year
2014
Total Cost
$53,282
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305