Ancient Population Genomics

Abstract

Recent advances in genome sequencing technologies and the rapid decline in the cost of sequencing have enabled researchers to study the genomics of ancient populations. In the past decade, ancient population genomic studies led to a number of important discoveries that revealed the (1) relationship between modern and archaic humans such as Neanderthals and Denisovans, (2) contribution of ancient but anatomically modern humans to the ancestry of populations living today, (3) temporal dynamics of ancient population sizes in response to climate change, (4) role of natural selection in shaping the evolution of phenotypes, (5) origins of animal domestication, (6) divergence times between ancient and modern populations and (7) evolution of human pathogens.

Key Concepts

  • Ancient population genomics revolutionised our understanding about past evolutionary and demographic events.
  • Rate of evolution could be estimated using time‐stamped ancient samples.
  • Ancient DNA studies revealed the rise and fall of mammalian population sizes in response to climate change.
  • Reconstructing extinct genomes helped to decipher the signatures of genetic admixture between archaic and modern humans.
  • Present‐day Europeans were derived from three ancient human populations.
  • Ancient genomes helped us to understand the role of adaptive evolution in the past.

Keywords: ancient DNA; population genomics; archaic admixture; natural selection; effective population size; migration; domestication; population phylogeny; divergence time

Figure 1. Estimating the rate of evolution using time‐stamped ancient and modern penguin mitochondrial DNA sequences. The carbon‐dated age of penguin bones excavated from the Antarctic can be used as the time for the tips of penguin lineages. The difference in the branch lengths (Δd = d1− d2) between two time‐stamped tips will provide the number of mutations accumulated over the time elapsed (Δt = t1− t2). Hence the rate of evolution can be calculated as r = Δd/Δt.
Figure 2. Temporal pattern of population size variations in response to climate change. The ancestral effective population sizes of horse over time were estimated using mitochondrial and nuclear genome data through Bayesian skyline plot and pairwise sequentially Markovian coalescent (PSMC) methods, respectively. The population sizes reached a peak around 30 Kyr and declined sharply after that because of the drastic reduction in the temperature during the Last Glacial Maximum (LGM). Data obtained from Orlando et al. 2013.
Figure 3. (a) Pictorial representation of genetic admixture between archaic (Neanderthal) and modern (non‐African) humans. The F1 generation contains one chromosome from each parent. The proportion of Neanderthal genome fades away over time because of subsequent breeding with modern humans. Note that the ancient but anatomically modern humans have higher proportion (and longer tracts) of Neanderthal genome than contemporaneous non‐Africans. (b) Admixture between archaic (extinct) and modern genomes of human, cattle, horse and dogs. The level of admixture was determined by the D‐statistics developed specifically for this purpose. Data from Green et al. 2010; Reich et al. 2010; Schubert et al. 2014b; Park et al. 2015 and Skoglund et al. 2015.
Figure 4. Ancestral contribution of three ancient populations to all Europeans living today. The proportions of Western Hunter‐Gatherer (WHG), Early European Farmers (EEF) and Ancient North Eurasians (ANE) in a number of modern populations across Europe are shown. Note a gradual decline in the WHG (and increase in EEF) ancestry from North to Southern Europe. Data from Lazaridis et al. 2014.
Figure 5. Derived allele frequencies (DAF) of four SNPs in ancient and modern genomes of Europe. The average of the DAFs of three ancient (ANE, EEF and WHG) populations is shown in blue columns. Similarly, the orange columns show the mean DAFs calculated from four modern European populations (Spanish, Italian, British and Utah Americans). The error bars denote the standard error of the mean. Data obtained from Mathieson et al. 2015.
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Further Reading

Leonardi M, Librado P, Der Sarkissian C, et al. (2017) Evolutionary patterns and processes: lessons from ancient DNA. Systematic Biology 66: e1–e29.

Morozova I, Flegontov P, Mikheyev AS, et al. (2016) Toward high‐resolution population genomics using archaeological samples. DNA Research 23: 295–310.

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Paijmans JL, Gilbert MT and Hofreiter M (2013) Mitogenomic analyses from ancient DNA. Molecular Phylogenetics and Evolution 69: 404–416.

Slatkin M and Racimo F (2016) Ancient DNA and human history. Proceedings of the National Academy of Sciences of the United States of America 113: 6380–6387.

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Subramanian, Sankar(Feb 2018) Ancient Population Genomics. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0027512]