Ancient genome sequencing technologies now provide the opportunity to study natural selection in unprecedented detail. Rather than making inferences from indirect footprints left by selection in present-day genomes, we can directly observe whether a given allele was present or absent in a particular region of the world at almost any period of human history within the last 10,000 years. Methods for studying selection using ancient genomes often rely on partitioning individuals into discrete time periods or regions of the world. However, a complete understanding of natural selection requires more nuanced statistical methods which can explicitly model allele frequency changes in a continuum across space and time. Here we introduce a method for inferring the spread of a beneficial allele across a landscape using two-dimensional partial differential equations. Unlike previous approaches, our framework can handle time-stamped ancient samples, as well as genotype likelihoods and pseudohaploid sequences from low-coverage genomes. We apply the method to a panel of published ancient West Eurasian genomes to produce dynamic maps showcasing the inferred spread of candidate beneficial alleles over time and space. We also provide estimates for the strength of selection and diffusion rate for each of these alleles. Finally, we highlight possible avenues of improvement for accurately tracing the spread of beneficial alleles in more complex scenarios.
Keywords: ancient DNA; diffusion; evolution; evolutionary biology; human; lactase persistence; natural selection; spatiotemporal inference.
Analyzing the genomes of our ancient ancestors can reveal how certain traits spread through the human population over the course of evolution. Mutations that make individuals better equipped to survive their environment are more likely to be passed on to the next generation and become more common. For example, a genetic variant that enables adult people to digest sugars in dairy products has become more common in humans over time. Yet evolution does not only happen across time: it transverses space as well. Modeling the geographic spread of such genetic mutations is challenging using existing methods. To overcome this, Muktupavela et al. developed a new computational method that uses modern and ancient human genomes to study the evolution of specific genetic variants across space and time. The tool can determine where certain variants first emerged, how quickly they spread across geographic areas, and how rapidly they became prevalent in human populations. Muktupavela et al. applied their new method, which was based on a previously published framework, to track the spread of two common genetic variations that have previously been reported to be subject to natural selection: one that allows adult humans to digest dairy products, and another associated with skin pigmentation. They found that the mutation that enabled dairy consumption originated around what is now southwestern Russia or eastern Ukraine. The variation then spread westward, becoming increasingly more common over the course of the Holocene. The mutation related to skin pigmentation emerged further south than the dairy-related variation, and then also spread westward. Massive human migrations during the Neolithic and Bronze Age eras may have helped disperse both variants. The model developed by Muktupavela et al. could help scientists track the geographic spread of other genetic variants in human populations, as well as provide new insights into how humans adapt to changing environmental conditions. Incorporating major events into the model, like mass migrations or glacial retreats, may lead to even more insights.
© 2022, Muktupavela et al.