UCL Division of Biosciences


Past demography and natural selection on the human genome

Anatomically modern humans were restricted to Sub-Saharan Africa for most of their evolutionary history. Some 60-100k years ago, some populations started expanding and eventually colonised the entire world. This expansion exposed human populations to radically different selective pressures linked to diet, climate and pathogens. Later developments such as the Neolithic revolution (the invention of farming) led to further selective pressures on the human genome. We are interested in uncovering signals of these events in the human genome.

Climate and past human demography

The extent to which past climate change has dictated the pattern and timing of the out-of-Africa expansion by anatomically modern humans is currently unclear. In particular, the incompleteness of the fossil record makes it difficult to quantify the effect of climate. Here, we take a different approach to this problem; rather than relying on the appearance of fossils or archaeological evidence to determine arrival times in different parts of the world, we use patterns of genetic variation in modern human populations to determine the plausibility of past demographic parameters. We develop a spatially explicit model of the expansion of anatomically modern humans and use climate reconstructions over the past 120 ky based on the Hadley Centre global climate model HadCM3 to quantify the possible effects of climate on human demography. The combinations of demographic parameters compatible with the current genetic makeup of worldwide populations indicate a clear effect of climate on past population densities. Our estimates of this effect, based on population genetics, capture the observed relationship between current climate and population density in modern hunter-gatherers worldwide, providing supporting evidence for the realism of our approach. Furthermore, although we did not use any archaeological and anthropological data to inform the model, the arrival times in different continents predicted by our model are also broadly consistent with the fossil and archaeological records. Our framework provides the most accurate spatiotemporal reconstruction of human demographic history available at present and will allow for a greater integration of genetic and archaeological evidence.

Environmental adaptation

We are interested in understanding how species, and in particular humans, genetically adapted to their environment and how their pattern of DNA variation can be investigated to infer the organisms' evolutionary history. We are studying how Arctic populations (i.e. Inuit and polar bears) colonised the high Arctic region and adapted to cold climate and a lipid-rich diet (Liu et al. Cell 2014; Moltke et al. Am J Hum Genet. 2015). [1] We also collaborate with other research groups for population genetics analysis of model and non-model organisms, e.g. wild and domesticated horses (Jonsson et al. Proc Natl Acad Sci U S A. 2014; Schubert et al. Proc Natl Acad Sci U S A. 2014).

Human mitochondrial rates of substitution

Reliable estimates of the rate at which DNA accumulates mutations (the substitution rate) are crucial for our understanding of the evolution and past demography of virtually any species. In humans, we noticed considerable uncertainties around these rates, with substantial variation among recent published estimates. Substitution rates have traditionally been estimated by associating dated events to the root (e.g. the divergence between humans and chimpanzees) or to internal nodes in a phylogenetic tree (e.g. first entry into the Americas). However, the recent availability of ancient mtDNA sequences allows for a more direct calibration by assigning the age of the sequenced samples to the tips within the human phylogenetic tree. By estimating substitution rates using calibrations based both on dated nodes and tips, we demonstrated that, for the same dataset and considering an unified methodology, estimates based on individual dated tips are far more consistent with each other than those based on nodes and should thus be considered as more reliable.