Jeremy Rio

PhD Student in Anthropology & Evolutionary Simulations

  • T: +41 22 379 69 65
  • office 4-406 (Sciences II)
  • Investigating population continuity with ancient DNA under a spatially explicit simulation framework. BMC Genet. 2017 Dec;18(1):114. 10.1186/s12863-017-0575-6. 10.1186/s12863-017-0575-6. PMC5731203.


    Recent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples.

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  • Temporal fluctuations in the environment and intra-specific polymorphism: A model simulating the flowering phenology of gorse (Ulex europaeus)


    The onset and conservation of genetic polymorphism is a major question in evolutionary ecology. The influence of temporal fluctuations in the environment was invoked by early theorists such as J.B.S. Haldane and S. Jayakar in a controversial article published in, 1963, but their frequently cited model has almost never been used with empirical evidence. In this paper, we present a simulation model inspired by the biology of common gorse (Ulex europaeus), a species which shows polymorphism of flowering phenology: long flowering plants produce flowers from winter to spring and short flowering plants only flower in the spring. The early fruits of the former run the risk of frost, but largely escape seed predation, while those of the latter escape the risk of frost but are subject to a strong risk of seed predation. These two selection pressures vary unpredictably from year to year, making this flowering phenotype a good candidate to test Haldane and Jayakar’s model. Assuming that both flowering types are determined by a single major locus, we devise a simulation model firstly in a diploid form, and secondly by taking into account the hexaploid characteristic of gorse. Our results show that the combination of the two selective pressures acting on gorse flowering phenology can lead to fitness values meeting the Haldane and Jayakar’s conditions on geometric and arithmetic means, and to long term maintenance of polymorphism. In addition, the values of the parameters allowing polymorphism persistence and the relative proportions obtained are in agreement with values observed in natural populations. We also show that hexaploidy strongly increases the range of parameters in which polymorphism is self sustaining. These results are discussed in the context of climatic change, where increases of both mean temperature and its variance are predicted.

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