Simon Aeschbacher

I am a population geneticist interested in the evolution and maintenance of genetic diversity in natural populations. My focus is on the interplay of gene flow with natural selection, on how recombination mediates the effect of selection across genes, and on the impact of demography on the efficacy of natural selection. I study these interactions because they are key to better understanding local adaptation and speciation and because they inform us about the principal processes that create biological variation.

Unprecedented progress in DNA sequencing technology has shaped population genetics into a data-driven discipline. This offers novel opportunities to address long-standing questions in evolutionary biology, but requires appropriate models and innovative methodologies that apply to a genomic scale. Combining mathematics, population-genetic theory, and computational approaches, I build and analyse such models. I design inference procedures and apply them to a range of study systems in plants and animals, including humans.

Keywords: population genomics, speciation, local adaptation, human evolution, natural selection, gene flow, demographic inference, recombination

Education and professional positions

More detailed CV - 2023 (PDF, 409 KB)

• Laetsch DR, Bisschop G, Martin SH, Aeschbacher S, Setter D, and Lohse K (2023) Demographically explicit scans for barriers to gene flow using gIMble. PLoS Genetics 19(10):e1010999. DOI: 10.1371/journal.pgen.1010999
• Poyet F., Aeschbacher S., Thiéry A., Excoffier L. (2018). Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences. eLife 2018;7:e36317. DOI: 10.7554/eLife.36317
• Aeschbacher S., Selby JP., Willis JH., Coop G. (2017). Population-genomic inference of the strength and timing of selection against gene flow. Proceedings of the National Academy of Sciences of the United States of America 114 (27): 7061–7066. DOI: 10.1073/pnas.1616755114
• Jurić I., Aeschbacher S., Coop G. (2016). The strength of selection against Neanderthal introgression. PLoS Genetics 12 (11): e1006340. DOI: 10.1371/journal.pgen.1006340
• Yeaman S., Aeschbacher S., Bürger R. (2016). The evolution of genomic islands by increased establishment probability of linked alleles. Molecular Ecology 25 (11): 2542–2558. DOI: 10.1111/mec.13611
• Aeschbacher S., Bürger R. (2014). The effect of linkage on establishment and survival of locally beneficial mutations. Genetics 197 (1): 317–336. DOI: 10.1534/genetics.114.163477
• Aeschbacher S., Futschik A., Beaumont MA. (2013). Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates. Molecular Ecology 22 (4): 987–1002. DOI: 10.1111/mec.12165
• Aeschbacher S., Beaumont MA., Futschik S. (2012). A novel approach for choosing summary statistics in approximate Bayesian computation. Genetics 192 (3): 1027–1047. DOI: 10.1534/genetics.112.143164

For a full record of publications and reviewing activities, see ORCiD.