Estimating and disentangling the contribution of different evolutionary processes such as genetic drift, mutation or gene flow is a central issue in statistical population genetics. The genetic configuration of a population is affected by its past demography. Thus, the demographic structure of a population can be inferred from genetic data; even if one is primarily interested in detecting where selection acts on the genome, demography has to be accounted for. Stefanie Belohlavy is finding ways to use haplotype structure to disentangle signals of selection from ancestral population structure; we have applied this method to help analyse a selection experiment on mice (Castro wet al., 2019). Parvathy Surendranadh is testing methods for demographic inference against the Antirrhinum data. Sean Stankowski and Daria Shipilina (Uppsala Univ.) are working with Frank Chan (MPI Tübingen) to use “haplotagging” to better understand how selection and population structure interact (Meier et al., 2020).
Lohse, K., Chmelik, M., Martin, S.H., Barton, N.H. 2016. Efficient strategies for calculating blockwise likelihoods under the coalescent. Genetics 202: 775-786
Castro, J.P.L., Marchini, M., Belohlavy, S., Yancoskie, M.N., Kucka, M., Beluch, W.H., Naumann, R., Barton, N.H., Rolian, C., Chan, Y.F. 2019. An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice. eLife 8:e42014
Meier, J.I., Salazar, P.A., Kucka, M., Davied, R.W., Dreau, A., Aldas, I., Power, O.B., Nadeau, N.J., Bridle, J.R., Rolian, C., Barton, N.H., McMillan, O., Jiggins, C.D., Chan, Y.F. 2020. Haplotype tagging reveals parallel formation of hybrid races in two butterfly species. PNAS (subm)