Work in the Goldberg lab analyses modern and ancient genetic data from multiple species in the context of demographic, archeological, paleontological, and environmental records. We also have a strong interest in theory and methods development. Some ongoing interests are described below.




Image result for alouatta carayaEvolutionary models of disease
A new line of work in the lab aims to combine population genetics with classic mathematical models of disease transmission. Current work focuses on malaria epidemiology in Botswana & Brazil. We are also working on related, empirically-driven projects on human adaptation to disease pressures and yellow fever susceptibility in primates. 



Genetics of Admixed Populations
Admixed populations have been leveraged for the inference of population history, disease association studies, and identification of genomic regions under selection. However, the history of these populations is often more complex than captured by classical models. In particular, there may have been multiple waves of admixture over time, or non-random mating. We develop mechanistic models to study sex-biased admixture and assortative mating in recently admixed populations. Current work includes a collaboration with Sandra Beleza on assortative mating in the admixed population of Cape Verde.

Figure 3 from Goldberg et al. 2014.  For a single admixture event, the variance of the autosomal admixture fraction in a hybrid population as a function of the sex-specific contributions from a source population at three time points, g=1, g=2, g=8.



 Holocene Population Dynamics
The early and middle Holocene was a time of immense climatic and cultural change. We are interested in disentangling the interplay between human & animal demography, the environment, and cultural change, particularly in the Americas. This system can act as an important model for current climate change. 

Complex processes such as domestication, population expansions, and mass extinctions have far reaching effects and multiple causes. Therefore, incorporating data from multiple sources provides increased resolution. Towards this goal, we are developing methods for demographic inference leveraging archeology, ancient DNA, and modern genetic data. 

The figure depicts estimates for human-occupied area across South America from 3 to 2 ka.