Historical reconstruction using genetic sharing analysis - geographical models and Jewish history

Our history is imprinted in our genes: population structure and ancient migrations were found to be encoded in human genetic variation. With the revolution of high-throughput DNA genotyping and sequencing, history can now be uncovered in unprecedented detail.

I propose to develop new tools for geography-based historical reconstruction. Contrast to previous approaches, I will use sharing analysis- the study of the lengths of genomic segments shared between individuals. Recent algorithmic breakthrough of the host lab, combined with data from new sequencing technologies, enable now the use of this method, which is expected to be more informative compared to other approaches.

My first goal will be the application of sharing analysis to globally distributed populations. I will then attempt to explain the observed sharing statistics by constructing a geographical model that involves a series of colonization events. I will determine parameters such as migration and admixture rates and bottleneck sizes as those that best fit the data. I will also use our model to resolve long-standing debates over the nature of the distribution of migration rates.

I will also investigate Jewish genetics, for which the host lab has exclusive access to the largest existing collection of genetic variation data. I will study for the first time the relation between Jewish genetics and geography and create geographical models accordingly. Particular properties of Jewish history make its modeling in some cases relatively easy (e.g., one dimensional), and thus, models will be made highly detailed.