Multi-genomic data provide an unprecedented opportunity to study many critical evolutionary processes in human and other populations. A particularly striking example is provided by the increasing use of joint nuclear-cytoplasmic data, where an individual's nuclear genes are inherited through both parents, while their cytoplasmically-housed genes, such as those in their mitochondria, are usually inherited solely through the mother. As a result of this asymmetrical inheritance, a population's joint nuclear-cytoplasmic makeup encodes invaluable information about many important processes that are not accessible by traditional means. Such data provide, for instance, the first effective way to study the distinctive patterns of assortative mating, selection, and migration within zones of genetic admixture between two populations, as well as the many gender-specific processes that shape the evolution of human and other animal populations. However, much of this vital biological information remains untapped due to the lack of adequate theory. The major long-term goal of this research is to develop the mathematical and statistical frameworks needed to fully exploit the immense evolutionary value of joint cytonuclear data.
One specific aim i s to identify the best method for detecting and estimating differential gene flow by males and females, which will allow unprecedented insight into human migrations. This will be achieved by developing a series of theoretical models to assess the utility of recent data involving novel combinations of cytoplasmic, autosomal and sex-linked marker. A second major goal is to provide the first formal cytonuclear guidelines for inferring the possible evolutionary processes in spatially structured populations, and the potential causes of the differential introgression often shown by autosomal, sex-linked, and cytoplasmic markers across such regions. The final major aim is to develop theory to understand the evolutionary implications of intriguing new forms of cytonuclear selection, including those in human mitochondrial diseases, where nuclear genes can trigger the mitochondrial mutations associated with the disease. Together, the results will allow empirical researchers to exploit standard cytonuclear systems with autosomal nuclear markers in exciting new ways, as well as to extract the unprecedented evolutionary information provided by cytonuclear systems with sex-linked markers. In addition, the general cytonuclear framework developed here has broad applicability to many other important biological systems, ranging from the evolution of mobile element suppressors to the coevolution of host-pathogen systems.
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