PROJECT SUMMARY Infectious diseases are a major public health burden throughout the world. Tuberculosis (TB), caused by the pathogen Mycobacterium tuberculosis (Mtb), is estimated to kill nearly 2 million individuals worldwide every year alone. Notably, humans show remarkable differences in susceptibility to many pathogens, including Mtb. Arguably, this heterogeneity arises from variation in the immune response, which is responsible for preventing and controlling infection. Although a significant proportion of inter-individual variation in susceptibility to Mtb infection can be attributed to environmental factors, a substantial portion is due to host genetic factors. The importance of host genetic factors in susceptibility to clinical TB has been demonstrated by twin and family studies. However, the underlying genetic factors that drive inter-individual differences in susceptibility to Mtb infection remain largely unknown, especially at the population level. Using combined expertise in functional genomics, computational biology, human immunology, and population genetics, I propose to: (i) characterize the inter-individual and inter-population transcriptional variation in the innate immune response to Mtb infection; (ii) map expression quantitative trait loci (eQTLs) that are associated with variation in the response to Mtb infection ; and (iii) determine the role of recent positive selection in shaping ancestry-associated differences in gene expression. This work will yield unprecedented insight into the genetic determinants underlying inter-individual and population-associated variation in the transcriptional innate immune response to Mtb infection. Further, these efforts will establish innovative, novel, and empirically-grounded transcriptional profiling strategies to pinpoint highly-promising genetic candidates for Mtb susceptibility, which will allow us to identify the individuals who are at increased risk for TB, one of the greatest health burdens facing modern human populations.