Infection with respiratory syncytial virus (RSV) can result in a wide spectrum of pulmonary manifestations, from mild upper respiratory symptoms to severe bronchiolitis and pneumonia. Although there are several known risk factors for severe RSV disease, namely, premature birth, chronic lung disease, congenital heart disease, and T cell immunodeficiency, the majority of young children who develop severe RSV disease are otherwise healthy children. Genetic susceptibility to RSV infection is emerging as a complex trait, in which many different host genetic variants contribute to risk for distinct disease manifestations. Initially, host genetic studies focused on severe RSV disease using the candidate gene approach to interrogate common single nucleotide polymorphisms (SNPs). Many studies have reported genetic associations between severe RSV bronchiolitis and SNPs in genes within plausible biological pathways, such as in innate host defense genes (SPA, SPD, TLR4, and VDR), cytokine or chemokine response genes (CCR5, IFN, IL6, IL10, TGFB1), and altered Th1/Th2 immune responses (IL4, IL13). Due to the complexity of RSV susceptibility, genome studies done on a larger scale, such as genome-wide association studies have certainly identified more of the host factors that contribute to the development of severe RSV bronchiolitis or excessive pathology. Furthermore, whole-genome approaches can reveal robust associations between genetic markers and RSV disease susceptibility. Recent introduction of 'exome' genotyping or sequencing, which specifically analyzes the majority of coding variants, should be fruitful in sufficiently large, well-powered studies. The advent of new genomic technologies together with improved computational tools offer the promise of interrogating the host genome in search of genetic factors, rare, uncommon, or common that should give new insights into the underlying biology of susceptibility to or protection from severe RSV infection. Careful assessment of novel pathways and further identification of specific genes could identify new approaches for vaccine development and perhaps lead to effective risk modeling.