Hereditary hearing loss is the most common sensory disorder, affecting 1 in 500 newborns. There are more than 538 million individuals with genetic hearing loss worldwide and this number is expected to grow to 1 billion over the next three decades. Currently, the only option for individuals with hearing loss is mechanical intervention such as hearing aids or cochlear implants. In the past decade, many studies have highlighted the need for personalized gene therapy or molecular intervention to treat genetic deafness. However, in order to fulfill this vision a comprehensive understanding of the intricate mutation-gene-phenotype nuances and relationships is required. Toward this goal, we unraveled novel mutation-gene-phenotype associations and mechanisms in four deafness-causing genes (CIB2, COL11A1, CEACAM16 and DFNA5), by using a combination of in-depth phenotyping, human genetics, cutting edge genomic technologies, murine mutant models, and functional assays. These novel insights revealed mutations in CIB2 do not cause Usher Syndrome, mutations in COL11A1 can cause either non-syndromic or syndromic hearing loss, CEACAM16-related deafness is due to two distinct mechanisms, loss of function and gain of function, and coding variants can influence mRNA assembly and cause DFNA5-related hearing loss. Elucidating these novel mutation-gene-phenotype relationships has improved our knowledge of the pathogenic mechanisms underlying hearing loss and provided much needed answers to individuals seeking a diagnosis for their deafness. Recognizing the complexities associated with genetic hearing loss and the challenges in interpreting the clinical significance of genetic variants, we established the first deafness-specific variant database, the Deafness Variation Database (DVD), which classifies over 876,000 variants across 152 deafness-associated genes. This breadth of data provided us with a unique opportunity to explore the molecular landscape of deafness. We show that over 96% of coding variants are rare and novel and that mutational signatures are unique to each gene and are driven by minor allele frequency thresholds, variant effect, and protein domain. The mutational landscape we define shows complex gene-specific variability, making an understanding of these nuances foundational for improved accuracy in variant interpretation. Overall the work presented in this thesis improves our understanding of deafness biology, identifies novel targets for therapeutics and enhances clinical decision-making.