In Africa, where Anopheles gambiae is the primary vector, the intensity of transmission and the spread of resistance in parasite and vector populations pose major challenges to malaria control. New insecticides and novel vector control strategies complementary to existing ones are badly needed. Foundational genomic resources for novel vector-based strategies are newly available for An. gambiae. Together, they enable detailed population genomics and genome-wide association studies (GWAS) aimed at understanding the genetic basis of epidemiologically important traits. However, An. gambiae is highly polymorphic for chromosomal inversions. Failing to account for inversions can mislead population genetic and genome-wide association studies and obscure relationships between inversions and epidemiologically relevant traits. Yet despite rapid advances in genome technology, cytogenetic determination of inversion status is the only method currently available. Inversion status is not obvious from genome re-sequencing data, as alleles are mapped to their position on a reference genome and not to their actual physical locations. Unfortunately, cytogenetic analysis is impractical or even prohibitive. Addressing this gap, the central goal of this R01 is to develop and validate computational and molecular inversion genotyping approaches, enabling a modern assessment of the association between inversions and epidemiologically relevant traits. Toward this end, we propose three specific Aims: (1) Develop a computational karyotyping approach applicable to SNP genotype data. Our preliminary data for two inversions, based on existing Ag1000G sequences, indicates that there are SNPs that can serve as surrogate markers for alternative orientations. Using field-collected mosquitoes of known karyotype and with sequencing support from Ag1000G, we will validate these results on wider geographic samples and extend them to additional inversions. (2) Develop a molecular karyotyping approach applicable without sequencing. Using an existing battery of karyotyped samples, we will develop simple and rapid molecular assays that eliminate the need to PCR amplify across variable breakpoint regions, and are accessible to any lab. (3) Assess the association between karyotype and malariologically important parameters. Leveraging existing An. gambiae samples, we will apply our computational and molecular karyotyping methods to test for a relationship between karyotype, indoor resting behavior, and parasite rate. Together, these tools will empower efforts to map and monitor epidemiologically important traits in vector populations.