Integrative genomics combines data from different ‘omic sources to link genotypes and phenotypes with the aim of unravelling biological networks and pathways that undergird complex traits, particularly with respect to disease. In this respect, integrative genomics using population and functional genomic data can be employed to understand evolutionary processes that have shaped adaptation to infectious diseases in domestic cattle. This approach can be particularly informative for African cattle, which exhibit a complex mosaic of Bos taurus (taurine) and Bos indicus (indicine) genomic ancestry. Some African taurine populations have an important evolutionary adaptation known as trypanotolerance, a genetically determined tolerance of infection by trypanosome parasites (Trypanosoma spp.) that cause African animal trypanosomiasis (AAT) disease. AAT is one of the largest constraints to livestock production in sub-Saharan Africa and causes a financial burden of approximately $4.5billion annually. In this study we identified putative candidate genes underlying trypanotolerance through the integration of local ancestry inference (LAI) from genome-wide SNP data for multiple trypanotolerant and trypanosusceptible hybrid cattle populations with RNA-seq and expression microarray transcriptomics data from multiple tissues collected across time course trypanosome infection experiments. These candidate genes included AGO2, CBL, CNOT1, EDN1, IL1B, NFKB1, RIPK1, and TRAF2. Functional analysis of the gene set outputs from this work highlighted GO terms associated with the immune system (including the major histocompatibility complex – MHC) and cell signalling processes. These results signpost future work to elucidate the cellular networks and pathways that drive trypanotolerance.