Integrative genomics combines data from different omics 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, leveraging population and functional genomic data, can be employed to understand the 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 genomic ancestry from Bos taurus (taurine) and Bos indicus (indicine) populations. Some African taurine populations have an important evolutionary adaptation known as trypanotolerance, a genetically determined tolerance to infection by trypanosome parasites (Trypanosoma spp.) that cause African animal trypanosomiasis (AAT). AAT is one of the largest constraints to livestock production in sub-Saharan Africa and causes a financial burden of approximately $4.5 billion annually. In this study, we identified putative candidate genes underlying trypanotolerance by integrating local ancestry inference (LAI) from genome-wide SNP data across multiple trypanotolerant and trypanosusceptible hybrid cattle populations with RNA-seq and expression microarray transcriptomic 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.