Fertility is arguably a very important economic trait in dairy cattle. Despite recent advances, reproductive performance remains suboptimal in most dairy herds, resulting in significant economic losses for the dairy industry. Recent studies suggest that a significant percentage of reproductive failure is attributable to bull subfertility. As such, our main objective was to dissect the genetic architecture of sire fertility in US Jersey cattle. The data set included 1.5k Jersey bulls with sire conception rate (SCR) records and 96k single nucleotide polymorphism (SNP) markers spanning the whole genome. The analysis included whole-genome scans for both additive and non-additive effects, and subsequent functional enrichment analyses using KEGG Pathway, Gene Ontology (GO) and Medical Subject Headings (MeSH) databases. The association analyses identified 10 different regions associated with Jersey bull fertility. These 10 1.5 Mb SNP windows jointly accounted for roughly 7% of the SCR additive genetic variance. Several candidate genes were annotated in these regions, such as PKDREJ, STX2, PDHB, and RhoA. These genes are directly involved in spermatogenesis, sperm differentiation, sperm capacitation and fertilization process. Moreover, the non-additive scan revealed 3 putative fertility genes, FER1L5, CNNM4 and DNAH3, with marked recessive effects. The gene-set analysis identified several significant functional terms, including gap junction, MAPK signaling pathway, regulation of cation channel activity, pyrophosphatase activity, synaptic vesicle exocytosis, GTPase activity, membrane fusion, and calcium channels. Most of these terms are known to be involved in biological processes and functions closely related to male fertility. Overall, our results contribute to the identification of genomic regions and pathways underlying sire fertility in Jersey cattle, which may point out new strategies for improving service sire fertility via marker-assisted selection.