Midbrain dopamine neurons are thought to signal reward prediction errors (RPEs) but the mechanisms underlying RPE computation, particularly contributions of different neurotransmitters, remain poorly understood. Here we used a genetically-encoded glutamate sensor to examine the pattern of glutamate inputs to dopamine neurons. We found that glutamate inputs exhibit virtually all of the characteristics of RPE, rather than conveying a specific component of RPE computation such as reward or expectation. Notably, while glutamate inputs were transiently inhibited by reward omission, they were excited by aversive stimuli. Opioid analgesics altered dopamine negative responses to aversive stimuli toward more positive responses, while excitatory responses of glutamate inputs remained unchanged. Our findings uncover previously unknown synaptic mechanisms underlying RPE computations; dopamine responses are shaped by both synergistic and competitive interactions between glutamatergic and GABAergic inputs to dopamine neurons depending on valences, with competitive interactions playing a role in responses to aversive stimuli.