Recently, the concept of a “Proteomic Constraint” was introduced to explain the frequency of genetic code deviations in mitochondrial genomes. The Proteomic Constraint was proposed to be proportional to the size of the mitochondrially encoded proteome, hence small proteomes are expected to experience smaller total numbers of errors resulting from genetic code deviations, leading to less likelihood of causing lethality. The concept is now extended to encompass several other aspects of the genetic information system. When the Proteomic Constraint is small, it is proposed that there is little selective pressure to evolve or maintain error correction mechanisms, as a result of the smaller total number of errors that accumulate. Conversely, a large Proteomic Constraint is proposed to result in a correspondingly large selective pressure to evolve or maintain error correction mechanisms. Differences in the size of the Proteomic Constraint can help to explain differences in replicational, transcriptional, and translational fidelities between genomes. A key piece of evidence is the existence of negative power law relationships between proteome size and error rates; these are demonstrated to be diagnostic of the action of the Proteomic Constraint. The Proteomic Constraint is argued to be a major factor determining mutation rates in a diverse range of DNA genomes, implying that mutation rates are clock like. A small Proteomic Constraint partly explains why RNA viruses possess high mutation rates. A reduced Proteomic Constraint in intracellular pathogenic bacteria predicts a drift upwards in mutation rates. Differences in the Proteomic Constraint also appear to be linked to differences in recombination rates between eukaryotes. In addition, a reduced Proteomic Constraint may explain features of resident genomes, such as loss of DNA repair pathways, increased substitution rates, and AT biases, in addition to the occurrence of genetic code deviations. Thus, it is argued that the Proteomic Constraint is a universal factor that influences a wide range of properties of the genetic information system.