The explosion of protein sequences deduced from genetic code has led to both a problem and a potential resource: Efficient data use requires interpreting the functional impact of sequence change without experimentally characterizing each protein variant. Several groups have hypothesized that interpretation could be aided by analyzing the sequences of naturally-occurring homologues. To that end, myriad sequence/function analyses have been developed to predict which conserved, semi-, and non-conserved positions are functionally important. These positions must be discriminated from the non-conserved positions that are functionally silent. However, the assumptions that underlie sequence analyses are based on experimental results that are sparse and usually designed to address different questions. Here, we use three homologues from a test family common to bioinformatics – the LacI/GalR transcription repressors – to test a common assumption: If a position is functionally important for one family member, it has similar importance in all homologues. We generated experimental sequence/function information for each non-conserved position in the 18 amino acids that link the DNA-binding and regulatory domains of three LacI/GalR homologues. We find that the functional importance of each position is preserved among the three linkers, albeit to different degrees. We also find that every linker position contributes to function, which has two-fold implications. (1) Since the linker positions range from highly to semi- to non-conserved, and contribute to affinity, selectivity, and allosteric response, we assert that sequence/function analyses must identify positions in the LacI/GalR linkers to be qualified as “successfulâ€