The missense of smell: functional variability in the human odorant receptor repertoire


Humans have 400 intact odorant receptors, but each individual has a unique set of genetic variations that lead to variation in olfactory perception. We used a heterologous assay to determine how often genetic polymorphisms in odorant receptors alter receptor function. We identified agonists for 18 odorant receptors and found that 63% of the odorant receptors we examined had polymorphisms that altered in vitro function. On average, two individuals have functional differences at over 30% of their odorant receptor alleles. To show that these in vitro results are relevant to olfactory perception, we verified that variations in OR10G4 genotype explain over 15% of the observed variation in perceived intensity and over 10% of the observed variation in perceived valence for the high-affinity in vitro agonist guaiacol but do not explain phenotype variation for the lower-affinity agonists vanillin and ethyl vanillin.

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Figure 1: Dose-response curves of the receptor encoded by the most common functional allele for 27 receptors.
Figure 2: Unrooted tree based on similarity of amino acid properties.
Figure 3: Functional testing of odorant receptor variants.
Figure 4: Summary of functional variation.
Figure 5: Functional differences between participants.
Figure 6: Effects of genetic variation in OR10G4 on perceived intensity and valence.


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This work was supported by R01 DC005782, R01 DC012095, R03 DC011373, R01 DC013339, T32 DC000014 and a National Research Service Award postdoctoral fellowship F32 DC008932 to J.D.M. A portion of the work was performed using the Monell Chemosensory Receptor Signaling Core and Genotyping and DNA/RNA Analysis Core, which are supported, in part, by funding from the US National Institutes of Health NIDCD Core Grant P30 DC011735. A portion of the work was supported by the Defense Advanced Research Project Agency RealNose Project. Collection of psychophysical data was supported by grant # UL1 TR000043 from the Clinical and Translational Science Award program at the National Center for Advancing Translational Sciences. The FACS analysis was performed using the Duke Cancer Institute Flow Cytometry Core. We thank D. Marchuk for sharing equipment, L.B. Vosshall for supervising the collection of psychophysical data and DNA samples by A.K. in her laboratory, and R. Molday (University of British Columbia Centre for Macular Research) for 4D2 anti-rhodopsin antibody.

Author information




J.D.M. and H.M. conceived and designed the project. J.D.M., C.T., A.H.M., L.L.S., S.Z., W.L.L.L., T.Z., Y.R.L., H.Z., S.S.L., A.L. and K.A.A. performed research. A.K. collected the psychophysical data and provided DNA samples. J.D.M. carried out the analysis and wrote the paper with help from all authors. H.M. supervised the project.

Corresponding author

Correspondence to Joel D Mainland.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Outline of the screening procedure.

Supplementary Figure 2 Relative surface expression, measured by a fluorescence-activated cell sorter, does not correlate with relative potency (a) (Spearman rho=-0.01, n=38, p=0.95) or relative efficacy (b) (Spearman rho=0.16, n=38, p=0.33).

For each variant we compared the change in mean surface expression (PE fluorescence intensity) to the change in the receptor potency (EC50 from the best-fit sigmoidal model) or receptor efficacy (top-bottom from the best-fit sigmoidal model) relative to the most common functional variant. Source data

Supplementary Figure 3 We calculated 20 chemical descriptors, previously shown to explain more than 62% of the variance in functional responses in a heterologous system, for 2718 odorants17.

For display purposes, the odorants are projected onto a 2D space made of the first and second principal components. Black crosses represent all 2718 odorants, red circles represent the 55 odorants chosen to span olfactory space. Source data

Supplementary Figure 4 Sensitivity-ordered tuning curves for odorant receptors.

The y-axis represents the luciferase response normalized by Renilla Luciferase. The 55 odorants are displayed along the x-axis according to the strength of response they elicited from the reference allele of each receptor (defined as the most frequent allele that shows activity significantly higher than the vector control). If a given odorant did not significantly activate any of the variant receptors above the no-odor control (2-tailed t-test, α=0.05/55), that odorant's response was set to zero across all variants. The odors eliciting the strongest response are placed at the center of the distribution. The order of odorants is the same across all variants of a given receptor, but is different across receptors. Odorant information can be found in the linked source data file. Error bars represent standard error. Source data

Supplementary Figure 5 Dose response curves for odorant receptors.

Y-axis values are normalized to the reference allele (shown in blue), here defined as the most frequent allele in the 1000 genomes population that shows activity significantly higher than the vector control. SNPs are named relative to the hg19 reference sequence. Error bars represent standard error. Source data

Supplementary Figure 6 Functional characterization of OR10G4 polymorphisms.

Y-axis values are normalized to the reference allele (shown in blue), here defined as the most frequent allele in the 1000 genomes population that shows activity significantly higher than the vector control. SNPs are named relative to the hg19 reference sequence. Error bars represent standard error. Source data

Supplementary information

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Supplementary Figures 1–6 and Supplementary Table 1 (PDF 937 kb)

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Mainland, J., Keller, A., Li, Y. et al. The missense of smell: functional variability in the human odorant receptor repertoire. Nat Neurosci 17, 114–120 (2014).

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