Personal receptor repertoires: olfaction as a model
© Olender et al.; licensee BioMed Central Ltd. 2012
Received: 3 May 2012
Accepted: 26 July 2012
Published: 21 August 2012
Information on nucleotide diversity along completely sequenced human genomes has increased tremendously over the last few years. This makes it possible to reassess the diversity status of distinct receptor proteins in different human individuals. To this end, we focused on the complete inventory of human olfactory receptor coding regions as a model for personal receptor repertoires.
By performing data-mining from public and private sources we scored genetic variations in 413 intact OR loci, for which one or more individuals had an intact open reading frame. Using 1000 Genomes Project haplotypes, we identified a total of 4069 full-length polypeptide variants encoded by these OR loci, average of ~10 per locus, constituting a lower limit for the effective human OR repertoire. Each individual is found to harbor as many as 600 OR allelic variants, ~50% higher than the locus count. Because OR neuronal expression is allelically excluded, this has direct effect on smell perception diversity of the species. We further identified 244 OR segregating pseudogenes (SPGs), loci showing both intact and pseudogene forms in the population, twenty-six of which are annotatively “resurrected” from a pseudogene status in the reference genome. Using a custom SNP microarray we validated 150 SPGs in a cohort of 468 individuals, with every individual genome averaging 36 disrupted sequence variations, 15 in homozygote form. Finally, we generated a multi-source compendium of 63 OR loci harboring deletion Copy Number Variations (CNVs). Our combined data suggest that 271 of the 413 intact OR loci (66%) are affected by nonfunctional SNPs/indels and/or CNVs.
These results portray a case of unusually high genetic diversity, and suggest that individual humans have a highly personalized inventory of functional olfactory receptors, a conclusion that might apply to other receptor multigene families.
KeywordsOlfactory receptor Genetic polymorphism Haplotypes Single nucleotide polymorphism Copy number variation Olfaction Gene family
Olfaction, the sense of smell, is a versatile and sensitive mechanism for detecting and discriminating thousands of volatile odorants. Olfactory recognition is mediated by large repertoires of olfactory receptors (ORs), which activate a G-protein-mediated transduction cascade, located in the cilia of olfactory sensory neurons [1, 2]. The human OR repertoire has 851 loci, encompassing 78 genomic clusters and 57 singleton loci, residing on all but two human chromosomes [3–6]. Each sensory cell expresses a single allele of a single OR locus, thus transmitting a molecularly defined signal to the brain [7–10]. A single OR gene may recognize more than a single odorant molecule [11–15]. A widely accepted working hypothesis is that allelic variants of OR genes may harbor different functional characteristics and hence, may generate different odorant sensitivity phenotypes in different members of the human population [16–18].
Human ORs encompass a high number of pseudogenes, whereby more than 50% of the loci annotated as nonfunctional due to frame-disrupting mutations [3, 5, 6, 19]. Primates are less dependent than mouse and dog on olfactory cues, which appears to have resulted in a gradual gene loss process along this lineage [20–22]. Similar OR repertoire diminutions have been reported in other mammals . In higher apes, the gene loss has remarkably accelerated in humans . Such diminution of the functional OR repertoire in humans is an ongoing evolutionary process, as demonstrated by the past identification of OR genes that segregate between intact and pseudogene forms [25, 26], and by more recent surveys showing an enrichment of loss-of-function OR alleles [27, 28]. It was shown that every human individual is characterized by a different combination of such segregating pseudogenes (SPGs), constituting a pronounced genotypic diversity in the population, including ethnogeographic differences . More recently, using a high-resolution microarray applied to 20 individuals , and a read-depth-based Copy Number Variation (CNV) genotyping algorithm , we showed a wide range of copy-number values across individuals, ranging from zero to nine copies. These results are in-line with other surveys which found a significant enrichment of ORs in CNV regions [31, 32]. CNVs involving deletions (copy numbers of 0 or 1) were shown to affect 56 intact OR loci, 14% of the human OR gene repertoire .
Cell-surface receptors are often characterized by several haplotypic alleles in the population, sometimes with different functional properties. A prominent example is the group of the major histocompatibility proteins with varying specificities towards antigenic peptides [33, 34]. Other examples include the taste receptor TAS38, underlying responsiveness to the bitter compound phenylthiocarbamide (PTC) [35, 36], the melanocortin 1 receptor (MC1R), affecting human skin and hair pigmentation , and the green opsin OPN1MW, mediating red-green color vision discrimination . Likewise, in the olfactory system, two protein haplotypes of the olfactory receptor OR7D4 were shown to manifest large difference in sensing the steroid odorant androstenone [39, 40].
Some missense haplotypic alleles can be nonfunctional, due to a substitution of key amino acids governing protein folding or interaction with signal transduction components. A continuous spectrum of functionality among missense haplotypes may be quantified by algorithms such SIFT  or PolyPhen . An analogous algorithm, Classifier for Olfactory Receptor Pseudogenes (CORP) , was previously used to identify 30 SNP variations for which one of the alleles is likely inactive , with a broader estimate of as many as 135 functionally inactive missense alleles in the reference genome .
Here, we performed scrutiny of publicly available data to create a comprehensive catalog of genetic variability in the human OR repertoire. This includes a compendium of all available missense haplotypes of OR proteins and a dramatically expanded list of OR segregating pseudogenes. Our work creates a framework for understanding the evolution and function of OR genes, and a necessary infrastructure for genotype-phenotype association studies for smell deficits. It further highlights the utility of the olfactory system as a model for personalized gene repertoires.
Numerous allelic variants in intact ORs
We performed experimental validation for 68 nonfunctional SNPs (stop gain, stop loss, and loss of initiator methionine) and 200 frame-disrupting indels (Additional file 4). For this we designed a custom SNP array (Illumina GoldenGate) that included the total of 268 nonfunctional variations. These were genotyped in a cohort of 468 individuals of two ethnicities, providing validation for 184 of the variations, as compared to a most probable value of validation of 197 ± 2 based on the cohort size and specific minor allele frequencies (validation rate of 93.4%). The number of nonfunctional SNPs per individual (heterozygous and homozygous) thus discovered is shown in Additional file 1: Figure S4. A significant correlation was seen between the allele frequencies in the 1000 Genomes Project data and our validation sets (Additional file 1: Figure S5).
An OR variation compendium
Using various databases and experimental resources, we have compiled a compendium of synonymous, missense and nonsense SNPs, as well as copy number variations within OR coding regions. A major resource for this work was the 1000 Genomes Project’s whole genome sequence data , yielding variation and phase information. A significant caveat regarding such data is their low coverage in each sequenced individual and the imputation procedures used in the phasing process [56–58]. This is partly ameliorated by the fact that the main body of our analyses is based on cumulative data from 300–1300 human chromosomes. Another point of concern is that some of the variations were obtained from dbSNP , for which population frequencies or validation are sometimes not provided. Indeed, in our experimental validation of 268 OR nonfunctional SNPs, a majority (65%) of the unsupported variations were mined only from dbSNP.
Enormous gene variability
Our results portray an overview of the degree of inter-individual genomic variability harbored in the OR gene inventory. We report on an enormous amount of genomic variation (one variation per 66 bases), 2.5 times larger than in single coding exon control genes. Our analyses suggest that such enhanced variation is largely due to neutral drift, both because the propensity of variations per coding region is similar to that found for OR pseudogenes, and since the average pN/pS value for the intact ORs is 0.9 ± 0.6, consistent with neutrality.
Previous studies reported on positive selection acting in specific OR genes [60–62], potentially related to a recent evolutionary acquisition of a capacity to recognize specific behavior-related odorants . Our results do not provide clear evidence for such selection mode. Other reports suggest that the OR diversity may be maintained to some degree by balancing selection [54, 64], similar to that acting upon the major histocompatibility complex alleles [65, 66], leading to enhanced ligand recognition success at the population level . While balancing selection for ORs has been disputed  our results suggest that a fraction of OR genes may be under such selection mode, a mechanism consistent with the advantage for heterozygosity in a pathway endowed with allelically excluded expression. This is in line with a previous report showing higher than expected count of heterozygotes at OR SNPs in the HapMap populations, which led to the conclusion that the human ORs may have been shaped by balancing selection, stemming from overdominance .
Weak purifying selection has also been suggested to affect a subpopulation of human ORs, as seen by human-chimpanzee comparisons . In line with this, we identified nearly 60 ORs in our dataset showing evidence for this evolutionary mechanism. Such evolutionarily conserved OR genes may subserve the recognition of specific odorants important for survival and/or propagation of the species. Interestingly, this group of human genes has a higher fraction of candidate orthologs in mouse, as compared to dog, consistent with a presently accepted phylogeny whereby primates and rodents belong to the same clade, different from that of carnivores [70, 71], although a rodent-outside phylogeny was also suggested [72, 73].
In sum, it is difficult to negate the possibility that certain modes of selection act on subsets of human OR genes, but it is rather certain that no single mode applies to all ORs. Such heterogeneity of selection modes within the large OR repertoire has also been reported in dog [74, 75].
The human allele repertoire
Irrespective of evolutionary path, it is obvious that human ORs show an unusually high variability as compared to other intact protein-coding genes. We report that some human individuals have as many as 600 OR coding regions at their ~400 intact OR loci. Some of these allelic protein variants may have different odorant affinity and/or specificity . Previous reports demonstrate that olfactory sensory neurons express only one of the two alleles at a given locus [2, 76, 77] with a possibility that allelically excluded neurons report independently to olfactory bulb glomeruli in the brain . This, together with allele plurality, generates a powerful mechanism for augmenting functional variation and enhancing odorant recognition capacities. Furthermore, a higher size of the effective OR repertoire may also signify enhanced average sensitivity to odorants [79, 80]. The functional significance of allelic diversity most likely applies to other species as well [75, 81].
Loss of function alleles
One of the striking results of the present report is the extremely high prevalence of loss-of-function OR alleles. Based on the data mining performed, among the 851 human genomic OR loci, 438 have a frame-disrupting pseudogene apparently fixed in the entire population. Of the 413 remaining loci, 271 (66%) have at least one allele lacking an intact open reading frame, including frame disruptions and deletion CNV alleles. The CORP algorithm  predicts that an additional 37 loci have missense nonfunctional alleles, with a CORP score > 0.9, suggesting a probable non-functional OR protein. Thus, as many as 308 OR loci harbor one or more functionally disrupted alleles, and only 105 loci appear to be purely functional in the studied population. This is likely related to the emergence of a large number of OR pseudogenes in higher primate evolution [22, 82]. Further, the very high incidence of segregation between intact and nonfunctional alleles attests to a possible highly accelerated gene inactivation in recent human evolution. This potentially took place on a shorter time scale than the previously indicated human-specific acceleration in OR pseudogene accumulation relative to apes .
The presently reported number of 308 non-intact loci is fivefold larger than an earlier estimate of ~60 . This number will likely increase even further as many more human genomes become available. Curiously, among the non-intact loci are included 26 that were originally annotated as pseudogenes in the reference genome. Further sequencing would probably show additional such cases of “resurrected” ORs, most likely from among the 44 fixed OR pseudogenes that have only one frame disruption [6, 45]. It should be pointed out that OR pseudogenes are not processed pseudogenes , and hence are typically endowed with all features of intact ORs (cis regulatory elements, 5’ upstream introns and non-coding exons) and are only different from the intact form by frame-disrupting mutations.
Analysis of deletion CNVs with high-confidence breakpoints revealed that, for a typical individual, 40% of the deletion CNVs affect more than one (and up to six) intact OR genes, consistent with previous reports [29, 30], thus highlighting the large impact of CNVs as opposed to smaller variants. However the contribution of deletion CNVs to the overall number of disrupted alleles per individual is less pronounced.
Receptor diversity and ethnogeography
Our results generally suggest substantial differences among the three major ethnogeographical groups analyzed: Caucasians, Africans and Asians. The most significant result is that Africans have a higher number of OR protein haplotypic variants, with implications to chemosensory diversity. Such findings are in line with the reported higher genetic diversity in this ethnogeographical group [48, 84, 85]. Some of the protein variants are seen only in one or two of the groups, and others show great disparity of relative allele frequency. The three different human races also have distinct patterns of deletion allele genotypes, which again could affect chemosensory preferences. Previously, we have reported a slightly higher number of intact OR loci in Africans as compared to Caucasians . The results reported here, utilizing a much larger number of deletion loci, shows no statistically significant difference in this realm between ethnic groups.
We used data mining strategies to generate a comprehensive compendium of genomic variations in the inventory of human OR coding regions. Our analyses suggest that the effective size of the functional human OR repertoire is much higher than the number of intact loci, implying considerable enhancement of the potential of human smell perception diversity. Importantly, using both data-mining and experimental verification we show that more than two thirds of human OR loci segregate between an intact and inactivated alleles. These results portray a case of unusually high genetic diversity, and suggest that individual humans have a highly personalized “barcodes” of functional olfactory receptors, a conclusion that likely applies to other receptor multigene families as well.
Table S1 (Additional file 1) lists the data sources screened for genomic variations in the OR coding regions [26, 30, 55, 59, 86–93]. We used the UCSC table browser tool  to extract variations from dbSNP, and custom Perl scripts for other databases. We used the GRCh37/hg19 reference genome assembly, and when necessary genomic variations were converted to this version, using the liftOver tool (http://genome.ucsc.edu/cgi-bin/hgLiftOver). Variations that had the same type (SNP or CNV) in the same OR gene symbol with the same start and end locations were considered duplicates and were merged. Indel variations, often located in oligonucleotide repeat loci , might have more than a single valid mapping, and were therefore merged manually. Annotation and classification of the variations into the different categories presented in Figure 1 was done by a custom Perl script. Multi-allelic SNPs were removed from the analysis. Unique genomic mapping for dbSNP variations was ascertained by allowing only SNPs with “map weight” equal to 1. SNPs from other sources were analyzed for non-uniqueness by mapping flanking sequences (±50pb) with BLAT  and filtering out cases with multiple locations with ≤2 mismatches.
Bi-allelic CNV deletions reported by different sources (Additional file 1: Table S1) were merged by the following procedure: if both beginning and end coordinates of two CNV instances differed by ≤1 kb they were merged into a single entry, and the average genomic coordinates and allele frequencies were used (Additional file 4). From the 1000 Genomes Project data for the first 150 individuals (, union.2010_06.deletions.sites.vcf) we kept only deletions with allele frequencies. Multiple overlapped variants from this source were filtered using the following rules (in order):i) When a deletion spanning multiple ORs overlapped with deletions of individual ORs in the same location, the former was preferred; ii) Among overlapping deletions affecting the same OR, the smallest was favored.
OR haplotypes were computed based on phased SNP calling data from the Broad Institute Phase 1 1000 Genomes Project data files (http://www.1000genomes.org/) (AFR.BI_withr2.20100804.genotypes, ASN.BI_withr2.20100804.genotypes, EUR.BI_withr2.20100804.genotypes). Each OR haplotype was defined as a binary vector of non-synonymous segregating sites present in all 3 populations, with 1 denoting the non-reference variant. The OR haplotype frequencies for each population were then summarized in Additional file 3.
Haplotype protein functional score
and α i = −1 if in the sequence carries an allowed amino-acids in position i, and α i = 1 otherwise.
Variation frequency comparisons
Two control sets were used for variation frequency comparisons. The first was 581 single coding exon genes, retrieved from GeneLoc (, http://genecards.weizmann.ac.il/geneloc), further curated with the UCSC table tool  to remove non-protein-coding genes. SNPs in these genes were extracted from the 1000 Genomes Project data for the same set of 651 individuals and using the same computational procedures as applied to the ORs. The SNP count was normalized to gene length using the longest transcript.
The second control gene set was of 15,425 protein coding genes, extracted from GeneCards (http://www.genecards.org/, [50, 51]). The same source was also used to obtain SNPs in the 321 intact ORs listed within it. SNPs in OR pseudogenes were classified as “synonymous” or “non-synonymous” based on sequence translation using FASTY . For calling reversion of a pseudogene to an intact status, an open reading frame ≥300 amino-acids was used as a cutoff.
For SNP validation, a cohort of 480 DNA samples was used, collected under ethically-approved protocols as described [91, 99]. This panel included 366 individuals of Israeli Jewish origin (271 Ashkenazi, and others of mixed origin) used in a previous study , as well as 92 individuals of American origin (57 Caucasians and 22 Afro-Americans) was collected in the framework of a collaborative genotype-phenotype study [91, 100].
Genomic DNA was extracted from 10 ml of peripheral blood using a DNA Isolation Kit for Mammalian Blood (Roche) . DNA concentration was measured in the Beckman DTX880 Multi-Detection Microplate Reader using PicoGreen (Invitrogen). Genotyping of SNPs was carried out at the Rappaport Research Institute, Technion, Israel, using the Illumina GoldenGate assay according to the manufacturer’s instructions (Illumina Inc., SanDiego, CA, USA) http://www.illumina.com/technology/goldengate_genotyping_assay.ilmn.
The Illumina oligonucleotide pool assay (OPA) was designed using the Illumina Assay Design Tool (ADT) software, with inclusion of all OR nonfunctional variations showing an ADT designability score > 0.4. Inter-variation distances were kept at >60 bp, choosing the variants with highest designability score. The final design included 285 nonfunctional OR variations, of which 268 were successfully genotyped.
For computing the most probable value of validation, we used the minor allele frequencies for the genotyped SNPs, as shown in Additional file 1: Figure S9. We simulated 1000 cohorts of 445 individuals (to account for averaged null calls of 22 individuals per SNP) and obtained a mean and standard deviation for the rate of validation for each variant.
Resolving genotype ambiguities
We developed procedures to obtain unambiguous personal genotypes based on the mining of three independent genotype datasets: 1) The 1000 Genome Project imputed phased SNPs (Broad Institute, version 20100804); 2) The 1000 Genome Project imputed phased indels (Broad Institute, version 2010_07); 3) Bi-allelic CNV calls as described . Ambiguities arise when more than one of these sources reports heterozygosity in the same person and in the same gene. Regarding the merger of nonfunctional SNPs with indels, only 3 genes (OR1B1, OR4C5, OR7G3) showed such an ambiguity, and it was resolved by re-phasing using the PHASE program . The merger of CNV deletions with SNPs/indels was done by the following rules: a. for homozygous CNV deletion concomitant with nonfunctional SNP/indel, the latter was considered as imputation artifact and was ignored; b. heterozygous CNV deletion concomitant with apparently homozygous nonfunctional SNP/indel, was scored as compound heterozygosity; c. Heterozygous SNP/indels along with heterozygous CNV remained unsolved (3 cases). For Figure 3, in cases of unresolvable heterozygous indel/deletion along with claimed missense heterozygosity, one missense allele was selected randomly.
Analyses of selection signatures
The ratio of the number of polymorphic non-synonymous substitutions per non-synonymous sites to the number of polymorphic synonymous substitutions per synonymous sites (pN/pS) was calculated for ORs and control genes following published procedure  and using SNPs of the 1000 Genomes Project. This procedure was demonstrated to be correlated with Ka/Ks for divergence . Tajima’s D Neutrality test was computed with the DnaSP program .
Copy number variation
Single nucleotide polymorphism
Classifier for Olfactory Receptor Pseudogenes
The ratio of polymorphic non-synonymous substitutions per non-synonymous site to polymorphic synonymous substitutions per synonymous site.
We are grateful to E.E. Eichler, J.M. Kidd and M. Malig (University of Washington, Seatle, WA, USA) for providing access to fosmid clone reagents under the auspices of the Structural Variation Project; H. Lehrach (Max Plank Institute for Molecular Genetics, Berlin, Germany) for sequencing of OR genes; R. Radtke, A. Husain, S. Sinha, M. Mikati, W. Gallentine, D. Attix, J. McEvoy, E. Cirulli, V. Dixon, N. Walley, K. Linney, E. Heinzen, A. Need, J.P. McEvoy, J. Silver, M. Silver and D. Goldstein (Duke University, Durham NC, USA) for their role in collecting samples used in this study; D. Reed and A. Knaapila (Monell Chemical Senses Center, Philadelphia PA, USA) for collecting some of the samples studied in the work; Y. Hasin-Brumshtein for validating some of the nonfunctional variations; J. Korbel (EMBL, Heidelberg, Germany) for preferred access to the 1000 Genomes Project data and for fruitful discussions.
The work on the fosmid clone reagent (E.E. Eichler’s group) was supported by National Institutes of Health Grant HG004120 to E.E.E. Sample collection in D. Goldstein’s group was funded in part by NIMH Grant RC2MH089915. Support to DL was from NIDCD/NIH grant 5-R01-DC000298-18 and the Crown Human Genome Center at the Weizmann Institute of Science.
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