Journal of Heredity Advance Access published online on July 29, 2008
Journal of Heredity, doi:10.1093/jhered/esn057
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Canine Olfactory Receptor Gene Polymorphism and Its Relation to Odor Detection Performance by Sniffer Dogs
From the Institute of Genetics and Animal Breeding Polish Academy of Sciences, Jastrzebiec, Postepu 1, 05-552 Wolka Kosowska, Poland (Lesniak, Walczak, Jezierski, Sacharczuk, and Jaszczak); the Canine Department, Police Training Centre in Sulkowice, 05-560 Chynow, Poland (Gawkowski); and the Medical Research Center, Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland (Lesniak)
Address correspondence to A. Lesniak at the addresses above, or e-mail: anna.lesniak{at}cmdik.pan.pl.
The outstanding sensitivity of the canine olfactory system has been acknowledged by using sniffer dogs in military and civilian service for detection of a variety of odors. It is hypothesized that the canine olfactory ability is determined by polymorphisms in olfactory receptor (OR) genes. We investigated 5 OR genes for polymorphic sites which might affect the olfactory ability of service dogs in different fields of specific substance detection. All investigated OR DNA sequences proved to have allelic variants, the majority of which lead to protein sequence alteration. Homozygous individuals at 2 gene loci significantly differed in their detection skills from other genotypes. This suggests a role of specific alleles in odor detection and a linkage between single-nucleotide polymorphism and odor recognition efficiency.
Sniffer dogs have been used by police forces and civilian services worldwide as operational tools for more than 100 years. Tasks for sniffer dogs have included finding missing people or human bodies in disasters, tracking and identifying crime suspects, the detection of drugs, explosives, land mines, contraband, and molds, and more recently, detecting odor markers of cancer diseases. Practically, dogs can be trained to detect any odorous substance. Compared to instrumental methods, sniffer dogs represent a versatile detection device that remains reliable even in the presence of interfering and distracting odors (Schoon 1997; Furton and Myers 2001; Williams and Johnston 2002).
The canine olfactory system is well adapted for the detection of a vast number of odorous substances varying in shape and size (Buck 2000) as well as molecules showing subtle differences in stereoisomeric structure (Buck 2004; Firestein 2005). Even minute amounts of a particular odorant may be detected and recognized due to the extraordinary sensitivity of the dog's nose (Williams and Johnston 2002; Hepper and Wells 2005; Walker et al. 2006). This feature coupled with the ease with which they can be trained and willingness to cooperate with humans are crucial for canine detection.
The initial process of odor discrimination begins in the olfactory neuroepithelium located in the nasal cavity. Odorants activate olfactory receptors (hereafter referred to as OR) on the cell surface of an olfactory neuron which initiate further signal transduction to the brain (Firestein 2001). The OR genes belong to the G protein–coupled receptor (GPCR) superfamily containing approximately 1300 genes in the dog (Olender et al. 2004) and believed to be the largest gene family in the mammalian genome (Buck 2000, 2004; Malnic et al. 2004). The structural feature shared by GPCR receptors is that they possess 7 transmembrane (TM) domains, intercellular (IC) and extracellular (EC) loops which exhibit polymorphism (Tacher et al. 2005) that may play an important role in the accuracy of odor discrimination. The large size of the OR family suggests that the initial discrimination between different odorants depends on the selective binding affinity of ORs (Zhao and Firestein 1999). The binding affinity depends also on the concentration of a particular odorant in the odor mixture because ORs show a rather moderate affinity toward scent molecules (Duchamp-Viret et al. 1999).
It is thought that not all 7 TMs are equally important for odor discrimination. Due to their high divergence, only the TM3, TM4, and TM5 may play a crucial role in odor discrimination (Liu et al. 2003).
We investigated the polymorphisms of 5 OR genes in police sniffer dogs trained in different special fields of canine scent detection. The second aim of this study was to find possible links between these polymorphisms and the ranking of dogs according to their olfactory performance at the detection of various volatile organic compounds. The rationale was that particular alleles at an OR locus may influence odor recognition accuracy.
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Animals
The study involved an experimental group of 35 dogs. 31 individuals were specialist police dogs, predominantly German Shepherd males from the Canine Department of the Police Training Center in Sulkowice, Poland (see Table 1). These dogs were certified operational sniffer dogs that had passed the annual recertification procedure, or dogs in the last stage of training in a defined field of work before certification. The dogs were certified in 3 different fields:
- 1) identification of humans on the basis of individual scent (ID dogs, n = 16),
- 2) explosive search (ES dogs, n = 11), and
- 3) drug search (DS dogs, n = 4).
- 2) explosive search (ES dogs, n = 11), and
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The remaining dogs were trained to detect odor markers of cancer disease in humans (Tumor identification [TI] dogs, n = 4)—3 German shepherd male mixes and 1 purebred Labrador retriever male. They were provided by the Department of Animal Behavior, Institute of Genetics and Animal Breeding, Polish Academy of Sciences, Jastrzebiec, Poland. The 4 adult individuals had all completed 3 phases of specialist training to indicate samples of air exhaled by cancer patients.
All the experimental animals had passed a general test, standard for police dogs, that involves the following 10 traits: 1) ability to retrieve a thrown object, 2) searching for a hidden object (success), 3) persistence at searching, 4) ability to retrieve all kinds of objects, 5) behavior indoors (no fear), 6) behavior on slippery surfaces, 7) no fear reaction to noise/shot outdoors and indoors, 8) interest in treats, 9) good health, and 10) age 1–2 years.
Three skilled dog handlers participated in the experiment, each handled 1–3 dogs.
Dogs were housed all year round in outdoor individual roofed kennels (4 x 4 m) equipped with warm insulated chutes and access to open-air enclosures of 15 x 6 m situated in a secluded area. Animals were fed with standard dry dog food, had free access to fresh water, and were provided with daily walks. Veterinary surveillance and care was available to all dogs in case of illness or injury. All dogs were treated in a humane manner by both handlers and caretakers according to the standards of good practice of dog training. The training and testing process involved no compulsion or violence toward dogs and was based exclusively on positive reinforcement and clicker training.
Ranking of Dogs
The ranking of dogs according to their sniffing ability was made in 2 ways.
Ranking By Dog Handlers and Trainers
Experienced dog trainers and handlers from both training facilities were asked to make a ranking of dogs within each specialty group and training level (certified/recertified or in the last phase of training) according to the trainer's/handler's judgment of each dog's sniffing performance and ability to detect the specific substances/volatile compounds they had been trained on. A variety of different odor samples were used in the evaluation process depending on each dog’s specialty.
The human identification (ID) dogs were tested using a scent lineup of 5 individual human scents. Human scent samples were collected by holding a sterile cotton cloth in the palm for approximately 15 min. The samples were placed in twist jars which were labeled and stored for some days at room temperature before the testing began. Before searching the scent lineup, dogs were given a target sample to sniff. The target sample was then placed at a random position in the 5 human scent samples (1 target sample + 4 decoys). The dogs were trained to sniff all the samples in the lineup and to indicate the target sample by performing a trained response (sitting or lying down) in front it. Sitting or lying down in front of the decoy sample was classified as a false alarm, and a nonindication in front of the target sample (a miss) was classified as a false-negative reaction.
The training and testing procedure of the tumor identification (TI) dogs resembled that of ID dogs. The target samples were breath samples collected from patients with biopsy confirmed lung cancer (n = 75), breast cancer (n = 55), and melanoma (n = 45). The breath samples were collected by medical staff at 3 hospitals: the M. Sklodowska-Curie Institute of Oncology, the Institute of Tuberculosis and Lung Diseases, and the Central Clinical Hospital of the Military Medical Institute, Warsaw, Poland. Decoys were breath samples collected from 318 healthy volunteers.
In order to follow ethical requirements, all participants were informed about the sample collection procedures and the aim of the study. Patients and healthy subjects were asked to fill out a questionnaire with information on age, sex, last diet, medical treatment, and collection date, that is, factors that may influence the quality of the odor of the breath sample. Sample data on the location, histological type, and stage of the tumor were recorded.
For breath sampling, we used polypropylene sampling tubes equipped with removable caps at either end. In the tubes’ removable filters, special cotton absorbents were inserted for capturing volatile organic compounds (Defencetek, Pretoria, South Africa). Subjects were asked to exhale air through the open end of the tube 3–4 times. The tubes were then closed and labeled with the donor number. For dog training and testing, the removable filters were taken out of the tubes and put in sterile polypropylene boxes covered with perforated lids to prevent licking or touching by a dog's nose. For sniffing by dogs, the boxes were placed in concrete containers (stands) in a lineup on the floor of the sniffing room.
ES dogs were tested in a field setting on a range of military explosives (trinitrotoluene, powder fuse, semtex, and detonating cord), industrial explosives (dynamite and explosive ammonite), and pyrotechnic articles (fireworks and firecrackers). DS dogs were tested also in a field setting for searching of hidden samples of marijuana, amphetamine, LSD, cocaine, and heroine.
The ranking of specialist dogs was made within the specialty and proficiency level (from the best to the worst dog). In order to compensate the rank number depending on the number of dogs in a specialty/proficiency group, the grading score (GS) was calculated for each dog according to the formula:
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Ranking According to the Test to Sniff out a Treat
Additionally, 31 police dogs were tested for their ability to sniff out the odor of a treat in the lineup (hereafter referred to as "treat test, TT"). The aim of this test was to determine the sensitivity of the dogs’ sense of smell regardless of specialty. The experiment was carried out using a lineup of 5 jars in which equal small pieces of sausage were placed and covered with decreasing number of layers of 1-cm thick sterile lignin, that is, 5 layers in the first jar and 4, 3, 2, and 1 layer in the second, third, fourth, and fifth jar, respectively. During the test the dog passed the jars from the first to the fifth one and it was recorded at which jar the dog showed interest in getting the piece of sausage out of the jar. It was assumed that individuals with a better sense of smell would detect the sausage under more lignin layers.
The number of layers under which the dogs succeeded in finding the treat corresponded with the scores (score 5 = 5 layers and score 0 for dogs that failed to detect the treat under 1 layer). It was not clear whether dogs with a score of 0 were not able to detect the treat at all or showed no interest in the treat, and such dogs were excluded from the statistical analysis. The data as to the breed, specialty, proficiency class, the GS, and TT results for each dog are given in Table 1.
Blood Sample Collection
Two milliliters of fresh peripheral blood was collected from each dog with a sterile S-Monovette 2.7 ml EDTA-coated syringe (SARSTEDT AG, Nümbrecht, Germany) by a qualified veterinary surgeon.
DNA Isolation
DNA was isolated from frozen blood (stored at –20 °C) using the DNA Blood Isolation Spin-Kit (AppliChem, Darmstadt, Germany) and following standard protocols and procedures.
OR Gene Selection
A total of 5 canine olfactory receptor (cOR) genes (cOR1P2, cOR51H5, cOR52N9, cOR52P3, and cOR9S13) (Table 2) with intact open reading frames were chosen at random from various subfamilies composing the canine OR repertoire. Sequences and contigs were obtained from the CORDE (http://bip.weizmann.ac.il/HORDE/CORDE.html) (Aloni et al 2006) and Entrez NCBI (http://www.ncbi.nlm.nih.gov/) databases.
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Primer Design
Pairs of specific primers were designed using the Primer3 program (Rozen and Skaletsky 2000) (http://frodo.wi.mit.edu/cgibin/primer3/primer3_www.cgi) for each OR gene amplification and sequencing. Primers were purified using high pressure liquid chromatography. The primer sequences for each cOR gene are shown in Table 3.
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Additionally, primer properties such as Tm values, self-complementarity, and possible formation of "hairpin" structures were established using the Oligonucleotide Properties Calculator software (http://www.basic.northwestern.edu/biotools/oligocalc.html) in order to optimize the amplification process.
Polymerase Chain Reaction, Sequencing, and Sequence Analysis
Polymerase chain reaction (PCR) was conducted using a PT-200 thermal cycler (MJ Research, Waltham, MA) in a total volume of 25 µl that included 3 µl 10 ng of genomic DNA, 20-µl injection quality water (Polpharma, Starogard Gdanski, Poland), 0.51 µl dNTP (25 mM), 0.17 µl (25µM) of each specific primer, and 0.85 µl (2 U/µl) Taq DNA polymerase (Polgen, Lodz, Poland) suspended in 2.62 µl of a buffer containing 100 mM Tris-HCl, 20 mM MgCl2, and 500 mM KCl (Polgen). The following conditions for the reaction were applied: 3.5 min at 94 °C, followed by 32 amplification cycles (0:30 min at 94 °C, 0:45 min at 62 °C or 64 °C, 1:30 min at 72 °C), and the final elongation for 10 min at 72 °C. The mixture was then cooled to 4 °C. PCR products were then loaded onto a 1% agarose gel stained with ethidium bromide (AppliChem). Horizontal electrophoresis was carried out in the LKB-GNA 200 apparatus (Pharmacia, Erlangen, Germany) at 100 mA/cm and 120 V for 1 h.
Bands were excised from the agarose gel under transilluminator UV light (Cole-Parmer, Illkirch Cedex, France) with the use of a carbon steel sterile scalpel. DNA was extracted from the gel using the GenElute Agarose Spin Columns kit (Sigma–Aldrich, Germany). This procedure ensured higher sequencing accuracy.
Sequencing was carried out with the courtesy of the Institute of Biochemistry and Biophysics, Polish Academy of Sciences. Automated sequencing in both directions was performed with the use of the ABI PRISM 377 DNA Sequencer (Applied Biosystems, Foster City, CA) and the DYEnamic ET Terminator Cycle Sequencing Kit (Amersham Pharmacia Biotech Inc., Piscataway, NJ). Sequences were aligned and analyzed with the Sequencher Demo software (Gene Codes Corporation, Ann Arbor, MI). Single-nucleotide polymorphisms (SNPs) were identified by manual inspection of sequence traces as displayed by the software.
Complete cOR nucleotide sequences were translated using a Nucleic Acid Analysis and Manipulation Program from the Colorado State University website (http://www.vivo.colostate.edu/molkit/index.html) and then compared with a reference sequence using BLASTP program available from the NCBI bioinformatics tools package in order to find mismatches. Moreover, we predicted whether the occurring amino acid changes, being the outcome of SNPs, in analyzed cORs did not cause pseudogenization. The 
values for each conceptually translated cOR protein and their equivalents present in the NCBI database were calculated. The results were compared using the Classifier for Olfactory Receptor Pseudogenes program (http://bioportal.weizmann.ac.il/HORDE/CORP/) (Menashe et al. 2006) and the SIFT algorithm (Ng and Henikoff 2001; Ng and Henikoff 2003).
Additionally, we predicted the structure of each cOR protein with the use of a TMHMM service–predicting transmembrane protein topology with a hidden Markov model available at http://www.cbs.dtu.dk/services/TMHMM/ (Krogh et al 2001). The advantage of this program is that it can predict helix length as well as hydrophobicity. The estimation of hydrophobic patterns is crucial because it is thought that most variable residues taking part in ligand recognition and binding tend to be more hydrophobic.
PCR–RFLP
In order to confirm the polymorphic site in gene cOR9S13 in locus 592, PCR–restriction fragment length polymorphism (RFLP) was performed. The HaeIII enzyme was picked in silico with the use of the "NEBcutter V2.0" an online DNA restriction mapper tool (http://tools.neb.com/NEBcutter2/index.php) (BioLabs Inc., Ipswich, England). The reaction was carried out in a total volume 10 µl. The mixture was as follows: 8 µl of PCR product, 1 µl of reaction buffer 10x, and 1 µl (2 U/µl) of HaeIII endonuclease. All necessary reagents were supplies by the Polgen company (Lodz, Poland). Restriction fragments were loaded onto a 20/20 cm 2% agarose gel stained with ethidium bromide (AppliChem). Horizontal electrophoresis was performed in the LKB-GNA 200 apparatus (Pharmacia) at 100 mA/cm and 120 V for 2 h. PCR–RFLP fragments were visualized with the Molecular Imager FX (Bio-Rad, Hercules, CA).
Statistical Analysis
Data were analyzed using Statistica 7.1 Software because of a very uneven representation of particular dog breeds in the specialty/proficiency groups, and no comparison between breeds was made. To assess the differences in GS between genotypes in a particular cOR locus, a 1-way analysis of variance (ANOVA) followed by the Tukey test was applied. Results were represented as mean values ± standard error for each genotype of the cOR locus. The statistical analysis of differences between different genotypes in cOR locus was made in the following ways: 1) for pooled results of the GS of all specialty/proficiency groups, 2) within the ES group for pooled results of the GS, and 3) for pooled results of the TT of specialty/proficiency groups among police service dogs.
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Results |
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Canine Olfactory Receptor SNP
We chose 5 cOR genes for SNP analysis from various subfamilies composing the cOR repertoire (Table 2). The coding sequence of the 5 cOR genes was analyzed by DNA sequence analysis of 35 dogs representing 4 different fields of sniffer specialty. All the selected genes proved to be polymorphic and had allelic variants (Table 4). We identified a total of 18 SNPs from which 10 induced an amino acid change within the protein sequence. Changes are distributed in all parts of the receptor structure (Table 5).
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The remaining nucleotide changes appeared to be silent mutations and in the end had no influence on the amino acid sequence. In the case of 3 cORs (cOR1P2, cOR52P3, and cOR52N9), we noticed an insertion of an amino acid of a different chemical group. In the cOR1P2 gene, we detected a change from a tyrosine into a histidine at position 235 and in the cOR52P3 gene an aspartic acid into a glycine at position 20. In the cOR52N9 gene, a substitution of glycine to arginine at position 59 has occurred corresponding to IC1 in the protein structure. Alterations in the cOR1P2 and cOR52P3 genes occur in regions involved in ligand binding (Singer and Shepherd 1994; Pilpell and Lancet 1999), such as TM4 and IC3 which is considered an extension of TM6 involved in ligand binding in some GPCRs-like D2 dopamine receptors (Hibert et al. 1991). These alterations, however, showed no statistically significant influence on the GS parameter of the dogs’ performance. Alterations in 2 genes, cOR52N9 (a glycine to arginine substitution at position 59 corresponding to IC1) and cOR9S13 (a change from alanine to threonine at position 198 which corresponds to EC2), did prove to have statistically significant influences on the dogs’ sniffing performance.
The correlation rate calculated for the GS values and the outcome of the TT produced a low-positive (r = 0.166) correlation between these 2 rating parameters (Figure 1).
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A to G Transition at Position 176 in the cOR52N9 Gene
The A to G transition at position 176 in the cOR52N9 gene resulting in glycine to arginine substitution at position 59 in the IC1 receptor structure had a statistically significant unfavorable effect on the scenting ability of dogs trained in ES (F(2,8) = 4.254, P = 0.05). Particularly, homozygous individuals (GG) in this locus displayed lower mean GS in comparison to heterozygotes and AA homozygotes (Figure 2). The frequencies of the genotypes were as follows: 0.514 for the GG genotype, 0.314 for the AG genotype, and 0.171 for the AA genotype). There was also no relation between the genotype in the cOR locus and the abilities of dogs trained in different fields of specialty to detect food under layers of lignin (F(2,25) = 1.054, P > 0.05) (Figure 3). The results obtained for both ID and TI dogs were statistically insignificant (P > 0.05). No calculations for dogs specializing in DS were made due to a low number of individuals.
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G to A Transition at Position 592 in the cOR9S13 Gene
The G to A transition at position 592 in the cOR9S13 gene resulting in alanine to threonine substitution at position 198 in the EC2 receptor structure had a statistically significant influence on scent detection skills among dogs regardless of specialty [F(2,32) = 10.317, P < 0.001] (Figure 4). The post hoc Tukey analysis revealed a statistically significant decrease (P < 0.05) in the performance of homozygous AA dogs in comparison to AG heterozygotes (P < 0.01) and GG homozygotes (P < 0.05). The frequency of the GG, AG, and AA genotypes equaled 0.193, 0.290, and 0.516, respectively.
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There were no statistically significant differences between mean GS values among AG heterozygotes and GG homozygotes (P > 0.05). The G to A transition had a statistically significant influence in the TT among dogs regardless of specialty (F(2,28) = 4.327, P < 0.05) (Figure 5). The post hoc Tukey test revealed significant differences between AG and GG (P < 0.01) genotypes depending on the number of lignin layers after removing which the dog scented the treat. No differences were found between homozygotes (P > 0.05).
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PCR-RFLP analysis with the use of a HaeIII (2 U/µl) restriction enzyme showed a 542-bp and 337-bp band in AG heterozygotes. An absence of the 337-bp band was detected in AA homozygotes, whereas GG homozygotes lacked both 542-bp and 337-bp bands.
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As Walker et al. (2006) point out, despite the growing use of dogs for odor detection, recognition, and localization, no comprehensive methodology for quantifying the sniffing capabilities and/or efficacy of detection by dog-handler teams in the "real world" application has been reported so far. The performance of sniffer dogs used in police, military, or civilian service is influenced by a variety of environmental, behavioral, and genetic factors. It is generally believed that the most important feature for canine detection work is the acuity of a dog’s sense of smell. However, the use of sniffer dogs for operational purposes involves dog-handler cooperative work. Therefore, for assessment of the efficacy of canine detection, not only is the acuity of the dog's sense of smell important but also its ability to interact with the handler.
Among behavioral aspects of a dog's usefulness as a detector is the dog's trainability, motivation for sniffing, ability to focus on searching and ignore distracting stimuli, temperament, eagerness to search without being discouraged by a lack of success, and ability to work effectively in stressful situations. Rooney et al. (2004) listed 30 important features of a potential search dog identified during preliminary interviews and utilized them in questionnaires which may be useful as an evaluation method of search dogs. One of these characteristics is the acuity of the sense of smell, but no precise information was given as to how this trait was assessed. In their recent paper, Rooney et al. (2007) attempted to validate a method for assessing the ability of trainee specialist search dogs. They reduced the number of characteristics rated by trainers from 30 to 11 and came to the conclusion that subjective ratings made by scientists and experienced dog trainers are very similar and 2 uncorrelated factors may be assessed: general search ability and ability to work without false indications. Interestingly, Rooney et al. (2007) found that false indications are an important characteristic, for example, false indications by the ID dogs apparently were not reflected in the ratings of general search ability. This may indicate that an objective assessment of the efficacy of dogs’ sense of smell is still vague.
In the field settings it is difficult to distinguish precisely the acuity of a dog's olfactory organ from behavioral aspects and dog-handler cooperation during searching for defined odors and indicating them by a trained behavior. A good parameter to evaluate the dogs’ sniffing ability would be a detection threshold for particular substances. However, the methodology to assess such a threshold is still problematic. Walker et al. (2006) used a sophisticated setup to control odorant concentration sniffed by dogs, and calculated binomial probabilities that a dog's performance occurred by chance. After a 5-month training of 2 dogs, they estimated threshold concentrations of N-amyl acetate detected by the dogs as 1.14 and 1.9 ppt, respectively. The authors point out that there is an enormous variation in thresholds reported by different laboratories for any of a number of species-by-odorant combinations.
In the present work, the ranking of dogs by the trainers and handlers was done within dog specialty and proficiency level. This ranking is a subjective opinion of both the trainer and handler and may be biased by the attitude of the handler to the dog. The TT applied in our study was more handler-independent and involved sniffing of food instead of the substances the dogs were trained to detect. For that reason, the TT involves aspects of novelty and some dogs may be surprised or confused when sniffing food and may be uncertain what they are expected to do. ID dogs are accustomed to search for scents presented in a lineup, and to receive a treat for correct identification. Dogs trained in drug and explosive search, however, may have been confused to find a treat in the container and did not know how to react because they were trained with the use of other reinforcers, such as toys.
Despite some methodological weakness, an unequivocal ranking of the dogs can be made. However, there was a rather small correlation between the 2 ranking methods (r = 0.329) (Figure 1). This low correlation could be due to the fact that different ORs may be involved in identification of compounds present in objects used in these 2 tests.
It is well documented in canine practice that genetic differences in olfactory abilities in different individuals and breeds exist (e.g., Isser-Tarver and Rine 1996; Rooney and Bradshaw 2004). Some breeds used for hunting and tracking were selectively bred over generations for their ability to use olfactory cues. Isser-Tarver and Rine (1996) expressed the opinion that selection for enhanced olfactory sensitivity could have led to an increase in the number of functional OR genes. However, their analysis of the 4 OR gene subfamilies in 26 breeds of dogs has shown that the number of genes per subfamily was stable in spite of differential selection for olfactory acuity. These authors found a few size polymorphisms, but no expansion of the subfamilies. Tacher et al. (2005) found that the level of polymorphism of canine OR sequences was high, as all 16 investigated OR genes had allelic variants. Some alleles were breed specific and rare in the dog population, and others were the major allele in the breed concerned.
Quignon et al. (2003) hypothesize that a low percentage of pseudogenes in some canine ORs could partly explain the difference in olfaction between macro- and microsomatic species. These authors characterized 661 canine OR sequences from poodles and found 18% of pseudogenes in the OR repertoire that were spread over all chromosomes (Quignon et al. 2003). In a subsequent study, Quignon et al. (2005) retrieved 1094 boxer dog OR genes out of which 20.3% were pseudogenes. According to Tacher et al. (2005), it is evident that different animals or breeds may have a different subset of pseudogenes. In relation to results obtained by the former authors, Tacher et al. (2005) suggest that it is tempting to link the slightly higher percentage of OR pseudogenes found in the DNA of boxer dogs (20.3%) to that in poodles (18%), with the current opinion that boxers have a less acute sense of smell than poodles, which were used for retrieving and tracking wounded wild birds. Krautwurst et al. (1998) claim that strong evidence exists that the product of the cOR genes of a given subfamily recognize molecules of similar shape or chemical function. This statement may be of importance to our question.
The results of the present study have shown that some OR genes exhibit up to 7 polymorphic sites, and have also identified specific alleles which might predispose dogs to detecting defined odors. This work shows the presence of hypothetical polymorphic sites in 2 OR genes that may play a role in the effectiveness of odor discrimination.
There may be a relation between a certain genotype at a particular locus and the ability of more accurate scent detection of particular volatile organic compounds. None of the polymorphisms showing statistically significant influence on the dogs’ detecting abilities were located in the binding pocket of chosen cORs. These findings support a suggestion that alterations in other parts of the receptor structure may participate in developing better or worse odor detection ability.
The A to G transition in locus 176 of the cOR52N9 gene results in alteration in the protein sequence. Arginine, a basic amino acid, is substituted by glycine, a nonpolar amino acid. The above substitution occurs in the IC1 part of the receptor structure and is linked to a lower GS values among GG homozygous individuals (Figure 2). The calculated genotype frequencies revealed that GG homozygous individuals comprised 51.4% of the analyzed group of dogs. Heterozygous AG dogs and AA homozygotes constituted 31.4% and 17.1%, respectively. There was no significant difference between the GS values of heterozygotes and wild-type AA homozygotes which might suggest that the effect of the mutated G allele is compensated by the A allele. The relatively high frequency of the unfavorable GG genotype might be due to the fact that the recruitment system for candidates for police dogs is based mainly on the behavioral aspects and the dog's training potential. The mentioned A to G substitution had no statistically significant influence on the dogs’ capabilities to detect the food scent under layers of lignin (Figure 3).
The G to A transition in locus 592 of the cOR9S13 gene, resulting in alanine to threonine substitution in the EC2 receptor structure, had a positive impact on scenting abilities of heterozygous and GG homozygous individuals of all specialties, in comparison to the unfavorable AA genotype (Figure 4). Since homozygous AA individuals achieved lower mean scores during operational work, locus 592 may be a potential marker of olfactory abilities in dogs.
The G to A transition in the cOR9S13 gene also had an impact on treat-searching effectiveness in the experimental group of police dogs. The 1-way ANOVA showed a significant relation between the genotype in locus 592 of the cOR9S13 gene and the acuity of the dogs’ sense of smell as assessed by the number of layers under which the dog can detect the scent of food (F(2,28) = 4.327, P < 0.05). This relation was calculated for all 3 specialties altogether (Figure 5). In the TT, there were significant differences between the achieved score of homozygous GG and heterozygous AG dogs (P < 0.01). Low scores obtained by GG homozygous dogs in the TT that also represent the highest mean GS values suggests that the dogs may have the tendency to ignore the scent they were not trained to indicate.
In conclusion, our results suggest that the presence of the G allele in locus 592 in the cOR9S13 gene has a positive effect on the receptor-binding affinity of some odorous molecules. However, it is probable that a certain polymorphism in a given locus does not fully determine the dogs’ odor sensing skills. The question of the influence of polymorphic sites in detecting different substances requires further studies. A range of alternative approaches needs research, such as in vitro studies to determine the binding affinity of volatile compounds, which presumably are the substances detected by dogs with various receptor types. This approach should be followed by large-scale sequencing or quantitative trait loci mapping on a much larger group of dogs in police or military service.
These preliminary results show that molecular genetic studies on canine OR genes may be a valuable tool to improve the selection of sniffer dogs that are suitable for different special fields of canine detection.
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This project was financed by internal funding source (number S.II.1 and S.VI.3) of the Institute of Genetics and Animal Breeding Polish Academy of Sciences.
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Footnotes |
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Corresponding Editor: Elaine Ostrander
Received October 29, 2007
Accepted April 17, 2008
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