Chem. Senses 24: 373-385,
1999
© Oxford University Press 1999
Quantitative Trait Loci Associated with Short-term Intake of Sucrose, Saccharin and Quinine Solutions in Laboratory Mice
Center for Developmental and Health Genetics and Intercollege Graduate Program in Genetics, The Pennsylvania State University, University Park, PA 16802 1 Department of Biostructure and Function, University of Connecticut Health Center, Farmington, CT 06030, USA
Correspondence to be sent to: Dr David A. Blizard, Room 201, Research Building D, Pennsylvania State University, University Park, PA 16802, USA. e-mail:dab22{at}psu.edu
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Abstract |
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The goal of this study was simultaneously to map two genetic loci which, collectively, have a large effect on intake of sucrose, saccharin and quinine solutions in mice. These loci had been previously identified using long-term measurements with the traditional two-bottle test, but the present study used a short-term, one-bottle test. Intake of distilled water, 100 mM sucrose, 10 mM sodium saccharin and 1.1 mM quinine HCl over 6 h was measured on two occasions from a non-deprived group of 61 male and 72 female F2 mice derived from a cross of the C57BL/6J and DBA/2J mouse strains and used to detect quantitative trait loci (QTL). DNA from each animal was typed for polymorphisms in anonymous microsatellite markers on mouse chromosomes 4 and 6. Saccharin and sucrose relevant QTL were detected on distal chromosome 4 and a quinine relevant QTL was detected on medial/distal chromosome 6 in the region of Prp. The location of these QTL and the proportion of phenotypic variance they accounted for were similar to those arrived at following previous determinations using the two-bottle test. Measurement stability for the three gustatory phenotypes was high, product-moment correlation coefficients between first and second determinations varying between ~0.80 for sucrose and saccharin and 0.73 for quinine. QTL parameters assessed independently for first and second presentations of sucrose and saccharin were stable, but the location of the quinine QTL differed between presentations. The present experiment illustrates the utility of a 6 h fluid intake test in the mapping of Sac and Qui loci. The short duration of the test provides a simple means of measuring variation in gustatory processes and the discovery that these loci influence short-term as well as long-term fluid intake extends understanding of the mechanism of gene action.
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Introduction |
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Strain differences (Ninomiya and Funakoshi, 1993
) and selection
studies (Nachman, 1959; Dess and Minor, 1996)
illustrate the ubiquitous
contribution of genes to taste processes.
However, although the underlying genetic variations constitute a pool of enormous potential,
until recently, methodological limitations have rendered it impossible to explore the underlying
genetic architecture—the number of genes, the magnitude of effect associated with allelic
variation, and dominance relations at individual loci. Genemapping, or reverse genetics, has
dramatically changed the ability of the experimenter to decompose these behavioral variations
between strains to identify the contribution of individual genes to behavior (Blizard
and Darvasi, 1999). The aim of taste genetics is not merely to establish the existence of genes related to taste physiology and behavior, but to facilitate cloning and, ultimately, understanding of the cellular and molecular processes underlying tastemediated processes. By linking taste genes to markers whose chromosomal location is known, the stage is set for finemapping and cloning of the taste genes themselves.
When two inbred strains are crossed, the F 1 progeny are all essentially identical and heterozygous at all genetic loci where the parents had different alleles. The F2 generation, however, is genetically diverse as a result of random chromosomal assortment as well as chromosomal rearrangement of crossing over during duplication. Hence, the F 2 generation is suitable for studying genetic variability because the population has the same markers and genes as the parents but in different combinations. These combinations serve to establish the linkage between the taste-related genes and the known markers.
Traditional genetic studies that relied on behavioral measurements of F 2
generations had deficiencies in the measurement of both genotype and phenotype. The genotype
often could not be established unequivocally in the absence of suitable markers; phenotype (a
term used by geneticists to emphasize that the visible properties of an organism reflect the
interaction of genetic and environmental influences) usually was assessed only in a qualitative
manner. Newer methods using polymerase chain reaction (PCR) amplification of DNA can
directly establish the genotype of individual animals for which molecular biological markers are
known. These may be known genes with established functions, or may be so-called
`microsatellite markers' which are distinctive repeating nucleotide combinations
occurring at intervals throughout the genome. New methods also improve phenotypic assessment
by analyzing traits in a quantitative manner and parsing the contributions of different genes (or
chromosomal loci) with the quantitative measurement of phenotype. The quantitative trait locus
(QTL) method (Lander and Botstein, 1989) employs statistical programs
such as Mapmaker to
establish the chromosomal locations of genes that make statistically significant contributions to
the behavioral phenotype.
Recombinant-inbred (RI) strains (Bailey, 1971; Taylor,
1978) have been used
frequently as genetic mapping tools in studies of taste. They consist of multiple inbred strains,
each of which has been independently derived from a cross of two genetically diverse inbred
strains. As a result of inbreeding, each RI strain becomes fixed, i.e. homozygotic, at all loci.
After genotyping on numerous markers, sets or batteries of RI strains derived from the same pair
of progenitor strains, constitute a fixed repository of genotypes which can be correlated with
phenotypic measurements on those strains. RI strains therefore permit analysis of the relationship
between genotype and physiological and behavioral characters without additional genotyping.
For further discussion of the advantages of RI strains see Bailey (Bailey, 1971; ) and Taylor
(Taylor, 1978).
Assuming single or major gene control and using qualitative descriptions of
phenotypes (+, –), Azen et al. (Azen et al., 1986), Lush and co-workers
(Lush and Holland, 1988; Lush, 1991) and
Capeless et al. (Capeless et al.,
1992) have implicated the Prp region on mouse chromosome 6 in intake of
quinine,
sucrose octa-acetate (SOA) and other aversive solutions. In addition, on the basis of
characterizations of RI strains derived from C57BL/6J (B) and DBA/2J (D) strains and backcross
mice, Lush et al. (Lush et al., 1995) were able to
identify distal chromosome 4
as the most likely location for the Sac locus (Fuller, 1974).
Similarly, Ninomiya et
al. used categorical assignment procedures to map a gene, dpa, on proximal
chromosome 4, but used a different behavioral phenotype, i.e. variation in generalization of 0.1
M D-phenylalanine (D-phe) to 0.5 M sucrose (Ninomiya et al., 1991).
The more flexible approach to linkage detection, QTL analysis (Lander and
Botstein,
1989), has been used more sparingly in the field of gustatory research. In QTL
analysis, an
individual's phenotypic score is assumed to reflect the net influence of allelic variation in
the lkindividual components of a polygenic system which includes systematic and random
environmental variations to the phenotype. QTL analysis is especially appropriate for complex
traits, including behavioral and physiological processes, such as those involved in gustation,
because these are usually assumed to be controlled by many genes. Again, the principal approach
has been via RI strains (Plomin et al., 1991) and has been
applied to both
`sweet' (Belknap et al., 1992; Phillips et al., 1994) and
`bitter' (Harder and Whitney, 1998) solutions; a variety of
QTL sites have been
identified. The study by Phillips et al. (Phillips et al., 1994) is one of the few
QTL studies to use female mice and is particularly interesting for that reason. RI–QTL
studies are particularly useful in nominating QTL sites for further study. However, both
simulation (Belknap et al., 1996) and empirical (Tarantino et al., 1998) studies
suggest that because of the large number of statistical comparisons involved and the small size of
most RI sets, these nominations are susceptible to both false positive and false negative (Type I
and Type II) errors.
QTL analysis also can be conducted through analysis of F 2 or backcross
populations which can more flexibly address statistical power requirements, as well as permitting
exploration of dominance relations between alleles. Two brief reports (Bachmanov et al., 1996; Blizard et al., 1996)
introduced the QTL approach via F 2s to
gustatory research, including a recent full length report (Bachmanov et al.,
1997). In the
present experiment, previously presented in abstract (Blizard et al., 1996), we introduce
a novel behavioral phenotype—short-term intake from a single tube by non-deprived
animals (Kotlus and Blizard, 1998)— to determine whether this
faster test detected
previously reported QTL on chromosomes 4 and 6. Also, we studied several gustatory
phenotypes in order to evaluate the potential for detecting multiple QTLs in the same group of
animals. Finally, the mapping population included both males and females to broaden the scope
of generalization concerning QTL previously detected.
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Materials and methods |
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Animals and maintenance procedures
Inbred mice from the B (two males, three females) and D (seven males, four females)
strains, the B/D F 1 (nine males, nine females derived from a unidirectional cross)
and B/D derived F 2 (61 males, 72 females) were subjects for this experiment. They
were bred at the Center for Developmental and Health Genetics Animal Laboratory at
Pennsylvania State University. A 12 h/12 h light/dark cycle was maintained in the animal room.
Temperature was controlled at 70 ± 1°F. After weaning at 25–28 days,
animals were individually housed in clear plastic cages on wood-chip bedding until 60 days of
age, when fluid intake tests for alcohol preference and alcohol acceptance were administered; for
a description of procedures see Rodriguez et al. (Rodriguez et al.,
1994). Forty
days after completion of these tests, when mice were ~130 days old, the taste tests described
below were administered. One week before the beginning of the tests, the mice were switched
from tap to distilled water and this regime was continued until the completion of the experiment.
Fluid intake test
A short-term, fluid intake test was used to characterize individual variation in intake of `sweet' and `bitter' tastants. In this paper `sweet' and `bitter' are used to refer to chemical solutions usually classified with those descriptors by humans. Use of these terms to describe solutions is not intended to imply that the human taste qualities of sweet and bitter have counterparts in animals.
The rationale for the test has recently been described (Kotlus and Blizard, 1998) and
estimates of measurement stability provided. The test presents solutions to nondeprived animals
in single, 25 ml, graduated tubes in the position on the home-cage normally occupied by the
water-bottle. Intakes of relevant tastants are recorded for a 6 h period beginning 3 h prior to the
onset of the 12 h dark phase, thus ensuring that data collection coincides with the phase in the
circadian cycle when mice begin to drink. In the 18 h inter-test period animals are maintained on
distilled water ad libitum. The solutions were given on consecutive days in the
following order: distilled water (DW), sucrose (100 mM), sodium saccharin (10 mM), quinine
HCl (1.1 mM), and then repeated, the complete sequence lasting 8 days. Mice drink
approximately 1.0–2.0 ml of water, 1.0–10 ml of sucrose or saccharin and from 0
to 1.5 ml of quinine HCl in the 6 h period.
Genotyping
DNA was extracted from tail tips (Laird et al., 1991).
Anonymous
microsatellite markers (Research Genetics, Huntsville, AL) were used to type DNA from each
animal. Seven markers were used to type DNA on chromosome 4, and five on chromosome 6.
Care was taken to include markers which were close to the sites of Sac, Qui and dpa(see QTL section of Results). Amplification was performed on a Perkin-Elmer
9600 thermocycler. The total volume of kerning24 the reaction mixture was 12.5 ml,
consisting of 30 ng genomic DNA, 0.4 µm primers, 0.2 mM of each dNTP, 0.5 U Taq
polymerase (Perkin-Elmer Cetus, Foster City, CA), 10 mM Tris–HCl, pH. 8.3, 1.5 mM
MgCl 2, 50 mM KCl, and 0.16 mg/ml bovine serum albumen (BSA). Thermal
cycling included a 5 min. denaturation step at 94°C, 35 cycles of 30 s at 94°C, 30 s at
53°C, 30 s at 72°C and a final extension step for 10 min. at 72°C. PCR products
were separated on 4% agarose gels and visualized with ethidium bromide staining. Inbred strain
(B and D) and heterozygote DNA were included as standards with each batch of experimental
samples. The gels were photographed to provide a durable record of the results.
Statistical analysis
Statistical analysis of intake data
Statistical analyses were conducted with the Systat for Windows software package
(Wilkinson et al., 1992). F ratios and the degrees of freedom for
numerator and
denominator derived from analyses of variance are presented in the following manner: [F(1,130) = 26.27].
QTL analysis
Linkage between markers was determined using the IBMcompatible Mapmaker/EXP
(version 3.0) software package using a maximum likelihood procedure. QTL analyses of the
solution intakes were performed using Mapmaker/QTL (version 1.1), which employs an interval
mapping method to determine the position of a QTL and the proportion of phenotypic variance
that may be attributed to it (Lander et al., 1987). The principal
parameter used by
Mapmaker to determine statistical significance is the LOD score (log of the odds ratio). This
expresses the likelihood of the observed data (assuming the presence of a QTL at a particular
location) divided by the likelihood of no QTL at that position (the null hypothesis) as log to the
base 10. Thus, a LOD score of 3.0 represents an odds ratio of 1000 to 1 that a specific QTL exists
at a given location. Due to the multiple comparisons which occur during whole genome scans a
`protected' LOD score of 4.3 has been suggested (Lander and
Kruglyak, 1995) to
equate to the (P < 0.05) conventional two-tailed level of significance in an F 2 intercross (where there are three independent genetic classes and therefore n– 1, or 2 degrees of
freedom). Mapmaker conducts separate analyses according to
different assumptions about dominance relations at each marker: free, degree of dominance
estimated from the data; dominant, B allele kerning24 completely dominant; recessive, B
allele completely recessive; additive, heterozygote is the mean of homozygotes. For one model to
be preferred over another, convention requires a difference between LOD scores 
1.0. The
1-LOD support interval (which approximates the 95% confidence interval) is
estimated as the interval defined by values on the QTL plot at 1 LOD below the peak LOD score.
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Results |
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Inbred strains and F 1s
Repeated measures analysis of variance of first and second presentations of the four solutions only found a statistically significant change in the case of sucrose. For this solution, intake on the second presentation was significantly higher [F(1,28) = 6.62, P < 0.02]. There was no interaction of day of presentation with strain or gender. Pearson productmoment correlations (r) of the pooled data revealed high positive correlations between first and second presentations of all three flavored solutions (sucrose, 0.88; saccharin, 0.85; quinine, 0.73; P< 0.0001 in all cases), but a low correlation (0.28, P< 0.12) between first and second water intakes. Intakes for first and second presentations of each solution were therefore summed for statistical analysis. Pearson product-moment correlational analysis of the combined scores revealed a high positive correlation between sucrose and saccharin intake and between water and quinine intake (Table 1). These high correlations are likely the result of associations among strain means in the different measures of intake rather than individual variability within genotypes.
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The combined intakes of the three different flavored solutions are shown in Table 2. There were no statistically significant differences between males and females in intake of any of the solutions, so gender was ignored in subsequent analyses. Analysis of variance revealed highly significant differences between the three genetic groups [F(2,31) (sucrose = 20.15, P < 0.0001; saccharin = 23.43, P < 0.0001; quinine = 6.47, P < 0.004)]. Post-hoc comparisons using the Bonferroni protection procedure showed that B mice drank more sucrose (P < 0.001) and saccharin (P < 0.0001) and less quinine (P < 0.03) than D mice. F 1 intake of the `sweet' solutions did not differ significantly from that of B mice and was higher than that of D mice (sucrose and saccharin, P < 0.0001). F 1 intake of quinine was similar to the level exhibited by D mice, differing significantly from B mice (P < 0.003). There were no statistically significant differences in 6 h water intake between the groups (P < 0.31). Separate analyses of variance of first and second presentations of each solution yielded similar group differences to those provided by analyses of combined intakes (P < 0.0001 for both presentations of sucrose and saccharin; P < 0.002, P < 0.04 for first and second presentations of quinine; water, not significant on both occasions).
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Considering changes from baseline water intake, Table 2 shows clearly that B and F1 mice drank more of both sucrose and saccharin solutions. Repeated measures analyses of variance of intakes within the D strain suggested that the D mice (n = 11) also drank more of the `sweet' solutions than water [F(1,10) (sucrose, = 4.01, P < 0.07; saccharin = 5.87, P < 0.04)] but that the magnitude of the increase was modest and statistical significance was borderline. Table 2 also shows that B mice drank less quinine than water. Repeated measures analysis of combined quinine intakes indicated that D and F 1 mice also drank significantly less of the quinine solution than water [D mice, F(1,10) = 30.01, P < 0.0001; F 1 mice, F(1,17) = 16.16, P < 0.001)], these levels of significance obviating the need for post hoc protection.
F 2 generation
Repeated measures analyses of variance of first and second presentations of the four solutions found a statistically significant change for all three solutions: sucrose [F(1,127) = 14.02, P < 0.0001], saccharin [F(1,127) = 18.9, P < 0.0001], quinine [F(1,126) = 3.92, P < 0.05] and water [F(1,131) = 51.13, P <<0.0001]. Sucrose (3.62 versus 4.15 ml), saccharin (3.79 versus 4.34 ml) and water (1.10 versus 1.40 ml) intakes increased on the second presentation while quinine intake (0.78 versus 0.73 ml) decreased. There was no interaction of presentation order with gender or genotype at the microsatellite marker that was later found to best predict intake of the different solutions (see below). In spite of these changes in intake which occurred between presentations, correlational analysis revealed similar relationships between first and second presentations of the three solutions to that found among the inbred strains and F1s [r(sucrose, 0.79; saccharin, 0.81; quinine, 0.73; P< 0.0001)] in all cases. First and second water intakes were also significantly correlated (r = 0.45, P < 0.0001) at a slightly higher level than that seen in analyses of the fixed genotypes.
Intakes for first and second presentations of each solution were therefore summed for statistical analysis. Analysis of the combined intakes (Table 3) shows a strong positive relationship between sucrose and saccharin intakes, a modest positive correlation between either sucrose or saccharin intake and quinine intake; and water intake correlated modestly with intake of all three flavored solutions. To explore whether the relationship of quinine to sucrose and saccharin intake was dependent on their common relationship to water intake, the three variables were regressed on water intake and the relationships among the residuals explored. A small positive relationship was preserved among residuals [r(sucrose/quinine = 0.21, P < 0.022; saccharin/ quinine = 0.26, P < 0.005)].
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The covariation among fluid intakes was not based on variation in body weight which did not correlate significantly with intake of any of the solutions when data from the entire group were analyzed. Among males, there was no significant relationship between body weight and any measure of fluid intake, and significant correlations with body weight among females were restricted to combined kerning24 sucrose (r = 0.34, P < 0.004) and combined saccharin intakes (r = 0.39, P < 0.001).
Analyses of variance, carried out to assess the contribution of gender to each variable, revealed that female mice exhibited slightly higher fluid intakes than males [F(1,131) (water = 3.93, P < 0.05, male 2.36 ± 0.09, female 2.63 ± 0.09; sucrose = 4.05, P < 0.05, male 6.98 ± 0.54, female 8.44 ± 0.49; saccharin = 6.34, P < 0.01, male 7.19 ± 0.51, female 8.93 ± 0.47)]. There was no gender difference in intake of the quinine solution [F(1,131) =1.62, P < 0.21].
As noted above, water intake was associated significantly with intake of all three solutions in the F 2 generation. To assess the appropriateness of adjusting intake of the three solutions for baseline water intake in QTL analyses, we calculated product-moment correlation coefficients between water and solution intake within the three allelic classifications (BB, BD, DD) for those markers which were later found to be the best predictors of intake of the `sweet' and `bitter' solutions (D4Mit42 for sucrose and saccharin, D6Mit338 for quinine). The numbers of animals within these genotypic classes are recorded in Table 6. For the D4Mit42 marker, correlations were statistically significant among mice which were DD homozygotes [r(water/sucrose = 0.61, P < 0.0001; water/saccharin = 0.59 P < 0.0001)], but not statistically significant or of borderline significance among mice which were heterozygotes [r(water/sucrose = kerning24 0.25, not significant; water/saccharin = 0.27, not significant)] or BB homozygotes [r(water/sucrose = 0.26, not significant, water/saccharin = 0.31 P < 0.05)]. For the D6Mit338 marker there was a statistically significant relationship between intake of water and quinine among DD mice [r(water/quinine = 0.35, P < 0.05)] and heterozygotes: [r(water/quinine = 0.38, P < 0.002)], but not among BB homozygotes [r(water/ quinine = 0.27, not significant)]. In all of these cases, possession of the allelic variant which was associated with a large deviation of solution intake from baseline water intake perturbed the `usual' relationship between intake of water and flavored solutions.
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The effect of gender on solution intake was also dependent on genotypic class. For both sucrose and saccharin solutions, females drank significantly more than males if their genotypic classification at D4Mit42 was BB [F(1,40) saccharin = 6.67, P < 0.01, male 8.03 ± 1.0, female 11.27 ± 0.75; sucrose = 4.04, P < 0.05, male 7.73 ± 1.09, female 10.46 ± 0.81)], exhibited a non-significant trend in the same direction if their genotype was BD (saccharin, male 8.08 ± 0.64, female 9.31 ± 0.0.70; sucrose, male 7.67 ± 0.69, female 9.09 ± 0.76), but did not differ from males if their D4Mit42 classification was DD (saccharin, male 4.74 ± 0.66, female 5.29 ± 0.59; sucrose, male 4.96 ± 0.82, female 4.91 ± 0.74).
The variability in the relationship between water intake and the three other solutions within the different genotypic classes precluded use of water intake for the purpose of statistical adjustment. Gender corrections could not be applied for the same reason.
QTL analyses
Sucrose and saccharin intakes
Combined intakes were used for the primary Mapmaker analyses. Log transformations
were also applied to intakes to remove slight deviations from normality.
As shown in Figures 1A and B, both sucrose
and saccharin intakes were strongly
related to variation on distal chromosome 4 (for sucrose intake the peak LOD score was 8.85 and
for saccharin, 10.61). Sucrose and saccharin QTL accounted, respectively, for 27.7 and 31.2% of
the phenotypic variance. Complete dominance of the B allele for increased intake was the model
which provided the best fit for sucrose intakes. The peak LOD score of 8.45 for the dominant
model did not differ significantly from the `free' LOD score and exceeded that
calculated for the additive model (7.41) by more than 1 log unit. The dominant model also
provided the best fit for the saccharin data. Again, the relevant LOD score of 9.93 did not differ
significantly from that calculated for the free model, but in this case did not differ significantly
from that based on an additive model (LOD = 9.34). For both solutions, the recessive model was
unambiguously rejected (see Figures 1 and 2).
The statistical properties of the QTL on distal
chromosome 4 are summarized in Table 4. The QTL peaks for both
solutions were within 1 cM
of D4Mit42 at 81 cM which is close to the location estimated for the Sac locus
(Lush et al., 1995), but because no markers were typed distal to D4Mit42, the
1-LOD support interval or 95% confidence interval for the sucrose and saccharin QTL,
represented in Figures 1 and 2 by the dark
horizontal bar, only extends in a proximal or
centromeric direction. A more realistic confidence interval for the sucrose QTL would likely
project from D4Mit33 + 2.5 cM to the end of the chromosome which is currently
estimated by the Mammalian Genome Database (http:// www.informatics.jax.org), to be 3.0 cM
distal to D4Mit42, for a total of 10.4 cM. The analogous estimate for the saccharin QTL
extends from D4Mit33 + 4.0 cM to the end of the chromosome, a total distance of 9.4
cM.
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No other sucrose or saccharin relevant QTL emerged from Mapmaker analyses of the other regions of chromosomes 4 and 6, including the region of chromosome 4 swept by D4Mit286 at 14.5 cM which is ~4.0 cM proximal to the location for dpa suggested by Ninomiya et al. (Ninomiya et al., 1991
). However,
given that the large
effect of the QTL on distal chromosome 4 would appear in the error term of other QTL, sucrose
and saccharin intakes were regressed on allelic status at D4Mit42 (the marker closest to
the relevant QTL peaks) and Mapmaker analyses conducted on the residuals. No additional peaks
were detected on either chromosome.
Quinine intake
As shown in Figure 2, analysis of log-transformed, combined quinine
intakes
found a QTL in the region of D6Mit338 on chromosome 6 with a peak LOD score of
4.73 which accounted for 19.3% of the phenotypic variance. D6Mit338 at 62.3 cM is
close to Prp at 63.6 cM. Additive (LOD = 4.56) and recessive models (LOD = 3.91) for
the B allele for increased quinine consumption did not differ from the free model but the
dominant model was rejected (Table 4). The 95% confidence interval is
represented by the dark
horizontal bar.
No other QTL emerged from Mapmaker analyses of combined quinine intakes for
other regions of chromosomes 4 and 6. In addition, when quinine intakes were regressed on their
relationship to D6Mit338 and the residuals subjected to Mapmaker analysis, no
statistically significant LOD scores were detected. The only indication of the presence of QTL in
analyses of adjusted data were LOD scores of 1.89 and 1.78, found, respectively, near D4Mit246 and D4Mit286 (although not at D4Mit178 which is located
between them). Although not statistically significant or even `suggestive' using
Lander and Kruglyak's criterion (Lander and Kruglyak, 1995),
these findings are reported
in case similar results are obtained by other investigators in the future.
QTL-stability
To provide information on QTL stability, Mapmaker analyses were conducted separately on intakes obtained during first and second presentations of the three solutions. kerning24 As shown in Table 5, these revealed good agreement between QTL parameters (LOD score, proportion of phenotypic variance accounted for, and QTL location) for first and second presentations of sucrose and saccharin.
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Also shown in Table 5 are the QTL parameters for quinine on tests 1 and 2. In this case, the LOD score and proportion of phenotypic variance accounted for were similar on both test occasions, but the QTL peak in test 1 was to the left of D6Mit338 and to the right of the same marker in test 2.
Analyses of variance of F 2 data
Table 6 shows the mean differences in solution intake associated with allelic variation at markers closest to the QTL peaks. Log transformations of the raw data removed slight deviations from normality and were uniformly adopted before proceeding with statistical analyses. Analysis of variance of intake of `sweet' solutions using allelic variation at the D4Mit42 locus as the independent variable yielded highly significant F ratios [F(2,130) sucrose = 23.46, P < 0.00001; saccharin = 29.37, P < 0.00001]. Bonferroni-protected post hoc tests indicated that both BB and BD mice (at D4Mit42) drank more of both solutions than DD mice (P < 0.0001 in all comparisons). Analysis of variance of quinine intakes, using allelic status at the D6Mit338 locus as the independent variable also yielded a significant difference between the groups [F(2,130) = 10.52, P < 0.0001]. Bonferroni-protected post hoc tests indicated that BB mice (at D6Mit338) drank less quinine than BD (P < 0.006) and DD mice (P < 0.0001), while the difference between BD and DD groups did not reach statistical significance (P < 0.09).
Paralleling the Mapmaker analyses of the adjusted quinine intakes where a non-significant trend had been noted on chromosome 4, analysis of covariance of quinine intake using D6Mit338 as the covariate gave the following results: D4Mit246, F(2,128) = 2.70, P < 0.07; D4Mit286, F(2,128) = 2.24, P < 0.11. The means and standard errors in quinine intake associated with these differences were as follows: D4Mit246 (BB 1.25 ± 0.15; BD 1.55 ± 0.10; DD 1.63 ± 0.13); D4Mit286 (BB 1.21 ± 0.16; BD 1.59 ±f2 0.10; DD 1.57 ± 0.12).
Summary
In summary, among male and female offspring of an intercross of B and D mice, ~30% of the total phenotypic variation in sucrose and saccharin intake during a 6 h test period appears to be determined by the same locus or loci on distal chromosome 4. Analogously, for quinine intake, a locus or loci on medial/distal chromosome 6 accounts for ~20% of the variation. The bulk of the evidence supported a dominant role for the B allele on chromosome 4 in increased intake of sucrose and saccharin, while intermediate or additive inheritance (defined as the midpoint between the B and D alleles) of the alleles on chromosome 6 provided the best model to account for variation in quinine intake.
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Discussion |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionReferences |
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Short-term test of fluid intake
Previous research using long-term two-bottle preference kerning24 procedures has
implicated specific regions of mouse chromosomes 4 and 6, respectively, in intake of
`sweet' (Belknap et al., 1992; Phillips et al., 1994; Lush et
al., 1995; Bachmanov et al., 1997) and
`bitter' (Azen et al.,
1986; Lush and Holland, 1988; Lush, 1991; Capeless et al.,
1992; Harder and
Whitney,
1998) solutions. We mapped QTL which influenced 6 h intake of sucrose, saccharin
and quinine
solutions to the same chromosomal regions. Thus, both longand short-term tests are influenced
by at least two of the same genetic variations.
Fuller (Fuller, 1974) reported complete dominance of the B allele for
increased
saccharin consumption based on his comparisons of the B and D parental strains and their F1 hybrid. More specifically, Bachmanov et al. (Bachmanov et al., 1997)
reported that the same dominance model fitted allelic interactions at the Sac locus on
distal chromosome 4 in their study of two-bottle sucrose consumption in F 2 mice
derived from a cross of C57BL/6By and 129/J strains. Using the B and D strains, we found
allelic variation on distal chromosome 4 governing 6 h intake of both sucrose and saccharin to be
best described by the same dominant model, although an additive model for saccharin
consumption could not be rejected. For quinine consumption, the present experiment found that
an additive model best described allelic influences at the QTL on chromosome 6, although a
recessive mode of action for the B allele for increased quinine consumption could not be
rejected.
The proportion of phenotypic variance accounted for by and the location of the Sac
locus were similar to previous estimates by Bachmanov et al. (Bachmanovet al., 1997). Thus, inclusion of both males and females in the present
experiment was not
associated with a disproportionate loss of statistical power. This would suggest that any variation
associated with the estrous cycle or any other sexually dimorphic character did not substantially
increase the phenotypic variance. Inclusion of both genders in future studies would increase
knowledge of the role of gender in genetically based individual variation in gustatory processes.
The short-term test provides more specific information regarding the time required for
the genes to manifest their effects. By comparison, the two-bottle procedure provides information
regarding the stability of the variation in fluid intake over substantial periods of time. Thus, the
results obtained with the different measurement procedures are usefully supplementing each
other. Fluid intake during the 6 h test occurs mainly during the 3 h dark phase after
`lightoff' (D.A. Blizard, unpublished results). Nevertheless, both 3 and 6 h periods
are long enough to permit fluid intake to be influenced by post-ingestional factors (Davis, 1973).
These could include the physiological effects of the particular solution ingested (Beauchamp and
Fisher, 1993), or the effects of food-intake on fluid consumption (Kotlus
and Blizard, 1998).
Despite these limitations, the 6 h test provides a reliable short-term screen of fluid intake from a
large number of animals using a discrete trial approach and is eminently suitable for
gene-mapping experiments of the type described in this report.
Multiple phenotyping
The present experiment used a multiple phenotyping strategy encompassing solutions with contrasting effects on behavior in an effort to increase the return from the large effort involved in genotyping. The results affirm its utility: QTL predicted to occupy specific chromosomal regions were unambiguously detected and they accounted for approximately the same degree of phenotypic variance estimated in previous determinations. In addition, although analyses of variance found statistically significant differences between first and second presentations of the three flavored solutions, the QTL for sucrose and saccharin were reliably detected on each of the two measurement occasions. In the case of quinine intake, LOD scores did not reach acceptable levels of statistical significance on both measurement occasions and the estimated location of the QTL shifted. Without additional data, it is impossible to determine if the quinine results are due to variation introduced by the particular sequence of solutions used or simply from the loss of reliability resulting from use of one versus combined samples of fluid intake.
In our analyses of intakes combined across both presentations, we discovered that taste genes can be mapped reliably even when contrast effects, other sequence effects, and access to ethanol 1 month before could have contributed to total phenotypic variability. This means that the relevant genes influence intake of `sweet' and `bitter' solutions in a variety of circumstances. Nevertheless, multiple phenotyping may not always prove to be a good experimental strategy. Although the combination of solutions used in this experiment and the specific sequence that was used did not have a major impact on QTL detection, different combinations and sequences may.
Multiple phenotyping also had the additional benefit of revealing a statistically
significant positive correlation in the F 2 group between the two
`sweet' solutions, on the one hand, and quinine, on the other, even after
adjustments for their relationship to water intake. This is a phenotypic correlation and therefore
could be caused by either genetic or environmental influences. The differences in intake between
first and second presentations of all solutions in F 2 mice bespeak an environmental
influence (for example, contrast or sequence effects) which could contribute to the association.
Alternatively, the putative influence of genes such as f1 agustducin on intake of both
`sweet' and `bitter' solutions provides a genetic basis for such an
association (Wong et al., 1996).
Mechanisms of gene action at the Sac locus
Frank and Blizard (Frank and Blizard, 1996, 1999) showed that chorda tympani (CT)
response to sucrose and saccharin was greater in B than D mice and that the CT threshold to
sucrose was also lower in B mice. In addition, Bachmanov et al. (Bachmanov et al., 1997) showed that the C57BL/6By strain (which is
closely related to the B strain used in
our experiment) exhibited similar differences in CT response to sucrose compared to the 129/J
strain. Both experiments draw attention to the periphery as a possible site of action of the Saclocus. However, strain comparisons between inbred strains of diverse genetic origin
necessarily involve confounding of differences at a specific genetic locus with many other allelic
differences. Unless there is only one gene in a cross that contributes to the relevant phenotypic
variation, strain comparisons are only the first step in identifying biological mechanisms for
further study. In the Bachmanov et al. (Bachmanov et al., 1997) study, it was
estimated that the two QTL which influenced intake of sucrose accounted for some 50% of the
genetic variance. The inference to be drawn is that there are additional genes that account for the
residual genetic variance in sucrose intake. In efforts to identify these, two RI–QTL
studies (Belknap et al., 1992; Phillips et al.,
1994) have nominated possible
sites (aside from chromosome 4) on chromosomes 1, 3, 6, 8, 9, 12, 13, 15 and 18 governing
two-bottle saccharin consumption in the B/D lineage.
Thus, strain comparisons of possible mechanisms need to be supplemented by studies
in which allelic variation at a specific locus are used as the independent variables. A pioneering
example of this is the experiment by Bachmanov et al. (Bachmanov et
al.,
1997) who studied CT response in F 2 animals derived from an
intercross of
C57BL6/By and 129/J strains and found that the number of B alleles at the D4Mit42
marker on distal chromosome 4 was positively correlated with the relative magnitude of CT
response to supra-threshold sucrose solutions. This evidence supports the working hypothesis
that variants at the Saclocus exert their effect by altering the peripheral receptive
apparatus in the two strains. It seems highly likely that a similar relationship between allelic
variants at the Saclocus and CT response exists in the B and D strains. The B/D strain
difference in CT response mirrors that found between C57BL/6By and 129/J strains. In addition,
careful comparisons by Capeless and Whitney (Capeless and Whitney, 1996) have documented
close parallels between the twobottle saccharin intake phenotype exhibited by D and 129/J
strains.
That the Saclocus exerts its influence upon one or more peripheral gustatory
processes is consistent with the fact that two of the three solutions (saccharin, sucrose and
acesulfame) whose intake has been shown to be influenced by Sac(Lushet al.,
1995; Bachmanov et al. 1996, 1997; Frank and Blizard,
1996, 1999) are
artificial
sweeteners. Hence, it is highly unlikely that the alterations in intake associated with Sac are related to metabolic processes or post-ingestional effects. The `peripheral'
interpretation is also supported by the results of the present experiment in which a short-term test
designed to minimize postingestional influences was used and Sacexerted the same
magnitude of effect previously seen in studies which measured intake over periods of days.
Mechanisms of gene-action at the Qui locus
Frank and Blizard (Frank and Blizard, 1996, 1999) reported that, relative to B mice, D
mice exhibit lower aversion and a greater CT response to quinine. Thus, assuming a simple
relationship between the degree of quinine aversion and activity in the chorda tympani, a
peripheral site of action for Qui does not seem to be a reasonable working hypothesis.
However, there may be a variety of genes in the B/D lineage that exert effects on quinine intake
and interpretation of the relationship between Qui and CT response to quinine must
await their investigation. No whole genome kerning24 scan of quinine intake in the B/D
lineage has been published. However, a recent RI–QTL study of quinine and
propylthiouracil (PROP) intake in the BXH RI set by Harder and Whitney (Harder
and Whitney,
1998) nominated locations on chromosomes 3, 6, 7, 8 and 9.
The region of chromosome 6 defined by the Qui confidence interval has also
been associated with variation in intake of other `bitter' solutions, including
cycloheximide, raffinose acetate and glycine in the BxD lineage (Lush, 1986; Lush and
Holland, 1988), and with SOA and PROP in other lineages (Capeless et al., 1992;
Harder and Whitney, 1998). Lush (Lush, 1984, 1986) has speculated that the results
obtained
within the BxD lineage are consistent with the presence of a family of closely linked
genes, each with varying degrees of specificity for the different solutions, a view which has been
sharply challenged by Harder and Whitney (Harder and Whitney, 1998)
who questioned the
independence of these loci and offered a more parsimonious view in which the associations of
this region of chromosome 6 with variation in intake of `bitter' solutions was more
plausibly understood as the result of allelic variation at a single locus, Soa. The effects
of Soa are proposed to reflect allelic variation in the closely linked Prp family
of genes, which control the secretion of proline-rich proteins in saliva (Azen et
al.,
1986; Azen, 1991). Consistent with this, haplotype variation
in Prp across several
mouse strains predicts SOA aversion to a remarkable degree (Harder et
al.,
1992). Nevertheless, direct evidence of a functional link between SOA aversion and
the Prp gene has not yet been obtained.
Soa and Qui map to the same location of mouse chromosome 6 (albeit in
different lineages) and may be the same gene (Harder and Whitney, 1998). However, until
identity is established it seems useful to maintain separate nomenclatures. A compelling reason is
that compared to D mice, B mice strongly avoid quinine while the opposite relation of the two
strains exists regarding two-bottle intake of a 1 mM sucrose octa-acetate solution (Harder et
al., 1992). If the same gene accounts for the contrasting strain variations, its
mechanism of
action will need to be understood in enough detail to explain its opposite effects on intake of two
`bitter' solutions.
To summarize, although there are several promising avenues of investigation for both Sac and Qui, it is not yet known how the allelic variants exert their effect at
either locus. Among other possibilities, anatomic differences in the number of taste buds,
receptors or modality-specific primary afferents could alter, separately or collectively, the
magnitude of the neural response to supra-threshold solutions and be a plausible peripheral site
for gene action. Alternatively, in the absence of anatomical differences, the allelic variants at Sac and Qui loci could alter the biochemical events (for example, Spielmanet al.,
1994) which link receptor occupation to stimulation of an action potential in the
afferent neuron.
Sac and Qui: a human perspective
It is conceivable that Sac and Qui have homologues in other species,
including humans. If so, mutations at these loci may contribute significantly to the individuality
of human gustatory sensibility. As discussed by Bachmanov et al. (Bachmanov et
al., 1997), knowledge of the chromosomal locations of genes in mice is helpful
in
suggesting regions of the human genome that may contain homologues of the relevant genes. A
logical extension of the QTL approach is to fine-map the present loci and attempt positional
cloning of the relevant genes. This has been successfully achieved for several single genes in
other fields of inquiry (Probst et al., 1998) but has yet to be
carried out for a QTL.
Nevertheless, Sacand Qui (or Soa) are attractive candidates for
positional cloning because the phenotypic effect of allelic substitutions at these loci is large and
this is a major advantage in relating phenotype to genotype. Lush et al. (Lush et al., 1995) used categorical assignment procedures (i.e. preferring versus
non-preferring) to
map Sac to a more precise location distal to D4Mit42. Their approach assumed
that loci in other chromosomal locations had little or no influence on intake of relevant solutions.
If such loci exist, however, their contribution to the scores of individual animals could result in
mis-classification and errors in estimating the location of Sac. Thus, in addition to
providing potential new models for investigation, the results of QTL studies of the whole genome
will assist the fine-mapping of Sac and Qui by describing the genetic
architecture underlying intake of relevant solutions.
Other QTL sites on chromosomes 4 and 6
As previously noted, Ninomiya et al. (Ninomiya et al., 1991)
reported the existence of a gene (dpa) on proximal chromosome 4 that influenced
variation in CTA generalization from D-phe to sucrose in a cross of C57BL/6CrSlc
and BALB/cCrSlc strains. Bachmanov et al. (Bachmanov et al.,
1997) also
detected a provisional QTL on proximal chromosome 4 that contributed to variation in two-bottle
sucrose intake in their cross. Their data furthermore suggested an important interaction between
proximal and distal QTL: demonstration of an influence of allelic variation at the proximal
location required the presence of a C57BL6By allele on distal chromosome 4 (and vice versa).
They suggested that the proximal QTL was likely to correspond to dpa. Aside from our
inability to detect a QTL on proximal chromosome 4 using both raw intakes of sucrose and
saccharin as well as intakes adjusted for the large effect of D4Mit42 on distal
chromosome 4, analyses of variance provided no indication of an interaction between proximal
and distal markers. However, our failure to detect a QTL in this location should not be taken as
evidence for or against the existence of the dpa locus. We used a different phenotyping
procedure than the two earlier studies and the DBA/2J (the strain we crossed with B) and
BALB/cCrSlc— the strain Ninomiya et al. (Ninomiya et al.,
1991)
crossed with C57BL/6CrSlc—strains may carry different alleles at the dpa locus.
To clarify the possible contribution of the other variables to the experimental
outcomes, it would be useful to carry out studies in which the different phenotypes were mapped
in the same lineage. In this case, Capeless and Whitney's strain comparison of
consumption of a range of concentrations of D-phe and saccharin using the
two-bottle test would be helpful in selecting suitable strains for crossing (Capeless
and Whitney,
1996). No other locations on chromosomes 4 and 6 reached statistical significance.
Overview
The large effects that Sac and Qui exert on intake of
`sweet' and `bitter' solutions are consistent with the existence of
genes which play an important role in gustation. As noted, Sac may well work via a
peripheral site of action, but the gene(s) responsible remains to be identified. As confidence
intervals circumscribing these QTL are reduced by implementation of fine-mapping protocols
(Darvasi, 1997), both cloning and candidate gene approaches will become practical. One
candidate gene, 
-gustducin, has not yet been mapped but, given the effects of an f1
-transducin knockout preparation on intake of both `sweet' and
`bitter' solutions (Wong et al., 1996), it would be
a provocative candidate
for either Sac or Qui, if it is found to reside in the pertinent regions of
chromosomes 4 or 6. In the final stages of manuscript completion, another candidate gene has
emerged as a plausible candidate for Sac. TR1 is a clone of a 7-transmembrane domain
protein receptor (Hoon et al., 1999). The sequences it shares
with candidate mammalian
sensory receptors, its specific expression in taste receptor cells of the tongue and palate and its
high topographic selectivity (it is differentially expressed in fungiform versus circumvallate
papillae) suggest it as a highly plausible candidate for Sac. There is an urgent need to
conduct studies in which Sac and TRI are typed in appropriate mapping populations.
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Acknowledgments |
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We thank the following colleagues at the Center for Developmental and Health Genetics: Helen A. Lake for help with animal husbandry, Lisa M. Tarantino and Scott M. Hofer for discussions of statistical issues and Eric Gudas for help with genotyping. Thomas P. Hettinger of the Department of Biostructure and Function gave valuable advice at many stages of the investigation. Supported by DC-02230 to DAB and DC-00058 to MEF.
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Accepted March 23, 1999
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M. Inoue, S. A. McCaughey, A. A. Bachmanov, and G. K. Beauchamp Whole Nerve Chorda Tympani Responses to Sweeteners in C57BL/6ByJ and 129P3/J Mice Chem Senses, September 1, 2001; 26(7): 915 - 923. [Abstract] [Full Text] [PDF]
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A. A. Bachmanov, X. Li, D. R. Reed, J. D. Ohmen, S. Li, Z. Chen, M. G. Tordoff, P. J. de Jong, C. Wu, D. B. West, et al. Positional Cloning of the Mouse Saccharin Preference (Sac) Locus Chem Senses, September 1, 2001; 26(7): 925 - 933. [Abstract] [Full Text] [PDF]
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 R. Sandberg, R. Yasuda, D. G. Pankratz, T. A. Carter, J. A. Del Rio, L. Wodicka, M. Mayford, D. J. Lockhart, and C. Barlow From the Cover: Regional and strain-specific gene expression mapping in the adult mouse brain PNAS, September 26, 2000; 97(20): 11038 - 11043. [Abstract] [Full Text] [PDF]
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