1 Department of Biology, Portland State University, Portland, 97207
2 Department of Behavioral Neuroscience and Portland Alcohol Research Center, Oregon Health and Science University and Veterans Affairs Medical Center, Portland, Oregon 97201
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ABSTRACT |
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alcohol; temperature regulation; recombinant inbred strains; genetics
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INTRODUCTION |
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For mice and rats, individual differences in sensitivity to the thermoregulatory effects of ethanol are known to be partially controlled by genetics (20). The probability of identifying genes that underlie these different effects of ethanol has been greatly increased by a number of recently developed procedures. One approach is to "knock out" various genes and their products and assess each genes importance by measuring subsequent effects on the system of interest. A more global approach is to evaluate the likelihood of all genes involvement in a particular response. We used one such global approach, employing the statistical association of physiological responses with genetic markers to identify quantitative trait loci (QTLs).
Each physiological response that a population of animals exhibits typically reflects a varied contribution of many genes. In this study, such phenotypic traits include changes in Tc, variability in Tc, and changes in tail temperature (Tta) following ethanol administration. The continuous distributions of individual differences that underlie such responses confirm the influence of multiple genes, with each gene exerting a quantitative, rather than an all-or-none, effect on the trait. Sites on a chromosome that contain one or more genes that influence a measured phenotype are termed QTLs (10). One method for identifying and mapping QTLs involves the use of panels of recombinant inbred (RI) mouse strains. Because they are inbred, mice of the same sex from each of these strains are similar to monozygotic twins with identical alleles at each genetic locus.
A widely utilized RI panel (BXD) was derived from an F2 cross between C57BL/6J (B6) and DBA/2J (D2) mice. The development and use of this approach has been described (10). Briefly, inbred strains (in this case B6 and D2 mice) are crossed to form an F1 generation that is heterozygous for all genes that differ in the parents. Crossing F1 mice produces an F2 generation that is segregated genetically. Unique BXD RI strains were produced by inbreeding novel F2 individuals for many generations; each RI strain now has a fixed, different pattern of B6 and D2 alleles due to genetic recombination (3). Genetic markers at more than 1,500 loci signify the allelic status at these loci (B6 or D2) of each RI strain as well as the B6 and D2 progenitor strains.
The BXD RI panel is useful for locating any genes of interest that are polymorphic between the B6 and D2 progenitor strains. For the traits described in this study (Tc, etc.), polymorphism at some genes is likely since the two strains respond differentially to ethanol (14). B6 mice are more sensitive to the effects of ethanol on regulated temperature, whereas D2 mice are more affected by actions of ethanol that decrease the overall accuracy of the regulatory system. Differences between these two strains can thus be exploited by QTL methodology to identify genes most likely to be involved in mediating the different effects of ethanol on thermoregulation (9, 11).
To perform a QTL analysis using the BXD RI strains, each progenitor strain and RI strain is tested for the average degree of expression of phenotypic traits. The possession of specific alleles at genetic markers is then correlated with the mean strain phenotypic response in these 26 genotypes. Since each allele is known to derive from either a B6 or a D2 strain, if a particular marker allele is highly correlated with a phenotypic response characteristic, then it is inferred that a nearby (linked) gene affects the trait.
The purpose of the current study is to evaluate the genetic basis for the effects of ethanol on the thermoregulatory system using the above approach. A varying ambient temperature (Ta) regime was employed to allow simultaneous evaluation of the effects of ethanol on regulated body temperature (mean change in Tc) and on accuracy of temperature regulation (variation in Tc) after administration of 1.5, 2.5, and 3.5 g/kg ethanol. In addition, an index of a thermoregulatory effector response (Tta) was monitored after administration of 2.5 g/kg ethanol. Twenty-four RI strains were evaluated, and a QTL analysis was performed on the strain means.
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METHODS |
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Injection protocols.
Ethanol was administered intraperitoneally as a 10% vol/vol solution. Each mouse was tested in two blocks of injections. The first block involved the alternating temperature experiments and was organized in the following sequence: saline, 1.5 g ethanol/kg, 2.5 g ethanol/kg, 3.5 g ethanol/kg. The second block comprised the constant temperature experiments, which consisted of a saline injection and a 2.5 g ethanol/kg injection. The saline injections contained the diluent for ethanol (0.9% NaCl) and were administered in a volume equivalent to the 3.5 g ethanol/kg injections. All injection solutions were warmed to 38°C. Saline injections were treated as the final stage of habituation and as confirmation that the mouse responded in a normal way to the injection procedure per se. These data were not used in the comparisons across the strains tested. Injections of NaCl alone were followed by at least 2 days of rest. A minimum of 3 days of rest followed each ethanol injection.
Alternating temperature experiments.
Partially restrained mice were exposed to cyclic changes in Ta as depicted in Fig. 1 and described in detail in Crawshaw et al. (14). Briefly, changes in Ta were produced by airflows that emanated from two air sources, regulated at 46.5 ± 0.3 and 10.0 ± 0.2°C. Entrance and exhaust fans directed the air from either of the two sources into the chamber that held the mouse. A timer switched the fans for one source off, and for the other source on, every 6 min. Passive one-way valves prevented air leakage between the two sources. The usual thermal extremes in the mouse chamber, as recorded by a thermocouple just in front of the mouse, were 14 and 42°C. The rate of airflow in the vicinity of the mouse varied from 13 m/s. An important function of the restraint was to maintain a relatively fixed orientation of the animal with respect to the airflow.
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Partial restraint was accomplished by fitting mice with a rubber-lined plastic collar that was affixed to a track and could thus slide forward or backward (but not sideways) for 10 cm. To minimize stress during the procedures, mice were habituated to experimental conditions as follows: days 1 and 2, 1015 min of handling; days 3 and 4, alone in cage with collar on for 2 h; days 5 and 6, in partial restraint system as used in experiments for 2 h; days 7 and 8, mice partially restrained and placed in an alternating temperature habituation environment (extremes of 39 and 23°C with a period of 12 min) for 2 h.
To begin an experiment, the animal was first weighed and then placed in the restrainer. Next, an epoxy tipped 36-gauge copper-constantin thermocouple (Pirelli Cable) was inserted 2.5 cm past the rectum and taped to the tail. A strip chart recorder (Linear model 0595) was used to monitor Ta and Tc as calibrated voltages. The instrumented and restrained mouse was then placed inside the chamber, and video recording was initiated. The video recording was continued throughout the experiment. After 15 min, the air flow was initiated. At this time, if Tc was 37.5°C or above, the experiment was started with a cooling interval. If Tc was below 37.5°C, the experiment was started with a heating interval. Injections were always made just after a cooling interval; normally the baseline period was thus 3 or 3.5 full cycles (36 or 42 min) depending on whether the experiment was initiated with a warming or a cooling interval. If the baseline was not stable at this time, another cycle was run. If the baseline remained unstable after 4 (or 4.5) cycles, the experiment was terminated. Otherwise, the run was continued for 3 cycles (36 min) after the injection.
Data analysis is best understood by reference to Fig. 1. Initially, Tc was transcribed at the end of each warming and cooling interval. These numbers were termed end values. To assess changes in the regulated temperature, postinjection Tc was subtracted from preinjection Tc. Postinjection Tc was the mean of the end values 24 and 30 min after the injection. Preinjection Tc was the mean of the end values 6 min before the injection and just before the injection (slightly before time 0). Disruption of the regulated temperature was evaluated by assessing the extent to which Tc varied between successive warming and cooling cycles. This number was derived from the mean of the absolute differences between the postinjection end values at 12 and 18 min, 18 and 24 min, 24 and 30 min, and 30 and 36 min.
Constant temperature experiments.
After completion of the experiments in the alternating temperature chamber, the mice were tested in a Ta of 26 ± 0.1°C. This Ta was employed because under the conditions of this experiment, 26°C was just below the threshold for active vasodilation. As Ta was increased above 26°C, vasodilation became more common, and it was difficult to obtain a steady baseline. As Ta was lowered below 26°C, the Tta response declined or disappeared. The air flow rate adjacent to the mouse was 0.50.6 m/s. If more than a week elapsed after the completion of the alternating temperature experiments, then the habituation procedure was repeated once before the mice were run in the constant temperature experiments.
To initiate an experiment, a mouse was partially restrained and outfitted with a rectal thermocouple (as above); in addition, a thermocouple was secured to the dorsal surface 1.5 cm distal to the base of the tail and covered with one layer of Johnson & Johnson clear tape. After 25 min at 26°C, Tta was monitored for a steady baseline. After at least 20 min of Tta within 1°C of Ta, the mouse was injected with either saline or ethanol. Ta, Tta, and Tc were recorded for 40 min after the injection. Changes in Tta were quantified by integrating the difference from baseline (in degree·minute) over the 18-min period following the injection. The response thus arrived at was termed "Tta response." Changes in Tc were quantified by taking the difference between mean Tc for the 18-min postinjection period and baseline Tc.
These latter experiments utilized Tta to evaluate blood flow changes in superficial tail regions. The goal was to use a thermoregulatory effector response for QTL analysis.
Statistical analyses.
Unless noted otherwise, statistical analyses utilized a two-way ANOVA for repeated measures or Students t-test for the difference between means. ANOVA values were utilized to produce estimates of heritability (h2), which were calculated as SSB/SST where SSB is the sum of squares between subjects for the factor strain, and SST is the sum of squares total. This estimate of h2 provides the proportion of the individual differences that is due to genetic influences. All results given in the text and in Figs. 2 and 3 are for the mean value ± one standard error of the mean (SE). The number of individuals tested from each strain was 1416 with the following exceptions: B6, n = 24; RI lines 1 and 25, n = 13; RI line 31, n = 17; RI line 8, n = 8. BXD line 8 (BXD-8) mice do not reproduce well. They have low fertility and small litters. Consequently, few animals were available for this study. Coupled with this was their apparent sensitivity to some feature of the procedure which led to the loss of several BXD-8 mice during the early phases of testing. Nevertheless, eight individuals completed the entire series of tests without incident, and the BXD-8 line was included in the QTL analysis. Genetic correlations among strain means were estimated using the Pearson product moment correlation (19). Unless otherwise mentioned, differences were taken to be significant at an level of P < 0.05.
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We report all provisional associations in Table 1, defining provisional to include those correlations significant at P < 0.01. Of the associations we have reported in other work achieving P < 0.01 in the RIs only, 50% have subsequently been found to represent false-positive associations when further populations were studied (8, 10). We present the larger group of provisional associations, because it is difficult to know in advance which will prove to be true and which will be false-positive associations. We believe it is important to reveal such provisional associations, even if some prove eventually to be false positive, because this protects us against a second type of error (type II error), which Lander and Kruglyak did not consider (5, 22). That is, if we prematurely reject a potentially important association because it does not achieve the very high level of significance demanded by Lander and Kruglyak, then we may miss an important gene when we turn to additional studies in other populations.
To evaluate the possibility of important covariates within the RI strain battery, the mean responses of the RI lines obtained in this study were correlated with the mean body weight of each RI line at the time of testing. The mean responses were also correlated with the rate of ethanol elimination for each strain (Grisel JE, Metten P, Wenger CD, Merrill CM, and Crabbe JC, unpublished observations).
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RESULTS |
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For change in Tc during alternating Ta, all doses produced a statistically significant difference across the strains tested [1.5 g/kg, F(25,368) = 2.62, P 0.001; 2.5 g/kg, F(25,363) = 4.96, P
0.001; and 3.5 g/kg, F(25,357) = 4.18, P
0.001]. For these same doses, respectively, genotype (h2) accounted for 15%, 26%, and 25% of the total variance.
For changes in the excursion, or range, of Tc following ethanol injections, only the two highest doses were statistically significant [1.5 g/kg, F(25, 369) = 1.40, P 0.1; 2.5 g/kg, F(25,363) = 2.11, P
0.002; and 3.5 g/kg, F(25,358) = 2.72, P
0.001]. Genotype accounted for 9%, 13%, and 16% of the total variance for these range values.
For the mice tested at a constant Ta of 26°C after 2.5 g/kg ethanol, neither the changes in Tc [F(25, 340) = 1.33, P 0.14], nor the changes in Tta [F(25,340) = 1.19, P
0.24] were statistically significant across strains. Genotype accounted for 9% and 8% of the total variance for these two measures.
Because of low heritability, QTLs located for changes in the range of Tc at 1.5 g/kg, and the two measures of the constant temperature experiments would be more likely to reflect type I errors. Therefore, QTLs for changes in the range at 1.5 g/kg and changes in Tta are not reported. Because of relatively strong correlations among the strain means of the decreases in Tc in the alternating temperature experiments and the constant temperature experiments (see below), QTLs located for decreases in Tc at a constant Ta were included as an alternate means of validating the QTLs involving thermal variables in this and other studies.
Live video observations of the mice during experiments and later reviews of the video recordings gave a good indication of the animals responses to the apparatus. There was invariably an initial brief struggle, usually followed by acquiescence. The intensity and duration of the initial struggle was relatively similar across BXD lines. If an animal struggled continuously or violently, then the experiment was terminated.
Correlations among RI strain means.
The data collected in this study made it possible to estimate genetic correlations by correlating RI strain means among measures. These correlations were performed for the alternating temperature experiments and are displayed in Table 2. Correlations with P 0.15 only occurred between closely related measures. Strain means for change in Tc were significantly correlated for both pairs of adjacent doses. Changes in Tc after 1.5 and 3.5 g/kg ethanol were moderately correlated. A similar pattern of correlations pertained between strain means for changes in the range of Tc. Finally, the decreases in Tc at a constant Ta (only 2.5 g/kg was used) were significantly correlated with the decreases in Tc with the changing Ta for all doses given.
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Correlations between RI strain means and other factors.
All correlations between strain means for weight and thermal responses to ethanol were low and ranged from -0.29 (P 0.15) to +0.17 (P
0.42). Correlations between strain means for ethanol elimination rates and thermal responses were also low, ranging from -0.38 (P
0.06) to 0.16 (P
0.45). Thus, of the 24 correlations (the 8 measures of this study and body weight or ethanol elimination at 2.0 and 3.0 g/kg), none was statistically significant.
QTL analysis for BXD RI strains.
Table 1 lists correlations indicating suggestive and provisional QTLs for the various measures of the study. In each case, only the genetic marker in each region showing the highest correlation with each trait is shown. In the alternating temperature experiments, for change in Tc, there were 14 suggestive and provisional QTLs: 6 at 1.5 g/kg, 5 at 2.5 g/kg, and 3 at 3.5 g/kg ethanol. For the range of Tc, there were 7 such QTLs: 3 at 2.5 g/kg and 4 at 3.5 g/kg ethanol. For the experiments run at a constant Ta, there were 6 such QTLs for change in Tc. Eight QTLs achieved suggestive levels of linkage, and these are identified by an asterisk in Table 1. Figure 4 illustrates locations on schematic mouse chromosomes for all suggestive and provisionally mapped QTLs and also includes provisional QTLs from other studies investigating the hypothermic effect of ethanol.
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DISCUSSION |
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The phenotype of regulated temperature is represented by the mean change in Tc across several cycles of the Ta. The mean Ta over a full cycle is very close to the thermoneutral Ta for an awake, alert mouse and without appropriate activation of thermoregulatory effectors, little change in Tc is expected. However, with coordinated activation of heat loss mechanisms, the thermoregulatory system can cause a rapid decrease in Tc.
The phenotype of thermoregulatory disruption is represented by the extent to which Tc is increased and decreased during the warming and cooling portions of the Ta cycle. Greater disruption of the thermoregulatory system causes Tc to increase more rapidly when Ta is above thermoneutrality and to decrease more rapidly when Ta is below thermoneutrality. The experiments at a constant Ta were designed to measure the effects of ethanol on the phenotype represented by a prominent thermoregulatory effector system, i.e., the alteration of thermal conductivity by vasomotor changes.
The phenotypes described above are all complex and could well be confounded with other variables. Ethanol metabolism, body weight, energy reserves, arousal state, stress, motor activity, and postural adjustments all influence Tc. Although none of these influences can be discounted with certainty, available evidence indicates that, with the exception of energy reserves, such interactions were minimal.
In a study on ethanol pharmacokinetic differences among RI strains, mice were given intraperitoneal ethanol injections of 2.0 or 3.0 g/kg ethanol and had blood levels of ethanol monitored periodically over the next several hours. From the rates of metabolism in each strain, we estimated the pseudo-zero-order elimination rates. We then subjected the elimination constant, as well as the blood level at 60 min after injection, for each dose to a QTL analysis following the methods described in this paper. In this analysis, two significant and several suggestive QTLs were found. However, when the locations of the metabolism-related QTLs were compared with the locations of the four QTLs with strongest associations in the current study, there was no overlap. As an additional test, the strain mean values for ethanol elimination rates were correlated with the values obtained in this study for the BXD RI strains. The range of correlations between elimination rates after 2 or 3 g/kg ethanol and the seven temperature regulation variables was from -0.38 to +0.16, and all correlations were nonsignificant. We conclude that ethanol metabolism did not play a role in the thermoregulatory responses of the QTLs we report.
Body weight of the RI lines showed very small correlations with any of the responses of this study. Thus it is unlikely that factors directly related to body weight affected the results of this study. However, selection experiments indicated that important energetic aspects can vary independently of body weight. Thus, although mice selected for high and low heat loss did not differ in body weight, the high heat loss line showed an increased expression of ribosomal protein L3 in both the hypothalamus and in the brown adipose tissue (2).
Somewhat more than a dozen QTLs have been identified relating to body fat content. These QTLs are described or mentioned in Refs 21, 25, and 30. Of these, three overlap with significant or provisional sites of the current study. These QTLs will be mentioned as the sites are discussed.
The remaining potential confounds were not quantified and could only be subjectively assessed by viewing the video tape recordings. Motor activity was minimal and similar in all lines, once the initial struggle was over. Arousal level was also similar in the various lines. The mice remained alert throughout the experiments except for the expected tranquilizing and anesthetizing effects of the ethanol. Likewise, posture and location in the apparatus was similar. Although the level of stress likely differed to some degree across the RI lines, there were no overt indications that stress was a major factor in the analysis.
For all responses, there was separation between the B6 and D2 progenitor strains within the BXD RI strain distribution. The position of these progenitor strains in the distributions varied in an interesting pattern. For decreases in Tc, the B6 mice always evidenced a greater decrease than the did the D2 mice, but the difference decreased at the higher doses. As illustrated in Fig. 2, the relationship between magnitude of response and strain order for the RI strains showed similarity across doses, although there was notable variation.
For the alternating temperature experiments, there was no overlap between the 14 associations for regulatory changes and 7 associations implicated in the disruption of regulation. These results indicate the genetic distinctiveness of these two effects. The associations also differed across dose. For decreases in the regulated Tc, twice as many associations were identified at the lowest dose compared with the highest dose of ethanol. For decreased thermoregulatory accuracy, there were four associations at the highest dose and three at the middle dose. These results are consistent with the concept that the genetic contribution to level of regulation is more affected by low doses of ethanol, whereas the disruption of regulation is more affected by higher doses.
Unlike locomotor activity, which is augmented by low doses of ethanol and decremented by high doses (15, 16), all responses monitored in this study depicted monotonic increases in magnitude as the dose of ethanol was increased. For both of the measures in the alternating temperature experiments, there were significant differences among the RI and progenitor strains which reflected an underlying genetic variation.
The elaborate genetic map that exists for the BXD RI battery of strains allowed us to detect a number of suggestive and provisional QTLs. An advantage of this approach is that these chromosome locations were identified without the necessity of prior hypotheses or specific genotyping. A further advantage of the current technique is that the results of this study are based on genetically stable strains and will be valid for comparison with past and future investigations. The ensuing discussion will focus on associations that attained the suggestive level as defined in the METHODS.
For decreases in Tc at a constant Ta of 26°C, we located six suggestive or provisional QTLs, of which two overlapped with such QTLs for decreases in the regulated Tc in the alternating temperature experiments. None of these six overlapped with the suggestive or provisional QTLs for decreased accuracy of thermoregulation. In the following discussion, unless otherwise mentioned, changes in Tc will refer to results from the alternating temperature experiments.
Of the genetic loci identified in this study, four sites appear particularly interesting. These sites are more likely to represent true QTL associations because, even with the limited number of genotypes tested (26 genotypes), these associations were well beyond our criterion for suggestive linkage. In our studies with other phenotypes, all regions originally identified in RI strains at this level of significance have subsequently been verified as true associations when other populations have been studied. Some of the four sites described above were also the locations of provisional QTLs for other thermoregulatory traits assessed in this study or from other thermoregulatory studies. Three of the sites were associated with a decrease in Tc in the alternating or constant temperature experiments, and these will be discussed first. Next, a site associated with disruption of thermoregulation will be addressed. Consideration of potentially relevant genes will be limited to genes mapping within 10 cM of the QTL under discussion.
A strong association was found on chromosome 2 at 69 cM, which involved a fall in Tc for all three doses of ethanol. In addition, markers in this region were also highly associated with a decrease in Tc at a constant Ta. This locus is also the site of a QTL influencing heat loss (25). Genes identified in this area code for interleukins-1 and -1ß,
2b-adrenergic receptors, and arginine vasopressin. These systems have all been implicated in different aspects of the control of body temperature. For example, the interleukin-1 system has hypnogenic properties and affects the regulated temperature, particularly during fever (28), the
-adrenergic system has been implicated in the maintenance of Tc in both thermoneutral and cool environments (17), and arginine vasopressin has been suggested as a possible mediator for the hypothermia that accompanies severe hypoxia (31).
A second highly significant association for decreased Tc was found in mid-chromosome 8 at 33 cM, for both the 1.5 and 2.5 g/kg doses. The 2.5 g/kg dose was found to have a provisional association at this locus. Potential candidate genes in this region include the neuropeptide Y receptor gene, Npy1r.
The strongest association in this study was found on chromosome 7 at 53 cM, for a decrease in Tc at a constant Ta. Provisional QTLs at this locus were also identified by Crabbe et al. (11) for hypothermia following doses of both 2 and 4 g/kg ethanol. This is also the locus of the tubby (tub) gene, which influences fatness in mice (see Ref. 21), as well as the locus of QTLs associated with heat loss (25) and the amount of body fat (30). Gene products coded for at this site include two subtypes of non-voltage-gated sodium channels.
The strongest associations between genetic markers and the disruption of thermoregulation by ethanol occurred on chromosome 11 at 59 cM. The association was found only for the lowest dose of ethanol (1.5 g/kg). This site is strongly associated with markers D11Mit14 and Tstap91a and is near genes coding for a voltage-gated sodium channel and a calcium channel.
Although no individual marker on chromosome 1 reached our suggestive criterion, the proximal portion had a series of strong provisional associations at 20 cM. Decreases in Tc for all three doses of ethanol as well as decreases in Tc in the constant temperature experiments were all highly linked with this area. In this same area, Crabbe et al. (11) identified a provisional QTL for ethanol-induced hypothermia after a dose of 4.0 g/kg ethanol. Genes coding for interleukin receptors 1 and 2 have been identified in this area. As mentioned earlier, the interleukin-1 system is involved with both sleep and fever (28).
The hypothermic response to ethanol has been examined in two other QTL studies. In these studies, both a decrease in the regulated body temperature and disruption of the thermoregulatory system presumably contributed to the degree of hypothermia observed. Crabbe et al. (11) employed female B6, D2, and BXD RI strains of mice and administered doses of 1, 2, 3, and 4 g/kg ethanol. Erwin et al. (15) utilized male LS, SS, and LSXSS RI strains after 4.2 g/kg ethanol. Both other studies used protocols that involved manually recording Tc before and after ethanol injection in mice maintained at a Ta of 2223°C. For mice, this is a condition of moderate cold stress.
We evaluated the commonality of the suggestive and provisional QTLs identified in these other studies by comparing them with those identified in this study. QTLs were considered common if they were derived from reasonably similar doses of ethanol and were within 10 cM, which is the approximate accuracy range of mapping with these RI strains. There was a correspondence on the order of 30% between the suggestive and provisional QTLs of the other studies and those of this study. This low level of correspondence appears reasonable, given the relative specificity of the effects of particular genes (see Ref. 1) and the fact that changes in Tc can be produced a number of ways, many of which are not directly involved in the thermoregulatory system (see Ref. 12). Such effects include alterations in arousal state, emotional responses, motor activity, and postural adjustments. These responses were probably elicited to different degrees by the different protocols and thus implicated different genes in the resultant alteration of Tc. In addition, the genetic makeup of the mice utilized by Erwin et al. (15) differed from that of the mice in this study. Although the LS and SS mice were created from a foundation stock that included DBA/2 and C57BL/6 inbred strains, the foundation stock also involved intercrosses of six other inbred mouse strains (24). Finally, sex differences may have played a role.
The provisional identification of QTLs in this study is only the initial step in localizing the set of genes that are involved in mediating the effects of ethanol upon thermoregulatory processes. One example of the steps that will produce a better resolution can be found in Buck et al. (8). Further confirmation or rejection of these QTLs could come from the characterization of F2 animals (the offspring of B6 and D2 intercrosses) or the study of phenotypically selected individuals from the F2. In these populations, phenotyping and the subsequent genotyping of individuals can provide increased evidence of association.
The confidence intervals surrounding these provisional QTLs are large, and each region contains hundreds of genes, any one (or group) of which could be responsible for the association. Therefore, discussions of potential candidate genes would be highly speculative, but as confidence intervals are reduced, many fewer candidate genes will remain.
Several steps would still be necessary to achieve the goal of cloning a gene responsible for a QTL. One method that is currently in progress involves creation of congenic mice, created from B6 and D2 genotypes. By backcrossing, mice are being created with a background genotype of 99% D2 or B6, with a small region of chromosome derived from the other progenitor strain containing the verified QTL. This region will then be made progressively smaller through backcrossing, genotyping, and selection of recombinant individuals, thus further delimiting the area containing the QTL (10).
In conclusion, we have utilized different response measures to locate potential genetic loci responsible for two separate effects of ethanol on the thermoregulatory system. Alterations of the regulated temperature and disruptive actions on physiological regulation are represented in different portions of the mouse genome. Further work is needed to clarify which of these potential QTLs are valid contributors to the effects of ethanol on this physiological system.
Perspectives
The QTL approach is one of many ways to further understanding of physiological function. This particular approach links the responses of a whole system with the genes that code for component parts exerting the greatest influence on measured variables. Because of the high degree of synteny between the mouse and the human genome, genes implicated in mice will often lead directly to corresponding genes in humans. Although the path from QTL to gene is not currently direct, data that produce QTL will remain available for a future time when more complete genetic maps will allow a more accurate QTL localization and the procedures for identifying genes from these discrete QTL are standardized.
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ACKNOWLEDGMENTS |
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This research was supported by National Institute of Alcohol Abuse and Alcoholism Grant AA-10760, by a grant from the Department of Veterans Affairs, and by support from Portland State University.
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FOOTNOTES |
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Address for reprint requests and other correspondence: L. I. Crawshaw, Dept. of Biology, Portland State Univ., PO Box 751, Portland, OR 97207 (E-mail: crawshl{at}pdx.edu).
10.1152/physiolgenomics.00041.2001.
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REFERENCES |
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