The results of this investigation, to our knowledge, represent the first identification of genomic locations associated with the regulation of voluntary wheel running activity in mice. In this study, we have also supported previous observations of the heritability of wheel running behavior and differential activity patterns between sexes and have noted a lack of differences between the F2
substrains suggesting that the genetic influences on physical activity were not transferred predominantly through either the maternal or paternal lines. Furthermore, in the F2
cohort, we have identified two significant and several suggestive experimentally derived QTL that are linked with one or more of our three indexes of activity. The significant QTL on chromosomes 9 and 13 were confirmed with a HAM analysis, which also indicated several sites in these regions for further candidate gene investigation. Given the conserved synteny between human and mouse genomes, these results provide a significant foundation for further research investigating the genetic regulation of voluntary daily activity in rodents and humans (2
It has only recently become accepted that voluntary daily activity has a significant heritable component (12
). In support of this contention, we found that the broad-sense heritability of wheel running behavior was substantial, ranging between 49% and 58% depending on the activity measurement considered, which is similar to previously reported values (16
). Not surprisingly, our broad-sense estimates of heritability are somewhat higher than previous non-adjusted narrow-sense heritability estimates for wheel running (0.12−0.24; Ref. 32
); however, the additive genetic component estimates in the present study and previous studies (adjusted realized heritability = 0.28; Ref. 32
) are similar.
Whereas the portion of the heritability/phenotypic variance that was accounted for by the QTL ranged from 11% to 34% depending on the activity index used, it is probable that there are other QTL or genetic factors that explain more of the variability that were not uncovered in our limited cohort of F2
animals. For example, Tsao et al. (34
) demonstrated that an overexpression of GLUT4 glucose transporters leads to a fourfold increase in daily activity in male mice. However, the GLUT4 gene is located on chromosome 11 (40 cM), an area in which none of the QTL we identified in the present study was found. Our haplotype mapping results certainly indicated other sites on chromosomes 9 and 13 that may contain QTL that influence activity. Additionally, while the near absence of significant epistasis among the identified QTL was somewhat surprising (37
), this does not rule out the possibility of epistasis among loci that were not detected as main-effect QTL. While these possibilities will require further investigation to identify all of the chromosomal locations that are linked to the regulation of physical activity, the present study has identified two major and several other suggestive loci that control voluntary daily activity in mice.
As additional QTL for measures of voluntary daily activity are eventually discovered in other mouse models, it will be interesting to see whether their mode of action is comparable to that seen for the QTL we have located. For example, it is unclear whether the lack of sex-specific QTL for the activity traits measured here indicates that the sex-mediated regulation of activity is a result of other biological factors not related to genetic regulation (i.e., “downstream” of genetic regulation) or whether we simply did not have sufficient power to detect them in our mouse population (see below). Certainly QTL that act differentially in the sexes have been detected for other traits in mice (14
). The mean levels of the standardized additive/dominance genotypic values and percentage contributions for our QTL, however, are generally quite comparable to those reported by Kenney-Hunt et al. (11
) for a large number of QTL influencing a battery of body size components in a LG/J × SM/J intercross population of mice.
While no other study has identified QTL directly linked to the activity traits we used (i.e., wheel running activity), other studies have identified QTL linked to other locomotion-related behaviors. In 25 recombinant inbred (RI) mouse strains developed from C57BL/6J and DBA/2J inbred strains, Phillips et al. (25
) identified five QTL in 87-day-old female mice associated with the magnitude of horizontal movement in an activity monitoring chamber. Of these five QTL, three (chromosome 9, 26−36 cM; chromosome 13, 9−10 cM; chromosome 5, 20−30 cM) colocalize with QTL identified in the present study—the significant QTL we identified on chromosomes 9 (DIST9.1
) and 13 (DUR13.1, DIST13.1
, and SPD13.1
) as well as the suggestive QTL SPD5.1
. Unfortunately, Phillips and colleagues only reported measures of correlation and did not report any measure of QTL strength; thus it is unknown whether these QTL reached either an experimentwise or a chromosomewise level of significance (25
Using 22 recombinant inbred rat strains—the HXB/BXH RI strains derived from SHR/O1a and the inbred congenic BN.Lx
/Cub strain—that were 11−13 wk old, Conti et al. (5
) identified two significant QTL on chromosomes 3 (47 cM; D3Rat180 proximal marker) and 18 (40 cM; D18Rat55 proximal marker) related to open-maze locomotion behavior. Additionally, Gershenfeld and colleagues (8
) investigated the genetic regulation of open-field behavior (e.g., vertical rearing and response to novelty) and identified several significant QTL on chromosomes 1, 3, 10, and 19 and five additional suggestive QTL in 10- to 11-wk-old F2
mice derived from A/J and C57Bl/6J progenitor strains. Comparisons of the results from Conti et al. (5
) and Gershenfeld et al. (8
) to those in the present study are difficult because of the shorter time interval of the locomotor phenotyping used by Conti et al. (5-min observation) and Gershenfeld et al. (15-min observation) compared with our longer-term measurements (21 days). Additionally, Mill et al. (23
) observed that home cage activity in mice, similar to our measures of activity, was not correlated with open-field locomotor testing measures similar to those employed by Gershenfeld et al. (8
). Furthermore, open-field testing and maze testing similar to those used by Conti et al. (5
) are now widely considered a measurement of fear and anxiety rather than voluntary locomotion in rodents (24
). Thus it is not surprising that none of the QTL (or QTL homologs) identified by either Conti and colleagues (5
) or Gershenfeld et al. (8
) is similar to the QTL associated with the longer-term indexes of activity that we used in this study.
Additionally, other locomotor-associated behaviors have been examined genetically, such as the efforts made to determine QTL associated with the amplitude of the daily oscillation in locomotion between day and night (33
). This effort monitored activity with a tethered-EMG implant system in C57BL/6, Balb/cBy, and 13 RI strains. Unfortunately, only male mice were monitored for a 48-h period and no significant QTL were discovered associated with the variation in activity (total 24-h activity among all of the strains was not different). However, several suggestive QTL were identified by these authors, one being located on chromosome 12 (23 cM), in a location similar to our SPD12.1
It is tempting to hypothesize that QTL for physiological traits associated with high exercise endurance (e.g., mitochondrial density, cardiac output) are associated with the functional ability to be active for long periods of time. However, these hypotheses are not justified at this time because of two issues. First, several studies, including work from our lab, have shown that physical activity and exercise endurance in mice are not correlated and are therefore probably distinct phenotypes (e.g., Refs. 16
). Further strengthening the contention that maximal exercise endurance and high/low physical activity are distinct phenotypes is the fact that the activity QTL noted in the present study do not colocalize with any of the mouse QTL recently published for exercise endurance (21
). Second, given our inability to determine the length and intensity of the individual exercise bouts that the mice were performing, it is difficult to determine what type of physiological trait might have functionally allowed the increased activity in our F2
cohort. If the mice were performing multiple short, intense bouts of exercise, we would naturally want to investigate colocalization of QTL of physiological traits favoring intense exercise bouts (e.g., % of type II fiber composition, increased lactate dehydrogenase). Conversely, if the mice were completing exercise in longer, less intensive bouts, then we would be interested in QTL for traits leading to longer duration exercise (e.g., type I fiber composition, increased mitochondrial biogenesis). These types of QTL comparisons are logical for future studies when the types of activity bouts can be monitored.
Our general finding of higher activity levels in female mice supports results from multiple rodent studies that have found similar results (e.g., Refs. 12
). However, as noted above, the lack of sex-related QTL could indicate that the differential regulation of activity due to sex is downstream of any genetic regulation. In fact, studies have clearly established that estrogen mediates physical activity through the estrogen receptor-α pathway (24
). While the subsequent downstream pathways activated by the estrogen receptor-α pathway are still somewhat unclear, it has been postulated that estrogen receptor-α modulates several neurotransmitters, including dopamine in the female, which may lead to increased physical activity (24
). Supporting a possible dopamine linkage are two studies (26
) that have suggested a role for various dopamine mechanisms in influencing activity. Interestingly, while no genes with known control of any sex hormones are located in the QTL regions identified in the present study, identified QTL that affect the physiological behavior of dopamine colocalize within some of the suggestive QTL sites we identified. Dbh
(chromosome 2, 15.5 cM), a gene that produces dopamine β-hydroxylase, an enzyme that catalyzes the dopamine-to-norepinephrine pathway, is located within our SPD2.1
Additionally, while no dopamine receptor genes are located within any of our identified significant QTL, there are two QTL, Drb2 (chromosome 5, 54.0 cM) and Drb5 (chromosome 12, 25.0 cM), both of which are associated with dopamine receptor binding, that colocalize within our identified SPD5.1 and SPD12.1 sites. Therefore, given the location of these dopamine-associated regions within three of our suggestive QTL sites and the apparent lack of estrogen-controlling genes in any of the identified QTL sites, we hypothesize that while the genetic regulation of activity may involve dopamine (i.e., through dopamine receptor and/or dopamine metabolism) the sex-related estrogenic effects on activity appear to be nongenetic in nature and potentially occur downstream of other genetic regulatory mechanisms.
In summary, this study has experimentally identified 4 significant and at least 14 suggestive QTL associated with spontaneous activity in mice. The significant QTL on chromosomes 9 and 13 were validated with a HAM approach, which also identified several other genomic loci where potential QTL may exist. This study also noted a clear sex difference in activity patterns, but we hypothesize that this sex difference results from a nongenetic mechanism functioning downstream of genetic regulation. Future research will focus on reducing the intervals where these identified QTL exist to ultimately identify genes that regulate physical activity.