Identification and time dependence of quantitative trait loci for basal locomotor activity in the BXD recombinant inbred series and a B6D2 F2 intercross

The impact of a high-fat diet on physical activity and dopamine neurochemistry in the striatum is sex and strain dependent in C57BL/6J and DBA/2J mice

BACKGROUND

Obesity has been linked to behavioral and biochemical changes, such as reduced physical activity, dysregulated dopamine metabolism, and gene expression alterations in the brain. The impact of a continuous high-fat diet and resulting state of obesity may vary depending on sex and genetics.

OBJECTIVE

The aim of this study was to investigate the impact of a high-fat diet on physical activity, gene expression in the striatum, and dopamine neurochemistry using male and female mice from different strains as a model to examine sex and strain influences on dopamine-mediated behavior and neurobiology.

METHODS

Male and female mice from the C57BL/6J (B6J) and DBA/2J (D2J) strains were randomly assigned a control low-fat diet with 10% kcal fat or a high-fat diet with 60% kcal fat for 16 weeks. We assessed ambulation and habituation using the open field test; dopamine release and reuptake using ex-vivo fast scan cyclic voltammetry; and striatal mRNA expression of dopamine receptor D2, alpha synuclein, and tyrosine hydroxylase.

RESULTS

Mice fed a high-fat diet exhibited reduced motor activity, but only obese B6J male mice displayed reduced habituation. Dopamine clearance in the dorsal striatum was reduced only in obese D2J mice, while dopamine clearance in the nucleus accumbens core was reduced only in male obese D2J mice. Striatal dopamine receptor D2 gene expression was upregulated exclusively in obese male B6J mice.

CONCLUSION

Our study provides evidence for important sex and strain influences on the impact of a high-fat diet and obesity-induced behavior alterations and neurobiology dysregulation in the striatum.

On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption

We and many others have noted the advantages of using heterogeneous (HS) animals to map genes and gene networks associated with both behavioral and non-behavioral phenotypes. Importantly, genetically complex Mus musculus crosses provide substantially increased resolution to examine old and new relationships between gene expression and behavior. Here we report on data obtained from two HS populations: the HS/NPT derived from eight inbred laboratory mouse strains and the HS-CC derived from the eight collaborative cross inbred mouse strains that includes three wild-derived strains. Our work has focused on the genes and gene networks associated with risk for excessive ethanol consumption, individual variation in ethanol consumption and the consequences, including escalation, of long-term ethanol consumption. Background data on the development of HS mice is provided, including advantages for the detection of expression quantitative trait loci. Examples are also provided of using HS animals to probe the genes associated with ethanol preference and binge ethanol consumption.

Use of the expanded panel of BXD mice narrow QTL regions in ethanol-induced locomotor activation and motor incoordination

BACKGROUND

Alcohol-related responses are under strong genetic regulation. A wealth of alcohol-related data from recombinant inbred (RI) mouse strains enables genetic correlation and mapping of these traits. Previous studies using RI strains have identified numerous chromosomal locations that underlie differential alcohol sensitivity, although the regions identified are typically large. One means to improve power and precision for genetic analysis is to use a larger genetic reference population. The expanded panel of BXD RI mice was used to identify quantitative trait loci (QTLs) associated with sensitivity to locomotor stimulatory and motor incoordinating effects of alcohol. The goals of this study were to determine whether previously reported QTLs were replicated and refined and to determine whether novel QTLs would be identified.

METHODS

Following an i.p. dose of 2.25 g/kg of ethanol (EtOH) or saline control, locomotor activation was assessed using an activity chamber and motor incoordination was assessed using the accelerating rotarod. Male and female BXD mice from over 55 strains were tested. Two treatment paradigms were utilized to evaluate the effects of EtOH versus saline treatment-order.

RESULTS

Activity chamber measures showed significant differences in strain, sex, and treatment-order whereas rotarod measures showed significant differences in strain and treatment-order. Significant QTLs for various measures of EtOH-induced locomotor activation were identified on chromosomes 2 and 5 that narrowed QTL regions previously identified from 19 to < 2 Mb. Further, a novel significant QTL for EtOH-induced motor incoordination on chromosome 7 was identified.

CONCLUSIONS

Using the expanded RI BXD panel, along with a high precision marker map, several novel QTLs were found and several previously identified QTL regions were confirmed and narrowed. The isogenic nature of the population facilitated detection of treatment-order and sex-specific differences. Smaller QTL regions reduced the number of positional candidates thereby increasing the efficiency with which polymorphisms underlying the QTL will be identified.

Forward genetic approaches to understanding complex behaviors

Assigning function to genes has long been a focus of biomedical research.Even with complete knowledge of the genomic sequences of humans, mice and other experimental organisms, there is still much to be learned about gene function and control. Ablation or overexpression of single genes using knockout or transgenic technologies has provided functional annotation for many genes, but these technologies do not capture the extensive genetic variation present in existing experimental mouse populations. Researchers have only recently begun to truly appreciate naturally occurring genetic variation resulting from single nucleotide substitutions,insertions, deletions, copy number variation, epigenetic changes (DNA methylation,histone modifications, etc.) and gene expression differences and how this variation contributes to complex phenotypes. In this chapter, we will discuss the benefits and limitations of different forward genetic approaches that capture the genetic variation present in inbred mouse strains and present the utility of these approaches for mapping QTL that influence complex behavioral phenotypes.

Fine mapping quantitative trait loci that influence alcohol preference behavior in the High and Low Alcohol Preferring (HAP and LAP) mice

The High Alcohol Preferring (HAP1) and Low Alcohol Preferring (LAP1) mouse lines were selectively bred for differences in alcohol intake. The HAP1 and LAP1 mice are essentially non-inbred lines that originated from an outbred colony of HS/Ibg mice, a heterogeneous stock developed from intercrossing 8 inbred strains of mice. In a former genomewide SNP association study, we identified quantitative trait loci (QTL) on chromosomes 1, 3, 5, and 9 (Bice et al. 2009). Provisional QTL were also identified on chromosomes 8 and X. In the present study, using the same F2 DNA samples, we placed a much denser set of SNPs within each of those QTL regions. Using the same analytical approach employed previously, which utilizes ancestral recombination to fine map the QLT interval, we obtained significant LOD scores on chromosomes 1, 3, and 9, only. Our results using a dense set of SNP markers suggest that there are multiple loci contributing to alcohol preference on those three chromosomes.

QTL analysis of measures of mouse home-cage activity using B6/MSM consomic strains

The activity of mice in their home cage is influenced greatly by the cycle of light and dark. In addition, home-cage activity shows remarkable time-dependent changes that result in a prominent temporal pattern. The wild-derived mouse strain MSM/Ms (MSM) exhibits higher total activity in the home cage than does C57BL/6 (B6), a commonly used laboratory strain. In addition, there is a clear strain difference in the temporal pattern of home-cage activity. This study aimed to clarify the genetic basis of strain differences in the temporal pattern of home-cage activity between MSM and B6. Through the comparison of temporal patterns of home-cage activity between B6 and MSM, the pattern can be classified into five temporal components: (1) resting phase, (2) anticipation phase, (3) 1st phase, (4) 2nd phase, and (5) 3rd phase. To identify quantitative trait loci (QTLs) involved in these temporal components, we used consomic strains established from crosses between B6 and MSM. Five consomic strains, for Chrs 2T (telomere), 3, 4, 13, and 14, showed significantly higher total activity than B6. In contrast, the consomic strains of Chrs 6C (centromere), 7T, 9, 11, and 15 were less active than B6. This indicates that multigenic factors regulate the total activity. Further analysis showed an impact of QTLs on the temporal components of home-cage activity. The present data showed that each temporal component was regulated by different combinations of multigenic factors, with some overlap. These temporal component-related QTLs are important to understand fully the genetic mechanisms that underlie home-cage activity.

Quantitative trait loci contributing to physiological and behavioural ethanol responses after acute and chronic treatment

The aim of the present study was the identification of gene loci that contribute to the development and manifestation of behaviours related to acute and chronic alcohol exposure, as well as to alcohol withdrawal. For this purpose, we performed a serial behavioural phenotyping of 534 animals from the second filial (F2) generation of a C57BL/6J and C3H/HeJ mice intercross in paradigms with relevance to alcohol dependence. First, ethanol-induced hypothermia was determined in ethanol-naive animals. The mice then received an ethanol solution for several weeks as their only fluid source. Ethanol tolerance, locomotor activity and anxiety-related behaviours were evaluated. The ethanol was next withdrawn and the withdrawal severity was assessed. The ethanol-experienced animals were finally analysed in a two-bottle choice paradigm to determine ethanol preference and stress-induced changes in ethanol preference. The genotypes of these mice were subsequently assessed by microsatellite marker mapping. We genotyped 264 markers with an average marker distance of 5.56 cM, which represents a high-density whole genome coverage. Quantitative trait loci (QTL) were subsequently identified using univariate analysis performed with the R/qtl tool, which is an extensible, interactive environment for mapping QTL in experimental crosses. We found QTL that have already been published, thus validating the serial phenotyping protocol, and identified several novel loci. Our analysis demonstrates that the various responses to ethanol are regulated by independent groups of genes.

Bone, muscle, and physical activity: structural equation modeling of relationships and genetic influence with age

Correlations among bone strength, muscle mass, and physical activity suggest that these traits may be modulated by each other and/or by common genetic and/or environmental mechanisms. This study used structural equation modeling (SEM) to explore the extent to which select genetic loci manifest their pleiotropic effects through functional adaptations commonly referred to as Wolff's law. Quantitative trait locus (QTL) analysis was used to identify regions of chromosomes that simultaneously influenced skeletal mechanics, muscle mass, and/or activity-related behaviors in young and aged B6xD2 second-generation (F(2)) mice of both sexes. SEM was used to further study relationships among select QTLs, bone mechanics, muscle mass, and measures of activity. The SEM approach provided the means to numerically decouple the musculoskeletal effects of mechanical loading from the effects of other physiological processes involved in locomotion and physical activity. It was found that muscle mass was a better predictor of bone mechanics in young females, whereas mechanical loading was a better predictor of bone mechanics in older females. An activity-induced loading factor positively predicted the mechanical behavior of hindlimb bones in older males; contrarily, load-free locomotion (i.e., the remaining effects after removing the effects of loading) negatively predicted bone performance. QTLs on chromosomes 4, 7, and 9 seem to exert some of their influence on bone through actions consistent with Wolff's Law. Further exploration of these and other mechanisms through which genes function will aid in development of individualized interventions able to exploit the numerous complex pathways contributing to skeletal health.

Intrasession and intersession habituation in mice: from inbred strain variability to linkage analysis

When placed in a novel environment, mice tend to explore for a period of time, and then reduce the level of exploration. This reduction in locomotor or exploratory behavior is known as habituation and can occur within a single session or across sessions, respectively, termed intrasession and intersession habituation. Recent research indicates that there is a genetic component to habituation behavior and that some of the genes involved differ between the two types of habituation. The genetic evidence also suggests that intrasession habituation and intersession habituation are measuring somewhat different conceptual entities and with more such evidence may eventually help us understand the different pathways involved. Some of the genetic methods and tools used to unravel the roles of specific genes in both types of habituation are outlined here, with examples from the literature, as well as new data, to illustrate that this seemingly simple behavior is actually very complicated in terms of genetics. Evidence to date suggests that a number of genetic regions play roles in one or both types of habituation, and further research will be necessary to determine the specific genes involved.

QTL analyses of temporal and intensity components of home-cage activity in KJR and C57BL/6J strains

BACKGROUND

A variety of mouse strains exhibit diversity in spontaneous activity consistent with an important genetic contribution. To date, many studies have defined spontaneous home-cage activity as total distance or total counts of activity within a test period. However, spontaneous activity is, in fact, a composite of elements of 'temporal' and 'intensity' that is similar to 'velocity'. Here, we report on quantitative trait loci for different components of spontaneous activity, an important step towards dissection of the underlying genetic mechanisms.

RESULTS

In the analysis of total home-cage activity (THA) after habituation in female mice, KJR strain exhibit higher activity than C57BL/6J (B6). In this study, THA was partitioned into two components: active time (AT) was an index of the 'temporal element' of THA, average activity during active time (AA) was an index of 'intensity'. Correlation analysis using B6xKJR F2 female mice indicated that AA is a major component of THA, whereas AA and AT were associated to a lesser degree. To explore the genetic basis of the activity differences, we conducted quantitative trait loci (QTL) analysis on data of THA and its components, AT and AA. Three significant QTL affecting variation of different components of home cage activity were identified, two linked QTL Hylaq1 and Hylaq2 on Chr 2, and Hylaq3 on Chr 10. Chromosomal positions of these QTL were previously implicated in locomotor activity (Chr 2) or open-field ambulation (Chr 10). The results indicated that Hylaq1 influences AT, Hylaq2, AA, while Hylaq3 is associated with both AA and AT.

CONCLUSION

Through this study, we found that variation in total home cage activity over a 3 day period is affected by variation in active time and intensity of activity. The latter two variables are distinct components of home cage activity with only partially overlapping genetic architecture.

Genetic architecture for hole-board behaviors across substantial time intervals in young, middle-aged and old mice

A quantitative trait locus (QTL) analysis of behaviors across the life span was conducted in F(2) mice from a C57BL/6J x DBA/2J cross and 22 BXD recombinant inbred (RI) strains. Mice of three age groups were tested in a hole-board apparatus for 3 min on three occasions approximately 1 month apart (average age at test 150, 450 and 750 days, approximately 400 mice per group, divided equally by sex). Quantitative trait loci with small effect size were found on 11 chromosomes for hole-board activity (Hbact) and hole-board rearing (Hbrear). Analysis of 22 RI strains tested at 150 and 450 days of age found only suggestive linkage, with four QTL for Hbact overlapping with those from the F(2) analysis. There was a significant phenotypic correlation between Hbact and Hbrear (approximately 0.55-0.69) and substantial commonality among QTL for the two behaviors. QTL analyses of head-pokes (HP) and fecal boli (FB) only identified QTL at the suggestive level of significance. Age accounted for approximately 15% of the phenotypic variance (sex approximately 3%), and there were genotype by age interactions at approximately 25% of the Hbact and Hbrear QTL. Quantitative trait loci for Hbrear were relatively stable across the three measurement occasions (those for Hbact somewhat less so), although mean levels of each index declined markedly comparing the first to subsequent trials. Considered as a whole, the polygenic system influencing exploratory behaviors accounts for approximately the same amount of phenotypic variance as age (within the range studied), is stable across substantial periods of time, and acts, for the most part, independently of age and sex.

Both cell-autonomous and cell non-autonomous functions of GAP-43 are required for normal patterning of the cerebellum in vivo

Growth-associated protein 43 (GAP-43) is required for development of a functional cerebral cortex in vertebrates; however, its role in cerebellar development is not well understood. Recently, we showed that absence of GAP-43 caused defects in proliferation, differentiation, and polarization of cerebellar granule cells. In this paper, we show that absence of GAP-43 causes defects in cerebellar patterning that reflect both cell-autonomous and non-autonomous functions. Cell-autonomous effects of GAP-43 impact precursor proliferation and axon targeting: In its absence, (1) proliferation of granule cell precursors in response to sonic hedgehog and fibroblast growth factor is inhibited, (2) proliferation of neuroepithelial precursors is inhibited, and (3) targeting of climbing fibers to the central lobe is disrupted. Cell non-autonomous effects of GAP-43 impact differentiated Purkinje cells in which GAP-43 has been downregulated: In its absence, both maturation and mediolateral patterning of Purkinje cells are inhibited. Both cell-autonomous and non-autonomous functions of GAP-43 involve its phosphorylation by protein kinase C. GAP-43 is phosphorylated in granule cell precursors in response to sonic hedgehog in vitro, and phosphorylated GAP-43 is also found in proliferating neuroepithelium and climbing fibers. Phosphorylated GAP-43 is specifically enriched in the presynaptic terminals of parallel and climbing fibers that innervate Purkinje cell bodies and dendrites. The cell-autonomous and non-autonomous effects of GAP-43 converge on the central lobe. The multiple effects of GAP-43 on cerebellar development suggest that it is a critical downstream transducer of signaling mechanisms that integrate generation of cerebellar structure with functional parcellation at the central lobe.

High-resolution genetic mapping of mammalian motor activity levels in mice

The generation of motor activity levels is under tight neural control to execute essential behaviors, such as movement toward food or for social interaction. To identify novel neurobiological mechanisms underlying motor activity levels, we studied a panel of chromosome substitution (CS) strains derived from mice with high (C57BL/6J strain) or low motor activity levels (A/J strain) using automated home cage behavioral registration. In this study, we genetically mapped the expression of baseline motor activity levels (horizontal distance moved) to mouse chromosome 1. Further genetic mapping of this trait revealed an 8.3-Mb quantitative trait locus (QTL) interval. This locus is distinct from the QTL interval for open-field anxiety-related motor behavior on this chromosome. By data mining, an existing phenotypic and genotypic data set of 2445 genetically heterogeneous mice (http://gscan.well.ox.ac.uk/), we confirmed linkage to the peak marker at 79 970 253 bp and refined the QTL to a 312-kb interval containing a single gene (A830043J08Rik). Sequence analysis showed a nucleotide deletion in the 3' untranslated region of the Riken gene. Genome-wide microarray gene expression profiling in brains of discordant F(2) individuals from CS strain 1 showed a significant upregulation of Epha4 in low-active F(2) individuals. Inclusion of a genetic marker for Epha4 confirmed that this gene is located outside of the QTL interval. Both Epha4 and A830043J08Rik are expressed in brain motor circuits, and similar to Epha4 mutants, we found linkage between reduced motor neurons number and A/J chromosome 1. Our findings provide a novel QTL and a potential downstream target underlying motor circuitry development and the expression of physical activity levels.

Behavioural analysis of congenic mouse strains confirms stress-responsive Loci on chromosomes 1 and 12

The way in which animals respond to stressful environments correlates with anxiety-related behaviour. To begin identifying the genetic factors that influence anxiety, we have studied the stress-responsiveness of inbred mouse strains using a modified form of the open field activity test (OFA), termed the elevated (e) OFA. In particular, two strains show high (DBA/2J) or low (C57BL/6J) stress-responsiveness in the eOFA. Genetic studies of an F(2) intercross between these two strains previously identified two regions, on chromosomes (Chr) 1 and 12, linked to anxiety-related behaviour. To confirm that these regions contain loci for stress-responsiveness, we established separate congenic mouse strains for the linked Chr1 and Chr12 regions. Each congenic strain harbours a DBA/2J-derived interval encompassing the linked region on the C57BL/6J genetic background: the congenic intervals are between, but not including approximately 48.6 Mb and approximately 194.8 Mb on Chr1, and approximately 36.2 Mb and the distal end of Chr12. Cohorts of DBA/2J, C57BL/6J and congenic mice were analysed for a series of stress-responsive phenotypes using the eOFA test. Both congenic strains had significantly different stress-responsive phenotypes compared to the low-stress C57BL/6J parental strain, but the DBA/2J-derived Chr12 interval had a greater genetic effect than the DBA/2J-derived Chr1 interval for changing the behavioral phenotype of the parental C57BL/6J mouse strain. These results confirmed the presence of stress-responsive loci on Chr1 and Chr12. New stress-related phenotypes were also identified, which aided in comparing and differentiating DBA/2J, C57BL/6J and congenic mice.

Further studies on using multiple-cross mapping (MCM) to map quantitative trait loci

We have completed whole-genome scans for quantitative trait loci (QTLs) associated with acute ethanol-induced activation in the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2) , BALB/cJ (C), and LP/J (LP) inbred strains. The goal was to test the hypothesis that given the relatively simple structure of the laboratory mouse genome, the same QTLs will be detected in multiple crosses which in turn will provide support for the strategy of multiple-cross mapping (MCM). QTLs with LOD scores greater than 4 were detected on Chrs 1, 2, 3, 8, 9, 13, 14, and 16. Only for the QTL on distal Chr 1 was there convincing evidence that the same or at least a very similar QTL was detected in multiple crosses. We also mapped the Chr 2 QTL directly in heterogeneous stock (HS) animals derived from the four inbred strains. At G(19) the QTL was mapped to an approximately 3-Mbp interval and this interval was associated with a haplotype block with a largely biallelic structure: B6-L:C-D2. We conclude that mapping in HS animals not only provides significantly greater QTL resolution, at least in some cases it provides significantly more information about the QTL haplotype structure.

A genetic screen for behavioral mutations that perturb dopaminergic homeostasis in mice

Disruption of dopaminergic (DA) systems is thought to play a central role in the addictive process and in the pathophysiology of schizophrenia. Although inheritance plays an important role in the predisposition to these disorders, the genetic basis of this is not well understood. To provide additional insight, we have performed a modifier screen in mice designed to identify mutations that perturb DA homeostasis. With a genetic background sensitized by a mutation in the dopamine transporter (DAT), we used random chemical mutagenesis and screened for mutant mice with locomotor abnormalities. Four mutant lines were identified with quantitatively elevated levels of locomotor activity. Mapping of mutations in these lines identified two loci that alter activity only when dopamine levels are elevated by a DAT mutation and thus would only have been uncovered by this type of approach. One of these quantitative trait loci behaves as an enhancer of DA neurotransmission, whereas the other may act as a suppressor. In addition, we also identified three loci which are not dependent on the sensitized background but which also contribute to the overall locomotor phenotype.

Quantitative trait loci for novelty/stress-induced locomotor activation in recombinant inbred (RI) and recombinant congenic (RC) strains of mice

The objective of the present study was to map and compare quantitative trait loci (QTLs) for an anxiety-related trait (novelty/stress-induced activation) in the AXB/BXA recombinant inbred (RI) and AcB/BcA recombinant congenic (RC) strains of mice derived from the A/J and C57BL/6J inbred progenitor strains. Activational responses to a novel open field (OF) were measured under identical stressful conditions (no prior handling or exposure to testing procedures) in both the RI and RC strains. Naive male and female mice were weighed, injected with IP saline and locomotor activity was monitored in a computerized OF apparatus for 15 min. Measures obtained from this experimental design included: (1) total activity scores, (2) time course of response (5 min time blocks over the 15 min session). Data for the RI strains were subjected to a QTL analysis using composite interval mapping. Significant loci were identified on chr 5 (D5Mit356, 41 cM), chr 8 (D8Mit305, 37 cM) and chr 14 (D14Mit36, 6 3cM). Single locus association analysis of the AcB/BcA RC strains identified 15 putative regions, 7 of which overlapped regions independently mapped in the RI strains on chr 1 (58.5-63.1cM), chr 4 (21.9-28.6 cM), chr 5 (19-45 & 74-86 cM), chr 6 (0.5-20.4cM), chr 9 (15-38 cM), chr 13 (47cM) and chr 19 (47cM). The loci identified on chr 5 near D5Mit356 (41cM) in both the AXB/BXA RIS and AcB/BcA RCS maps to a region containing the genes for several GABA(A) receptor subunits. Additionally, the present study provides further confirmation of a frequently identified QTL on chromosome 1. The results are discussed in the context of previous QTL studies of anxiety-related traits that have used genetic crosses that include the A or B6 progenitors.

A strategy for the integration of QTL, gene expression, and sequence analyses

Although hundreds if not thousands of quantitative trait loci (QTL) have been described for a wide variety of complex traits, only a very small number of these QTLs have been reduced to quantitative trait genes (QTGs) and quantitative trait nucleotides (QTNs). A strategy, Multiple Cross Mapping (MCM), is described for detecting QTGs and QTNs that is based on leveraging the information contained within the haplotype structure of the mouse genome. As described in the current report, the strategy utilizes the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2), BALB/cJ (C), and LP/J (LP) inbred mouse strains. Focusing on the phenotype of basal locomotor activity, it was found that in all three B6 intercrosses, a QTL was detected on distal Chromosome (Chr) 1; no QTL was detected in the other three intercrosses, and thus, it was assumed that at the QTL, the C, D2, and LP strains had functionally identical alleles. These intercross data were used to form a simple algorithm for interrogating microsatellite, single nucleotide polymorphism (SNP), brain gene expression, and sequence databases. The results obtained point to Kcnj9 (which has a markedly lower expression in the B6 strain) as being the likely QTG. Further, it is suggested that the lower expression in the B6 strain results from a polymorphism in the 5'-UTR that disrupts the binding of at least three transcription factors. Overall, the method described should be widely applicable to the analysis of QTLs.

A new set of BXD recombinant inbred lines from advanced intercross populations in mice

Background

Recombinant inbred (RI) strains are an important resource for mapping complex traits in many species. While large RI panels are available for Arabidopsis, maize, C. elegans, and Drosophila, mouse RI panels typically consist of fewer than 30 lines. This is a severe constraint on the power and precision of mapping efforts and greatly hampers analysis of epistatic interactions.

Results

In order to address these limitations and to provide the community with a more effective collaborative RI mapping panel we generated new BXD RI strains from two independent advanced intercrosses (AI) between C57BL/6J (B6) and DBA/2J (D2) progenitor strains. Progeny were intercrossed for 9 to 14 generations before initiating inbreeding, which is still ongoing for some strains. Since this AI base population is highly recombinant, the 46 advanced recombinant inbred (ARI) strains incorporate approximately twice as many recombinations as standard RI strains, a fraction of which are inevitably shared by descent. When combined with the existing BXD RI strains, the merged BXD strain set triples the number of previously available unique recombinations and quadruples the total number of recombinations in the BXD background.

Conclusion

The combined BXD strain set is the largest mouse RI mapping panel. It is a powerful tool for collaborative analysis of quantitative traits and gene function that will be especially useful to study variation in transcriptome and proteome data sets under multiple environments. Additional strains also extend the value of the extensive phenotypic characterization of the previously available strains. A final advantage of expanding the BXD strain set is that both progenitors have been sequenced, and approximately 1.8 million SNPs have been characterized. This provides unprecedented power in screening candidate genes and can reduce the effective length of QTL intervals. It also makes it possible to reverse standard mapping strategies and to explore downstream effects of known sequence variants.

A region on chromosome 15 controls intersession habituation in mice

Habituation to a novel environment, as measured by a change in exploratory activity over time, can be measured both within (intrasession) and across (intersession) sessions. The role of genetics in intrasession habituation has been investigated previously in quantitative trait loci studies, but little attention has been focused on the role of genetics on intersession habituation. We reported recently that inbred strains respond differently in an intersession habituation test. By testing a total of 25 BXD recombinant inbred lines, we were able to map a chromosomal region that strongly influences the way in which mice habituate. This region located on chromosome 15 appears to the major one affecting habituation and accounts for 80% of the genetic variance. We subsequently confirmed this map position by testing (C57BL/6J x DBA/2J) F2 mice.

Identifying loci for behavioral traits using genome-tagged mice

Identification of behavioral loci through complex trait mapping remains a widely employed approach but suffers from poor gene localization and low replicability. Genome-tagged mice (GTMs) are overlapping sets of congenic strains spanning the whole genome and offer the possibilities of superior mapping power and reproducibility. In this study, three GTM strains each consisting of an average approximately 27 cM DBA/2J genomic intervals introgressed onto a C57BL/6J background were employed for localization of behavioral traits. These GTMs were chosen because the corresponding chromosomal regions had been previously identified as containing loci for learning and memory. Analysis of the GTMs allowed confirmation of the learning and memory loci, and one on chromosome 3 was in addition fine mapped to an 8.8-cM region of overlap between two of the GTMs. Moreover, loci for prepulse inhibition of the startle response, acoustic startle response, and spontaneous locomotor activity were also mapped. These results suggest that the GTMs should be a valuable resource for mapping and confirmation of loci contributing to complex behavioral traits in the mouse.

Genome-wide linkage scan for physical activity levels in the Quebec Family study

PURPOSE AND METHODS

It is commonly recognized that there is familial aggregation for physical activity level. However, the genes and sequence variants responsible for the familial clustering have not been investigated. We performed a genome-wide linkage scan based on 432 markers typed in 767 subjects from 207 families of the Quebec Family study with the aim of identifying loci affecting physical activity levels. Four physical activity level phenotypes were used.

RESULTS

Promising evidence of linkage (P < 0.0023) was found for physical inactivity on chromosome 2p22-p16. Suggestive linkages (0.0023<P < 0.01) were found for inactivity (7p11.2, 20q13.1), total physical activity (13q22-q31), moderate to strenuous physical activity (4q28.2, 7p11.2, 9q31.1, 13q22-q31), and time spent in physical activity (11p15 and 15q13.3).

CONCLUSION

This study identified several chromosomal regions harboring genes that may contribute to the propensity to be physically active or sedentary.

Genetic contributions to body weight in mice: relationship of exploratory behavior to weight

OBJECTIVE

The A/J and C57BL/6J mouse strains differ markedly in their exploratory behavior and their weight gain on a high-fat diet. We examined the genetic contributions of exploratory behavior to body weight and tested for shared, pleiotropic loci influencing energy homeostasis.

RESEARCH METHODS AND PROCEDURES

Segregating (AxB6)F2 intercross (n = 514) and (B6AF1xA/J)N2 backcross (N = 223) populations were studied, phenotyping for weight and exploratory behaviors. Relationships among traits were analyzed by correlations. Weight traits were dissected with a genome-wide scan.

RESULTS

Modest correlations were found between exploratory behaviors and weight, explaining 2% to 14% of the variance. Quantitative trait loci (QTL) for body weight at 8 weeks (wgt8), 10 weeks (wgt10), and 2-week weight gain (difference between weeks 8 and 10) on a 6% fat diet were mapped. Two QTL on chromosome 1 (peaks at 66 cM and 100 cM; Bw8q1) affected wgt8 [likelihood of the odds ratio (Lod), 3.0 and 4.4] and wgt10 (Lod, 2.2 and 3.4), respectively. In the backcross, a significant QTL on chromosome 4 (peak at 66 cM; Bw8q2) affected wgt 8 (Lod, 3.3) and wgt10 (Lod, 3.1). For 2-week weight gain, suggestive QTL were mapped on chromosomes 4 and 6. The chromosome 6 QTL region overlaps a human 7q locus for obesity. A search for between-strain sequence polymorphisms in the leptin and NPY genes was unrevealing.

DISCUSSION

In mice, loci influencing exploratory activity play a modest role in body-weight regulation. Some forms of obesity may emerge from loci regulating normal body weight.

Genetic analysis of the psychomotor stimulant effect of ethanol

Genetic influences on the psychomotor stimulant effect of ethanol may be a key feature of abuse liability. While earlier work has shown the activational effects of ethanol to be under the influence of a relatively uncomplicated additive genetic system, preliminary data from our laboratory suggested the possibility of nonadditive genetic variance. In the present study, a full Mendelian cross was conducted to further characterize gene action and search for quantitative trait loci (QTL) influencing the psychomotor stimulant properties of ethanol. We tested 3062 mice of the six Mendelian cross genotypes (P1, P2, F1, F2, BC1 and BC2) derived from a cross between the C57BL/6J (B6) and C3H/HeJ (C3H) inbred strains of mice. On day 1, mice were injected with saline, put in a holding cage for 5 min, then placed in an activity monitor for 5 min. On day 2, mice were injected with 1.5 g/kg ethanol, and activity again monitored for 5 min. Analysis showed the expected activation in the C3H strain and little activation in the B6 strain, with no effect of sex. Biometrical genetic analysis showed a best-fit model that included the mean (m), additive effect (a), and an epistatic parameter (i = homozygote by homozygote interaction). Analysis showed good evidence for QTL on chromosomes 1 (logarithm of odds (LOD) 3.4-7.5, 88-100 cM), 6 (LOD 9.1-10.4, 46-50 cM) and 15 (LOD 7.3-8.8, 28-32 cM). While the regions on chromosomes 1 and 6 have previously been implicated in several different ethanol-related phenotypes, this is the first report of a QTL influencing the psychomotor stimulant properties of ethanol on chromosome 15. Other studies have identified QTL in this region of chromosome 15 mediating locomotor activation caused by other psychostimulants, including cocaine, amphetamine and phencyclidine.

Multiple cross mapping (MCM) markedly improves the localization of a QTL for ethanol-induced activation

This study examines the use of multiple cross mapping (MCM) to reduce the interval for an ethanol response QTL on mouse chromosome 1. The phenotype is the acute locomotor response to a 1.5-g/kg i.p. dose of ethanol. The MCM panel consisted of the six unique intercrosses that can be obtained from the C57BL/6J (B6), DBA/2J (D2), BALB/cJ (C) and LP/J (LP) inbred mouse strains (N > or = 600/cross). Ethanol response QTL were detected only with the B6xD2 and B6xC intercrosses. For both crosses, the D2 and C alleles were dominant and decreased ethanol response. The QTL information was used to develop an algorithm for sorting and editing the chromosome 1 Mit microsatellite marker set (http://www.jax.org). This process yielded a cluster of markers between 82 and 85cM (MGI). Evidence that the QTL was localized in or near this interval was obtained by the analysis of a sample (n = 550) of advanced cross heterogenous stock animals. In addition, it was observed that one of the BXD recombinant inbred strains (BXD-32) had a recombination in the interval of interest which produced the expected change in behavior. Overall, the data obtained suggest that the information available within existing genetic maps coupled with MCM data can be used to reduce the QTL interval. In addition, the MCM data set can be used to interrogate gene expression data to estimate which polymorphisms within the interval of interest are relevant to the QTL.

Quantitative genetics and mouse behavior

Quantitative differences are observed for most complex behavioral and pharmacological traits within any population. Both environmental and genetic influences regulate such individual differences. The mouse has proven to be a superb model in which to investigate the genetic basis for quantitative differences in complex behaviors. Genetically defined populations of mice, including inbred strains, heterogeneous stocks, and selected lines, have been used effectively to document these genetic differences. Recently, quantitative trait loci methods have been applied to map the chromosomal regions that regulate variation with the goal of eventually identifying the gene polymorphisms that reside in these regions.

Mapping of quantitative trait loci with knockout/congenic strains

Recently we have explored the use of knockout/congenic mouse strains for isolating and mapping quantitative trait loci (QTLs). Because most knockout strains have been bred to be B6.129 congenic strains, they can be used to test for QTLs in the targeted chromosomal area as long as there is a genetic difference between B6 and 129. Thus, we have tested a number of knockout/congenic strains in a series of behavioral tests in which mouse performance has a significant genetic component. We have also developed a breeding scheme for distinguishing the effects of background flanking genes from the targeted ablation. In screening several knockout/congenics, we have found at least one that harbors a behavioral QTL in the 129 chromosomal segment. The position of this QTL was confirmed subsequently by several F1 crosses.

Chipping away at complex behavior: transcriptome/phenotype correlations in the mouse brain

Highly parallel gene expression profiling has the potential to provide new insight into the molecular mechanisms of complex brain diseases and behavioral traits. We review how gene expression profiling in various brain regions of inbred mouse strains has been used to identify genes that may contribute to strain-specific phenotypes. New data, which demonstrate the use of gene expression profiling in combination with behavioral testing to identify candidate genes involved in mediating variation in running wheel activity, are also presented. These and other studies suggest that a combination of gene expression profiling and more traditional genetic approaches, such as quantitative trait locus analysis, can be used to identify genes responsible for specific neurobehavioral phenotypes.

Effect of genetic cross on the detection of quantitative trait loci and a novel approach to mapping QTLs

A genome-wide scan was conducted in two F(2) intercrosses, C57BL/6J (B6)xDBA/2J (D2) and BALB/cJ (C)xLP/J (LP), for three different phenotypes: basal locomotor activity, ethanol-induced locomotor activity, and haloperidol-induced catalepsy. For basal activity, significant quantitative trait loci (QTLs, LOD> or =4.3) were detected on chromosomes 9 and 19 for the CxLP intercross and chromosome 1 for the B6xD2 intercross. Significant QTLs for ethanol-induced activation were detected on chromosome 6 for the CxLP intercross, and on chromosomes 1 and 2 for the B6xD2 intercross. For haloperidol-induced catalepsy, significant QTLs were detected on chromosome 14 (two different QTLs) in the CxLP intercross, and chromosomes 1 and 9 in the B6xD2 intercross. These data illustrate the importance of the genetic cross for QTL detection. Finally, the data reported here, and elsewhere, are also used to demonstrate a novel approach to QTL detection and localization.