Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits.

We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.

Genomic regulation of natural variation in cortical and noncortical brain volume.

BACKGROUND: The relative growth of the neocortex parallels the emergence of complex cognitive functions across species. To determine the regions of the mammalian genome responsible for natural variations in cortical volume, we conducted a complex trait analysis using 34 strains of recombinant inbred (Rl) strains of mice (BXD), as well as their two parental strains (C57BL/6J and DBA/2J). We measured both neocortical volume and total brain volume in 155 coronally sectioned mouse brains that were Nissl stained and embedded in celloidin. After correction for shrinkage, the measured cortical and noncortical brain volumes were entered into a multiple regression analysis, which removed the effects of body size and age from the measurements. Marker regression and interval mapping were computed using WebQTL. RESULTS: An ANOVA revealed that more than half of the variance of these regressed phenotypes is genetically determined. We then identified the regions of the genome regulating this heritability. We located genomic regions in which a linkage disequilibrium was present using WebQTL as both a mapping engine and genomic database. For neocortex, we found a genome-wide significant quantitative trait locus (QTL) on chromosome 11 (marker D11Mit19), as well as a suggestive QTL on chromosome 16 (marker D16Mit100). In contrast, for noncortex the effect of chromosome 11 was markedly reduced, and a significant QTL appeared on chromosome 19 (D19Mit22). CONCLUSION: This classic pattern of double dissociation argues strongly for different genetic factors regulating relative cortical size, as opposed to brain volume more generally. It is likely, however, that the effects of proximal chromosome 11 extend beyond the neocortex strictly defined. An analysis of single nucleotide polymorphisms in these regions indicated that ciliary neurotrophic factor (Cntf) is quite possibly the gene underlying the noncortical QTL. Evidence for a candidate gene modulating neocortical volume was much weaker, but Otx1 deserves further consideration.

Cocaine self-administration behavior in inbred mouse lines segregating different capacities for inhibitory control.

RATIONALE: Various dimensions of impulsivity have been linked to substance abuse and dependence, both as consequences of, and as predisposing factors to addiction. With respect to the latter, they may be quantitative indicators of liability for substance use disorders (SUD) and aid in determining underlying genetic influences. We have previously determined that inhibitory control over impulsive responding, as measured by a reversal learning task, is heritable and under substantial genetic control, however their role as explaining variables for aspects of SUD have not been well explored. OBJECTIVE: The aim of this study was to test for an association between genetically determined differences in inhibitory control and addiction-related phenotypes, such that phenotypes of poor inhibitory control would predict propensity for elevated operant drug-seeking and -taking behaviors. METHODS: Mice from BxD strains with either good reversal learning (GRL) or poor reversal learning (PRL) ability were tested for intravenous cocaine self-administration under FR1, FR2, and FR5 reinforcement schedules. Additionally, locomotor responses to experimenter-delivered cocaine were assessed. RESULTS: Compared to GRL strains, PRL strains acquired self-administration behavior more rapidly and administered cocaine at greater rates under all schedules of reinforcement, without any differences in discrimination index. In addition, PRL mice also exhibited increased responding during time-out periods. PRL strains also showed larger locomotor responses to 10 or 20 mg/kg injections of cocaine. CONCLUSIONS: These studies demonstrate that heritable strain differences in inhibitory control do influence drug self-administration, thus suggest that genetically driven impulsivity of this type may predispose susceptibility to drug abuse and addiction.

Genetic dissection of behavioral flexibility: reversal learning in mice.

BACKGROUND: Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. METHODS: We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels. RESULTS: Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p < .05 genome-wide). Variance in messenger RNA levels of select transcripts expressed in neocortex, hippocampus, and striatum correlated with the reversal learning phenotype, including Syn3, Nt5dc3, and Hcfc2. CONCLUSIONS: This work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology.