Independent quantitative trait loci influence ventral and dorsal hippocampal volume in recombinant inbred strains of mice

Variable cardiac α-actin (Actc1) expression in early adult skeletal muscle correlates with promoter methylation

Different genes encode the α-actin isoforms that are predominantly expressed in heart and skeletal muscle. Mutations in the skeletal muscle α-actin gene (ACTA1) cause muscle diseases that are mostly lethal in the early postnatal period. We previously demonstrated that the disease phenotype of ACTA1 mouse models could be rescued by transgenic over-expression of cardiac α-actin (ACTC1). ACTC1 is the predominant striated α-actin isoform in the heart but is also expressed in developing skeletal muscle. To develop a translatable therapy, we investigated the genetic regulation of Actc1 expression. Using strains from The Collaborative Cross (CC) genetic resource, we found that Actc1 varies in expression by up to 24-fold in skeletal muscle. We defined significant expression quantitative trait loci (eQTL) associated with early adult Actc1 expression in soleus and heart. eQTL in both heart and soleus mapped to the Actc1 locus and replicate an eQTL mapped for Actc1 in BXD heart and quadriceps. We built on this previous work by analysing genes within the eQTL peak regions to prioritise likely candidates for modifying Actc1 expression. Additionally we interrogated the CC founder haplotype contributions to enable prioritisation of genetic variants for functional analyses. Methylation around the Actc1 transcriptional start site in early adult skeletal muscle negatively correlated with Actc1 expression in a strain-dependent manner, while other marks of regulatory potential (histone modification and chromatin accessibility) were unaltered. This study provides novel insights into the complex genetic regulation of Actc1 expression in early adult skeletal muscles.

Linking traits based on their shared molecular mechanisms

There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait-trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits.

Systems genetics of the lateral septal nucleus in mouse: heritability, genetic control, and covariation with behavioral and morphological traits

The lateral septum has strong efferent projections to hypothalamic and midbrain regions, and has been associated with modulation of social behavior, anxiety, fear conditioning, memory-related behaviors, and the mesolimbic reward pathways. Understanding natural variation of lateral septal anatomy and function, as well as its genetic modulation, may provide important insights into individual differences in these evolutionarily important functions. Here we address these issues by using efficient and unbiased stereological probes to estimate the volume of the lateral septum in the BXD line of recombinant inbred mice. Lateral septum volume is a highly variable trait, with a 2.5-fold difference among animals. We find that this trait covaries with a number of behavioral and physiological phenotypes, many of which have already been associated with behaviors modulated by the lateral septum, such as spatial learning, anxiety, and reward-seeking. Heritability of lateral septal volume is moderate (h(2) = 0.52), and much of the heritable variation is caused by a locus on the distal portion of chromosome (Chr) 1. Composite interval analysis identified a secondary interval on Chr 2 that works additively with the Chr 1 locus to increase lateral septum volume. Using bioinformatic resources, we identified plausible candidate genes in both intervals that may influence the volume of this key nucleus, as well as associated behaviors.

Genetic dissection of acute ethanol responsive gene networks in prefrontal cortex: functional and mechanistic implications

Background

Individual differences in initial sensitivity to ethanol are strongly related to the heritable risk of alcoholism in humans. To elucidate key molecular networks that modulate ethanol sensitivity we performed the first systems genetics analysis of ethanol-responsive gene expression in brain regions of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens, and ventral midbrain) across a highly diverse family of 27 isogenic mouse strains (BXD panel) before and after treatment with ethanol.

Results

Acute ethanol altered the expression of ∼2,750 genes in one or more regions and 400 transcripts were jointly modulated in all three. Ethanol-responsive gene networks were extracted with a powerful graph theoretical method that efficiently summarized ethanol's effects. These networks correlated with acute behavioral responses to ethanol and other drugs of abuse. As predicted, networks were heavily populated by genes controlling synaptic transmission and neuroplasticity.

Several of the most densely interconnected network hubs, including Kcnma1 and Gsk3β, are known to influence behavioral or physiological responses to ethanol, validating our overall approach. Other major hub genes like Grm3, Pten and Nrg3 represent novel targets of ethanol effects. Networks were under strong genetic control by variants that we mapped to a small number of chromosomal loci. Using a novel combination of genetic, bioinformatic and network-based approaches, we identified high priority cis-regulatory candidate genes, including Scn1b, Gria1, Sncb and Nell2.

Conclusions

The ethanol-responsive gene networks identified here represent a previously uncharacterized intermediate phenotype between DNA variation and ethanol sensitivity in mice. Networks involved in synaptic transmission were strongly regulated by ethanol and could contribute to behavioral plasticity seen with chronic ethanol. Our novel finding that hub genes and a small number of loci exert major influence over the ethanol response of gene networks could have important implications for future studies regarding the mechanisms and treatment of alcohol use disorders.

Novel candidate genes associated with hippocampal oscillations

The hippocampus is critical for a wide range of emotional and cognitive behaviors. Here, we performed the first genome-wide search for genes influencing hippocampal oscillations. We measured local field potentials (LFPs) using 64-channel multi-electrode arrays in acute hippocampal slices of 29 BXD recombinant inbred mouse strains. Spontaneous activity and carbachol-induced fast network oscillations were analyzed with spectral and cross-correlation methods and the resulting traits were used for mapping quantitative trait loci (QTLs), i.e., regions on the genome that may influence hippocampal function. Using genome-wide hippocampal gene expression data, we narrowed the QTLs to eight candidate genes, including Plcb1, a phospholipase that is known to influence hippocampal oscillations. We also identified two genes coding for calcium channels, Cacna1b and Cacna1e, which mediate presynaptic transmitter release and have not been shown to regulate hippocampal network activity previously. Furthermore, we showed that the amplitude of the hippocampal oscillations is genetically correlated with hippocampal volume and several measures of novel environment exploration.

Appetitive operant conditioning in mice: heritability and dissociability of training stages

To study the heritability of different training stages of appetitive operant conditioning, we carried out behavioral screening of 5 standard inbred mouse strains, 28 recombinant-inbred (BxD) mouse lines and their progenitor strains C57BL/6J and DBA/2J. We also computed correlations between successive training stages to study whether learning deficits at an advanced stage of operant conditioning may be dissociated from normal performance in preceding phases of training. The training consisted of two phases: an operant nose poking (NP) phase, in which mice learned to collect a sucrose pellet from a food magazine by NP, and an operant lever press and NP phase, in which mice had to execute a sequence of these two actions to collect a food pellet. As a measure of magazine oriented exploration, we also studied the nose poke entries in the food magazine during the intertrial intervals at the beginning of the first session of the nose poke training phase. We found significantly heritable components in initial magazine checking behavior, operant NP and lever press-NP. Performance levels in these phases were positively correlated, but several individual strains were identified that showed poor lever press-NP while performing well in preceding training stages. Quantitative trait loci mapping revealed suggestive likelihood ratio statistic peaks for initial magazine checking behavior and lever press-NP. These findings indicate that consecutive stages toward more complex operant behavior show significant heritable components, as well as dissociability between stages in specific mouse strains. These heritable components may reside in different chromosomal areas.

Genetic dissection of the mouse CNS using magnetic resonance microscopy

PURPOSE OF REVIEW

Advances in magnetic resonance microscopy (MRM) make it practical to map gene variants responsible for structural variation in brains of many species, including mice and humans. We review results of a systematic genetic analysis of MRM data using as a case study a family of well characterized lines of mice.

RECENT ADVANCES

MRM has matured to the point that we can generate high contrast, high-resolution images even for species as small as a mouse, with a brain merely 1/3000th the size of humans. We generated 21.5-micron data sets for a diverse panel of BXD mouse strains to gauge the extent of genetic variation, and as a prelude to comprehensive genetic and genomic analyses. Here we review MRM capabilities and image segmentation methods; heritability of brain variation; covariation of the sizes of brain regions; and correlations between MRM and classical histological data sets.

SUMMARY

The combination of high throughput MRM and genomics will improve our understanding of the genetic basis of structure-function correlations. Sophisticated mouse models will be critical in converting correlations into mechanisms and in determining genetic and epigenetic causes of differences in disease susceptibility.

The genetic control of neocortex volume and covariation with neocortical gene expression in mice

Background

The size of the cerebral cortex varies widely within human populations, and a large portion of this variance is modulated by genetic factors. The discovery and characterization of these genes and their variants can contribute to an understanding of individual differences in brain development, behavior, and disease susceptibility. Here we use unbiased stereological techniques to map quantitative trait loci (QTLs) that modulate the volume of neocortex.

Results

We estimated volumes bilaterally in an expanded set of BXD recombinant inbred strains (n = 56 strains and 223 animals) taken from the Mouse Brain Library . We generated matched microarray data for the cerebral cortex in the same large panel of strains and in parental neonates to efficiently nominate and evaluate candidate genes. Volume of the neocortex varies widely, and is a heritable trait. Genome-wide mapping of this trait revealed two QTLs – one on chromosome (Chr) 6 at 88 ± 5 Mb and another at Chr 11 (41 ± 8 Mb). We generated both neonatal and adult neocortical gene expression databases using microarray technology. Using these databases in combination with other bioinformatic tools we have identified positional candidates on these QTL intervals.

Conclusion

This study is the first to use the expanded set of BXD strains to map neocortical volume, and we found that normal variation of this trait is, at least in part, genetically modulated. These results provide a baseline from which to assess the genetic contribution to regional variation in neocortical volume, as well as other neuroanatomic phenotypes that may contribute to variation in regional volume, such as proliferation, death, and number and packing density of neurons

Genetic modulation of striatal volume by loci on Chrs 6 and 17 in BXD recombinant inbred mice

Natural variation in the absolute and relative size of different parts of the human brain is substantial, with a range that often exceeds a factor of 2. Much of this variation is generated by the cumulative effects of sets of unknown gene variants that modulate the proliferation, growth and death of neurons and glial cells. Discovering and testing the functions of these genes should contribute significantly to our understanding of differences in brain development, behavior and disease susceptibility. We have exploited a large population of genetically well-characterized strains of mice (BXD recombinant inbred strains) to map gene variants that influence the volume of the dorsal striatum (caudate-putamen without nucleus accumbens). We used unbiased methods to estimate volumes bilaterally in a sex-balanced sample taken from the Mouse Brain Library (www.mbl.org). We generated a matched microarray data set to efficiently evaluate candidate genes (www.genenetwork.org). As in humans, volume of the striatum is highly heritable, with greater than twofold differences among strains. We mapped a locus that modulates striatal volume on chromosome (Chr) 6 at 88 +/- 5 Mb. We also uncovered an epistatic interaction between loci on Chr 6 and Chr 17 that modulates striatal volume. Using bioinformatic tools and the corresponding expression database, we have identified positional candidates in these quantitative trait locus intervals.

Genetic influences on hippocampal structure and function in recombinant inbred mice

Previously, we identified separate genetic influences on ventral versus dorsal hippocampal volume in BXD recombinant inbred mice [Martin MV, Dong HX, Vallera D, Lu L, Williams RW, Rosen GD, et al. Independent quantitative trait loci influence ventral and dorsal hippocampal volume in recombinant inbred strains of mice. Genes Brain Behav 2006;5:614-23]. Based on genotype at genetic markers associated with ventral hippocampal volume, we evaluated BXD mouse strains with relatively small versus large ventral hippocampal volumes using numerous behavioral paradigms known to rely upon hippocampal function and several other tasks that tap into behaviors analogous to those often impaired in schizophrenia. We observed a relationship between genotype at markers known to influence ventral hippocampal volume and working memory at an intermediate memory load. There was no association between genotype at markers known to influence ventral hippocampal volume and spatial reference memory, prepulse inhibition, or elevated plus maze performance. The relevance of these findings for understanding the pathophysiology of schizophrenia are discussed, including the possibility that genetic predisposition toward anterior hippocampal volume reductions and working memory deficits in schizophrenia may be related through a shared genetic locus.

3D-reconstruction and functional properties of GFP-positive and GFP-negative granule cells in the fascia dentata of the Thy1-GFP mouse

Granule cells of the mouse fascia dentata are widely used in studies on neuronal development and plasticity. In contrast to the rat, however, high-resolution morphometric data on these cells are scarce. Thus, we have analyzed granule cells in the fascia dentata of the adult Thy1-GFP mouse (C57BL/6 background). In this mouse line, single neurons in the granule cell layer are GFP-labeled, making them amenable to high-resolution 3D-reconstruction. First, calbindin or parvalbumin-immunofluorescence was used to identify GFP-positive cells as granule cells. Second, the dorsal-ventral distribution of GFP-positive granule cells was studied: In the dorsal part of the fascia dentata 11% and in the ventral part 15% of all granule cells were GFP-positive. Third, GFP-positive and GFP-negative granule cells were compared using intracellular dye-filling (fixed slice technique) and patch-clamp recordings; no differences were observed between the cells. Finally, GFP-positive granule cells (dorsal and ventral fascia dentata) were imaged at high resolution with a confocal microscope, 3D-reconstructed in their entirety and analyzed for soma size, total dendritic length, number of segments, total number of spines and spine density. Sholl analysis revealed that dendritic complexity of granule cells is maximal 150-200 mum from the soma. Granule cells located in the ventral part of the hippocampus revealed a greater degree of dendritic complexity compared to cells in the dorsal part. Taken together, this study provides morphometric data on granule cells of mice bred on a C57BL/6 background and establishes the Thy1-GFP mouse as a tool to study granule cell neurobiology.

Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy

Magnetic resonance microscopy (MRM) has created new approaches for high-throughput morphological phenotyping of mouse models of diseases. Transgenic and knockout mice serve as a test bed for validating hypotheses that link genotype to the phenotype of diseases, as well as developing and tracking treatments. We describe here a Markov random fields based segmentation of the actively stained mouse brain, as a prerequisite for morphological phenotyping. Active staining achieves higher signal to noise ratio (SNR) thereby enabling higher resolution imaging per unit time than obtained in previous formalin-fixed mouse brain studies. The segmentation algorithm was trained on isotropic 43-mum T1- and T2-weighted MRM images. The mouse brain was segmented into 33 structures, including the hippocampus, amygdala, hypothalamus, thalamus, as well as fiber tracts and ventricles. Probabilistic information used in the segmentation consisted of (a) intensity distributions in the T1- and T2-weighted data, (b) location, and (c) contextual priors for incorporating spatial information. Validation using standard morphometric indices showed excellent consistency between automatically and manually segmented data. The algorithm has been tested on the widely used C57BL/6J strain, as well as on a selection of six recombinant inbred BXD strains, chosen especially for their largely variant hippocampus.

Genetic loci modulating amyloid-beta levels in a mouse model of Alzheimer's disease

Genetic studies have demonstrated very high heritability for Alzheimer's disease (AD) risk in humans; however, these genetic contributions have proven extremely challenging to map in large studies of AD patients. Processing of the amyloid precursor protein (APP) to produce amyloid-beta (Abeta) peptide is increasingly believed to be of central importance in AD pathogenesis. Intriguingly, mice from the C57BL/6J and DBA2/J inbred strains carrying the R1.40 APP transgene produce identical levels of unprocessed APP, but demonstrate significant, heritable differences in Abeta levels. To identify specific loci responsible for the observed genetic control of Abeta metabolism in this model system, we have performed a whole-genome quantitative trait locus (QTL) mapping experiment on a total of 516 animals from a C57BL/6JxDBA/2J intercross using a dense set of SNP genetic markers. Our studies have identified three loci on mouse chromosomes 1, 2, and 7 showing significant or suggestive associations with brain Abeta levels, several of which contain regions syntenic to previous reports of linkage in human AD.