Literature DB >> 19349225

Genetic dissection of the mouse brain using high-field magnetic resonance microscopy.

A Badea1, G A Johnson, R W Williams.   

Abstract

Magnetic resonance (MR) imaging has demonstrated that variation in brain structure is associated with differences in behavior and disease state. However, it has rarely been practical to prospectively test causal models that link anatomical and functional differences in humans. In the present study we have combined classical mouse genetics with high-field MR to systematically explore and test such structure-functional relations across multiple brain regions. We segmented 33 regions in two parental strains-C57BL/6J (B) and DBA/2J (D)-and in nine BXD recombinant inbred strains. All strains have been studied extensively for more than 20 years using a battery of genetic, functional, anatomical, and behavioral assays. We compared levels of variation within and between strains and sexes, by region, and by system. Average within-strain variation had a coefficient of variation (CV) of 1.6% for the whole brain; while the CV ranged from 2.3 to 3.6% for olfactory bulbs, cortex and cerebellum, and up to approximately 18% for septum and laterodorsal thalamic nucleus. Variation among strain averages ranged from 6.7% for cerebellum, 7.6% for whole brain, 9.0% for cortex, up to approximately 26% for the ventricles, laterodorsal thalamic nucleus, and the interpeduncular nucleus. Heritabilities averaged 0.60+/-0.18. Sex differences were not significant with the possible (and unexpected) exception of the pons ( approximately 20% larger in males). A correlation matrix of regional volumes revealed high correlations among functionally related parts of the CNS (e.g., components of the limbic system), and several high correlations between regions that are not anatomically connected, but that may nonetheless be functionally or genetically coupled.

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Year:  2009        PMID: 19349225      PMCID: PMC2667384          DOI: 10.1016/j.neuroimage.2009.01.021

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  64 in total

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