Genetic analysis of posterior medial barrel subfield (PMBSF) size in somatosensory cortex (SI) in recombinant inbred strains of mice

Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.
BMC Neuroscience (Impact Factor: 2.67). 02/2008; 9(1):3. DOI: 10.1186/1471-2202-9-3
Source: PubMed


Quantitative trait locus (QTL) mapping is an important tool for identifying potential candidate genes linked to complex traits. QTL mapping has been used to identify genes associated with cytoarchitecture, cell number, brain size, and brain volume. Previously, QTL mapping was utilized to examine variation of barrel field size in the somatosensory cortex in a limited number of recombinant inbred (RI) strains of mice. In order to further elucidate the underlying natural variation in mouse primary somatosensory cortex, we measured the size of the posterior medial barrel subfield (PMBSF), associated with the representation of the large mystacial vibrissae, in an expanded sample set that included 42 BXD RI strains, two parental strains (C57BL/6J and DBA/2J), and one F1 strain (B6D2F1). Cytochrome oxidase labeling was used to visualize barrels within the PMBSF.
We observed a 33% difference between the largest and smallest BXD RI strains with continuous variation in-between. Using QTL linkage analysis from WebQTL, we generated linkage maps of raw total PMBSF and brain weight adjusted total PMBSF areas. After removing the effects of brain weight, we detected a suggestive QTL (likelihood ratio statistic [LRS]: 14.20) on the proximal arm of chromosome 4. Candidate genes under the suggestive QTL peak for PMBSF area were selected based on the number of single nucleotide polymorphisms (SNPs) present and the biological relevance of each gene. Among the candidate genes are Car8 and Rab2. More importantly, mRNA expression profiles obtained using GeneNetwork indicated a strong correlation between total PMBSF area and two genes (Adcy1 and Gap43) known to be important in mouse cortex development. GAP43 has been shown to be critical during neurodevelopment of the somatosensory cortex, while knockout Adcy1 mice have disrupted barrel field patterns.
We detected a novel suggestive QTL on chromosome 4 that is linked to PMBSF size. The present study is an important step towards identifying genes underlying the size and possible development of cortical structures.

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Available from: Robert Scott Waters, Sep 30, 2015
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    • "However, after normalizing for this overall size difference, V1 is 12% larger in the C57Bl/6J strain than in the DBA/2J strain whereas PMBSF is 10% larger in the C57Bl/6J strain than in the DBA/2J strain (Airey et al., 2005). Likewise, V1 size and barrel patterning differ in inbred laboratory rats versus wild caught rats (Campi and Krubitzer, 2010; Jan et al., 2008). "
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    ABSTRACT: We describe mechanisms regulating development and plasticity of area patterning of the neocortex, the predominant region of the mammalian cerebral cortex. This process, termed arealization, is regulated by genetic mechanisms intrinsic to the cortex and extra-genetic influences, principally thalamocortical axons (TCAs) relaying input from the sensory periphery to the cortex. Intrinsic genetic mechanisms are based on morphogens secreted by patterning centers positioned at the perimeter of the dorsal telencephalon that generate across the nascent cortex, the graded expression of transcription factors (TFs) in cortical progenitors. TFs with prominent roles in arealization are Emx2, Pax6, Sp8, and COUP-TF1, which determine area patterning by specifying or repressing area identities within cortical progenitors. Emx2 preferentially imparts identities associated with posterior visual areas, Pax6 and Sp8 impart identities associated with anterior frontal/motor areas, and COUP-TF1 represses the function of any TF, including Pax6 and Sp8, that specifies frontal/motor identity. Extra-genetic mechanisms operate within this genetic framework and complement the TFs to help generate area patterning. We review features that characterize areas, contributions of genetic specification to critical features including output projection neurons, consider variants and plasticity of area patterning, and discuss models and concepts of area patterning. We also compare mechanisms of regionalization of the cerebral cortex to neocortical arealization.
    Patterning and Cell Type Specification in the Developing Cns and Pns, Volume 1 edited by John Rubenstein, Pasko Rakic, 05/2013: chapter Chapter 4 - Area Patterning of the Mammalian Cortex: pages 61-85; Academic Press., ISBN: 978-0-12-397265-1
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    • "These strains have been genotyped at over 3000 markers enabling quantitative trait loci (QTL) mapping with high precision using established tools [15]. The BXD family has now been systematically analyzed using advanced stereological methods for close to 15 years, and is part of a comprehensive genetic dissection of the CNS including deep data on the hippocampus [16]–[18], several thalamic nuclei [19], basolateral amygdala [20]–[22], striatum [23], [24], neocortex [25]–[27], olfactory bulb [28], and cerebellum [29]. Even more remarkably, there are deep gene expression data sets for many brain regions and thousands of behavioral phenotypes, which allows for detailed construction of networks of covariation [30]. "
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    PLoS ONE 08/2012; 7(8):e44236. DOI:10.1371/journal.pone.0044236 · 3.23 Impact Factor
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    • "Neuronatomical phenotypes on BXD strains have been acquired , usually based on histology , for the hippocampus ( Peirce , Chesler et al . 2003 ) , cerebellum ( Airey , Lu et al . 2001 ) , olfactory bulb ( Williams , Airey et al . 2001 ) ( Williams et al . , 1999 ) , neocortex ( Jan , Lu et al . 2008 ) , thalamus ( Seecharan , Kulkarni et al . 2003 ) , and striatum ( Rosen et al . , 2009 ) ( Rosen , Pung et al . 2008 ) , and have led to identification of genes ( QTL ) that modulate variation in CNS architecture . These studies have often been conducted on the same strains , but mostly using different animals . This makes it difficult"
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    Current opinion in neurology 07/2009; 22(4):379-86. DOI:10.1097/WCO.0b013e32832d9b86 · 5.31 Impact Factor
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