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Co-expression Profiling of Autism Genes in the Mouse Brain

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  • Idan Menashe
  • Pascal Grange
  • Eric C Larsen
  • Sharmila Banerjee-Basu
  • Partha P Mitra

Abstract

Autism spectrum disorder (ASD) is one of the most prevalent and highly heritable neurodevelopmental disorders in humans. There is significant evidence that the onset and severity of ASD is governed in part by complex genetic mechanisms affecting the normal development of the brain. To date, a number of genes have been associated with ASD. However, the temporal and spatial co-expression of these genes in the brain remain unclear. To address this issue, we examined the co-expression network of 26 autism genes from AutDB (http://mindspec.org/autdb.html), in the framework of 3,041 genes whose expression energies have the highest correlation between the coronal and sagittal images from the Allen Mouse Brain Atlas database (http://mouse.brain-map.org). These data were derived from in situ hybridization experiments conducted on male, 56-day old C57BL/6J mice co-registered to the Allen Reference Atlas, and were used to generate a normalized co-expression matrix indicating the cosine similarity between expression vectors of genes in this database. The network formed by the autism-associated genes showed a higher degree of co-expression connectivity than seen for the other genes in this dataset (Kolmogorov–Smirnov P = 5×10−28). Using Monte Carlo simulations, we identified two cliques of co-expressed genes that were significantly enriched with autism genes (A Bonferroni corrected P

Suggested Citation

  • Idan Menashe & Pascal Grange & Eric C Larsen & Sharmila Banerjee-Basu & Partha P Mitra, 2013. "Co-expression Profiling of Autism Genes in the Mouse Brain," PLOS Computational Biology, Public Library of Science, vol. 9(7), pages 1-10, July.
    • Handle: RePEc:plo:pcbi00:1003128
    DOI: 10.1371/journal.pcbi.1003128
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    1. Irina Voineagu & Xinchen Wang & Patrick Johnston & Jennifer K. Lowe & Yuan Tian & Steve Horvath & Jonathan Mill & Rita M. Cantor & Benjamin J. Blencowe & Daniel H. Geschwind, 2011. "Transcriptomic analysis of autistic brain reveals convergent molecular pathology," Nature, Nature, vol. 474(7351), pages 380-384, June.
    2. Catherine Lord, 2011. "How common is autism?," Nature, Nature, vol. 474(7350), pages 166-167, June.
    3. Brian J. O’Roak & Laura Vives & Santhosh Girirajan & Emre Karakoc & Niklas Krumm & Bradley P. Coe & Roie Levy & Arthur Ko & Choli Lee & Joshua D. Smith & Emily H. Turner & Ian B. Stanaway & Benjamin V, 2012. "Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations," Nature, Nature, vol. 485(7397), pages 246-250, May.
    4. Edwin H. Cook Jr & Stephen W. Scherer, 2008. "Copy-number variations associated with neuropsychiatric conditions," Nature, Nature, vol. 455(7215), pages 919-923, October.
    5. R. Luce & Albert Perry, 1949. "A method of matrix analysis of group structure," Psychometrika, Springer;The Psychometric Society, vol. 14(2), pages 95-116, June.
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