IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1003128.html
   My bibliography  Save this article

Co-expression Profiling of Autism Genes in the Mouse Brain

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003128
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1003128&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1003128?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Catherine Lord, 2011. "How common is autism?," Nature, Nature, vol. 474(7350), pages 166-167, June.
    5. Edwin H. Cook Jr & Stephen W. Scherer, 2008. "Copy-number variations associated with neuropsychiatric conditions," Nature, Nature, vol. 455(7215), pages 919-923, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tetsushi Sadakata & Yo Shinoda & Akira Sato & Hirotoshi Iguchi & Chiaki Ishii & Makoto Matsuo & Ryosuke Yamaga & Teiichi Furuichi, 2013. "Mouse Models of Mutations and Variations in Autism Spectrum Disorder-Associated Genes: Mice Expressing Caps2/Cadps2 Copy Number and Alternative Splicing Variants," IJERPH, MDPI, vol. 10(12), pages 1-19, November.
    2. Li Liu & Aniko Sabo & Benjamin M Neale & Uma Nagaswamy & Christine Stevens & Elaine Lim & Corneliu A Bodea & Donna Muzny & Jeffrey G Reid & Eric Banks & Hillary Coon & Mark DePristo & Huyen Dinh & Tim, 2013. "Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls," PLOS Genetics, Public Library of Science, vol. 9(4), pages 1-15, April.
    3. Simone Celant, 2013. "Two-mode networks: the measurement of efficiency in the profiles of actors’ participation in the occasions," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3289-3302, October.
    4. Yudong Gao & Daichi Shonai & Matthew Trn & Jieqing Zhao & Erik J. Soderblom & S. Alexandra Garcia-Moreno & Charles A. Gersbach & William C. Wetsel & Geraldine Dawson & Dmitry Velmeshev & Yong-hui Jian, 2024. "Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    5. Noah E. Friedkin, 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity," Sociological Methods & Research, , vol. 12(3), pages 235-261, February.
    6. Le Breton, Michel & Weber, Shlomo, 2009. "Existence of Pure Strategies Nash Equilibria in Social Interaction Games with Dyadic Externalities," CEPR Discussion Papers 7279, C.E.P.R. Discussion Papers.
    7. Zhu, Yongjun & Yan, Erjia, 2017. "Examining academic ranking and inequality in library and information science through faculty hiring networks," Journal of Informetrics, Elsevier, vol. 11(2), pages 641-654.
    8. Zhuqi Miao & Balabhaskar Balasundaram & Eduardo L. Pasiliao, 2014. "An exact algorithm for the maximum probabilistic clique problem," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 105-120, July.
    9. Eric van Diessen & Willemiek J E M Zweiphenning & Floor E Jansen & Cornelis J Stam & Kees P J Braun & Willem M Otte, 2014. "Brain Network Organization in Focal Epilepsy: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
    10. Henderson, Geraldine R. & Iacobucci, Dawn & Calder, Bobby J., 1998. "Brand diagnostics: Mapping branding effects using consumer associative networks," European Journal of Operational Research, Elsevier, vol. 111(2), pages 306-327, December.
    11. Etienne Farvaque & Frédéric Gannon, 2018. "Profiling giants: the networks and influence of Buchanan and Tullock," Public Choice, Springer, vol. 175(3), pages 277-302, June.
    12. Glenn N Saxe & Alexander Statnikov & David Fenyo & Jiwen Ren & Zhiguo Li & Meera Prasad & Dennis Wall & Nora Bergman & Ernestine C Briggs & Constantin Aliferis, 2016. "A Complex Systems Approach to Causal Discovery in Psychiatry," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-20, March.
    13. Sokolov, Denis, 2022. "Shapley value for TU-games with multiple memberships and externalities," Mathematical Social Sciences, Elsevier, vol. 119(C), pages 76-90.
    14. Giuliani, Elisa & Pietrobelli, Carlo, 2014. "Social Network Analysis Methodologies for the Evaluation of Cluster Development Programs," Papers in Innovation Studies 2014/11, Lund University, CIRCLE - Centre for Innovation Research.
    15. Oleksandra Yezerska & Sergiy Butenko & Vladimir L. Boginski, 2018. "Detecting robust cliques in graphs subject to uncertain edge failures," Annals of Operations Research, Springer, vol. 262(1), pages 109-132, March.
    16. Vanhaverbeke, W.P.M. & Beerkens, B.E. & Duysters, G.M., 2003. "Explorative and exploitative learning strategies in technology-based alliance networks," Working Papers 03.22, Eindhoven Center for Innovation Studies.
    17. Mingshuo Nie & Dongming Chen & Dongqi Wang, 2022. "Graph Embedding Method Based on Biased Walking for Link Prediction," Mathematics, MDPI, vol. 10(20), pages 1-13, October.
    18. Benjamin A Samuels & E David Leonardo & Alex Dranovsky & Amanda Williams & Erik Wong & Addie May I Nesbitt & Richard D McCurdy & Rene Hen & Mark Alter, 2014. "Global State Measures of the Dentate Gyrus Gene Expression System Predict Antidepressant-Sensitive Behaviors," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    19. K. Parthasarathy, 1964. "Enumeration of paths in digraphs," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 153-165, June.
    20. Zhong, Haonan & Mahdavi Pajouh, Foad & Prokopyev, Oleg A., 2021. "Finding influential groups in networked systems: The most degree-central clique problem," Omega, Elsevier, vol. 101(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1003128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.