Quantitative Biology

, Volume 1, Issue 1, pp 91–100

Computational neuroanatomy and co-expression of genes in the adult mouse brain, analysis tools for the Allen Brain Atlas

  • Pascal Grange
  • Michael Hawrylycz
  • Partha P. Mitra
Review

Abstract

We review quantitative methods and software developed to analyze genome-scale, brain-wide spatially-mapped gene-expression data. We expose new methods based on the underlying high-dimensional geometry of voxel space and gene space, and on simulations of the distribution of co-expression networks of a given size. We apply them to the Allen Atlas of the adult mouse brain, and to the coexpression network of a set of genes related to nicotine addiction retrieved from the NicSNP database. The computational methods are implemented in BrainGeneExpressionAnalysis (BGEA), a Matlab toolbox available for download.

Supplementary material

40484_2013_11_MOESM1_ESM.pdf (192 kb)
Supplementary material, approximately 192 KB.

References

  1. 1.
    Bota, M., Dong, H.W. and Swanson, L.W. (2003) From gene networks to brain networks. Nat. Neurosci. 6, 795–799.PubMedCrossRefGoogle Scholar
  2. 2.
    Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176.PubMedCrossRefGoogle Scholar
  3. 3.
    Sunkin, S. M., Hohmann, J. G. (2007) Insights from spatially mapped gene expression in the mouse brain. Hum. Mol. Genet. 16, 2.CrossRefGoogle Scholar
  4. 4.
    Ng, L., Hawrylycz, M. and Haynor, D. (2005) Automated highthroughput registration for localizing 3D mouse brain gene expression using ITK, Insight-Journal.Google Scholar
  5. 5.
    Ng, L., Pathak, S. D., Kuan, C., Lau, C., Dong, H., et al. (2007) Neuroinformatics for genome-wide 3D gene expression mapping in the mouse brain. IEEE/ACM Trans. Comput. Biol. Bioinform. Jul–Sep 4(3), 382–393.PubMedCrossRefGoogle Scholar
  6. 6.
    Jones, A. R., Overly, C. C. and Sunkin, S. M. (2009) The Allen Brain Atlas: 5 years and beyond. Nat. Rev. Neurosci. 10, 821–828.PubMedCrossRefGoogle Scholar
  7. 7.
    Hawrylycz, M., Ng, L., Page, D., Morris, J., Lau, C., Faber, S., Faber, V., Sunkin, S., Menon, V., Lein, E., et al. (2011) Multi-scale correlation structure of gene expression in the brain. Neural Netw. 24, 933–942.PubMedCrossRefGoogle Scholar
  8. 8.
    Computational analysis of user-defined sets of genes from the Allen Atlas of mouse and human brain can be conducted online at addiction. http://brainarchitecture.org
  9. 9.
    Grange, P., Bohland, J.W., Hawrylycz, M. and Mitra, P. P. (2012) Brain Gene Expression Analysis: a MATLAB toolbox for the analysis of brain-wide gene-expression data, arXiv:1211.6177 [q-bio.QM].Google Scholar
  10. 10.
    Li, C. Y., Mao, X. and Wei, L. (2008) Genes and (common) pathways underlying drug addiction. PLOS Comput. Biol. 4, e2.PubMedCrossRefGoogle Scholar
  11. 11.
    Saccone, S. F., Saccone, N. L., Swan, G. E., Madden, P. A. F., Goate, A. M., Rice, J. P. and Bierut, L. J. (2008) Systematic biological prioritization after a genome-wide association study: an application to nicotine dependence. Bioinformatics 24, 1805–1811.PubMedCrossRefGoogle Scholar
  12. 12.
    Altschul, S. F., Gish, W., Miller, W., Myers, E. W. and Lipman, D. J. (1990) Basic local alignment search tool. J. Mol. Biol. 215, 403–410.PubMedGoogle Scholar
  13. 13.
    Ng, L., Lau, C., Young, R., Pathak, S., Kuan, L., Sodt, A., Sutram, M., Lee, C. K., Dang, C. and Hawrylycz, M. (2007) NeuroBlast: a 3D spatial homology search tool for gene expression. BMC Neurosci. 8, 11.CrossRefGoogle Scholar
  14. 14.
    Ng, L., Bernard, A., Lau, C., Overly, C. C., Dong, H. W., Kuan, C., Pathak, S., Sunkin, S. M., Dang, C., Bohland, J. W., et al. (2009) An anatomic gene expression atlas of the adult mouse brain. Nat. Neurosci. 12, 356–362.PubMedCrossRefGoogle Scholar
  15. 15.
    Zhang, B. and Horvath, S. (2005) A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, e17.Google Scholar
  16. 16.
    Olszewski, P. K., Cedernaes, J., Olsson, F., Levine, A. S. and Schiöth, H. B. (2008) Analysis of the network of feeding neuroregulators using the Allen Brain Atlas. Neurosci. Biobehav. Rev. 32, 945–956.PubMedCrossRefGoogle Scholar
  17. 17.
    Dong, H.W. (2007) The Allen reference atlas: a digital brain atlas of the C57BL/6J male mouse, Wiley.Google Scholar
  18. 18.
    Grange, P. and Mitra, P. P. (2012) Computational neuroanatomy and gene expression: Optimal sets of marker genes for brain regions. IEEE, in CISS 2012, 46th annual conference on Information Science and Systems (Princeton), arXiv:1205.2721 [q-bio.QM].Google Scholar
  19. 19.
    Lau, C., Ng, L., Thompson, C., Pathak, S., Kuan, L., Jones, A. and Hawrylycz, M. (2008) Exploration and visualization of gene expression with neuroanatomy in the adult mouse brain. BMC Bioinformatics 9, 153.PubMedCrossRefGoogle Scholar
  20. 20.
    Hawrylycz, M., Baldock, R. A., Burger, A., Hashikawa, T., Johnson, G. A., Martone, M., Ng, L., Lau, C., Larson, S. D., Nissanov, J., et al. (2011) Digital atlasing and standardization in the mouse brain. PLOS Comput. Biol. 7, e1001065.PubMedCrossRefGoogle Scholar
  21. 21.
    The Allen Brain Atlas can be used online at http://www.brain-map.org/
  22. 22.
    Tarjan, R. E. (1972) Depth first search and linear graph algorithms. SIAM J. Comput. 1, 146–160.CrossRefGoogle Scholar
  23. 23.
    Bohland, J. W., Bokil, H., Pathak, S. D., Lee, C. K., Ng, L., Lau, C., Kuan, C., Hawrylycz, M. and Mitra, P. P. (2010) Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy. Methods 50, 105–112.PubMedCrossRefGoogle Scholar
  24. 24.
    The developmental atlas of the mouse brain is available from http://developingmouse.brain-map.org/
  25. 25.
    Menashe, I., Grange, P., Larsen, E. C., Banerjee-Basu, S. and Mitra, P. P. (2012) Co-expression profiling of autism genes in the mouse brain. SFN Abstracts, and submitted.Google Scholar
  26. 26.
    Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391–399.PubMedCrossRefGoogle Scholar
  27. 27.
    Warren, W. C., Clayton, D. F., Ellegren, H., Arnold, A. P., Hillier, L.W., Künstner, A., Searle, S., White, S., Vilella, A. J. and Fairley, S. (2010) The genome of a songbird. Nature 464, 757–762.PubMedCrossRefGoogle Scholar
  28. 28.
    Data can be retrieved from the ZEBrA database. (Oregon Health and Science University, Portland, OR 97239; http://www.zebrafinchatlas.org).
  29. 29.
    Miller, J. A., Horvath, S. and Geschwind, D. H. (2010) Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc. Natl. Acad. Sci. USA 107, 12698–12703.PubMedCrossRefGoogle Scholar
  30. 30.
    Rossner, M. J., Hirrlinger, J., Wichert, S. P., Boehm, C., Newrzella, D., Hiemisch, H., Eisenhardt, G., Stuenkel, C., von Ahsen, O. and Nave, K. A. (2006) Global transcriptome analysis of genetically identified neurons in the adult cortex. J. Neurosci. 26, 9956–9966.PubMedCrossRefGoogle Scholar
  31. 31.
    Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J. Neurosci. 28, 264–278.PubMedCrossRefGoogle Scholar
  32. 32.
    Doyle, J. P., Dougherty, J. D., Heiman, M., Schmidt, E. F., Stevens, T. R., Ma, G., Bupp, S., Shrestha, P., Shah, R. D., Doughty, M. L., et al. (2008) Application of a translational profiling approach for the comparative analysis of CNS cell types. Cell 135, 749–762.PubMedCrossRefGoogle Scholar
  33. 33.
    Chung, C. Y., Seo, H., Sonntag, K. C., Brooks, A., Lin, L. and Isacson, O. (2005) Cell type-specific gene expression of midbrain dopaminergic neurons reveals molecules involved in their vulnerability and protection. Hum. Mol. Genet. 14, 1709–1725.PubMedCrossRefGoogle Scholar
  34. 34.
    Arlotta, P., Molyneaux, B. J., Chen, J., Inoue, J., Kominami, R. and Macklis, J. D. (2005) Neuronal subtype-specific genes that control corticospinal motor neuron development in vivo. Neuron 45, 207–221.PubMedCrossRefGoogle Scholar
  35. 35.
    Heiman, M., Schaefer, A., Gong, S., Peterson, J. D., Day, M., Ramsey, K. E., Suárez-Fariñas M., Schwarz, C., Stephan, D. A., Surmeier, D. J., et al. (2008) A translational profiling approach for the molecular characterization of CNS cell types. Cell 135, 738–748.PubMedCrossRefGoogle Scholar
  36. 36.
    Sugino, K., Hempel, C. M., Miller, M. N., Hattox, A. M., Shapiro, P., Wu, C., Huang, Z. J. and Nelson, S. B. (2006) Molecular taxonomy of major neuronal classes in the adult mouse forebrain. Nat. Neurosci. 9, 99–107.PubMedCrossRefGoogle Scholar
  37. 37.
    Lee, C. K., Sunkin, S. M., Kuan, C., Thompson, C. L., Pathak, S., Ng, L., Lau, C., Fischer, S., Mortrud, M., Slaughterbeck, C., et al. (2008) Quantitative methods for genome-scale analysis of in situ hybridization and correlation with microarray data. Genome Biol. 9, R23.PubMedCrossRefGoogle Scholar
  38. 38.
    Grange, P., Bohland, J.W., Bokil, H., Nelson, S., Okaty, B., Sugino, K., Ng, L., Hawrylycz, M. and Mitra, P. P. (2011) A cell-type based model explaining co-expression patterns of genes in the brain, arXiv:1111.6217 [q-bio.QM].Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH 2013

Authors and Affiliations

  • Pascal Grange
    • 1
  • Michael Hawrylycz
    • 2
  • Partha P. Mitra
    • 1
  1. 1.Cold Spring Harbor LaboratoryCold Spring HarborNew YorkUSA
  2. 2.Allen Institute for Brain ScienceWashingtonUSA

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