Abstract
Highly differentiated brain structures with distinctly different phenotypes are closely correlated with the unique combination of gene expression patterns. Using a genome-wide in situ hybridization image dataset released by Allen Mouse Brain Atlas, we present a data-driven method of dictionary learning and sparse coding. Our results show that sparse coding can elucidate patterns of transcriptome organization of mouse brain. A collection of components obtained from sparse coding display robust region-specific molecular signatures corresponding to the canonical neuroanatomical subdivisions including fiber tracts and ventricular systems. Other components revealed finer anatomical delineation of domains previously considered homogeneous. We also build an open-access informatics portal that contains the detail of each component along with its ontology and expressed genes. This portal allows intuitive visualization, interpretation and explorations of the transcriptome architecture of a mouse brain.
Similar content being viewed by others
References
Belgard, T. G., Marques, A. C., Oliver, P. L., et al. (2011). A transcriptomic atlas of mouse neocortical layers. Neuron, 71, 605–616. doi:10.1016/j.neuron.2011.06.039.
Bernard, A., Lubbers, L. S., Tanis, K. Q., et al. (2012). Transcriptional architecture of the primate neocortex. Neuron, 73, 1083–1099. doi:10.1016/j.neuron.2012.03.002.Transcriptional.
Bohland, J. W., Bokil, H., Pathak, S. D., et al. (2010). Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy. Methods, 50, 105–112. doi:10.1016/j.ymeth.2009.09.001.
Cahoy, J., Emery, B., Kaushal, A., et al. (2004). A transcriptome database for astrocytes, neurons, and oligodendrocytes: A new resource for understanding brain development and function. Journal of Neuro-Oncology, 28, 264–278. doi:10.1523/JNEUROSCI.4178-07.2008.
Chen, H., Liu, T., Zhao, Y., et al. (2015). Optimization of large-scale mouse brain connectome via joint evaluation of DTI and neuron tracing data. NeuroImage, 115, 202–213. doi:10.1016/j.neuroimage.2015.04.050.
Comon, P. (1994). Independent component analysis: A new concept. IEEE Trans Signal Process, 36, 287–314. doi:10.1016/0165-1684(94)90029-9.
Dong, H. (2008). Allen reference atlas. A digital color brain atlas of the C57BL/6J male mouse - by H. W. Dong. John Wiley & Sons.
Elad, M., & Aharon, M. (2006). Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 15, 3736–3745. doi:10.1109/ICIG.2009.101.
Hawrylycz, M., Bernard, A., Lau, C., et al. (2010). Areal and laminar differentiation in the mouse neocortex using large scale gene expression data. Methods, 50, 113–121. doi:10.1016/j.ymeth.2009.09.005.
Heintz, N. (2004). Gene expression nervous system atlas (GENSAT). Nature Neuroscience, 7, 483. doi:10.1038/nn0504-483.
Hyvärinen, A. (1999). Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks, 10, 626–634. doi:10.1109/72.761722.
Ishizuka, N., Weber, J., & Amaral, D. (1990). Organization of intrahippocampal projections originating from CA3 pyramidal cells in the rat. The Journal of Comparative Neurology, 295, 580–623.
Jiang, C. H., Tsien, J. Z., Schultz, P. G., & Hu, Y. (2001). The effects of aging on gene expression in the hypothalamus and cortex of mice. PNAS, 98, 1930–1934. doi:10.1073/pnas.98.4.1930.
Lein, E. S., Hawrylycz, M. J., Ao, N., et al. (2007). Genome-wide atlas of gene expression in the adult mouse brain. Nature, 445, 168–176. doi:10.1038/nature05453.
Lein, E. S., Zhao, X., & Gage, F. H. (2004). Defining a molecular atlas of the hippocampus using DNA microarrays and high-throughput in situ hybridization. The Journal of Neuroscience, 24, 3879–3889. doi:10.1523/JNEUROSCI.4710-03.2004.
Lv, J., Jiang, X., Li, X., et al. (2015). Sparse representation of whole-brain fMRI signals for identification of functional networks. Medical Image Analysis, 20, 112–134. doi:10.1016/j.media.2014.10.011.
Mairal, J., Bach, F., Ponce, J., & Sapiro, G. (2010). Online learning for matrix factorization and sparse coding. Journal of Machine Learning Research, 11, 19–60.
Mairal, J., Elad, M., & Sapiro, G. (2008). Sparse representation for color image restoration. IEEE Transactions on Image Processing, 17, 53–69. doi:10.1109/TIP.2007.911828.
Mody, M., Cao, Y., Cui, Z., et al. (2001). Genome-wide gene expression profiles of the developing mouse hippocampus. PNAS, 98, 8862–8867. doi:10.1073/pnas.141244998.
Molyneaux, B. J., Arlotta, P., Menezes, J. R. L., & Macklis, J. D. (2007). Neuronal subtype specification in the cerebral cortex. Nature Reviews. Neuroscience, 8, 427–437. doi:10.1038/nrn2151.
Mortazavi, A., Williams, B. A., McCue, K., et al. (2008). Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods, 5, 621–628. doi:10.1038/nmeth.1226.
Nelson, S. B., Sugino, K., & Hempel, C. M. (2006). The problem of neuronal cell types: a physiological genomics approach. Trends in Neurosciences, 29, 339–345. doi:10.1016/j.tins.2006.05.004.
Ng, L., Bernard, A., Lau, C., et al. (2009). An anatomic gene expression atlas of the adult mouse brain. Nature Neuroscience, 12, 356–362. doi:10.1038/nn.2281.
Thompson, C. L., Pathak, S. D., Jeromin, A., et al. (2008). Genomic anatomy of the hippocampus. Neuron, 60, 1010–1021. doi:10.1016/j.neuron.2008.12.008.
Tole, S., Christian, C., & Grove, E. A. (1997). Early specification and autonomous development of cortical fields in the mouse hippocampus. Development, 124, 4959–4970.
Tsien, J., Li, M., Osan, R., et al. (2013). On initial brain activity mapping of episodic and semantic memory code in the hippocampus. Neurobiology of Learning and Memory, 105, 200–210. doi:10.1016/j.nlm.2013.06.019.On.
Winden, K. D., Oldham, M. C., Mirnics, K., et al. (2009). The organization of the transcriptional network in specific neuronal classes. Molecular Systems Biology, 5, 1–18. doi:10.1038/msb.2009.46.
Woodhams, P., Celio, M., Ulfig, N., & Witter, M. (1993). Morphological and functional correlates of borders in the entorhinal cortex and hippocampus. Hippocampus, 3, 303–312. doi:10.1002/hipo.1993.4500030733.
Zeisel, A., Manchado, A.B.M., Codeluppi, S., et al. (2015). Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science, 347(80- ), 1138–42. doi: 10.1126/science.aaa1934.
Zhao, X., Lein, E. S., He, A., et al. (2001). Transcriptional profiling reveals strict boundaries between hippocampal subregions. The Journal of Comparative Neurology, 441, 187–196. doi:10.1002/cne.1406.
Acknowledgements
T. Liu is supported by NIH R01 DA-033393, NSF CAREER Award IIS-1149260, NIH R01 AG-042599, NSF BME-1302089, NSF BCS-1439051 and NSF DBI-1564736.
Author information
Authors and Affiliations
Corresponding author
Additional information
Yujie Li and Hanbo Chen are Co-first Authors.
Hanchuan Peng, Joe Z. Tsien and Tianming Liu are Joint Corresponding Authors.
Electronic supplementary material
ESM 1
(DOCX 4685 kb)
Rights and permissions
About this article
Cite this article
Li, Y., Chen, H., Jiang, X. et al. Transcriptome Architecture of Adult Mouse Brain Revealed by Sparse Coding of Genome-Wide In Situ Hybridization Images. Neuroinform 15, 285–295 (2017). https://doi.org/10.1007/s12021-017-9333-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12021-017-9333-1