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通过全基因组原位杂交图像的稀疏编码揭示成年小鼠大脑的转录组结构

Transcriptome Architecture of Adult Mouse Brain Revealed by Sparse Coding of Genome-Wide In Situ Hybridization Images.

作者信息

Li Yujie, Chen Hanbo, Jiang Xi, Li Xiang, Lv Jinglei, Li Meng, Peng Hanchuan, Tsien Joe Z, Liu Tianming

机构信息

Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA.

School of Automation, Northwestern Polytechnical University, Xi'an, China.

出版信息

Neuroinformatics. 2017 Jul;15(3):285-295. doi: 10.1007/s12021-017-9333-1.

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.

摘要

具有明显不同表型的高度分化的脑结构与基因表达模式的独特组合密切相关。利用艾伦小鼠脑图谱发布的全基因组原位杂交图像数据集,我们提出了一种数据驱动的字典学习和稀疏编码方法。我们的结果表明,稀疏编码可以阐明小鼠脑转录组组织的模式。从稀疏编码中获得的一组成分显示出与包括纤维束和脑室系统在内的典型神经解剖细分相对应的强大的区域特异性分子特征。其他成分揭示了先前被认为是均匀的区域更精细的解剖学划分。我们还建立了一个开放获取的信息学门户,其中包含每个成分的详细信息及其本体和表达基因。这个门户允许对小鼠脑转录组结构进行直观的可视化、解释和探索。

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本文引用的文献

1
Optimization of large-scale mouse brain connectome via joint evaluation of DTI and neuron tracing data.
Neuroimage. 2015 Jul 15;115:202-13. doi: 10.1016/j.neuroimage.2015.04.050. Epub 2015 May 4.
2
Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq.
Science. 2015 Mar 6;347(6226):1138-42. doi: 10.1126/science.aaa1934. Epub 2015 Feb 19.
3
Sparse representation of whole-brain fMRI signals for identification of functional networks.
Med Image Anal. 2015 Feb;20(1):112-34. doi: 10.1016/j.media.2014.10.011. Epub 2014 Nov 8.
4
On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus.
Neurobiol Learn Mem. 2013 Oct;105:200-10. doi: 10.1016/j.nlm.2013.06.019. Epub 2013 Jul 6.
5
Transcriptional architecture of the primate neocortex.
Neuron. 2012 Mar 22;73(6):1083-99. doi: 10.1016/j.neuron.2012.03.002. Epub 2012 Mar 21.
6
A transcriptomic atlas of mouse neocortical layers.
Neuron. 2011 Aug 25;71(4):605-16. doi: 10.1016/j.neuron.2011.06.039.
7
Areal and laminar differentiation in the mouse neocortex using large scale gene expression data.
Methods. 2010 Feb;50(2):113-21. doi: 10.1016/j.ymeth.2009.09.005. Epub 2009 Sep 30.
8
Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy.
Methods. 2010 Feb;50(2):105-12. doi: 10.1016/j.ymeth.2009.09.001. Epub 2009 Sep 3.
9
The organization of the transcriptional network in specific neuronal classes.
Mol Syst Biol. 2009;5:291. doi: 10.1038/msb.2009.46. Epub 2009 Jul 28.
10
An anatomic gene expression atlas of the adult mouse brain.
Nat Neurosci. 2009 Mar;12(3):356-62. doi: 10.1038/nn.2281. Epub 2009 Feb 15.

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