Department of Information Engineering, University of Parma, Parma, Italy.
PLoS One. 2013 Sep 9;8(9):e74481. doi: 10.1371/journal.pone.0074481. eCollection 2013.
RNA molecules specifically enriched in the neuropil of neuronal cells and in particular in dendritic spines are of great interest for neurobiology in virtue of their involvement in synaptic structure and plasticity. The systematic recognition of such molecules is therefore a very important task. High resolution images of RNA in situ hybridization experiments contained in the Allen Brain Atlas (ABA) represent a very rich resource to identify them and have been so far exploited for this task through human-expert analysis. However, software tools that may automatically address the same objective are not very well developed.
In this study we describe an automatic method for exploring in situ hybridization data and discover neuropil-enriched RNAs in the mouse hippocampus. We called it Hippo-ATESC (Automatic Texture Extraction from the Hippocampal region using Soft Computing). Bioinformatic validation showed that the Hippo-ATESC is very efficient in the recognition of RNAs which are manually identified by expert curators as neuropil-enriched on the same image series. Moreover, we show that our method can also highlight genes revealed by microdissection-based methods but missed by human visual inspection. We experimentally validated our approach by identifying a non-coding transcript enriched in mouse synaptosomes. The code is freely available on the web at http://ibislab.ce.unipr.it/software/hippo/.
神经元细胞的神经突，尤其是树突棘中特异性富集的 RNA 分子，因其参与突触结构和可塑性而引起神经生物学的极大兴趣。因此，系统地识别这些分子是一项非常重要的任务。Allen 大脑图谱 (ABA) 中包含的 RNA 原位杂交实验的高分辨率图像是识别这些分子的非常丰富的资源，迄今为止，这些图像已通过人工专家分析得到了充分利用。然而，能够自动实现这一目标的软件工具还不是很完善。
在这项研究中，我们描述了一种自动探索原位杂交数据并在小鼠海马体中发现神经突富集 RNA 的方法。我们称之为 Hippo-ATESC（使用软计算从海马区自动提取纹理）。生物信息学验证表明，Hippo-ATESC 在识别专家策展人在同一图像系列中手动识别为神经突富集的 RNA 方面非常有效。此外，我们还表明，我们的方法还可以突出基于微切割方法揭示但被人工视觉检查遗漏的基因。我们通过鉴定在小鼠突触体中富集的非编码转录本来验证我们的方法。该代码可在 http://ibislab.ce.unipr.it/software/hippo/ 上免费获得。
