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微小 RNA 有助于大鼠内侧隔核层状差异和神经元亚型的出生后发育。

MicroRNAs contribute to postnatal development of laminar differences and neuronal subtypes in the rat medial entorhinal cortex.

机构信息

Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.

Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University for Science and Technology, Trondheim, Norway.

出版信息

Brain Struct Funct. 2017 Sep;222(7):3107-3126. doi: 10.1007/s00429-017-1389-z. Epub 2017 Mar 4.

Abstract

The medial entorhinal cortex (MEC) is important in spatial navigation and memory formation and its layers have distinct neuronal subtypes, connectivity, spatial properties, and disease susceptibility. As little is known about the molecular basis for the development of these laminar differences, we analyzed microRNA (miRNA) and messenger RNA (mRNA) expression differences between rat MEC layer II and layers III-VI during postnatal development. We identified layer and age-specific regulation of gene expression by miRNAs, which included processes related to neuron specialization and locomotor behavior. Further analyses by retrograde labeling and expression profiling of layer II stellate neurons and in situ hybridization revealed that the miRNA most up-regulated in layer II, miR-143, was enriched in stellate neurons, whereas the miRNA most up-regulated in deep layers, miR-219-5p, was expressed in ependymal cells, oligodendrocytes and glia. Bioinformatics analyses of predicted mRNA targets with negatively correlated expression patterns to miR-143 found that miR-143 likely regulates the Lmo4 gene, which is known to influence hippocampal-based spatial learning.

摘要

内侧隔核(MEC)在空间导航和记忆形成中很重要,其各层具有不同的神经元亚型、连接性、空间特性和疾病易感性。由于对这些层状差异发育的分子基础知之甚少,我们分析了大鼠 MEC 层 II 和 III-VI 之间在出生后发育过程中的微小 RNA(miRNA)和信使 RNA(mRNA)表达差异。我们确定了 miRNA 对基因表达的层和年龄特异性调节,其中包括与神经元特化和运动行为相关的过程。通过逆行标记和层 II 星形神经元的表达谱分析以及原位杂交进一步显示,在层 II 中上调最多的 miRNA,miR-143,在星形神经元中富集,而在深层中上调最多的 miRNA,miR-219-5p,则在室管膜细胞、少突胶质细胞和神经胶质细胞中表达。与 miR-143 表达模式呈负相关的预测 mRNA 靶标的生物信息学分析发现,miR-143 可能调节 Lmo4 基因,该基因已知会影响基于海马的空间学习。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f805/5585308/e63969f7d24e/429_2017_1389_Fig1_HTML.jpg

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