Distinct neurogenomic states in basal ganglia subregions relate differently to singing behavior in songbirds.
Distinct neurogenomic states in basal ganglia subregions relate differently to singing behavior in songbirds.
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DOI：
10.1371/journal.pcbi.1002773
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发表时间：
2012
影响因子：
4.3
通讯作者：
White SA
中科院分区：
文献类型：
--
作者：
Hilliard AT;Miller JE;Horvath S;White SA
鸟类和哺乳动物的基底神经节都参与自主运动控制。在鸟类中，这些动作包括跳跃、栖息和飞行。区分鸣禽基底神经节的两个组织特征是纹状体和苍白质神经元是混合在一起的，并且专门用于声音-运动功能的神经元聚集在一个密集的细胞群中，称为X区，位于周围的纹状体-苍白质中。该规范允许我们对两个纹状体-苍白质亚区进行分子分析，比较专门用于发声运动功能（X区）的组织中的转录模式与包含类似细胞类型但支持非发声行为的组织中的转录模式：纹状体-苍白质腹侧X区（VSP），这是我们在这里的重点。由于任何行为都可能是由许多分子的协调作用支撑的，因此我们从微阵列数据构建了基因共表达网络，以研究这两个亚区域的大规模转录模式。我们的目标是研究VSP网络结构与歌唱之间的任何关系，并确定在VSP而不是x区域中发现的基因共表达组或模块。我们观察到VSP模块与歌曲谱特征之间的轻微但令人惊讶的关系，并发现了一组高度特定于该区域的四个VSP模块。这些模块与唱歌无关，但由参与许多生物过程的基因组成，这些过程与我们之前在x区特定的唱歌相关模块中观察到的相同。在帕金森氏病和亨廷顿氏病中，vsp特异性模块也被富集。我们的研究结果表明，单个途径的激活/抑制不足以在功能上指定X区域与VSP，并支持分子过程本身并不专门用于行为的概念。相反，在不同的行为状态下，分子通路之间独特的相互作用在特定的大脑区域产生了功能特异性。了解基因转录与行为的关系是具有挑战性的。习得的发声运动行为是一种复杂的特征，它代表了多种趋同基因、途径和神经活动模式的输出。在这里，我们应用了系统分析的方法来确定成千上万的基因是如何同时改变他们的表达水平在脊椎动物大脑的一个区域对发声运动功能很重要，基底神经节，在一个特定的发声运动行为，唱歌。基于鸣禽的鸣叫学习/产生和语言之间的相似性，我们使用了斑胸草雀，因为它们拥有一组专门用于唱歌的大脑次区域。微阵列被用来测量一个专门歌唱的区域和一个相邻的运动区域的基因表达水平，而这个运动区域被认为在发声功能中不起作用。这使我们能够解决是否可以在每个区域找到不同的基因共表达模式的问题。我们发现每个区域都包含独特的转录协同活性模式，但也有意想不到的重叠。我们得出的结论是，这些子区域支持的特定行为（唱歌与非声音行为）取决于每个子区域中发生的分子途径之间的特定相互作用。
Both avian and mammalian basal ganglia are involved in voluntary motor control. In birds, such movements include hopping, perching and flying. Two organizational features that distinguish the songbird basal ganglia are that striatal and pallidal neurons are intermingled, and that neurons dedicated to vocal-motor function are clustered together in a dense cell group known as area X that sits within the surrounding striato-pallidum. This specification allowed us to perform molecular profiling of two striato-pallidal subregions, comparing transcriptional patterns in tissue dedicated to vocal-motor function (area X) to those in tissue that contains similar cell types but supports non-vocal behaviors: the striato-pallidum ventral to area X (VSP), our focus here. Since any behavior is likely underpinned by the coordinated actions of many molecules, we constructed gene co-expression networks from microarray data to study large-scale transcriptional patterns in both subregions. Our goal was to investigate any relationship between VSP network structure and singing and identify gene co-expression groups, or modules, found in the VSP but not area X. We observed mild, but surprising, relationships between VSP modules and song spectral features, and found a group of four VSP modules that were highly specific to the region. These modules were unrelated to singing, but were composed of genes involved in many of the same biological processes as those we previously observed in area X-specific singing-related modules. The VSP-specific modules were also enriched for processes disrupted in Parkinson's and Huntington's Diseases. Our results suggest that the activation/inhibition of a single pathway is not sufficient to functionally specify area X versus the VSP and support the notion that molecular processes are not in and of themselves specialized for behavior. Instead, unique interactions between molecular pathways create functional specificity in particular brain regions during distinct behavioral states. Understanding how gene transcription relates to behavior is challenging. Learned vocal-motor behavior is a complex trait that represents the output of multiple converging genes, pathways, and patterns of neural activity. Here, we applied a systems analytical approach to determine how thousands of genes change their expression levels simultaneously in a region of the vertebrate brain important for vocal-motor function, the basal ganglia, during a specific vocal-motor behavior, singing. We used the zebra finch species of songbird based on similarities between song learning/production and speech, and because they possess a set of brain subregions dedicated to singing. Microarrays were used to measure gene expression levels in one such song-dedicated region and in an adjacent motor area that is not thought to play a role in vocal function. This allowed us to address the question of whether distinct gene co-expression patterns could be found in each area. We found that each area contained unique patterns of transcriptional co-activity, but there were also unexpected overlaps. We conclude that the particular behaviors (singing versus non-vocal behaviors) supported by these subregions depend on the particular sets of interactions between molecular pathways that occur in each subregion.
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