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视网膜神经元人口统计学数据的基因组控制

Reese BE, Keeley PW

期刊名称:Progress in Retinal and Eye Research

卷期:2016年第55卷

摘要

成熟的视网膜结构由各种类型的神经元组成,每种神经元大小不同,并且局限于特定层,细胞在其局部组织中表现为特征性图案。视网膜神经细胞群的这些人口统计学特征具有复杂的性状,受发育期间影响不同过程的多个基因控制,这些遗传性状可以受重组近交小鼠品系基因组结构性状相关变异影响。根据这一思路,我们正在考虑十二种不同类型的视网膜神经元的数量变化是如何彼此独立的,包括共享转录调控以及那些映射到不同的基因组位点的突触连接。使用两种视网膜中间神经元,水平细胞和胆碱能无长突细胞群,我们发现了进一步详细的例子,这些例子存在神经元数量变化,以及马赛克图案或层流定位变化,每个均映射到离散的调节这些特征的等位基因变体的基因组位点。在这些位点,我们确定了那些以及何时被赋予非功能性时特性的候选基因,改变那些特别的人口学特点,并且反过来,我们确定了编码或调解变体的候选基因,这些基因可分别改变蛋白质结构或基因表达。这种前向遗传方法提供了一种破解神经元人口学动态分子遗传控制的替代方法,每个基因位点可作为一个因果锚,从中我们可以最终了解负责控制这些性状的发育规律。

The mature retinal architecture is composed of various types of neuron, each population differing in size and constrained to particular layers, wherein the cells achieve a characteristic patterning in their local organization. These demographic features of retinal nerve cell populations are each complex traits controlled by multiple genes affecting different processes during development, and their genetic determinants can be dissected by correlating variation in these traits with their genomic architecture across recombinant-inbred mouse strains. Using such a resource, we consider how the variation in the numbers of twelve different types of retinal neuron are independent of one another, including those sharing transcriptional regulation as well as those that are synaptically-connected, each mapping to distinct genomic loci. Using the populations of two retinal interneurons, the horizontal cells and the cholinergic amacrine cells, we present in further detail examples where the variation in neuronal number, as well as the variation in mosaic patterning or in laminar positioning, each maps to discrete genomic loci where allelic variants modulating these features must be present. At those loci, we identify candidate genes which, when rendered non-functional, alter those very demographic properties, and in turn, we identify candidate coding or regulatory variants that alter protein structure or gene expression, respectively, being prospective contributors to the variation in phenotype. This forward-genetic approach provides an alternative means for dissecting the molecular genetic control of neuronal population dynamics, with each genomic locus serving as a causal anchor from which we may ultimately understand the developmental principles responsible for the control of those traits.


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