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Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

机译:人类X染色体失活模式分布比完全随机选择模型更适合遗传影响的选择模型

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摘要

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice.
机译:在真热的哺乳动物中,每个XX体细胞中的一个X染色体通过X染色体失活(XCI)过程被转录沉默。因此,雌性是功能性嵌合体,其中一些细胞表达来自父系X的基因,其他细胞表达来自母体X的基因。两个细胞群体的相对丰度(X灭活模式,XIP)可能对某些雌性具有重要的医学意义。在小鼠中,在早期胚胎的每个细胞中,无论是母本还是父本,X都失活的“选择”受到了遗传影响。在人类中,XCI选择的时机以及选择是完全随机发生还是在遗传影响下进行的辩论。在这里,我们通过分析XIPs在大量正常女性中的分布来探讨这些问题。生成模型以预测完全随机或遗传影响的选择所导致的XIP分布。每个模型都描述了XCI出现时的离散一次分布,以及连续的二次分布,这些分布说明了由于开发和老化而导致的XIP的变化。统计方法用于将模型与丹麦和犹他州人口的经验数据进行比较。严格的数据处理策略可最大化信息内容,并允许无阶段使用XIP数据。 Anderson-Darling拟合优度统计数据和似然比检验表明,受基因影响的XCI选择模型比完全随机选择模型更适合经验数据。

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