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

AI Article Synopsis

  • In eutherian mammals, X-chromosome inactivation (XCI) silences one of the two X-chromosomes in females, creating functional mosaicism where cells express genes from either the maternal or paternal X-chromosome.
  • Research explores whether the choice of which X-chromosome to inactivate is random or genetically influenced, with implications for health in females.
  • Statistical analysis of XCI patterns in populations from Denmark and Utah indicates that genetically influenced choice models fit the data better than random choice models.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3831084PMC
http://dx.doi.org/10.1038/ejhg.2013.84DOI Listing

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