Landscape of X chromosome inactivation across human tissues
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Author(s)
Tukiainen, Taru
Villani, Alexandra-Chloé
Rivas, Manuel A.
Marshall, Jamie L.
Satija, Rahul
Aguirre, Matt
Gauthier, Laura
Fleharty, Mark
Kirby, Andrew
Cummings, Beryl B.
Date Issued
October 2017
Journal
Nature
Publisher
Springer Nature
Citation
Tukiainen, Taru, Alexandra-Chloé Villani, Angela Yen, Manuel A. Rivas, Jamie L. Marshall, Rahul Satija, Matt Aguirre, et al. “Landscape of X Chromosome Inactivation Across Human Tissues.” Nature 550, no. 7675 (October 11, 2017): 244–248 © 2017 Macmillan Publishers Limited, part of Springer Nature
Version
Final published version
Abstract
X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals1,2. The extent to which XCI is shared between cells and tissues remains poorly characterized3,4, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression5 and phenotypic traits6. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity6,7. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/NATURE24265
