Conserved microRNA targeting reveals preexisting gene dosage sensitivities that shaped amniote sex chromosome evolution
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Genome Res.-2018-Naqvi-474-83.pdf
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3.53 MB
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Author(s)
Bellott, Daniel W.
Naqvi, Sahin
Lin, Kathy S.
Page, David C
Date Issued
February 2018
Journal
Genome Research
Publisher
Cold Spring Harbor Laboratory Press
Citation
Naqvi, Sahin et al. “Conserved microRNA Targeting Reveals Preexisting Gene Dosage Sensitivities That Shaped Amniote Sex Chromosome Evolution.” Genome Research 28, 4 (February 2018): 474–483 © 2018 Naqvi et al
Version
Final published version
Abstract
Mammalian X and Y Chromosomes evolved from an ordinary autosomal pair. Genetic decay of the Y led to X Chromosome inactivation (XCI) in females, but some Y-linked genes were retained during the course of sex chromosome evolution, and many X-linked genes did not become subject to XCI. We reconstructed gene-by-gene dosage sensitivities on the ancestral autosomes through phylogenetic analysis of microRNA (miRNA) target sites and compared these preexisting characteristics to the current status of Y-linked and X-linked genes in mammals. Preexisting heterogeneities in dosage sensitivity, manifesting as differences in the extent of miRNA-mediated repression, predicted either the retention of a Y homolog or the acquisition of XCI following Y gene decay. Analogous heterogeneities among avian Z-linked genes predicted either the retention of a W homolog or gene-specific dosage compensation following W gene decay. Genome-wide analyses of human copy number variation indicate that these heterogeneities consisted of sensitivity to both increases and decreases in dosage. We propose a model of XY/ZW evolution incorporating such preexisting dosage sensitivities in determining the evolutionary fates of individual genes. Our findings thus provide a more complete view of the role of dosage sensitivity in shaping the mammalian and avian sex chromosomes and reveal an important role for post-transcriptional regulatory sequences (miRNA target sites) in sex chromosome evolution.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1101/gr.230433.117
