Genome-wide impact of a recently expanded microRNA cluster in mouse
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Zheng-2011-Genome-wide impact o.pdf
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Author(s)
Zheng, Grace X. Y.
Ravi, Arvind
Gould, Genevieve Michelle
Burge, Christopher B.
Sharp, Phillip A.
Date Issued
September 2011
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
National Academy of Sciences (U.S.)
Citation
Zheng, G. X. Y. et al. “Genome-wide Impact of a Recently Expanded microRNA Cluster in Mouse.” Proceedings of the National Academy of Sciences 108.38 (2011): 15804–15809. Web. ©2011 by the National Academy of Sciences.
Version
Final published version
Abstract
Variations in microRNA (miRNA) gene and/or target repertoire are likely to be key drivers of phenotypic differences between species. To better understand these changes, we developed a computational method that identifies signatures of species-specific target site gain and loss associated with miRNA acquisition. Interestingly, several of the miRNAs implicated in mouse 3′ UTR evolution derive from a single rapidly expanded rodent-specific miRNA cluster. Located in the intron of Sfmbt2, a maternally imprinted polycomb gene, these miRNAs (referred to as the Sfmbt2 cluster) are expressed in both embryonic stem cells and the placenta. One abundant miRNA from the cluster, miR-467a, functionally overlaps with the mir-290-295 cluster in promoting growth and survival of mouse embryonic stem cells. Predicted novel targets of the remaining cluster members are enriched in pathways regulating cell survival. Two relevant species-specific target candidates, Lats2 and Dedd2, were validated in cultured cells. We suggest that the rapid evolution of the Sfmbt2 cluster may be a result of intersex conflict for growth regulation in early mammalian development and could provide a general model for the genomic response to acquisition of miRNAs and similar regulatory factors.
MIT Department
Whitaker College of Health Sciences and Technology
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1073/pnas.1112772108
