Abstracts (first author)

Talk 

New microRNAs in Drosophila – Birth, death and immortality through cycles of evolution

Author(s): Tang T, Lyu Y, Shen Y, Li H, Zhao Y, Hungate E, Shi S, Wu C

Summary:

The evolutionary dynamics of the entire repertoire of microRNAs (miRNAs) has been debated. Disagreements were not resolved partly because new miRNA-like genes emerged constantly but few were evolutionarily or functionally significant. With an extensive search, we identify 12 new adaptive miRNAs that emerged de novo (and often in clusters) in Drosophila melanogaster in the last 4 million years (Myrs). Interestingly, even though they are adaptively evolving at birth, more than 95% of these new miRNAs disappear over time. They serve a useful function, but for only a transient evolutionary period. After 30 Myrs, all surviving miRNAs make the transition from the adaptive phase of rapid evolution to the conservative phase of slow evolution, apparently becoming integrated into the genome. During this transition, the expression shifts from being tissue-specific, predominantly in testes and imaginal discs, to a broader distribution in many other tissues. Unexpectedly, a measurable fraction (20-30%) of these conservatively evolving miRNAs experience "evolutionary reactivation" and begin rapidly evolving again. These reactivated miRNAs start another cycle of adaptive-neutral-conservative evolution that could also lead to death. In conclusion, new adaptive miRNAs go through cycles of evolution, resulting in very slow turnover. Since most new miRNAs evolve adaptively for a transient period of variable length and then disappear, the phenomenon may shed some light on the regulatory roles of miRNAs in general.



Contacts

Chairman: Octávio S. Paulo
Tel: 00 351 217500614 direct
Tel: 00 351 217500000 ext22359
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email: mail@eseb2013.com

Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

Website

Computational Biology & Population Genomics Group 
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