Evolutionary patterns of metazoan microRNAs reveal targeting principles in the let-7 and miR-10 families
- Justin M. Wolter1,2,3,
- Hoai Huang Thi Le3,
- Alexander Linse3,
- Victoria A. Godlove2,
- Thuy-Duyen Nguyen3,4,
- Kasuen Kotagama1,2,3,
- Alissa Lynch1,3,
- Alan Rawls3 and
- Marco Mangone2,3
- 1Molecular and Cellular Biology Graduate Program, Arizona State University, Tempe, Arizona 85287, USA;
- 2Virginia G. Piper Center For Personalized Diagnostics, The Biodesign Institute at Arizona State University, Tempe, Arizona 85287, USA;
- 3School of Life Sciences, Arizona State University, Tempe, Arizona 85287, USA;
- 4Barrett Honors College, Arizona State University, Tempe, Arizona 85287, USA
- Corresponding author: mangone{at}asu.edu
Abstract
MicroRNAs (miRNAs) regulate gene output by targeting degenerate elements in mRNAs and have undergone drastic expansions in higher metazoan genomes. The evolutionary advantage of maintaining copies of highly similar miRNAs is not well understood, nor is it clear what unique functions, if any, miRNA family members possess. Here, we study evolutionary patterns of metazoan miRNAs, focusing on the targeting preferences of the let-7 and miR-10 families. These studies reveal hotspots for sequence evolution with implications for targeting and secondary structure. High-throughput screening for functional targets reveals that each miRNA represses sites with distinct features and regulates a large number of genes with cooperative function in regulatory networks. Unexpectedly, given the high degree of similarity, single-nucleotide changes grant miRNA family members with distinct targeting preferences. Together, our data suggest complex functional relationships among miRNA duplications, novel expression patterns, sequence change, and the acquisition of new targets.
Footnotes
-
[Supplemental material is available for this article.]
-
Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.209361.116.
-
Freely available online through the Genome Research Open Access option.
- Received May 3, 2016.
- Accepted October 27, 2016.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
