Inferring the evolutionary history of primate microRNA binding sites: overcoming motif counting biases.
The first microRNAs (miRNAs) were identified as essential, conserved regulators of gene expression, targeting the same genes across nearly all bilaterians. However, there are also prominent examples of conserved miRNAs whose functions appear to have shifted dramatically, sometimes over very brief periods of evolutionary time. To determine whether the functions of conserved miRNAs are stable or dynamic over evolutionary time scales, we have here defined the neutral turnover rates of short sequence motifs in predicted primate 3'-UTRs. We find that commonly used approaches to quantify motif turnover rates, which use a presence/absence scoring in extant lineages to infer ancestral states, are inherently biased to infer the accumulation of new motifs, leading to the false inference of continually increasing regulatory complexity over time. Using a maximum likelihood approach to reconstruct individual ancestral nucleotides, we observe that binding sites of conserved miRNAs in fact have roughly equal numbers of gain and loss events relative to ancestral states and turnover extremely slowly relative to nearly identical permutations of the same motif. Contrary to case studies showing examples of functional turnover, our systematic study of miRNA binding sites suggests that in primates, the regulatory roles of conserved miRNAs are strongly conserved. Our revised methodology may be used to quantify the mechanism by which regulatory networks evolve.
Program in Bioinformatics & Integrative Biology, University of Massachusetts Medical SchoolDepartment of Neurology, University of Massachusetts Medical SchoolSwiss Institute of Bioinformatics (SIB), Lausanne, Switzerland alfred.simkin@umassmed.edu.
Alfred T
AT
Simkin
Program in Bioinformatics & Integrative Biology, University of Massachusetts Medical School.
Jeffrey A
JA
Bailey
Department of Neurology, University of Massachusetts Medical School.
Fen-Biao
FB
Gao
Swiss Institute of Bioinformatics (SIB), Lausanne, SwitzerlandEcole Polytechnique Federale de Lausanne (EPFL), School of Life Sciences, Lausanne, Switzerland.
Jeffrey D
JD
Jensen
D020413:3' Untranslated Regions; D000818:Animals; D001483:Base Sequence; D001665:Binding Sites; D017124:Conserved Sequence; D019143:Evolution, Molecular; D006801:Humans; D016013:Likelihood Functions; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism*; D010802:Phylogeny; D011323:Primates / Q000235:genetics*; D012641:Selection, Genetic
D020413:3' Untranslated Regions; D035683:MicroRNAs
miRNA evolution; molecular evolution; molecular phylogeny; motif turnover; parsimony; regulatory network