MicroRNA analysis in model species based on evolutionary rates

MicroRNAs (miRNAs) are major post-transcriptional regulators of gene expression. In an attempt to gain insights into miRNAs at the macroevolutionary level, we performed a systematic analysis of miRNAs in six model organisms based on their evolutionary rates. First, we calculated their miRNA evolutio...

Full description

Saved in:
Bibliographic Details
Published inGenetics and molecular research Vol. 15; no. 1
Main Authors Mao, X F, Cao, Y C
Format Journal Article
LanguageEnglish
Published Brazil 28.03.2016
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:MicroRNAs (miRNAs) are major post-transcriptional regulators of gene expression. In an attempt to gain insights into miRNAs at the macroevolutionary level, we performed a systematic analysis of miRNAs in six model organisms based on their evolutionary rates. First, we calculated their miRNA evolutionary rates, and found that they did not correlate with the complexity of the organisms. A correlation between evolutionary rates and single nucleotide polymorphisms (SNPs) in the miRNA sequence suggested that slow-evolving miRNAs in humans tolerate more SNPs than miRNAs with similar evolutionary rates in other species. However, fast-evolving miRNAs had lower SNP densities in humans than in the fruit fly. We also found that evolutionary rates were correlated with the proportion of parasite or clustered miRNAs. This correlation exhibited a different pattern in zebrafish, which may be related to significant genome duplication in the early vertebrates. The minimized free energy of the miRNA stem-loop structure was not correlated with the evolutionary rates of any species in our analysis. After evaluating relative miRNA expression levels, we observed that newly emerged miRNAs in complex species would integrate into the gene network at a faster pace and be functionally important; therefore, miRNAs may have accelerated human evolution.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1676-5680
1676-5680
DOI:10.4238/gmr.15017216