title: microRNAs in the Same Clusters Evolve to Coordinately Regulate Functionally Related Genes.
abstract: MicroRNAs (miRNAs) are endogenously expressed small noncoding RNAs. The genomic locations of animal miRNAs are significantly clustered in discrete loci. We found duplication and de novo formation were important mechanisms to create miRNA clusters and the clustered miRNAs tend to be evolutionarily conserved. We proposed a "functional co-adaptation" model to explain how clustering helps newly emerged miRNAs survive and develop functions. We presented evidence that abundance of miRNAs in the same clusters were highly correlated and those miRNAs exerted cooperative repressive effects on target genes in human tissues. By transfecting miRNAs into human and fly cells and extensively profiling the transcriptome alteration with deep-sequencing, we further demonstrated the functional co-adaptation between new and old miRNAs in the miR-17-92 cluster. Our population genomic analysis suggest that positive Darwinian selection might be the driving force underlying the formation and evolution of miRNA clustering. Our model provided novel insights into mechanisms and evolutionary significance of miRNA clustering.
authors.affiliation: State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
authors.forename: Yirong
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Luo
authors.affiliation: State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China luj@pku.edu.cn.
authors.forename: Jian
authors.initials: J
authors.lastname: Lu
mesh_terms: D000818:Animals; D005075:Biological Evolution; D016000:Cluster Analysis; D017124:Conserved Sequence; D019143:Evolution, Molecular; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D005810:Multigene Family; D012641:Selection, Genetic; D017423:Sequence Analysis, RNA / Q000379:methods; D059467:Transcriptome
chemical_list: D035683:MicroRNAs
keywords: coordinated regulation; evolution; functional co-adaptation; mRNA-Seq; miR-17–92 cluster.; miRNA clusters; natural selection