microRNAs and the evolution of complex multicellularity: identification of a large,diverse complement of microRNAs in the brown alga Ectocarpus

There is currently convincing evidence that microRNAs have evolved independently in at least six different eukaryotic lineages: animals, land plants, chlorophyte green algae, demosponges, slime molds and brown algae. MicroRNAs from different lineages are not homologous but some structural features are strongly conserved across the eukaryotic tree allowing the application of stringent criteria to identify novel microRNA loci. A large set of 63 microRNA families was identified in the brown alga Ectocarpus based on mapping of RNA-seq data and nine microRNAs were confirmed by northern blotting. The Ectocarpus microRNAs are highly diverse at the sequence level with few multi-gene families, and do not tend to occur in clusters but exhibit some highly conserved structural features such as the presence of a uracil at the first residue. No homologues of Ectocarpus microRNAs were found in other stramenopile genomes indicating that they emerged late in stramenopile evolution and are perhaps specific to the brown algae. The large number of microRNA loci in Ectocarpus is consistent with the developmental complexity of many brown algal species and supports a proposed link between the emergence and expansion of microRNA regulatory systems and the evolution of complex multicellularity.     

基于microRNA共调控网络的microRNA调控机制研究

已有研究通过计算和实验的手段,证明了不同的microRNA(miRNA)通过相互之间的合作,来共同调控它们所共有的靶基因。对miRNA之间这种合作行为的特性的研究,能够帮助我们更好的理解miRNA的调控机理。本文建立了一个网络来描述miRNA之间的合作关系,并通过对该网络的分析,得出了四点关于miRNA调控机制的性质。第一,基因靶标数目越多的miRNA倾向于与越多的miRNA伙伴进行合作。第二,进化上保守的miRNA所具有的共调控伙伴的数目显著多于非保守的miRNA。第三,以上的性质是跨物种的存在的(人与小鼠)。第四,miRNA与蛋白质在系统层面性质存在一定的相似。     

microRNA target predictions across seven Drosophila species and comparison to mammalian targets

microRNAs are small noncoding genes that regulate the protein production of genes by binding to partially complementary sites in the mRNAs of targeted genes. Here, using our algorithm PicTar, we exploit cross-species comparisons to predict, on average, 54 targeted genes per microRNA above noise in Drosophila melanogaster. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. We also predict combinatorial targets for clustered microRNAs and find that some clustered microRNAs are likely to coordinately regulate target genes. Furthermore, we compare microRNA regulation between insects and vertebrates. We find that the widespread extent of gene regulation by microRNAs is comparable between flies and mammals but that certain microRNAs may function in clade-specific modes of gene regulation. One of these microRNAs (miR-210) is predicted to contribute to the regulation of fly oogenesis. We also list specific regulatory relationships that appear to be conserved between flies and mammals. Our findings provide the most extensive microRNA target predictions in Drosophila to date, suggest specific functional roles for most microRNAs, indicate the existence of coordinate gene regulation executed by clustered microRNAs, and shed light on the evolution of microRNA function across large evolutionary distances. All predictions are freely accessible at our searchable Web site http://pictar.bio.nyu.edu.     

p53直接调控microRNA及其靶基因的高通量筛选

通过对676条人microRNA进行筛选,共得到了53条新的具有p53-DNA结合位点且调控p53上游转录因子和下游靶基因的microRNA．结合已有蛋白质互作关系与microRNA调控信息,构建了p53-microRNA相互作用网络图,其中FAS受多条microRNA调控,FAS是介导细胞凋亡的关键因子,因此,FAS-microRNA的相互作用可能在细胞凋亡途径中起着关键的作用．随后,提出了microRNA参与p53调控的假设机制,认为p53调控靶基因与microRNA的同时也受上游转录因子与microRNA的调控,从而形成了以p53为中心的一种平衡,当这种调控平衡一旦被打破则会引起信号通路的紊乱,从而可能引发相应的疾病．对这53条microRNA进行靶基因预测,共得到15 500个靶基因,对这些基因的出现频率进行聚类分析共得到27个簇,将出现频率大于10的基因进行功能注释分析,发现多数基因功能属于近来发现的p53靶基因新的功能分类——细胞粘连和细胞运动,目前研究认为,p53通过与这些具有细胞粘连和运动功能的靶基因结合来抑制肿瘤的迁移．通过对15 500个基因进行功能注释分析,得到了30条感兴趣的参与细胞周期调控、细胞凋亡和细胞增殖的microRNA,其中有9条microRNA于3种生物学进程均有参与,这9条microRNA分别是: hsa-mir-181a-1、hsa-mir-181b-1、hsa-mir-181c、hsa-mir-181d、hsa-mir-195、hsa-mir-497、hsa-mir-495、hsa-mir-543和hsa-mir-548c．这暗示着这9条microRNA在p53信号通路的调节中可能起着关键的作用,它们互相作用共同调节着多个p53信号环路．最后在36个物种的基因组中对这30条microRNA进行了同源性搜索与保守性分析,结果发现有10条高度保守的且为目前数据库所未收录的microRNA．这10条microRNA分别是：hsa-mir-497、hsa-mir-495、hsa-mir-543、hsa-mir-19a、hsa-mir-19b-1、hsa-mir-200b、hsa-mir-448、 hsa-mir-28、hsa-mir-455和hsa-mir-590．     

Computational identification of microRNA targets

Recent experiments have shown that the genomes of organisms such as worm, fly, human, and mouse encode hundreds of microRNA genes. Many of these microRNAs are thought to regulate the translational expression of other genes by binding to partially complementary sites in messenger RNAs. Phenotypic and expression analysis suggests an important role of microRNAs during development. Therefore, it is of fundamental importance to identify microRNA targets. However, no experimental or computational high-throughput method for target site identification in animals has been published yet. Our main result is a new computational method that is designed to identify microRNA target sites. This method recovers with high specificity known microRNA target sites that have previously been defined experimentally. Based on these results, we present a simple model for the mechanism of microRNA target site recognition. Our model incorporates both kinetic and thermodynamic components of target recognition. When we applied our method to a set of 74 Drosophila melanogaster microRNAs, searching 3'UTR sequences of a predefined set of fly mRNAs for target sites which were evolutionary conserved between D. melanogaster and Drosophila pseudoobscura, we found that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.     

MicroRNA enrichment among short 'ultraconserved' sequences in insects

MicroRNAs are short (approximately 22 nt) regulatory RNA molecules that play key roles in metazoan development and have been implicated in human disease. First discovered in Caenorhabditis elegans, over 2500 microRNAs have been isolated in metazoans and plants; it has been estimated that there may be more than a thousand microRNA genes in the human genome alone. Motivated by the experimental observation of strong conservation of the microRNA let-7 among nearly all metazoans, we developed a novel methodology to characterize the class of such strongly conserved sequences: we identified a non-redundant set of all sequences 20 to 29 bases in length that are shared among three insects: fly, bee and mosquito. Among the few hundred sequences greater than 20 bases in length are close to 40% of the 78 confirmed fly microRNAs, along with other non-coding RNAs and coding sequence.     

An analysis of human microRNA and disease associations

It has been reported that increasingly microRNAs are associated with diseases. However, the patterns among the microRNA-disease associations remain largely unclear. In this study, in order to dissect the patterns of microRNA-disease associations, we performed a comprehensive analysis to the human microRNA-disease association data, which is manually collected from publications. We built a human microRNA associated disease network. Interestingly, microRNAs tend to show similar or different dysfunctional evidences for the similar or different disease clusters, respectively. A negative correlation between the tissue-specificity of a microRNA and the number of diseases it associated was uncovered. Furthermore, we observed an association between microRNA conservation and disease. Finally, we uncovered that microRNAs associated with the same disease tend to emerge as predefined microRNA groups. These findings can not only provide help in understanding the associations between microRNAs and human diseases but also suggest a new way to identify novel disease-associated microRNAs.     

Developmental biology: micromanaging muscle growth

Much remains to be learnt about the in vivo function of specific microRNAs. Recently, the conserved microRNA miR-1 has been found to be essential for Drosophila development. miR-1 mutants die during the rapid larval growth phase with severe muscle defects.