MicroRNAs (miRNAs) are a class of ～22 nt long endogenous non-coding RNAs that play important regulatory roles in diverse organisms. Up to now, little is known about the evolutionary properties of these crucial regulators. Most miRNAs were thought to be phylogenetically conserved, but recently, a number of poorly-conserved miRNAs have been reported and miRNA innovation is shown to be an ongoing process. In this work, through the characterization of an miRNA super family, we studied the evolutionary patterns of miRNAs in vertebrates. Recently generated miRNAs seem to evolve rapidly during a certain period following their emergence. Multiple lineage-specific expansions were observed. Homolgous premiRNAs may produce mature products from the opposite stem arms following tandem duplications, which may have important contribution to miRNA innovation. Our observations of miRNAs' complicated evolutionary patterns support the notion that these key regulatory molecules may play very active roles in evolution.
WANG XiaoWo, ZHANG XueGong & LI YanDa MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China
存在于自然群体中DNA片段的拷贝数变异(copy number variations,CNVs)是基因组结构性差异的常见形式.人们早已意识到它在人群中普遍存在,并设计出多种实验方法对其进行检测和量化.近年来,伴随着实验技术的进步,人群的CNV图谱被不断完善、细化;许多CNVs和疾病的相关性被陆续报道.对复杂疾病的CNV关联研究已成为当前医学遗传学研究的重要内容.本文将总结和关联研究有关的CNV遗传特性,分析CNV与疾病关联研究的进展与问题,并探讨实验设计和数据分析策略.
CpG island methylation plays important role in various biological processes. To investigate methylation landscape of all CpG islands on the human genome, we develop a model for predicting the CpG island methylation status. This model outperforms other existing methods. We apply the model on the whole human genome and predict the landscape of DNA methylation of all CpG islands. Based on the methylation profile, we find that about 31% of CpG islands are methylation-prone and CpG islands located in promoter regions are seldom methylated. There is no significant difference in the CpG island methylation level between R and G bands among the chromosomes. The occupancy of RNA polymerase II is significantly higher in methylation-resistant promoter CpG islands, indicating that genes with such promoter CpG islands tend to be more active.
The interaction strength between 2 proteins is not constant but variable under different conditions. For a given biological process, identification of protein-protein interactions (PPIs) undergoing dynamic change in interaction strength is highly valuable but never achieved before. In this work, we presented a computational approach to identify changed PPIs (cPPIs) on a global scale by analyzing the coexpression level of genes encoding the interacting protein pairs. This approach stemmed from the biological con-ception that the change of protein-protein interaction bore imprint at the gene coexpression level. We applied this method to identify cPPIs in cells treated with a cytokine TGFβ, as well as cPPIs in rheumatoid arthritis (RA) patients. The accuracy of identification was evaluated by comparing our results with data from the high-throughput experiment and literature mining. Our analysis demonstrated that this is a simple and effective method to infer cPPIs from a given set of PPIs or even from the whole interactome. Further analysis uncovered the biological functions of the cPPIs in RA patients, which included muscle contraction and antigen presentation. Our method could help to elucidate molecular mechanisms of dynamic biological processes.
