microRNA evolution in a human transcription factor and microRNA regulatory network

Background  

microRNAs (miRNAs) are important cellular components. The understanding of their evolution is of critical importance for the understanding of their function. Although some specific evolutionary rules of miRNAs have been revealed, the rules of miRNA evolution in cellular networks remain largely unexplored. According to knowledge from protein-coding genes, the investigations of gene evolution in the context of biological networks often generate valuable observations that cannot be obtained by traditional approaches.     

微小RNA起源及功能和动植物基因寻找计算方法

微小RNAs（microRNAs,miRNAs）是长度约为22个核苷酸（nt）的内源性非编码小分子RNA。miRNA作为重要的基因调节因子,通过多种机制抑制其靶mRNA的表达。miRNA的表达和／或功能异常与人类多种疾病密切相关。因此,近年miR—NA与人类疾病的相关研究备受关注,寻找miRNA基因显得尤为重要。过去对miRNA基因进行研究的范围较为局限,获得的新miRNA基因很少。目前,对miRNA基因目录的补充主要依赖于复杂计算工具的发展,随着计算工具的发展获得多种简易的寻找miRNA基因的方法,但对miRNA基因目录的补充仍未能起有效作用。本文在简单介绍动植物miRNA生物起源和功能及作用机制的基础上,主要关注动植物miRNA基因寻找的计算方法,可望为探索动植物miRNAs基因寻找的新的计算方法提供有价值的参考。     

Computational identification of microRNA gene loci and precursor microRNA sequences in CHO cell lines

MicroRNAs (miRNAs) have recently entered Chinese hamster ovary (CHO) cell culture technology, due to their severe impact on the regulation of cellular phenotypes. Applications of miRNAs that are envisioned range from biomarkers of favorable phenotypes to cell engineering targets. These applications, however, require a profound knowledge of miRNA sequences and their genomic organization, which exceeds the currently available information of ~400 conserved mature CHO miRNA sequences. Based on these recently published sequences and two independent CHO-K1 genome assemblies, this publication describes the computational identification of CHO miRNA genomic loci. Using BLAST alignment, 415 previously reported CHO miRNAs were mapped to the reference genomes, and subsequently assigned to a distinct genomic miRNA locus. Sequences of the respective precursor-miRNAs were extracted from both reference genomes, folded in silico to verify correct structures and cross-compared. In the end, 212 genomic loci and pre-miRNA sequences representing 319 expressed mature miRNAs (approximately 50% of miRNAs represented matching pairs of 5' and 3' miRNAs) were submitted to the miRBase miRNA repository. As a proof-of-principle for the usability of the published genomic loci, four likely polycistronic miRNA cluster were chosen for PCR amplification using CHO-K1 and DHFR (-) genomic DNA. Overall, these data on the genomic context of miRNA expression in CHO will simplify the development of tools employing stable overexpression or deletion of miRNAs, allow the identification of miRNA promoters and improve detection methods such as microarrays.     

Detecting microRNA activity from gene expression data

Background  

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions.