Analyses of a Glycine max Degradome Library Identify microRNA Targets and MicroRNAs that Trigger Secondary SiRNA Biogenesis

Plant microRNAs (miRNAs) regulate gene expression mainly by guiding cleavage of target mRNAs. In this study, a degradome library constructed from different soybean (Glycine max (L.) Merr.) tissues was deep-sequenced. 428 potential targets of small interfering RNAs and 25 novel miRNA families were identified. A total of 211 potential miRNA targets, including 174 conserved miRNA targets and 37 soybean-specific miRNA targets, were identified. Among them, 121 targets were first discovered in soybean. The signature distribution of soybean primary miRNAs (pri-miRNAs) showed that most pri-miRNAs had the characteristic pattern of Dicer processing. The biogenesis of TAS3 small interfering RNAs (siRNAs) was conserved in soybean, and nine Auxin Response Factors were identified as TAS3 siRNA targets. Twenty-three miRNA targets produced secondary small interfering RNAs (siRNAs) in soybean. These targets were guided by five miRNAs: gma-miR393, gma-miR1508, gma-miR1510, gma-miR1514, and novel-11. Multiple targets of these secondary siRNAs were detected. These 23 miRNA targets may be the putative novel TAS genes in soybean. Global identification of miRNA targets and potential novel TAS genes will contribute to research on the functions of miRNAs in soybean.     

动物 microRNA 靶基因的筛选与鉴定研究进展

miRNA（microRNA）是一类在生物体内广泛存在的长度约22nt的小分子非编码RNA,其在转录后水平调控靶基因的表达,在生物体生长发育过程中起重要的调控作用。近年来,miRNA的功能研究越来越受到人们的重视,而miRNA功能研究的关键在于其调控靶基因的确定。miRNA主要作用于靶基因mRNA的3’UTR区的结合位点．但由于miRNA和靶基因的作用位点并不完全匹配,没有明显的规律可寻,导致应用传统方法鉴定靶基因十分困难。近年来,人们开发了各种特异的、灵敏度高的高通量miRNA靶基因筛选与鉴定方法,极大地促进了miRNA的功能研究。     

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.     

Genome‐wide identification of urinary cell‐free microRNAs for non‐invasive detection of bladder cancer

Urinary microRNAs (miRNAs) are emerging as clinically useful tool for early and non‐invasive detection of various types of cancer including bladder cancer (BCA). In this study, 205 patients with BCA and 99 healthy controls were prospectively enrolled. Expression profiles of urinary miRNAs were obtained using Affymetrix miRNA microarrays (2578 miRNAs) and candidate miRNAs further validated in independent cohorts using qRT‐PCR. Whole‐genome profiling identified 76 miRNAs with significantly different concentrations in urine of BCA compared to controls (P < 0.01). In the training and independent validation phase of the study, miR‐31‐5p, miR‐93‐5p and miR‐191‐5p were confirmed to have significantly higher levels in urine of patients with BCA in comparison with controls (P < 0.01). We further established 2‐miRNA‐based urinary DxScore (miR‐93‐5p, miR‐31‐5p) enabling sensitive BCA detection with AUC being 0.84 and 0.81 in the training and validation phase, respectively. Moreover, DxScore significantly differed in the various histopathological subgroups of BCA and decreased post‐operatively. In conclusion, we identified and independently validated cell‐free urinary miRNAs as promising biomarkers enabling non‐invasive detection of BCA.