降解组测序技术在植物miRNA研究中的应用

目前, 利用芯片技术和miRNA测序可快速、准确地检测到物种中所含有的miRNA。随着越来越多的miRNA被发现, miRNA靶基因的确定已成为研究miRNA生物学功能的关键。传统的miRNA靶基因的寻找主要依赖生物信息学预测、AGO蛋白免疫共沉淀和荧光素酶法等。随着高通量测序技术的持续革新, 出现了一种新的miRNA靶基因的检测方法, 即降解组测序(degradome sequencing)法, 该方法拥有高通量测序技术、生物信息学分析和RACE验证三者的优势, 并已成功应用于拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)和小立碗藓(Physcomitrella patens)等模式植物miRNA靶基因的检测。基于已发表的相关文献和联川生物降解组测序平台, 该文对降解组测序技术应用于植物miRNA靶基因的研究进展及其实验原理进行了综述, 同时对运用该技术可进行的更深入研究进行了讨论。     

Identification of miRNAs and Their Target Genes in Peach (Prunus persica L.) Using High-Throughput Sequencing and Degradome Analysis

MicroRNAs play critical roles in various biological and metabolic processes. The function of miRNAs has been widely studied in model plants such as Arabidopsis and rice. However, the number of identified miRNAs and related miRNA targets in peach (Prunus persica) is limited. To understand further the relationship between miRNAs and their target genes during tissue development in peach, a small RNA library and three degradome libraries were constructed from three tissues for deep sequencing. We identified 117 conserved miRNAs and 186 novel miRNA candidates in peach by deep sequencing and 19 conserved miRNAs and 13 novel miRNAs were further evaluated for their expression by RT-qPCR. The number of gene targets that were identified for 26 conserved miRNA families and 38 novel miRNA candidates, were 172 and 87, respectively. Some of the identified miRNA targets were abundantly represented as conserved miRNA targets in plant. However, some of them were first identified and showed important roles in peach development. Our study provides information concerning the regulatory network of miRNAs in peach and advances our understanding of miRNA functions during tissue development.     

Genome-Wide Identification of Reverse Complementary microRNA Genes in Plants

MicroRNAs (miRNAs) are ∼21-nucleotide small RNAs (sRNAs) with essential regulatory roles in plants. They are generated from stem-loop-structured precursors through two sequential Dicer-like 1 (DCL1)-mediated cleavages. To date, hundreds of plant miRNAs have been uncovered. However, the question, whether the sequences reverse complementary (RC) to the miRNA precursors could form hairpin-like structures and produce sRNA duplexes similar to the miRNA/miRNA* pairs has not been solved yet. Here, we interrogated this possibility in 16 plant species based on sRNA high-throughput sequencing data and secondary structure prediction. A total of 59 RC sequences with great potential to form stem-loop structures and generate miRNA/miRNA*-like duplexes were identified in ten plants, which were named as RC-miRNA precursors. Unlike the canonical miRNAs, only a few cleavage targets of the RC-miRNAs were identified in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), and none in Soybean (Glycine max) based on degradome data. Surprisingly, the genomic regions surrounding some of the RC-miRNA target recognition sites were observed to be specifically methylated in both Arabidopsis and rice. Taken together, we reported a new class of miRNAs, called RC-miRNAs, which were generated from the antisense strands of the miRNA precursors. Based on the results, we speculated that the mature RC-miRNAs might have subtle regulatory activity through target cleavages, but might possess short interfering RNA-like activity by guiding sequence-specific DNA methylation.     

玉米microRNAs及其靶基因的生物信息学预测

microRNAs (miRNAs) 是一类非编码的小分子RNA, 通过碱基互补调控靶基因的表达。鉴定和发现新的miRNAs及其靶基因, 对揭示miRNAs在基因表达调控中的作用至关重要。玉米全基因组测序工作开展较晚, 已经鉴定登记的miRNAs很少, 对靶基因的调控作用尚待解明。文章根据miRNA进化上的保守性, 以已知的植物miRNAs为探针, 与相关数据库中玉米表达序列标签(EST)和基因组序列(GSS)中的非编码序列比对, 共发现11个新的miRNA前体。虽然在序列长度和二级结构方面各有变化, 但这11个前体均可折叠形成miRNA家族的标准二级结构。通过靶基因预测, 找到其中7条miRNAs的26个靶基因, 分别编码与新陈代谢、信号转导、转录调节、跨膜运输、生物和非生物胁迫及叶绿体组装等相关的蛋白。这些miRNAs及其靶基因的鉴定, 补充了miRNA数据库的不足。     

Identification of novel microRNAs in rice (Oryza sativa) based on the cleavage signals in precursors

MicroRNAs (miRNAs) are crucial regulators of gene expression in plants and a growing number of novel miRNA genes have been cloned in rice in recent years. However, there is no evidence that all miRNAs have been discovered, especially for those low expression ones which are difficult to be found by conventional methods. By taking advantage of the finding that DCL1-mediated cleavage signals for the processing of the miRNA precursors could be used as the clues for novel miRNAs’ discovery, a genome-wide search for rice miRNA candidates was carried out. As a result, 51 previously validated miRNAs and 24 novel miRNA candidates were discovered. After target prediction and degradome sequencing data-based validation, coupled with reverse approach retest, 10 miRNA candidate–mRNA target pairs were further identified, providing a basis for in-depth functional analysis of these miRNA candidates. Besides, some isomiRs found in this study showed more likely to be the real miRNAs. We also found an exceptional example which did not obey the rule that 22-nt miRNAs have the ability to trigger the phased siRNAs production from the cleaved targets.     

A non-canonical plant microRNA target site

Plant microRNAs (miRNAs) typically form near-perfect duplexes with their targets and mediate mRNA cleavage. Here, we describe an unconventional miRNA target of miR398 in Arabidopsis, an mRNA encoding the blue copper-binding protein (BCBP). BCBP mRNA carries an miR398 complementary site in its 5′-untranslated region (UTR) with a bulge of six nucleotides opposite to the 5′ region of the miRNA. Despite the disruption of a target site region thought to be especially critical for function, BCBP mRNAs are cleaved by ARGONAUTE1 between nucleotides 10th and 11th, opposite to the miRNA, like conventional plant target sites. Levels of BCBP mRNAs are inversely correlated to levels of miR398 in mutants lacking the miRNA, or transgenic plants overexpressing it. Introducing two mutations that disrupt the miRNA complementarity around the cleavage site renders the target cleavage-resistant. The BCBP site functions outside of the context of the BCBP mRNA and does not depend on 5′-UTR location. Reducing the bulge does not interfere with miR398-mediated regulation and completely removing it increases the efficiency of the slicing. Analysis of degradome data and target predictions revealed that the miR398-BCBP interaction seems to be rather unique. Nevertheless, our results imply that functional target sites with non-perfect pairings in the 5′ region of an ancient conserved miRNA exist in plants.     

miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.