Computational identification of novel microRNAs and targets in Brassica napus

MicroRNAs (miRNAs) are a newly discovered class of non-protein-coding small RNAs with roughly 22 nucleotide-long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation and apoptosis and stress responses. In this research, several approaches were combined to make computational prediction of potential miRNAs and their targets in Brassica napus. We used previously known miRNAs from Arabidopsis, rice and other plant species against both expressed sequence tags (EST) and genomic survey sequence (GSS) databases to search for potential miRNAs in B. napus. A total of 21 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database and found 67 potential targets in this species. According to the mRNA target information provided by NCBI (http://www.ncbi.nlm.nih.gov/), most of the target mRNAs appeared to be involved in plant growth, development and stress responses. To validate the prediction of miRNAs in B. napus, we performed a RT-PCR based assay of mature miRNA expression. Five miRNAs were identified in response to auxin, cadmium stress and phosphate starvation. So far, little is known about experimental or computational identification of miRNA in B. napus species. To improve efficiency for blast search, we developed an implementation (miRNAassist) that can identify homologs of miRNAs and their targets, with high sensitivity and specificity. The program is allowed to be run on Windows Operation System platform. miRNAassist is freely available if required.     

Data mining for miRNAs and their targets in the Triticeae.

MicroRNAs (miRNAs) and the mRNA targets of miRNAs were identified by sequence complementarity within a DNA sequence database for species of the Triticeae. Data screening identified 28 miRNA precursor sequences from 15 miRNA families that contained conserved mature miRNA sequences within predicted stem-loop structures. In addition, the identification of 337 target sequences among Triticeae genes provided further evidence of the existence of 26 miRNA families in the cereals. MicroRNA targets included genes that are homologous to known targets in diverse model species as well as novel targets. MicroRNA precursors and targets were identified in 10 related species, though the great majority of them were identified in bread wheat, Triticum aestivum, and barley, Hordeum vulgare, the two species with the largest EST data sets among the Triticeae.     

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.     

Computational identification of miRNAs in medicinal plant Senecio vulgaris (Groundsel)

RNAs Interference plays a very important role in gene silencing. In vitro identification of miRNAs is a slow process as it is difficult to isolate them. Nucleotide sequences of miRNAs are highly conserved among the plants and, this form the key feature behind the identification of miRNAs in plant species by homology alignment. In silico identification of miRNAs from EST database is emerging as a novel, faster and reliable approach. Here EST sequences of Senecio vulgaris (Groundsel) were searched against known miRNA sequences by using BLASTN tool. A total of 10 miRNAs were identified from 1956 EST sequences and 115 GSS sequences. The most stable miRNA identified is svu-mir-1. This approach will accelerate advance research in regulation of gene expression in Groundsel by interfering RNAs.     

Genome-wide profiling of novel and conserved <Emphasis Type="Italic">Populus</Emphasis> microRNAs involved in pathogen stress response by deep sequencing

MicroRNAs (miRNAs) are small RNAs, generally of 20–23 nt, that down-regulate target gene expression during development, differentiation, growth, and metabolism. In Populus, extensive studies of miRNAs involved in cold, heat, dehydration, salinity, and mechanical stresses have been performed; however, there are few reports profiling the miRNA expression patterns during pathogen stress. We obtained almost 38 million raw reads through Solexa sequencing of two libraries from Populus inoculated and uninoculated with canker disease pathogen. Sequence analyses identified 74 conserved miRNA sequences belonging to 37 miRNA families from 154 loci in the Populus genome and 27 novel miRNA sequences from 35 loci, including their complementary miRNA* strands. Intriguingly, the miRNA* of three conserved miRNAs were more abundant than their corresponding miRNAs. The overall expression levels of conserved miRNAs increased when subjected to pathogen stress, and expression levels of 33 miRNA sequences markedly changed. The expression trends determined by sequencing and by qRT-PCR were similar. Finally, nine target genes for three conserved miRNAs and 63 target genes for novel miRNAs were predicted using computational analysis, and their functions were annotated. Deep sequencing provides an opportunity to identify pathogen-regulated miRNAs in trees, which will help in understanding the regulatory mechanisms of plant defense responses during pathogen infection.     

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。     

Computational identification of novel family members of microRNA genes in Arabidopsis thaliana and Oryza sativa

MicroRNAs (miRNAs) are a class of endogenous small RNAs that play important regulatory roles in both animals and plants, miRNA genes have been intensively studied in animals, but not in plants. In this study, we adopted a homology search approach to identify homologs of previously validated plant miRNAs in Arabidopsis thaliana and Oryza sativa. We identified 20 potential miRNA genes in Arabidopsis and 40 in O. sativa, providing a relatively complete enumeration of family members for these miRNAs in plants. In addition, a greater number of Arabidopsis miRNAs (MIR168, MIR159 and MIR172) were found to be conserved in rice. With the novel homologs, most of the miRNAs have closely related fellow miRNAs and the number of paralogs varies in the different miRNA families. Moreover, a probable functional segment highly conserved on the elongated stem of pre-miRNA fold-backs of MIR319 and MIR159 family was identified. These results support a model of variegated miRNA regulation in plants, in which miRNAs with different functional elements on their pre-miRNA fold-backs can differ in their function or regulation, and closely related miRNAs can be diverse in their specificity or competence to downregulate target genes. It appears that the sophisticated regulation of miRNAs can achieve complex biological effects through qualitative and quantitative modulation of gene expression profiles 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.     

红花microRNAs靶基因的生物信息学预测

miRNA是一类动、植物细胞中负责转录后调控的非编码RNA,植物的miRNA通常来源于具有茎环结构的单链RNA前体上,加工成熟后同ARGONAUTE转变成蛋白复合体结构,通过结合并沉默蛋白合成模板的方式关闭完整的基因表达网络。由于miRNA存在组织表达的特异性,且miRNA在植物中的表达高度保守。通过高通量测序获得的红花(Carthamus tinctorious L.)miRNA序列信息与红花转录EST数据库比对,通过靶基因预测筛选,对属于104个家族的173个红花miRNA进行预测,其中得到109个miRNAs对应调控的385个红花靶基因。并且通过Nr基因注释表明多数红花miRNA的靶基因编码包括调控细胞生长发育、信号转导及新陈代谢等相关的功能蛋白。