Genome-wide identification and characterization of novel microRNAs in seed development of soybean

MicroRNAs (miRNAs) are important and ubiquitous regulators of gene expression in eukaryotes. However, the information about miRNAs population and their regulatory functions involving in soybean seed development remains incomplete. Base on the Dicer-like1-mediated cleavage signals during miRNA processing could be employed for novel miRNA discovery, a genome-wide search for miRNA candidates involved in seed development was carried out. As a result, 17 novel miRNAs, 14 isoforms of miRNA (isomiRs) and 31 previously validated miRNAs were discovered. These novel miRNAs and isomiRs represented tissue-specific expression and the isomiRs showed significantly higher abundance than that of their miRNA counterparts in different tissues. After target prediction and degradome sequencing data-based validation, 13 novel miRNA–target pairs were further identified. Besides, five targets of 22-nt iso-gma-miR393h were found to be triggered to produce secondary trans-acting siRNA (ta-siRNAs). Summarily, our results could expand the repertoire of miRNAs with potentially important functions in soybean.     

Detection and evolutionary analysis of soybean miRNAs responsive to soybean mosaic virus

MicroRNAs (miRNA) are a class of non-coding RNAs that have important gene regulatory roles in various organisms. However, the miRNAs involved in soybean’s response to soybean mosaic virus (SMV) are unknown. To identify novel miRNAs and biotic-stress regulated small RNAs that are involved in soybean’s response to SMV, two small RNA libraries were constructed from mock-inoculated and SMV-infected soybean leaves and sequenced. This led to the discovery of 179 miRNAs, representing 52 families, among which five miRNAs belonging to three families were novel miRNAs in soybean. A large proportion (71.5 %) of miRNAs arose from segmental duplication, similar to the process that drives the evolution of protein-coding genes. In addition, we predicted 346 potential targets of these identified miRNAs, and verified 12 targets by modified 5′-RACE analysis. Finally, three miRNAs (miR160, miR393 and miR1510) that are involved in plant resistance were observed to respond to SMV infection. The interaction between miRNAs and resistance-related genes provides a novel mechanism for pathogens to evade host recognition.     

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.     

Joint Genome-Wide Profiling of miRNA and mRNA Expression in Alzheimer's Disease Cortex Reveals Altered miRNA Regulation

Although microRNAs are being extensively studied for their involvement in cancer and development, little is known about their roles in Alzheimer''s disease (AD). In this study, we used microarrays for the first joint profiling and analysis of miRNAs and mRNAs expression in brain cortex from AD and age-matched control subjects. These data provided the unique opportunity to study the relationship between miRNA and mRNA expression in normal and AD brains. Using a non-parametric analysis, we showed that the levels of many miRNAs can be either positively or negatively correlated with those of their target mRNAs. Comparative analysis with independent cancer datasets showed that such miRNA-mRNA expression correlations are not static, but rather context-dependent. Subsequently, we identified a large set of miRNA-mRNA associations that are changed in AD versus control, highlighting AD-specific changes in the miRNA regulatory system. Our results demonstrate a robust relationship between the levels of miRNAs and those of their targets in the brain. This has implications in the study of the molecular pathology of AD, as well as miRNA biology in general.     

星形细胞瘤生存预后相关miRNA-mRNA调控关系对筛选

利用GEO数据库中的芯片数据,筛选与星形细胞瘤生存预后相关的miRNA-mRNA调控关系对,为后续研究提供理论支持.下载芯片数据利用R语言进行差异表达分析,得到星形细胞瘤较正常组织表达显著改变的miRNA与mRNA;通过miRNA靶基因预测,将靶基因与差异表达mRNA取交集,明确mRNA与miRNA之间的关系;利用GE...     

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.     

SeqTar: an effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants

In plants, microRNAs (miRNAs) regulate their mRNA targets by precisely guiding cleavages between the 10th and 11th nucleotides in the complementary regions. High-throughput sequencing-based methods, such as PARE or degradome profiling coupled with a computational analysis of the sequencing data, have recently been developed for identifying miRNA targets on a genome-wide scale. The existing algorithms limit the number of mismatches between a miRNA and its targets and strictly do not allow a mismatch or G:U Wobble pair at the position 10 or 11. However, evidences from recent studies suggest that cleavable targets with more mismatches exist indicating that a relaxed criterion can find additional miRNA targets. In order to identify targets including the ones with weak complementarities from degradome data, we developed a computational method called SeqTar that allows more mismatches and critically mismatch or G:U pair at the position 10 or 11. Precisely, two statistics were introduced in SeqTar, one to measure the alignment between miRNA and its target and the other to quantify the abundance of reads at the center of the miRNA complementary site. By applying SeqTar to publicly available degradome data sets from Arabidopsis and rice, we identified a substantial number of novel targets for conserved and non-conserved miRNAs in addition to the reported ones. Furthermore, using RLM 5'-RACE assay, we experimentally verified 12 of the novel miRNA targets (6 each in Arabidopsis and rice), of which some have more than 4 mismatches and have mismatches or G:U pairs at the position 10 or 11 in the miRNA complementary sites. Thus, SeqTar is an effective method for identifying miRNA targets in plants using degradome data sets.