A Plant MicroRNA Target Expression Database to study the microRNA (miRNA) functions by inferring their target gene expression profiles among the large amount of existing microarray data. You may also predict your miRNA targets and retrieve their microarray expression data.

A database of animal, plant and virus microRNA data maintained at the University of Poznan. The database provides: * 9980 miRNA candiates from 420 animal and plant species predicted in Expressed Sequence Tags * predicted targets for plant candidates * RNA-seq reads mapped to candidates from 29 species * external data from 12 databases that includes sequences, polymorphism, expression and regulation. miRNEST 1.0, it contains miRNA from 563 animals, plants and viruses plant species.

Additional file 2: Supplementary Table S1. Degradome/PARE-seq and small RNA-seq data used for TarDB database construction.

MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Convenient Analysis Tools (SRICATs). SRICATs encompasses all the necessary steps for plant miRNA analysis. Our results indicate that SRICATs outperforms currently popular software tools on the test data from five plant species. For non-commercial users, SRICATs is freely available at https://sourceforge.net/projects/sricats.

mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. quantitative real-time PCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. This database aims to be useful to anyone investigating the role of microRNAs in shaping plant development, organ formation and response to different biotic and abiotic stresses. To start exploring the database just press the "Browse Atlas" button or search for a particular microRNA record by typing at least two numbers from its ID in the window.

The miRBase Sequence Database -- Release 22
-------------------------------------------

1. SUMMARY

The miRBase database provides a searchable online repository for
published microRNA sequences and associated annotation. miRBase also
provides a gene naming and nomenclature function in the miRBase
Registry.

Release 22 of the database contains 38589 entries representing hairpin
precursor miRNAs, expressing 48885 mature miRNA products, in 271
species. The data are freely available to all through the web
interface at http://www.mirbase.org/ and in flatfile form from
ftp://mirbase.org/pub/mirbase/.


2. CHANGES SINCE RELEASE 21

10031 new hairpin sequences and 13149 new mature products have been
added, an increase in the number of sequences of over a third. The
first miRNAs in 48 new species are reported. 115 hairpins and 496
mature sequences have changed names; the overwhelming majority of
these changes are additions of lettered or numbered suffixes to
differentiate related loci. 87 misannotated and duplicate sequences
have been deleted. See the miRNA.diff file for the full description
of changes.

The "high confidence" microRNA dataset (as described in Kozomara and
Griffiths-Jones, NAR 2014) is available on the FTP site.


3. FILES

The following files are available from the above ftp site:

 miRNA.dat   - all entries in (almost) EMBL format
 hairpin.fa  - predicted miR stem-loop sequences in fasta format
 mature.fa   - mature sequences in fasta format
 miRNA.dead  - entries removed from the database
 miRNA.diff  - differences between the current and last release

The genomes/ directory contains gff files of genome coordinates for 152
species. See the individual files for the genome assemblies used.

The database_files/ directory contains dumps of the MySQL relational
database that is used to generate the web pages. The documentation
for this subset of files is non-existent - use at your peril!


4. LICENSE

miRBase is in the public domain. It is not copyrighted. You may
freely modify, redistribute, or use it for any purpose. See
ftp://mirbase.org/pub/mirbase/CURRENT/LICENSE for details.


5. HOW TO CITE THE miRNA DATABASE

The miRBase database is described in the following articles:

miRBase: annotating high confidence microRNAs using deep sequencing
data.
Kozomara A, Griffiths-Jones S.
Nucleic Acids Res. 2014 42:D68-D73

miRBase: integrating microRNA annotation and deep-sequencing data.
Kozomara A, Griffiths-Jones S.
Nucleic Acids Res. 2011 39:D152-D157

miRBase: tools for microRNA genomics.
Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ.
Nucleic Acids Res. 2008 36:D154-D158

miRBase: microRNA sequences, targets and gene nomenclature.
Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ.
Nucleic Acids Res. 2006 34:D140-D144

The miRNA Registry.
Griffiths-Jones S.
Nucleic Acids Res. 2004 32:D109-D111

Please cite us if you use the data we distribute, but also be sure to
cite the primary sources of miRNA sequences in your work.

Guidelines to miRNA annotation are published here:

A uniform system for microRNA annotation.
Ambros V, Bartel B, Bartel DP, Burge CB, Carrington JC, Chen X, 
Dreyfuss G, Eddy SR, Griffiths-Jones S, Marshall M, Matzke M,
Ruvkun G, Tuschl T. 
RNA 2003 9(3):277-279

Criteria for annotation of plant MicroRNAs.
Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao
X, Carrington JC, Chen X, Green PJ, Griffiths-Jones S, Jacobsen SE,
Mallory AC, Martienssen RA, Poethig RS, Qi Y, Vaucheret H, Voinnet O,
Watanabe Y, Weigel D, Zhu JK.
Plant Cell. 2008 20(12):3186-3190


6. FEEDBACK

Any queries about data, web services, naming requests or other
feedback should be directed to mirbase@manchester.ac.uk.


7. HISTORY

Version    Date    Entries

 1.0     12/02    218
 1.1     01/03    262
 1.2     04/03    295
 1.3     05/03    332
 1.4     07/03    345
 2.0     07/03    506
 2.1     09/03    558
 2.2     11/03    593
 3.0     01/04    719
 3.1     04/04    899
 4.0     07/04    1185
 5.0     09/04    1345
 5.1     12/04    1420
 6.0     04/05    1650
 7.0     06/05    2909
 7.1     10/05    3424
 8.0     02/06    3518
 8.1     05/06    3963
 8.2     07/06    4039
 9.0     10/06    4361
 9.1     02/07    4449
 9.2     05/07    4584
 10.0     08/07    5071
 10.1     12/07    5395
 11.0     04/08    6396
 12.0     09/08    8619
 13.0     03/09    9539
  14     09/09   10883
  15     04/10   14197
  16     08/10   15172
  17     04/11   16772
  18     11/11   18226
  19     08/12   21264
  20     06/13 24521
  21     06/14 28645
  22     03/18   38589

--
SGJ

*aqc = Aquilegia caerulea, csi = Citrus sinensis, vvi = Vitis vinifera, nta = Nicotiana tabacum.

MicroRNAs (miRNAs) are processed from longer precursors with fold-back structures. While animal MIRNA precursors have homogenous structures, plant precursors comprise a collection of fold-backs with variable size and shape. Here, we design an approach (SPARE) to systematically analyze miRNA processing intermediates and characterize the biogenesis of most of the evolutionary conserved miRNAs present in Arabidopsis thaliana. We found that plant MIRNAs are processed by four mechanisms, depending on the sequential direction of the processing machinery and the number of cuts required to release the miRNA. Classification of the precursors according to their processing mechanism revealed specific structural determinants for each group. We found that the complexity of the miRNA processing pathways occurs in both ancient and evolutionary young sequences, and that members of the same family can be processed in different ways. We observed that different structural determinants compete for the processing machinery and that alternative miRNAs can be generated from a single precursor. The results provide a mechanistic explanation for the structural diversity of MIRNA precursors in plants and new insights towards the understanding of the biogenesis of small RNAs. Approach to systematically analyze miRNA processing intermediates and characterize the biogenesis of conserved and young miRNAs present in Arabidopsis thaliana. MiRNA processing intermediates profiles of Wild type and Fiery mutants Arabidopsis plants were analyzed, using Illumina GAIIx.

Protein-Protein, Genetic, and Chemical Interactions for Kurihara Y (2006):The interaction between DCL1 and HYL1 is important for efficient and precise processing of pri-miRNA in plant microRNA biogenesis. curated by BioGRID (https://thebiogrid.org); ABSTRACT: It has been reported that some double-stranded RNA (dsRNA) binding proteins interact with small RNA biogenesis-related RNase III enzymes. However, their biological significance is poorly understood. Here we examine the relationship between the Arabidopsis microRNA- (miRNA) producing enzyme DCL1 and the dsRNA binding protein HYL1. In the hyl1-2 mutant, the processing steps of miR163 biogenesis were partially impaired; increased accumulation of pri-miR163 and reduced accumulation of short pre-miR163 and mature miR163 as well as misplaced cleavages in the stem structure of pri-miR163 were detected. These misplaced cleavages were similar to those previously observed in the dcl1-9 mutant, in which the second double-stranded RNA binding domain of the protein was disrupted. An immunoprecipitation assay using Agrobacterium-mediated transient expression in Nicotiana benthamiana showed that HYL1 was able to form a complex with wild-type DCL1 protein, but not with the dcl1-9 mutant protein. We also examined miR164b and miR166a biogenesis in hyl1-2 and dcl1-9. Increased accumulation of pri-miRNAs and reduced accumulation of pre-miRNAs and mature miRNAs were detected. Misplaced cleavage on pri-miR164b was observed only in dcl1-9 but not in hyl1-2, whereas not on pri-miR166a in either mutant. These results indicate that HYL1 has a function in assisting efficient and precise cleavage of pri-miRNA through interaction with DCL1.

MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs has accelerated with the development of high-throughput small RNA sequencing (sRNA-Seq) techniques and bioinformatics tools. However, generating high-quality comprehensive miRNA annotations remains challenging, due to the intrinsic complexity of sRNA-Seq data and inherent limitations of existing miRNA predictions. Here, we present iwa-miRNA, a Galaxy-based framework that can facilitate miRNA annotation in plant species by combining computational analysis and manual curation. iwa-miRNA is specifically designed to generate a comprehensive list of miRNA candidates, bridging the gap between already annotated miRNAs provided by public miRNA databases and new predictions from sRNA-Seq datasets. It can also assist users to select promising miRNA candidates in an interactive mode through the automated and manual steps, contributing to the accessibility and reproducibility of genome-wide miRNA annotation. iwa-miRNA is user-friendly and can be easily deployed as a web application for researchers without programming experience. With flexible, interactive, and easy-to-use features, iwa-miRNA is a valuable tool for annotation of miRNAs in plant species with reference genomes. We illustrated the application of iwa-miRNA for miRNA annotation of plant species with varying complexity. The sources codes and web server of iwa-miRNA is freely accessible at: http://iwa-miRNA.omicstudio.cloud/.

Protein-Protein, Genetic, and Chemical Interactions for Raghuram B (2015):MicroRNA biogenesis factor DRB1 is a phosphorylation target of mitogen activated protein kinase MPK3 in both rice and Arabidopsis. curated by BioGRID (https://thebiogrid.org); ABSTRACT: MicroRNA (miRNA) biogenesis requires AtDRB1 (double-stranded RNA binding protein)/HYL1 (Hyponastic Leaves1) protein for processing and maturation of miRNA precursors. The AtDRB1/HYL1 protein associates with AtDCL1 (Dicer-Like1) and accurately processes primary-miRNAs (pri-mRNAs) first to precursor-miRNAs (pre-miRNAs) and finally to mature miRNAs. The dephosphorylation of AtDRB1/HYL1 protein is very important for the precise processing of miRNA precursors. The monocot model crop plant Oryza sativa encodes four orthologues of AtDRB1/HYL1 protein, the only one encoded by Arabidopsis thaliana. The present study focuses on the functionality of the O. sativa DRBs as the orthologues of AtDRB1/HYL1 by using RNA binding assays and in planta protein-protein interaction analysis. Further, mitogen-activated protein kinase MPK3 is established as the kinase phosphorylating DRB1 protein in both the model plants, O. sativa and Arabidopsis. MicroRNA microarray analysis in atmpk3 and atmpk6 mutants indicate the importance of AtMPK3 in maintaining the level of miRNAs in the plant.

MicroRNAs (miRNA) are small endogenous RNA molecules, which regulate target gene expression at post-transcriptional level. Besides, miRNA activity can be controlled by a newly discovered regulatory mechanism called endogenous target mimicry (eTM). In target mimicry, eTMs bind to the corresponding miRNAs to block the binding of specific transcript leading to increase mRNA expression. Thus, miRNA-eTM-target-mRNA regulation modules involving a wide range of biological processes; an increasing need for a comprehensive eTM database arose. Except miRSponge with limited number of Arabidopsis eTM data no available database and/or repository was developed and released for plant eTMs yet. Here, we present an online plant eTM database, called PeTMbase (http://petmbase.org), with a highly efficient search tool. To establish the repository a number of identified eTMs was obtained utilizing from high-throughput RNA-sequencing data of 11 plant species. Each transcriptome libraries is first mapped to corresponding plant genome, then long non-coding RNA (lncRNA) transcripts are characterized. Furthermore, additional lncRNAs retrieved from GREENC and PNRD were incorporated into the lncRNA catalog. Then, utilizing the lncRNA and miRNA sources a total of 2,728 eTMs were successfully predicted. Our regularly updated database, PeTMbase, provides high quality information regarding miRNA:eTM modules and will aid functional genomics studies particularly, on miRNA regulatory networks.

MicroRNAs (miRNAs) are small non-coding RNAs that have important regulatory functions in plant growth, development, and response to abiotic stress. Increasing evidence also supports that plant miRNAs contribute to immune responses to pathogens. Here, we used deep sequencing of small RNA libraries for global identification of rice miRNAs that are regulated by fungal elicitors. We also describe 9 previously uncharacterized miRNAs in rice. Combined small RNA and degradome analyses revealed regulatory networks enriched in elicitor-regulated miRNAs supported by the identification of their corresponding target genes. Specifically, we identified an important number of miRNA/target gene pairs involved in small RNA pathways, including miRNA, heterochromatic and trans-acting siRNA pathways. We present evidence for miRNA/target gene pairs implicated in hormone signaling and cross-talk among hormone pathways having great potential in regulating rice immunity. Furthermore, we describe miRNA-mediated regulation of Conserved-Peptide upstream Open Reading Frame (CPuORF)-containing genes in rice, which suggests the existence of a novel regulatory network that integrates miRNA and CPuORF functions in plants. The knowledge gained in this study will help in understanding the underlying regulatory mechanisms of miRNAs in rice immunity and develop appropriate strategies for rice protection.

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Plant microRNAs (miRNAs) are predominantly 21 nucleotides (nt) long but non-canonical lengths of 22 and 20 nt are commonly observed in diverse plant species. While miRNAs longer than 21 nt can be attributed to the neglect of unpaired bases within asymmetric bulges by the ruler function of DICER-LIKE 1 (DCL1), how 20-nt miRNA is generated remains obscure. Analysis of small RNA data revealed that 20-nt miRNA can be divided into 3 main groups featured by atypical 3′ overhangs or shorter duplex regions. Asymmetric bulges or mismatches at specific positions are commonly observed within each group and were shown to be crucial for 20-nt miRNA formation. Analysis of DCL1 cleavage sites on 20-nt miRNA precursors suggests that these determinants might alter precursor structure or trigger 3′-end decay of mature miRNA. The results herein advance our understanding of miRNA biogenesis and demonstrate that the effect of asymmetric bulges on miRNA length could be position-dependent.

MicroRNAs (miRNAs) are important post-transcriptional regulators of plant development and seed formation. In Brassica napus, an important edible oil crop, valuable lipids are synthesized and stored in specific seed tissues during embryogenesis. The miRNA transcriptome of B. napus is currently poorly characterized, especially at different seed developmental stages. This work aims to describe the miRNAome of developing seeds of B. napus by identifying plant-conserved and novel miRNAs and comparing miRNA abundance in mature versus developing seeds. Members of 59 miRNA families were detected through a computational analysis of a large number of reads obtained from deep sequencing two small RNA and two RNA-seq libraries of (i) pooled immature developing stages and (ii) mature B. napus seeds. Among these miRNA families, 17 families are currently known to exist in B. napus; additionally 29 families not reported in B. napus but conserved in other plant species were identified by alignment with known plant mature miRNAs. Assembled mRNA-seq contigs allowed for a search of putative new precursors and led to the identification of 13 novel miRNA families. Analysis of miRNA population between libraries reveals that several miRNAs and isomiRNAs have different abundance in developing stages compared to mature seeds. The predicted miRNA target genes encode a broad range of proteins related to seed development and energy storage. This work presents a comparative study of the miRNA transcriptome of mature and developing B. napus seeds and provides a basis for future research on individual miRNAs and their functions in embryogenesis, seed maturation and lipid accumulation in B. napus.

With food, a huge variety of biological material gets into the human digestive tract, which the body uses for life support. The variety of food material entering the gastrointestinal tract, especially at the molecular level, cannot be distinguished from endogenous metabolites and these exogenous compounds can significantly alter the body's metabolism. Such compounds include plant miRNAs, which are indistinguishable from endogenous human miRNAs in physicochemical properties. Recently, publications have appeared about the ingestion of exogenous miRNAs into the human body, and therefore it is necessary to know how these miRNAs can be useful or harmful. In the absence of the expected effect of plant miRNAs on all human genes, one cannot be afraid of this effect. Therefore, it is necessary to clarify the degree of influence of exogenous plant miRNAs on the expression of human genes, since it is not known in advance what consequences can occur when plant miRNAs enters the human body. A huge amount of research does not allow experiments with all human genes and all plant miRNAs, so we have studied the effect of plant miRNAs on human genes using computer methods. The MirTarget program used by us with high efficiency determines the quantitative characteristics of the interaction of plant miRNAs with animal mRNAs. Supplemental data contain information that would occupy a large volume in the text of the article. But this information is necessary for understanding and confirming the conclusions of the work.

In this study we investigated the transcriptome and epigenome dynamics of the tomato fruit during post-harvest in ‘Lucariello’. ‘Lucariello’ belongs to a group of landraces collectively known as ‘Piennolo del Vesuvio’. This dataset includes: - RPKM expression values from three post-harvest stages of Lucariello fruits, time points RD0, RD60 and RD150. Each group has three biological replicates. The listed loci are from the Lucariello reference genome - Raw expression counts of miRNA from the same samples - DNA gene methylation levels from the same samples, divided for CG, CHG and CHH context - ChIP-seq peaks for H3K4me3, H3K9K14ac, H3K27me3 from the same samples, two biological replicates - Supplementary tables described in the main manuscript providing lists of Differentially Methylated Regions (DMR) and Differentially Expressed Genes (DEGs) across the different time points

miRNEST is a database of animal, plant and virus microRNAs, containing miRNA predictions conducted on Expressed Sequence Tags of animal and plant species.

Note: mac:Musa acuminata; mbg: Musa ABB Group The underlined was the mismatched bases between miRNAs and the known miRNA sequences in the miRBase; Location: the position of mature miRNA in precursor; LM: length of mature miRNA (nt); LP: length of precursor (nt); MFEs: minimal folding free energies (kcal mol−1). *: star miRNA.List of computer predicted banana miRNAs from the EST and GSS database.