Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search for new microRNAs. We present miRNEST (http://mirnest.amu.edu.pl), a comprehensive database of animal, plant and virus microRNAs.
The regulation of intragenic miRNAs by their own intronic promoters is one of the open problems of miRNA biogenesis. Here, we describe PROmiRNA, a new approach for miRNA promoter annotation based on a semi-supervised statistical model trained on deepCAGE data and sequence features. We validate our results with existing annotation, PolII occupancy data and read coverage from RNA-seq data.
MicroRNAs (miRNAs) are non-coding RNAs (ncRNAs) involved in regulation of gene expression. Intragenic miRNAs, especially those exhibiting a high degree of evolutionary conservation, have been shown to be coordinately regulated and/or expressed with their host genes, either with synergistic or antagonistic correlation patterns. However, the degree of cross-species conservation of miRNA/host gene co-location is not known and co-expression information is incomplete and fragmented among several studies.
MicroRNAs (miRNAs) are a class of small (~22 nucleotides) non-coding RNAs that post-transcriptionally regulate gene expression by interacting with target mRNAs. A majority of miRNAs is located within intronic or exonic regions of protein-coding genes (host genes), and increasing evidence suggests a functional relationship between these miRNAs and their host genes.
Splicing is one of the major contributors to observed spatiotemporal diversification of transcripts and proteins in metazoans. There are numerous factors that affect the process, but splice sites themselves along with the adjacent splicing signals are critical here. Unfortunately, there is still little known about splicing in plants and, consequently, further research in some fields of plant molecular biology will encounter difficulties.
Small RNAs (sRNAs) are non-coding transcripts exerting their functions in the cells directly. Identification of sRNAs is a difficult task due to the lack of clear sequence and structural biases. Most sRNAs are identified within genus specific intergenic regions in related genomes. However, several of these regions remain un-annotated due to lack of sequence homology and/or potent statistical identification tools.
IntmiR is a manually curated database of published intronic miRNAs of Human and Mouse genome. Each entry in the database, aims at providing a complete resource of intronic miRNA with their target gene and deregulation in various diseases with related tissues and pathways. The current release contains 426 intronic miRNA loci from human and 76 from mouse, expressing distinct target mRNA sequences. Database gives information on an intronic miRNA-disease relationship, including miRNA ID, pathaway connected and related tissues.
Identifying the tissues in which a microRNA is expressed could enhance the understanding of the functions, the biological processes, and the diseases associated with that microRNA. However, the mechanisms of microRNA biogenesis and expression remain largely unclear and the identification of the tissues in which a microRNA is expressed is limited.
The genome-wide identification of microRNA transcription start sites (miRNA TSSs) is essential for understanding how miRNAs are regulated in development and disease. In this study, we developed mirSTP (mirna transcription Start sites Tracking Program), a probabilistic model for identifying active miRNA TSSs from nascent transcriptomes generated by global run-on sequencing (GRO-seq) and precision run-on sequencing (PRO-seq).
Studies from flies and insects have reported the existence of a special class of miRNA, called mirtrons that are produced from spliced-out introns in a DROSHA-independent manner. The spliced-out lariat is debranched and refolded into a stem-loop structure resembling the pre-miRNA, which can then be processed by DICER into mature ~21 nt species. The mirtrons have not been reported from plants. In this study, we present MirtronPred, a web based server to predict mirtrons from intronic sequences.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
Updates History:
