Abstract: MicroRNAs are small non-coding RNA found in
many different species. They play crucial roles in cancer such as
biological processes of apoptosis and proliferation. The identification
of microRNA-target genes can be an essential first step towards to
reveal the role of microRNA in various cancer types. In this paper,
we predict miRNA-target genes for lung cancer by integrating
prediction scores from miRanda and PITA algorithms used as a
feature vector of miRNA-target interaction. Then, machine-learning
algorithms were implemented for making a final prediction. The
approach developed in this study should be of value for future studies
into understanding the role of miRNAs in molecular mechanisms
enabling lung cancer formation.
Abstract: MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.
Abstract: Among all microRNAs (miRNAs) in 12 plant species investigated in this study, only miR398 targeted the copper chaperone for superoxide dismutase (CCS). The nucleotide sequences of miRNA binding sites were located in the mRNA protein-coding sequence (CDS) and were highly homologous. These binding sites in CCS mRNA encoded a conservative GDLGTL hexapeptide. The binding sites for miR398 in the CDS of superoxide dismutase 1 mRNA encoded GDLGN pentapeptide. The conservative miR398 binding site located in the CDS of superoxide dismutase 2 mRNA encoded the GDLGNI hexapeptide. The miR398 binding site in the CDS of superoxide dismutase 3 mRNA encoded the GDLGNI or GDLGNV hexapeptide. Gene expression of the entire superoxide dismutase family in the studied plant species was regulated only by miR398. All members of the miR398 family, i.e. miR398a,b,c were connected to one site for each CuZnSOD and chaperone mRNA.
Abstract: MiRNAs participate in gene regulation of translation.
Some studies have investigated the interactions between genes and
intragenic miRNAs. It is important to study the miRNA binding sites
of genes involved in carcinogenesis. RNAHybrid 2.1 and ERNAhybrid
programmes were used to compute the hybridization free
energy of miRNA binding sites. Of these 54 mRNAs, 22.6%, 37.7%,
and 39.7% of miRNA binding sites were present in the 5'UTRs,
CDSs, and 3'UTRs, respectively. The density of the binding sites for
miRNAs in the 5'UTR ranged from 1.6 to 43.2 times and from 1.8 to
8.0 times greater than in the CDS and 3'UTR, respectively. Three
types of miRNA interactions with mRNAs have been revealed: 5'-
dominant canonical, 3'-compensatory, and complementary binding
sites. MiRNAs regulate gene expression, and information on the
interactions between miRNAs and mRNAs could be useful in
molecular medicine. We recommend that newly described sites
undergo validation by experimental investigation.
Abstract: In this study, three subtypes of influenza A viruses (pH1N1, H5N1 and H3N2) which naturally infected human were analyzed by bioinformatic approaches to find candidate human cellular miRNAs targeting viral genomes. There were 76 miRNAs targeting influenza A viruses. Among these candidates, 70 miRNAs were subtypes specifically targeting each subtype of influenza A virus including 21 miRNAs targeted subtype H1N1, 27 miRNAs targeted subtype H5N1 and 22 miRNAs targeted subtype H3N2. The remaining 6 miRNAs target on multiple subtypes of influenza A viruses. Uniquely, hsa-miR-3145 is the only one candidate miRNA targeting PB1 gene of all three subtypes. Obviously, most of the candidate miRNAs are targeting on polymerase complex genes (PB2, PB1 and PA) of influenza A viruses. This study predicted potential human miRNAs targeting on different subtypes of influenza A viruses which might be useful for inhibition of viral replication and for better understanding of the interaction between virus and host cell.
Abstract: Tumour suppressors are key participants in the
prevention of cancer. Regulation of their expression through
miRNAs is important for comprehensive translation inhibition of
tumour suppressors and elucidation of carcinogenesis mechanisms.
We studies the possibility of 1521 miRNAs to bind with 873 mRNAs
of human tumour suppressors using RNAHybrid 2.1 and ERNAhybrid
programmes. Only 978 miRNAs were found to be
translational regulators of 812 mRNAs, and 61 mRNAs did not have
any miRNA binding sites. Additionally, 45.9% of all miRNA binding
sites were located in coding sequences (CDSs), 33.8% were located
in 3' untranslated region (UTR), and 20.3% were located in the
5'UTR. MiRNAs binding with more than 50 target mRNAs and
mRNAs binding with several miRNAs were selected. Hsa-miR-5096
had 15 perfectly complementary binding sites with mRNAs of 14
tumour suppressors. These newly indentified miRNA binding sites
can be used in the development of medicines (anti-sense therapies)
for cancer treatment.
Abstract: Regulatory relationships of 686 intronic miRNA and 784 intergenic miRNAs with mRNAs of 51 intronic miRNA coding genes were established. Interaction features of studied miRNAs with 5'UTR, CDS and 3'UTR of mRNA of each gene were revealed. Functional regions of mRNA were shown to be significantly heterogenous according to the number of binding sites of miRNA and to the location density of these sites.
Abstract: It has been established that microRNAs (miRNAs) play
an important role in gene expression by post-transcriptional regulation
of messengerRNAs (mRNAs). However, the precise relationships
between microRNAs and their target genes in sense of numbers,
types and biological relevance remain largely unclear. Dissecting the
miRNA-target relationships will render more insights for miRNA
targets identification and validation therefore promote the understanding
of miRNA function. In miRBase, miRanda is the key
algorithm used for target prediction for Zebrafish. This algorithm
is high-throughput but brings lots of false positives (noise). Since
validation of a large scale of targets through laboratory experiments
is very time consuming, several computational methods for miRNA
targets validation should be developed. In this paper, we present an
integrative method to investigate several aspects of the relationships
between miRNAs and their targets with the final purpose of extracting
high confident targets from miRanda predicted targets pool. This is
achieved by using the techniques ranging from statistical tests to
clustering and association rules. Our research focuses on Zebrafish.
It was found that validated targets do not necessarily associate with
the highest sequence matching. Besides, for some miRNA families,
the frequency of their predicted targets is significantly higher in the
genomic region nearby their own physical location. Finally, in a case
study of dre-miR-10 and dre-miR-196, it was found that the predicted
target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR-
10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar
characteristics as validated target genes and therefore represent high
confidence target candidates.
Abstract: MicroRNAs (miRNAs) are a class of non-coding
RNAs that hybridize to mRNAs and induce either translation
repression or mRNA cleavage. Recently, it has been reported that
miRNAs could possibly play an important role in human diseases. By
integrating miRNA target genes, cancer genes, miRNA and mRNA
expression profiles information, a database is developed to link
miRNAs to cancer target genes. The database provides experimentally
verified human miRNA target genes information, including oncogenes
and tumor suppressor genes. In addition, fragile sites information for
miRNAs, and the strength of the correlation of miRNA and its target
mRNA expression level for nine tissue types are computed, which
serve as an indicator for suggesting miRNAs could play a role in
human cancer. The database is freely accessible at
http://ppi.bioinfo.asia.edu.tw/mirna_target/index.html.
Abstract: MicroRNAs (miRNAs) are small, non-coding and
regulatory RNAs about 20 to 24 nucleotides long. Their conserved
nature among the various organisms makes them a good source of
new miRNAs discovery by comparative genomics approach. The
study resulted in 21 miRNAs of 20 pre-miRNAs belonging to 16
families (miR156, 157, 158, 164, 165, 168, 169, 172, 319, 390, 393,
394, 395, 400, 472 and 861) in evergreen spruce tree (Picea). The
miRNA families; miR 157, 158, 164, 165, 168, 169, 319, 390, 393,
394, 400, 472 and 861 are reported for the first time in the Picea. All
20 miRNA precursors form stable minimum free energy stem-loop
structure as their orthologues form in Arabidopsis and the mature
miRNA reside in the stem portion of the stem loop structure. Sixteen
(16) miRNAs are from Picea glauca and five (5) belong to Picea
sitchensis. Their targets consist of transcription factors, growth
related, stressed related and hypothetical proteins.