MiRNA in
computational biology
The Nobel Prize in Physiology or Medicine
for 2006
Andrew Z. Fire and Craig C. Mello
for their discovery of
"RNA interference – gene silencing by
double-stranded RNA"
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contents
 Introduction miRNA
 Computational identification of miRNA
 Computational identification of target miRNA
 miRNA database
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Introduction miRNA
 MicroRNA are one class of newly identified
riboregulators of gene expression in many
eukaryotic organism.
 Mature miRNA have 20-24 nucleotides
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Tasks of miRNA
 They play important roles in multiple biological and
metabolic processes , including
 Developmental timing
 Signal transduction
 Differentiation
 Cell fate identity
 Diseases and carcinogenesis
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Coordinated action of miRNA
nodes in developmental timing and
tailoring leaf shape
www.cs.ucf.edu/~shzhang/CAP5510/lec14.ppt
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Produce mature miRNA
 Mature miRNA formation requires a multiple –step
process.
I. miRNA gene is first transcribed to a primary
miRNA by Pol II enzyme
II. Cleaved to a stem loop intermediate termed premiRNA by Drosha
III. Pre-miRNAs are further cleaved to miRNA:
miRNA* duplex
IV. Mature miRNA are releaseed for regulating
targeted gene expression
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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How microRNA regulates the target
mRNA genes
www.cs.ucf.edu/~shzhang/CAP5510/lec14.ppt
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Major characterstics of microRNAs
 Hairpin-shaped secondary structures
 High conservation for some miRNA
 High minimal folding free energy index
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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History identification of miRNA
 miRNAS were initially identified by a genetic
screening technology
 Recently , direct cloning of miRNAs , followed by
small RNA isolation
 Computational approaches
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Computational approaches
 The principles of computational approaches are base
on
I.
Hairpin-shaped stem loop secondary structure
II. High evolutionary conservation
III. High minimal folding free energy index
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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classification
 The computational approaches can be classified
into five major categories
I. Homology search-based
II. Gene search
III. Neighbor stem loop search
IV. Algorithms based on comparative genomics
V. Phylogentic shadowing-based
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Homology search-based approach
 Identifying miRNA genes by searching nucleotide
database using BLOST program
 It was well recognized that miRNA are
evolutionarily conserved
 Profile-based search programs , such as
I. ERPIN
II. miAlign
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Classification of homology s..
I.
GENOME-BASE SEARCH
II. ESTS-BASE SEARCH

Partial cDNA sequences of expressed gened
cloned into a plasmid

A powerfull approach to identify miRNA genes
in species whose genome sequence are not
available
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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GENE-FINDING APPROACH
 Gene-finding approaches are designed for
predicting animal miRNA
 Not depend on homology or miRNA conservation
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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How gene-finding work
I.
First need to identify conserved genomic regions
II. These regions into a window 110-n
III. Using a specific computer program
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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How program work
 Window is folded with secondary structure
program such as mfold or RNA fold
 hairpin-shaped stem loops for potential miRNA
candidates
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Computer programs
homology search based
 MiRseeker
 analyzing conserved sequences that adopt an
extended stem loop secondary structure
 Accuracy 75% for Drosophila miRNA
 miRscan
 Identify miRNA base on common characteristics
(such as base pairing and nucleotide bias )
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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MiRscan
 Scan to find conserve
hairpin structures
 Using known miRNA
genes at training set
Yong Huang. The discovery approaches and detection methods of microRNAs
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Processes of MiRscan
I.
A 110-nt window along both strand
II. Folding the window with RNAfold
III. A folding free energy of as a least -25 kcal/mol
IV. Passing a 21-nt window along each stem-loop
V. Assigning a log likelihood score to each position
for its similarity to know miRNA
Yong Huang. The discovery approaches and detection methods of microRNAs
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Program online
http://bioinforma.weebly.com/mirna-prediction.html
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MiRscan
http://bioinforma.weebly.com/mirna-prediction.html
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Computational identification of
microRNA TARGETS
 A high degree of complementarity to the miRNAs
 This allows the prediction of miRNA targets by
computational approaches
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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Computational approaches
are based on
 MiRNA are perfectly or near perfectly
complementary to their target miRNA
 The RNA-RNA duplex has a higher negative
folding free energy
 Binding sites of mRNA and miRNA is highly
conserved
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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programs
 Find miRNA
 Mir check
 Target scan
 MiRanda
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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miRNA database
 miR Base
 ASRP
 miRna AMap
Boahong zhang ,xiaoping pan , 2006. computational identification of miroRNA
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THANK YOU
END
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