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RNA Structure & Function 10/31/05
D Dobbs ISU - BCB 444/544X 1
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 1
10/31/05
RNA Structure & Function
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 2
Announcements
Seminar (Mon Oct 31)12:10 PM IG Faculty Seminar in 101 Ind Ed II
Plant Steroid Hormone Signal TransductionYanhai Yin, GDCB
• BCB Link for Seminar Schedules (updated)http://www.bcb.iastate.edu/seminars/index.html
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 3
Announcements
BCB 544 Projects - Important Dates:
Nov 2 Wed noon - Project proposals due to David/Drena
Nov 4 Fri 10A - Approvals/responses to students
Dec 2 Fri noon - Written project reports due
Dec 5,7,8,9 class/lab - Oral Presentations (20')
(Dec 15 Thurs = Final Exam)
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 4
RNA Structure & FunctionPrediction
Mon Review - promoter prediction
RNA structure & function
Wed RNA structure prediction2' & 3' structure prediction
miRNA & target prediction
RNA function prediction?
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 5
Reading Assignment (for Mon/Wed)
Mount Bioinformatics• Chp 8 Prediction of RNA Secondary Structure• pp. 327-355• Ck Errata: http://www.bioinformaticsonline.org/help/errata2.html
Cates (Online) RNA Secondary Structure Prediction Module• http://cnx.rice.edu/content/m11065/latest/
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Review last lecture:
Promoter Prediction
RNA Structure & Function 10/31/05
D Dobbs ISU - BCB 444/544X 2
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 7
Promoter Prediction
• Overview of strategies What sequence signals can be used? What other types of information can be used?
• Algorithms a bit more about these in later lectures• Promoter prediction software
• 3 major types• many, many programs!
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Promoter prediction: Eukaryotes vs prokaryotes
Promoter prediction is easier in microbial genomes
Why? Highly conservedSimpler gene structuresMore sequenced genomes!
(for comparative approaches)
Methods? Previously, again mostly HMM-based Now: similarity-based. comparative methods
because so many genomes available
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Promoter Prediction: Steps & Strategies
Closely related to gene prediction!• Obtain genomic sequence• Use sequence-similarity based comparison
(BLAST, MSA) to find related genesBut: "regulatory" regions are much less well-conserved than coding regions
• Locate ORFs• Identify TSS (Transcription Start Site)• Use promoter prediction programs• Analyze motifs, etc. in sequence (TRANSFAC)
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 10
Promoter Prediction: Steps & Strategies
Identify TSS --if possible?• One of biggest problems is determining exact TSS!
Not very many full-length cDNAs!• Good starting point? (human & vertebrate genes)
Use FirstEFfound within UCSC Genome Browseror submit to FirstEF web server
Fig 5.10Baxevanis &Ouellette 2005
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Promoter prediction strategies
1) Pattern-driven algorithms
2) Sequence-driven algorithms
3) Combined "evidence-based"
BEST RESULTS? Combined, sequential
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Promoter Prediction: Pattern-driven algorithms
• Success depends on availability of collections ofannotated binding sites (TRANSFAC & PROMO)
• Tend to produce huge numbers of FPs
• Why?• Binding sites (BS) for specific TFs often variable• Binding sites are short (typically 5-15 bp)• Interactions between TFs (& other proteins) influence
affinity & specificity of TF binding• One binding site often recognized by multiple BFs• Biology is complex: promoters often specific to
organism/cell/stage/environmental condition
RNA Structure & Function 10/31/05
D Dobbs ISU - BCB 444/544X 3
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Promoter Prediction: Pattern-driven algorithms
Solutions to problem of too many FP predictions?• Take sequence context/biology into account
• Eukaryotes: clusters of TFBSs are common• Prokaryotes: knowledge of σ factors helps
• Probability of "real" binding site increases ifannotated transcription start site (TSS) nearby• But: What about enhancers? (no TSS nearby!)
& Only a small fraction of TSSs have beenexperimentally mapped
• Do the wet lab experiments!• But: Promoter-bashing is tedious
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Promoter Prediction: Sequence-driven algorithms
• Assumption: common functionality can be deducedfrom sequence conservation• Alignments of co-regulated genes should highlight
elements involved in regulationCareful: How determine co-regulation?• Orthologous genes from difference species• Genes experimentally determined to be
co-regulated (using microarrays??)• Comparative promoter prediction:
"Phylogenetic footprinting" - more later….
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Problems:• Need sets of co-regulated genes• For comparative (phylogenetic) methods
• Must choose appropriate species• Different genomes evolve at different rates• Classical alignment methods have trouble with translocations, inversions in order of functional elements• If background conservation of entire region is highly
conserved, comparison is useless• Not enough data (Prokaryotes >>> Eukaryotes)
• Biology is complex: many (most?) regulatory elementsare not conserved across species!
Promoter Prediction: Sequence-driven algorithms
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Examples of promoterprediction/characterization software
Lab: used MATCH, MatInspectorTRANSFACMEME & MASTBLAST, etc.
Others?FIRST EFDragon Promoter Finder (these are links in PPTs)
also see Dragon Genome Explorer (has specializedpromoter software for GC-rich DNA, finding CpGislands, etc)
JASPAR
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Global alignment of human & mouse obesegene promoters (200 bp upstream from TSS)
Fig 5.14Baxevanis &Ouellette 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 18
Check out optional review &try associated tutorial:
Wasserman WW & Sandelin A (2004) Applied bioinformatics foridentification of regulatory elements. Nat Rev Genet 5:276-287http://proxy.lib.iastate.edu:2103/nrg/journal/v5/n4/full/nrg1315_fs.html
Check this out: http://www.phylofoot.org/NRG_testcases/
RNA Structure & Function 10/31/05
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Annotated lists of promoter databases &promoter prediction software
• URLs from Mount Chp 9, available onlineTable 9.12 http://www.bioinformaticsonline.org/links/ch_09_t_2.html
• Table in Wasserman & Sandelin Nat Rev Genet articlehttp://proxy.lib.iastate.edu:2103/nrg/journal/v5/n4/full/nrg1315_fs.htm
• URLs for Baxevanis & Ouellette, Chp 5:http://www.wiley.com/legacy/products/subject/life/bioinformatics/ch05.htm#links
More lists:• http://www.softberry.com/berry.phtml?topic=index&group=programs&subgroup=promo
ter• http://bioinformatics.ubc.ca/resources/links_directory/?subcategory_id=104• http://www3.oup.co.uk/nar/database/subcat/1/4/
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New Today:
RNA Structure & Function
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 21
RNA Structure & Function
• RNA structure• Levels of organization• Bonds & energetics
(more about this on Wed)
• RNA types & functions• Genomic information storage/transfer• Structural• Catalytic• Regulatory
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 22
Rob KnightUniv Colorado
RNA structure: 3 levels of organization
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 23
Fig 6.2Baxevanis &Ouellette 2005
Covalent & non-covalent bonds in RNA
Primary: Covalent bonds
Secondary/Tertiary Non-covalent bonds
• H-bonds (base-pairing)• Base stacking
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 24
G-C, A-U, G-U ("wobble") & variants
Base-pairing in RNA
http://www.imbjena.de/ImgLibDoc/nana/IMAGE_NANA.html#sec_element
See: IMB Image Library of Biological Molecules
RNA Structure & Function 10/31/05
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Fig 6.2Baxevanis &Ouellette 2005
Common structural motifs in RNA
Helices
Loops• Hairpin• Interior• Bulge• Multibranch
Pseudoknots
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RNA functions
• Storage/transfer of genetic information
• Structural
• Catalytic
• Regulatory
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 27
RNA functions
Storage/transfer of genetic information
• Genomes• many viruses have RNA genomes
single-stranded (ssRNA)e.g., retroviruses (HIV)
double-stranded (dsRNA)
• Transfer of genetic information• mRNA = "coding RNA" - encodes proteins
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 28
RNA functions
Structural• e.g., rRNA, which is major structural component of
ribosomes (Gloria Culver, ISU) BUT - its role is not just structural, also:
CatalyticRNA in ribosome has peptidyltransferase activity
• Enzymatic activity responsible for peptidebond formation between amino acids ingrowing peptide chain• Also, many small RNAs are enzymes
"ribozymes" (W Allen Miller, ISU)
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 29
RNA functionsRegulatory
Recently discovered important new roles for RNAs In normal cells:
• in "defense" - esp. in plants• in normal development
e.g., siRNAs, miRNAAs tools:
• for gene therapy or to modify gene expression• RNAi (used by many at ISU: Diane
Bassham,Thomas Baum, Jeff Essner, KristenJohansen, Jo Anne Powell-Coffman, Roger Wise, etc.)
• RNA aptamers (Marit Nilsen-Hamilton, ISU)
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RNA types & functions
regulation of transcription and translation,other??
regulatory RNAs (siRNA,miRNA, etc.)
mRNA processing, poly A addition <catalytic>rRNA processing/maturation/methylation
snRNA - small nuclearsnoRNA - small nucleolar
signal recognition particle (SRP)tRNA processing <catalytic>
scRNA - small cytoplasmic
precursors & intermediates of maturemRNAs & other RNAs
hnRNA - heterogeneous nuclear
translation (protein synthesis)t-RNA - transfer
translation (protein synthesis) <catalytic>rRNA - ribosomal
translation (protein synthesis)regulatory
mRNA - messenger
Primary Function(s)Types of RNAs
RNA Structure & Function 10/31/05
D Dobbs ISU - BCB 444/544X 6
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 31
Thanks to Chris Burge, MITfor following slides
Slightly modified from:Gene Regulation and MicroRNAs
Session introduction presented atISMB 2005, Detroit, MI
Chris Burge [email protected]
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 32
Expression of a Typical Eukaryotic Gene
DNA
…
Transcription
Protein
TranslationmRNA
Splicing
exon intron
AAAAAAAAA
Polyadenylation
Protein Coding Gene
Folding, Modification,Transport, Complex Assembly
Protein Complex
Degradation
Degradation
primary transcript / pre-mRNA
Export
For each of theseprocesses, there isa ‘code’
(set of defaultrecognition rules)
C Burge 2005
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 33
Gene Expression Challenges forComputational Biology
• Understand the ‘code’ for each step in gene expression(set of default recognition rules), e.g., the ‘splicing code’
• Understand the rules for sequence-specific recognition ofnucleic acids by protein and ribonucleoprotein (RNP) factors
• Understand the regulatory events that occur at each step andthe biological consequences of regulation
Lots of data
Genomes, structures, transcripts, microarrays, ChIP-Chip, etc.
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 34
Steps in Transcription
Emerson Cell 2002C Burge 2005
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 35
Sequence-specific Transcription Factors
• typically bind in clusters
» Regulatory modules
Kadonaga Cell 2004
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 36
Sequence-specific Transcription Factors
• have modular organization
» Understand DNA-binding specificity
Yan (ISU) A computational method to identify amino acidresidues involved in protein-DNA interactions
ATF-2/c-Jun/IRF-3 DNA complex
Panne et al. EMBO J. 2004
C Burge 2005
RNA Structure & Function 10/31/05
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10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 37
Maniatis & Reed Nature 2002
Integration oftranscription &RNA processing
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 38
Early Steps in Pre-mRNA Splicing
Matlin, Clark & Smith Nature Mol Cell Biol 2005
• Formation of exon-spanning complex
• Subsequent rearrangement to formintron-spanning spliceosomes whichcatalyze intron excision and exon ligation
hnRNP proteins
C Burge 2005
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 39
Alternative Splicing
Matlin, Clark & Smith Nature Mol Cell Biol 2005
Wang (ISU) Genome-wide Comparative Analysis of AlternativeSplicing in Plants
> 50% of human genesundergo alternative splicing
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 40
Splicing Regulation
Matlin, Clark & Smith Nature Mol Cell Biol 2005
ESE/ESS = Exonic Splicing Enhancers/Silencers
ISE/ISS = Intronic Splicing Enhancers/Silencers
C Burge 2005
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Coupling of Splicing & Nonsense-mediatedmRNA Decay (NMD)
Maniatis & Reed Nature 2002
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 42
C. elegans lin-4 Small Regulatory RNA
We now know that there are hundreds of microRNA genes
(Ambros, Bartel, Carrington, Ruvkun, Tuschl, others)
lin-4 precursor
lin-4 RNA
“Translationalrepression”
V. Ambros lablin-4 RNA
target mRNA
C Burge 2005
RNA Structure & Function 10/31/05
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MicroRNA Biogenesis
N. Kim Nature Rev Mol Cell Biol 2005
C Burge 2005 10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 44
miRNA and RNAi pathways
RISC
Dicerprecursor
miRNA siRNAs
Dicer
“translational repression”and/or mRNA degradation
mRNA cleavage, degradation
RNAi pathwaymicroRNA pathwayMicroRNA primary transcript Exogenous dsRNA, transposon, etc.
target mRNA
Drosha
RISCRISC
C Burge 2005
10/31/05 D Dobbs ISU - BCB 444/544X: RNA Structure & Function 45
miRNA Challenges for Computational Biology
• Find the genes encoding microRNAs
• Predict their regulatory targets
• Integrate miRNAs into gene regulatory pathways &networks
Computational Prediction of MicroRNA Genes & Targets
C Burge 2005
Need to modify traditional paradigm of"transcriptional control" by protein-DNA interactionsto include miRNA regulatory mechanisms