rnai blast blast smith water man
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8/7/2019 RNAi Blast BLAST Smith Water Man
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SmithSmith--Waterman vs Blast inWaterman vs Blast in
siRNA Oligonucleotide DesignsiRNA Oligonucleotide Designand Selectionand Selection
Christine LeeChristine Lee
Dr. Cecilie Boysen, Ph.D.Dr. Cecilie Boysen, Ph.D.
Paracel,Paracel, Applied High Performance ComputingApplied High Performance Computing
Southern California Bioinformatics InstituteSouthern California Bioinformatics Institute
Summer 2004Summer 2004
Funded by the National Science Foundation and National Institute of HealthFunded by the National Science Foundation and National Institute of Health
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OutlineOutline
History of RNAiHistory of RNAi
Small interfering RNA (siRNA) MechanismSmall interfering RNA (siRNA) Mechanism
siRNA design and selectionsiRNA design and selection
Blast vs SmithBlast vs Smith--WatermanWaterman
Project Objectives and ResultsProject Objectives and Results
Conclusions & Future WorkConclusions & Future Work
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History of RNAiHistory of RNAi
Discovered in 1998 by Andrew Fire, CraigDiscovered in 1998 by Andrew Fire, Craig
Mello, and colleaguesMello, and colleagues
RNAiRNAi silencing of gene expression bysilencing of gene expression bydsRNA moleculesdsRNA molecules
Organism used: Caenorhabditis elegansOrganism used: Caenorhabditis elegans
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Short interfering RNA (siRNA)Short interfering RNA (siRNA)
MechanismMechanism
http://www.bioteach.ubc.ca/MolecularBiology/AntisenseRNA/siRNA.gif
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siRNA Selection & Design:siRNA Selection & Design:
Avoiding CrossAvoiding Cross--HybridizationHybridization Important to guard against strong crossImportant to guard against strong cross--
hybridization to other geneshybridization to other genes
CrossCross--hybridization with nonhybridization with non--specific targetsspecific targetsresults in wasted lab time and materials, as wellresults in wasted lab time and materials, as wellas inaccurate conclusionsas inaccurate conclusions
Preliminary sequence analysis allows verificationPreliminary sequence analysis allows verificationof candidate oligos to protect against crossof candidate oligos to protect against cross--hybridizationhybridization
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siRNA Selection & DesignsiRNA Selection & Design
Hybridization concerns:Hybridization concerns: siRNA mismatch tolerancesiRNA mismatch tolerance
Insertion/deletion vs mismatchInsertion/deletion vs mismatch
Query: 1 GAACTTATCTTCCTTCTTC 19Query: 1 GAACTTATCTTCCTTCTTC 19
||||||||||||||||||||||||||||||||||||||
Sbjct: 3783 GAACTTATCTTCCTTCTTC 3801Sbjct: 3783 GAACTTATCTTCCTTCTTC 3801
Query: 19 GAAGAAGGAAGATAAGTTC 1
||||||||| || ||||||
Sbjct: 778 GAAGAAGGATGAGAAGTTC 796
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Blast vs SmithBlast vs Smith--WatermanWaterman
Blast may potentially miss relevant alignmentsBlast may potentially miss relevant alignments
Using word size seven, nearly 6% of allUsing word size seven, nearly 6% of allpossible alignments with three mismatchespossible alignments with three mismatchesbetween 21between 21--mers will be missedmers will be missed
Increasing word size or allowing moreIncreasing word size or allowing moremismatches contribute to higher rate of mismatches contribute to higher rate of
missed hitsmissed hits SmithSmith--Waterman is said to have higherWaterman is said to have higher
sensitivity, so why not use it?sensitivity, so why not use it?
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Project ObjectivesProject Objectives
Test set: 10,000 19Test set: 10,000 19--mer oligos/siRNAsmer oligos/siRNAs
Test database: RefSeqTest database: RefSeq
Comparison study between Blast andComparison study between Blast andSmith WatermanSmith Waterman
15/1915/19 --> Percent Identity threshold set to> Percent Identity threshold set to
78% e78% e--value adjustment from default of value adjustment from default of 10. E10. E--value 500 usedvalue 500 used
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A Closer Look at SmithA Closer Look at Smith--WatermanWaterman
& Blast Parameters& Blast Parameters
AlgorithmAlgorithm AlignmentAlignment Score/Score/
(ID)(ID)
ParamParam MatchMatch MisMis--
matchmatch
GO/GO/
GEGE
GapGap
TotalTotal
SmithSmith
Water manWater man
Query: 19 TCACCGTAGATGCTCTTTC 1Query: 19 TCACCGTAGATGCTCTTTC 1
|| |||| ||||||||||||| |||| |||||||||||
Sbjct: 2376 TCSbjct: 2376 TC--CCGTGGATGCTCTTTC 2393CCGTGGATGCTCTTTC 2393
2929
17/1917/19
(89%)(89%)
defaultdefault +2+2 --22 --33
BlastBlast Query: 1 gaaagagcatctacgg 16Query: 1 gaaagagcatctacgg 16
||||||||||| ||||||||||||||| ||||
Sbjct: 2393 gaaagagcatccacgg 2378Sbjct: 2393 gaaagagcatccacgg 2378
1212
15/1615/16
(93%)(93%)
W 7W 7
e 500e 500
DefaultDefault
+1+1 --33 GG --55
EE --22
--77
BlastBlastQuery: 1 gaaagagcatctacggtga 19Query: 1 gaaagagcatctacggtga 19
||||||||||| |||| ||||||||||||| |||| ||
Sbjct: 2393 gaaagagcatccacggSbjct: 2393 gaaagagcatccacgg--ga 2376ga 2376
2929
17/1917/19
(89%)(89%)
W7W7
e 500e 500
G 1G 1
q 2 r 2q 2 r 2
+2+2 --22 GG --11
EE --22
--33
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SmithSmith--Waterman vs. Blast ResultsWaterman vs. Blast Results
Percent Identity: 89% ,GATA3 gene
> gi|4503928|ref|NM_002051.1| Homo sapiensGATA binding protein 3
(GATA3), mRNA
Length = 2365
Score = 31.7 bits (38), Expect = 0.041
Identities = 19/19 (100%)
Strand = Plus / Plus
Query: 1 ctttttaacatcgacggtc 19
|||||||||||||||||||
Sbjct: 299 ctttttaacatcgacggtc 317
SWN hit-4 bin Blast hit-1 bin W7 G1 r2 q2 e500 E2
Original Query Sequence: CTTTTTAACATCGACGGTC
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SmithSmith--Waterman vs. Blast ResultsWaterman vs. Blast Results
> gi|4503928|ref|NM_002051.1| Homo sapiens GATA binding protein 3
(GATA3), mRNA
Length = 2365
Score = 31.7 bits (38), Expect = 0.041
Identities = 19/19 (100%)
Strand = Plus / Plus
Query: 1 ctttttaacatcgacggtc 19
|||||||||||||||||||
Sbjct: 299 ctttttaacatcgacggtc 317
> gi|4557424|ref|NM_001248.1| Homo sapiens ectonucleosidetriphosphate
diphosphohydrolase 3 (ENTPD3), mRNA
Length = 2797
Score = 24.6 bits (29), Expect = 5.7
Identities = 17/19 (89%), Gaps = 1/19 (5%)
Strand = Plus / Minus
Query: 1 aa-aatactgagagaggga 18
|| ||||||||| ||||||
Sbjct: 2044 aagaatactgagggaggga 2026
> gi|4503928|ref|NM_002051.1| Homo sapiensGATA binding protein 3
(GATA3), mRNA
Length = 2365
Score = 31.7 bits (38), Expect = 0.041
Identities = 19/19 (100%)
Strand = Plus / Plus
Query: 1 ctttttaacatcgacggtc 19
|||||||||||||||||||
Sbjct: 299 ctttttaacatcgacggtc 317
SWN hit-1 bin
Blast hit-4 bin
Original Query Sequence: AAAATACTGAGAGAGGGAG
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Conclusions and Future WorkConclusions and Future Work
Produce more conclusive statistics for occurrences of Produce more conclusive statistics for occurrences of more accurate Smithmore accurate Smith--Waterman resultsWaterman results
No consensus exists as to which hits are consideredNo consensus exists as to which hits are considereddangerous or significant for crossdangerous or significant for cross--hybridizationhybridization
Creation of a positionCreation of a position--specific matrixspecific matrix
Mutation tolerance on the 5 endMutation tolerance on the 5 end
Low tolerance on the 3 endLow tolerance on the 3 end GU wobbleGU wobble
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ReferencesReferences Novina, C and Sharp, P.Novina, C and Sharp, P. The RNAi revolution.The RNAi revolution.
Nature. 2004 Jul 8;430(6996):161Nature. 2004 Jul 8;430(6996):161--4.4. Dorsett, Y and Tuschl, T.Dorsett, Y and Tuschl, T. siRNAs: applications insiRNAs: applications in
functional genomics and potential asfunctional genomics and potential astherapeutics.therapeutics. Nat Rev Drug Discov. 2004Nat Rev Drug Discov. 2004
Apr;3(4):318Apr;3(4):318--29.29. Snove, O Jr. and Holen, T.Snove, O Jr. and Holen, T. Many commonlyMany commonly
used siRNAs risk off used siRNAs risk off--target activity.target activity. BiochemBiochemBiophys Res Commun. 2004 Jun 18;319(1):256Biophys Res Commun. 2004 Jun 18;319(1):256--63.63.
Paroo, Z and Corey, DR.Paroo, Z and Corey, DR. Challenges for RNAi inChallenges for RNAi invivo.vivo. Trends Biotechnol. 2004 Aug;22(8):390Trends Biotechnol. 2004 Aug;22(8):390--4.4.
Amarzguioui, M. et al.Amarzguioui, M. et al. Tolerance for mutationsTolerance for mutationsand chemical modifications in siRNAand chemical modifications in siRNA. Nucl Acids. Nucl AcidsResearch. 2003; 31(2)589Research. 2003; 31(2)589--595.595.
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AcknowledgementsAcknowledgements
Dr. Cecilie BoysenDr. Cecilie Boysen (advisor) Parcel Scientific Staff (advisor) Parcel Scientific Staff
David MeyerDavid Meyer Paracel Software EngineerParacel Software Engineer
Stephanie PaoStephanie Pao Paracel Technical Sales EngineerParacel Technical Sales Engineer
Frances TongFrances Tong Paracel InternParacel Intern
William WhiteWilliam White Paracel Technical WriterParacel Technical Writer
Southern Ca lifornia Bioinformat ics Inst it ut e 2004 Fa cult ySout hern Ca lifornia Bioinformat ics Inst it ut e 2004 Fa cult ya nd Staff :a nd Staff :Dr. Ja mil Moma nd, Dr. Na ncy Wa rt erDr. Ja mil Moma nd, Dr. Na ncy Wa rt er--Perez,Perez,Dr. Sa ndra Sha rp & Dr. Wendie Johnst on,Dr. Sa ndra Sha rp & Dr. Wendie Johnst on,& Ja ckie Leung& Ja ckie Leung
Fellow int ernsFellow int erns NIH & NSFNIH & NSF
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Short interfering RNA
Mechanism
Post-transcriptional gene
silencing.
Novina, C and Sharp, P. The RNAi
revolution. Nature Vol 430. July 8,
2004.
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Dorsett, Y and Tuschl, T.
siRNAs: applications in
functional genomics and
potential as therapeutics. Nat
Rev Drug Discov. 2004
Apr;3(4):318-29.
�Reverse genetic approaches ± expensive and time consuming
�siRNAmay be chemically synthesized or expressed from DNA vectors
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MicroRNAsMicroRNAs
Short RNAs 19Short RNAs 19--25 nucleotides25 nucleotides
Abundant, single stranded RNAs encoded inAbundant, single stranded RNAs encoded ingenomes of most multicellular organisms: from fewgenomes of most multicellular organisms: from fewthousand to 40,000 molecules per cellthousand to 40,000 molecules per cell
Some evolutionarily conserved andSome evolutionarily conserved anddevelopmentally regulateddevelopmentally regulated
Translational silencing.
Picture from:
Novina, C and Sharp, P. The RNAi
revolution. Nature Vol 430. July 8,
2004.
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Differences between siRNA andDifferences between siRNA and
miRNAmiRNAsiRNAsiRNA
Promote the cleavagePromote the cleavageor degradation of or degradation of
mRNAsmRNAs Sense strand hasSense strand has
exactly the sameexactly the samesequence as the target sequence as the target
strandstrand Target genes orTarget genes or
genetic elements fromgenetic elements fromwhich they originatedwhich they originated
miRNAmiRNA
Regulate theRegulate theexpression of mRNAs;expression of mRNAs;
transcription is not transcription is not impeded and mRNAsimpeded and mRNAsnot destroyednot destroyed
Imperfect baseImperfect base--pairingpairing
between mRNA targetsbetween mRNA targetsand miRNAand miRNA
Regulate separateRegulate separategenesgenes
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Interchangeability of siRNAs andInterchangeability of siRNAs and
miRNAsmiRNAs miRNA may act like siRNAmiRNA may act like siRNA
* perfect or near* perfect or near--perfect complementarity toperfect complementarity to
cellular mRNAscellular mRNAs Could siRNA also work like miRNA?Could siRNA also work like miRNA?
* synthetic siRNA partially complementary to* synthetic siRNA partially complementary to
reporter gene inhibited its expressionreporter gene inhibited its expression Distinction between single site with almost Distinction between single site with almost
exact complementarity and numerous partiallyexact complementarity and numerous partiallycomplementary binding sitescomplementary binding sites
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Laboratory and ClinicalLaboratory and Clinical
Applications of siRNAApplications of siRNA In C. elegans, simple experiment: inject dsRNA,In C. elegans, simple experiment: inject dsRNA,
soak in dsRNA solution, or feed with bacteriasoak in dsRNA solution, or feed with bacteria
expressing dsRNAexpressing dsRNA In worms, screening for obesity and ageingIn worms, screening for obesity and ageing
In fruitflies, purified long dsRNA used to identifyIn fruitflies, purified long dsRNA used to identifyroles of genes in cholesterol metabolism androles of genes in cholesterol metabolism andheart formationheart formation
Therapeutic potential of siRNAs for humansTherapeutic potential of siRNAs for humans
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FileFile TypeType BasesBases SequencesSequences # of Oligos# of Oligos
BRCA1BRCA1 fastafasta 32433243 11 32553255
GATA3GATA3 fastafasta 30703070 11 30703070
HLAHLA--moleculemolecule fastafasta 29182918 11 29182918
InsulinInsulin--likelike--
growthgrowth--factor factor
fastafasta 49894989 11 49714971
InterleukinInterleukin--receptor receptor
fastafasta 14511451 11 14331433
NFKB1NFKB1 fastafasta 41044104 11 41864186
Serine kinaseSerine kinase fastafasta 35063506 11 34883488
SerotoninSerotonin--
receptor receptor
fastafasta 19271927 11 19091909
TNF2TNF2 fastafasta 16691669 11 16511651
VinculinVinculin fastafasta 56475647 11 56295629
TotalTotal 3255432554 1010
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Paroo, Z and Corey, DR. C hallenges for RNAi in vivo.
Trends Biotechnol. 2004 Aug;22(8):390-4.