A Basic Introduction to A Basic Introduction to SFoldSFold

Kevin MacDonaldKevin MacDonald

December 7, 2004December 7, 2004

BI420 Final PresentationBI420 Final Presentation

Introduction to Gene KnockoutIntroduction to Gene Knockout

One method of studying gene expression and function is through One method of studying gene expression and function is through gene knockout. In this process the targeted gene is silenced gene knockout. In this process the targeted gene is silenced (inactivated) and the results are studied. (inactivated) and the results are studied.

One effective way in which genes are knocked out is through the One effective way in which genes are knocked out is through the use of small interfering RNAs (siRNAs), antisense oligonucleotides use of small interfering RNAs (siRNAs), antisense oligonucleotides and and transtrans-cleaving ribozymes. This is called RNA interference, -cleaving ribozymes. This is called RNA interference, RNAi.RNAi.

RNAi works by introducing siRNA, which are about 21 nucleotides RNAi works by introducing siRNA, which are about 21 nucleotides long, at the post-transcriptional phase to mRNA. The double-long, at the post-transcriptional phase to mRNA. The double-stranded siRNA induces gene silencing and is homologous to the stranded siRNA induces gene silencing and is homologous to the gene to be silenced.gene to be silenced.

RNAi continuedRNAi continued

Problems with RNAiProblems with RNAi1)1) siRNA has a short life span due to lack of stabilitysiRNA has a short life span due to lack of stability2)2) Lack of potency and effectiveness due to poor design of siRNAs Lack of potency and effectiveness due to poor design of siRNAs

and oligonucleotidesand oligonucleotides3)3) Cost EfficiencyCost Efficiency

SolutionsSolutions1)1) Increase lifespan of siRNA through conformational change: linear Increase lifespan of siRNA through conformational change: linear

siRNA short hairpin RNA (shRNA)siRNA short hairpin RNA (shRNA)2)2) Increase potency and cost efficiency through better designIncrease potency and cost efficiency through better design

-use of Target Accessibility Prediction -use of Target Accessibility Prediction and GC content analysisand GC content analysis

SFold provides an answer to all of these problems

siRNA production (InvivoGen)

Basics of SFoldBasics of SFold

Developed by Ye Ding and Charles Lawrence of the Wadsworth Developed by Ye Ding and Charles Lawrence of the Wadsworth Center, New York State Department of Public HealthCenter, New York State Department of Public Health

SFold is a software package that allows for Target Accessibility SFold is a software package that allows for Target Accessibility Prediction and rational design of siRNAs, antisense oligonucleotides Prediction and rational design of siRNAs, antisense oligonucleotides and and transtrans-cleaving ribozymes. It also provides general features and -cleaving ribozymes. It also provides general features and output for statistical RNA folding.output for statistical RNA folding.

How does SFold work?How does SFold work? -SFold uses a target accessibility algorithm combined with other -SFold uses a target accessibility algorithm combined with other algorithms that take into account empirical rules for siRNA design algorithms that take into account empirical rules for siRNA design (such as Tuschl’s rules) as well as RNA duplex thermodynamics(such as Tuschl’s rules) as well as RNA duplex thermodynamics

SFold Functions: siRNASFold Functions: siRNA

1.1. siRNA- performs target accessibility prediction and RNA duplex siRNA- performs target accessibility prediction and RNA duplex

thermodynamics for siRNA designthermodynamics for siRNA design 2.2. Input for siRNA: DNA sequence in either Plain Sequence, FASTA Input for siRNA: DNA sequence in either Plain Sequence, FASTA

or GenBank formator GenBank format

3.3. Output includes: Probability Profile of Accessibility Prediction, Output includes: Probability Profile of Accessibility Prediction, Loop Profiling, Internal Stability Profiling and siRNA score.Loop Profiling, Internal Stability Profiling and siRNA score.

-siRNA score indicates the potency of the -siRNA score indicates the potency of the designed siRNA (max score = 20)designed siRNA (max score = 20)

-SEE EXAMPLE USING Human Insulin Growth Factor II (NM 006546) -SEE EXAMPLE USING Human Insulin Growth Factor II (NM 006546)

SFold Functions: sOligoSFold Functions: sOligo

1.1. The function of sOligo is very similar to that of The function of sOligo is very similar to that of siRNA. Algorithms that take account of siRNA. Algorithms that take account of binding strength, GC content and avoidance of binding strength, GC content and avoidance of GGGG motifs are used to design antisense GGGG motifs are used to design antisense oligonucleotides.oligonucleotides.

2.2. Input is the same as for sRNAInput is the same as for sRNA

3.3. Output includes graphical accessibility Output includes graphical accessibility prediction profiles, listings of target sequences prediction profiles, listings of target sequences and antisense oligonucleotides, GC content and antisense oligonucleotides, GC content and oligo binding energiesand oligo binding energies

SFold Functions: sRibo and sRNASFold Functions: sRibo and sRNA

sRibo is used to design sRibo is used to design trans-trans-cleaving cleaving ribozymes for RNAiribozymes for RNAi

--Output includes graphical representation of Output includes graphical representation of ribozyme cleavage site probabilityribozyme cleavage site probability

sRNA provides general features for sRNA provides general features for statistical RNA foldingstatistical RNA folding

-Output includes graphical representation of the -Output includes graphical representation of the RNA molecule based upon free-energiesRNA molecule based upon free-energies

How does SFold solve the How does SFold solve the problems of RNAi?problems of RNAi?

SFold is the first program to take into account various SFold is the first program to take into account various aspects of RNA targeting nucleic acids into accountaspects of RNA targeting nucleic acids into account

--by analyzing target accessibility and GC content, it provides a by analyzing target accessibility and GC content, it provides a better probability of designing a more potent siRNA or antisense better probability of designing a more potent siRNA or antisense

oligonucleotideoligonucleotide

However, SFold is not perfect by any means and its However, SFold is not perfect by any means and its authors suggest using SFold along with a number of authors suggest using SFold along with a number of other methods when designing siRNAsother methods when designing siRNAs

--Currently there are studies being carried out to verify the predictions Currently there are studies being carried out to verify the predictions made by SFold, as well as to add to its functionsmade by SFold, as well as to add to its functions

ReferencesReferences

http://sfold.wadsworth.org/index.plhttp://sfold.wadsworth.org/index.pl Ding, Y.Ding, Y. and and Lawrence, C.E.Lawrence, C.E. (2004) Rational design of siRNAs with (2004) Rational design of siRNAs with

the the SSfold software. In fold software. In RNA Interference: from Basic Science to Drug RNA Interference: from Basic Science to Drug DevelopmentDevelopment, ed. Krishnarao Appasani, Cambridge University , ed. Krishnarao Appasani, Cambridge University Press. Press.

Ding, Y.Ding, Y. (2002) Rational statistical design of antisense (2002) Rational statistical design of antisense oligonucleotides for high throughput functional genomics and drug oligonucleotides for high throughput functional genomics and drug target validation. target validation. Statistica SinicaStatistica Sinica 1212, 273-296., 273-296.

http://www.invivogen.com/siRNA/siRNA_ohttp://www.invivogen.com/siRNA/siRNA_overview.htmverview.htm