target mrna abundance dilutes microrna and sirna activity aaron arvey ismb 2010 microrna mike needs...

Target mRNA abundance dilutes microRNA and siRNA activity

Aaron ArveyISMB 2010

MicroRNAMike needshelp todegrade all the mRNAtranscripts!

Target mRNA abundance dilutes microRNA and siRNA activity

Erik Larsson Chris Sander Christina Leslie Debbie Marks

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Background: Small RNAs mediate mRNA degradation

• Small RNAs are 19-25nt • RNA Induced Silencing

Complex (RISC)– Protein complex that uses small

RNA to guide degradation

• microRNAs– Processed from non-coding

genes

• siRNAs (for our purposes)– Transfected into the cell– Knockdown specific gene– Unintended “off-targets” are also

downregulated










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microRNA pathway

siRNA pathway

Background: Transfected small RNAs induce target mRNA degradation

• Double stranded RNA molecules are transfected into cell lines

• Concentrations of small RNA are very high, ~100nM

• Target mRNAs are degraded





microRNAs and siRNAs

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Background: Target Prediction

• microRNAs – Transcript 3’ UTR is most likely to

be targeted– microRNA 5’ “seed” region guides

targeting

• siRNAs– Off-targets have similar targeting

rules as microRNAs– Primary targets have nearly exact

complementarity





microRNA targets and siRNA off-targets

siRNA primary targets

microRNAs induce different amounts of downregulation



BigShift

LittleShift

Concept: Small RNAs with

many targets downregulate each individual target to a

lesser extent

Meta-analysis of high throughput studies to explore hypothesis

• 178 transfection experiments in HeLa and HCT116 cell lines– 61 miRNA-mimics (Lim 2005, Grimson 2007, He 2007, Linsley

2007, Selbach 2008)

– 98 siRNA (Kittler 2007, Anderson 2008, Jackson 2006, Schwarz 2006)

– 19 chimeras (Lim et al, 2005, Anderson 2008)

• Microarray assay pre- and post-transfection• RNA-Seq quantifies mRNA target abundance

(Morin 2008)



Downregulation is significantly correlated with target concentration





Downregulation of siRNA primary target and off-targets is significantly correlated with off-target concentration









Shared targets show that downregulation is determined by target abundance

Measure target abundance on all targets

Measure downregulation on shared targets



Pairwise examples

Examples of differential regulation on shared targets





Pairwise examplesQuickTime™ and a decompressor


• Smad5 downregulation– miR-155: -1.29– miR-106: -0.1

• Target abundance– miR-155: 142– miR-106: 315

• Differences– Downregulation: 1.19– Abundance: 173

Shared targets are more downregulated by microRNAs with fewer targets



Conclusion: Small RNAs with more targets downregulate each target to a lesser extent.

Consequences: Endogenous regulation by microRNAs

• Each microRNA is quantitatively unique– Definition of target should perhaps be different for different

microRNAs, targets are likely to be quantitatively different

• The cell as a very finely tuned system of regulation– Increase in one target mRNA detracts from downregulation of

another target mRNA– microRNA regulation is always using all available degradation

machinery (Khan et al2009), but is still stretched thin

• Evolutionary constraints– Possibility 1: anti-targets (mRNA transcripts that ‘avoid’ being

co-expressed with microRNA) enable the cell to avoid high target concentration

– Possibility 2: microRNA expression increases when target mRNAs increase, dosage compensation

Consequences: Target abundance limits siRNA activity

• Limits knockdown of primary target– May limit drug efficacy, especially in small

concentration– May limit functional genomic screens

• Limits the knockdown of off-targets– Increase in off-targets may actually

decrease toxicity (Anderson et al, 2008)

Functional Examples



Cancer:PTEN pseudogene 1 (PTENP1) regulates cell cycle by way of PTEN(Poliseno et al)

Environmental Response:Non-coding RNA regulates phosphate starvation response(Franco Zorrilla et al)



Kinetics

• Were we guaranteed to find this result?– No: Depends on dynamic range of kinetic relationship

• Degradation is a function of speed, time, and concentration– So far, we have only considered downregulation with respect to concentration

• Downregulation has been defined as the ratio:

• Can also consider the total number of molecules degraded v

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logxTx0

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⎝ ⎜

⎞

⎠ ⎟= log

x0 − v

x0

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⎝ ⎜

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⎠ ⎟

Background: RISC Kinetics

• Multi-turnover enzyme– Single loaded RISC is able to degrade many mRNA

transcripts (Hutvágner & Zamore, 2002)

• RISC is saturated with small RNA upon transfection (Khan et al, 2009)

• Degradation in lysate is very fast (Haley & Zamore, 2004)

[RISC] + [target] [RISC+target] [RISC] + [product]



Haley & Zamore (2004)

Kinetics in drosophila lysate

Pro

duct

(nM

)

Background: RISC Kinetics

• Degradation kinetics depend on target concentration

• 1nM RISC in lysate– Slope of line is velocity– Transcripts degraded at rate

of 72-300nM transcript/day

• Target concentration in cell is likely to be in the range 1-60nM

• 72nM > 60nM– Ignores transcriptional rate– Ignores cellular context– Ignores localization

Target Concentration (nM)

Cha

nge

in m

olec

ules

(vel

ocity

nM

/min

)

1nM

5nM

20nM

60nM

Velocity is correlated with target abundance and follows Michaelis-Menten kinetics

Velocity can be estimated by

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− x0 −xTx0

x0∑

x0 Assayed by RNA - Seq (or microarray)

xT / x0 Assayed by microarray

Velocity is correlated with target abundance and follows Michaelis-Menten kinetics



Concentration of Predicted Targets (RPN)

Vel

ocity

(a.

u.)

Questions




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ErikLarsson

ChrisSander

ChristinaLeslie

DebbieMarks





We control for several alternative explanations

• A+U content– Not correlated

• 3’ UTR length– Correlated, controllable by shared targets

• Expression of individual targets– Correlated, controllable by shared targets

Individual target abundance is correlated with downregulation

Caveats of shared-target analysis

• False positive rate may increase sub-linearly– If false positive rate increases with number of predicted

targets, becomes harder to control– The siRNA analysis completely controls for this (since

there is only a single primary target!)

• Length of UTR is 2x normal length in shared targets– Normal: 1167nt– Shared target: 2041nt– Longer 3’ UTR may lead to increased downregulation,

though this would not give preference for a specific microRNA

Methods: Target Prediction







Methods: Target Abundance


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Methods: Downregulation


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Time Course





Past Evidence - In Vivo

Franco-Zorrilla et al (2007)







Correlation between siRNA off-target abundance and primary target downregulation



Off Target Abundance

Log2

Exp

ress

ion

Rat

ioof

prim

ary

targ

et

Past Evidence: Dilution In Solution



Haley & Zamore (2004)

Past Evidence - Toxicity

Anderson et al (2008)

Past Evidence - Dilution In Cells

Ebert et al 2007

Normalization



target mrna abundance dilutes microrna and sirna activity aaron arvey ismb 2010 microrna mike needs...

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