RNA & NKS Erik A. Schultes Hedgehog Research hedgehogresearch.info June 16, 2006

5 3 Ribonucleic Acid: Universal biopolymer Linear, polarized

5 3 C ytosine U racil A denine G uanine Ribonucleic Acid: Universal biopolymer Linear, polarized 4 distinct nitrogenous bases (nt) RNA can store genetic info (like DNA)

5 3 C ytosine U racil A denine G uanine Ribonucleic Acid: Universal biopolymer Linear, polarized 4 distinct nitrogenous bases RNA can store genetic info (like DNA) Base-pairing rules: A with U C with G

5 3 C ytosine U racil A denine G uanine 5 3 C ytosine U racil A denine G uanine

Double-stranded RNA Helix

5 3 C ytosine U racil A denine G uanine Ribonucleic Acid: Universal biopolymer Linear, polarized 4 distinct nitrogenous bases RNA can store genetic info (like DNA) Base-pairing rules: A with U C with G RNA can act as an enzyme (like proteins)

Primary Structure Single-stranded RNA:

Primary Structure Secondary Structure Single-stranded RNA:

Primary Structure Secondary Structure Tertiary Structure Single-stranded RNA:

Hammer head VS HDV Group I Group II RNAse P Hairpin Single-stranded RNA:

16S rRNA Single-stranded RNA:

16S rRNA Universal Tree of Life

A New Kind of Science by Stephen Wolfram In our everyday experience with computers, the programs that we encounter are normally set up to perform very definite tasks.

In our everyday experience with computers, the programs that we encounter are normally set up to perform very definite tasks. Key idea: What happens if one instead just looks at simple arbitrarily chosen programs, created without any specific task in mind. A New Kind of Science by Stephen Wolfram

In our everyday experience with computers, the programs that we encounter are normally set up to perform very definite tasks. Key idea: What happens if one instead just looks at simple arbitrarily chosen programs, created without any specific task in mind. How do such programs typically behave? A New Kind of Science by Stephen Wolfram

computer (hardware) RNA molecule program (software) nucleotide sequence In our everyday experience with computers, the programs that we encounter are normally set up to perform very definite tasks. Key idea: What happens if one instead just looks at simple arbitrarily chosen programs, created without any specific task in mind. How do such programs typically behave? A New Kind of Science by Stephen Wolfram

In our everyday experience with RNAs, the sequences that we encounter are normally set up to perform very definite tasks. Key idea: What happens if one instead just looks at simple arbitrarily chosen sequences, created without any specific task in mind. How do such sequences typically behave? /. computer (hardware) RNA molecule /. program (software) nucleotide sequence A New Kind of Science by Stephen Wolfram

What do we mean by: RNA & NKS Arbitrary sequence? RNA behavior?

What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior?

What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior? folding dynamics

Never converges on a unique, specific fold Rapidly converges on a unique, specific fold What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior? folding dynamics

Never converges on a unique, specific fold Rapidly converges on a unique, specific fold What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior? folding dynamics Helix Poly(U) OrderedDisordered

What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior? folding dynamics Evolved ComplexNever converges on a unique, specific fold Rapidly converges on a unique, specific fold Helix Poly(U) OrderedDisordered

What do we mean by: RNA & NKS generated by random processArbitrary sequence? RNA behavior? folding dynamics Evolved Complex Rapidly converges on a unique, specific fold Helix Ordered Never converges on a unique, specific fold Poly(U) Disordered Classes I & IIClass IV Class III

1. Lead II chemical probing secondary structure uniqueness of folding 2. Native gel electrophoresis uniqueness of folding size of fold 3. Analytical centrifugation size & shape of fold Analyzing RNA Behavior RNA & NKS

Control Sequences tRNA PHE (76nt) HDV (85nt) Ligase (87nt) Reference Sequence Poly(U) Choosing Arbitrary Sequences RNA & NKS

Control Sequences tRNA PHE (76nt) HDV (85nt) Ligase (87nt) Reference Sequence Poly(U) 85 Arbitrary Sequences 10 Permuted HDV (85nt) 10 Isoheteropolymer (85nt) Choosing Arbitrary Sequences RNA & NKS

Automated DNA Synthesis

Structure Probing with Pb ++ Pb ++

Structure Probing with Pb ++

Pb ++ Structure Probing with Pb ++

OH ladder T1 ladder Time HDV Structure Probing with Pb ++

OH ladder T1 ladder Time HDV Structure Probing with Pb ++

Arbitrary sequences acquire sequence-specific folds

8% (29:1) 100mM THE, pH7.5 30mM KCl 0, 1, 10mM MgCl 2 3W, 2000Vhr XC = 100mm T = ºC Native Gel Electrophoresis - +

Arbitrary sequences acquire compact folds

Inferring molecular size and shape from the concentration distribution of pure sample under a centrifugal filed. Sedimentation Velocity Experiments

Reference Sample Sedimentation Velocity Experiments

Meniscus Sedimentation Velocity Experiments RNA

A 260 r (cm) Sedimentation Velocity Experiments 40,000 RPM 100,000 Xg

tRNA Sedimentation Velocity Experiments A 260 r (cm) S=4.072 S D=8.45Ficks M=25.2kDa R s =26.2 Å

Arbitrary sequences acquire compact folds

The behavior of arbitrary RNA Arbitrary sequences frequently have compact, sequence specific folding - properties that have always been assumed to be evolutionarily derived. So far: 20 seq, 2 compositions = (1/2 postdoc)

The behavior of arbitrary RNA Arbitrary sequences frequently have compact, sequence specific folding - properties that have always been assumed to be evolutionarily derived. So far: 20 seq, 2 compositions = (1/2 postdoc) Next step: 35,000 seq, 1700 compositions = ($100M)

The behavior of arbitrary RNA Arbitrary sequences frequently have compact, sequence specific folding - properties that have always been assumed to be evolutionarily derived. Principle of Computational Equivalence weak RNA PCE: complex, biologically relevant folds are abundant in seq space

The behavior of arbitrary RNA Arbitrary sequences frequently have compact, sequence specific folding - properties that have always been assumed to be evolutionarily derived. Principle of Computational Equivalence weak RNA PCE: complex, biologically relevant folds are abundant in seq space strong RNA PCE: specific folds may be abundant in seq space

Distribution of Folds in RNA Sequence Space

Prototype Ribozymes

Intersection Sequence

Testing for Ligation & Cleavage

Connecting the Prototypes by Neutral Paths

Connecting the Prototypes by Neutral Paths Prototype Ligase 42 mutations

Connecting the Prototypes by Neutral Paths Prototype HDV Prototype Ligase 42 mutations 44 mutations

Intersection of Fitness Landscapes

1. RNA NN exist - seq space is highly redundant in folds 1. New folds from existing folds 2. RNAs with different sequences and folds could still share ancestry 2. Different NN are proximal Conclusion Biological Implications

NKS and Neutral Networks 1. Are INT sequences typical or rare? 2. Are sequences on NN typical or evolved?

NKS and Neutral Networks 1. Are INT sequences typical or rare? 2. Are sequences on NN typical or evolved? 3. Does CA rule space have NN? 4. If so, are there INT rules?

Acknowledgments David P. Bartel Whitehead Institute NSF/Alfred P. Sloan Fellowship TMF/Charles A. King Trust Fellowship