Non-coding RNA

1
Non-coding RNA

• William Liu
• CS374 Algorithms in Biology
• November 23, 2004

2
Non-Coding RNA

• Background Basics
• Biology Overview
• Why ncRNA - Central Dogma?
• Problem Space
• HMM/sCFG Solution
• Paper
• Pair HMMs on Tree Structures
• Alignment of Trees, Structural Alignment
• Experimental Evaluation
• Conclusion

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Central Dogma of Molec. Bio.
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Biology Overview

• RNA merely plays an accessory role
• Complexity is defined by proteins encoded in the
  genome

5
Biology Overview

• Non-coding RNA (ncRNA) is a RNA molecule that
  functions w/o being translated into a protein
• Most prominent examples Transfer RNA (tRNA),
  Ribosomal RNA (rRNA)

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Why Non-coding RNA

• Protein-coding genes cant account for all
  complexity
• ncRNA is important!
• Gene regulators

Genome Biol. 2002 Beyond The Proteome
Non-coding Regulatory RNAs
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Non-coding RNA Problems

• Finding ncRNA genes in the genome locate these
  genes
• Finding Homologs of ncRNA figure out what they do

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Finding ncRNA Genes

• Protein Approaches
• Statistically biased (codon triplets)
• Open Reading Frames
• ncRNA Approaches
• High CG content (hyperthermophiles)
• Promoter/Terminator identification (E. Coli)

Comparative Genome Analysis
Comparative Genome Analysis
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Genetic Code
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Similarity Searching

• Proteins
• BLAST, Sequence Alignment (DP)
• Genes that code for proteins are conserved across
  genomes (e.g. low rate of mutation)
• ncRNA
• Secondary structure usually conserved
• Alignment scoring based on structure is imperative

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ncRNA Sequence vs Structure
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Alignment Approaches

• sCFGs Modeling secondary structure, scoring
  sequences
• HMM for scoring of sequence and secondary
  structure alignment

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Pair HMMs on Tree Structures

• Outline
• Alignment on Trees
• Structural Alignment
• Secondary Structure Representation
• Hidden Markov Model
• Recurrence Relations
• Experimental Evaluation
• Future Work

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Alignment on Trees
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Structural Alignment

• Problem Given an RNA sequence with known
  Secondary Structure and an RNA sequence (unknown
  structure), obtain the optimal alignment of the
  two

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Structural Representation

• Skeletal Tree

?(?, ?) Branch Structure ?(X, ?, Y)
Base-pairs ?(X, ?) or ?(?, Y) Unpaired
bases X,Y ?A,U,G,C
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Hidden Markov Model

• M Match state, I Insertion state, D Deletion
  state
• ?XY State transition probability from X to Y
• ?X Initial probability
• Emission probability for pair x,y
• X,Y ? M,I,D

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Notation

• Let wa1a2an be an unfolded RNA sequence of
  length n
• Let wi denote ith symbol in w
• Let wi,j denote a substring aiai1aj of w

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Notation

• Let T be a skeletal tree representing a folded
  RNA sequence (known structure)
• Let v(j) denote the label of node j in tree T
• Let Tj denote the subtree rooted at node j in
  tree T
• Let jn denote the nth child of node j in tree T

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Recurrence Relation (Match)
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Recurrence Relation (Delete)
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Recurrence Relation (Insert)
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Structural Alignment

• Intuition Given the ncRNA sequence, b with
  unknown structure, generate a predicted folded
  structure for b, align the resulting tree with
  the ncRNA with known secondary structure a.
• Complexity O(K M N3 )
• K states in pair HMM,
• M size of skeletal tree,
• N length of unfolded sequence

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Experimental Evaluation

• Dynamic Programming to calculate recurrence
  relations, prototype system to execute algorithm
• Experiments on 2 families of RNA Transfer RNAs
  and Hammerhead Ribozyme

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Parameters
Gorodkin et al. (1997)
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Results tRNA
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Results Hammerhead Ribozyme
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Future Work

• Since based on dynamic programming (of pairwise
  alignment), many DP techniques can apply
• Refine emission probabilities, relate score
  matrix (reliable alignment for RNA families)

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Conclusions

• ncRNA space is quite open - no really great
  techniques yet
• How many ncRNA genes are there?
• Absence of evidence ? evidence of absence
• Eddys call to arms

it is time for RNA computational biologists to
step up
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Thanks!
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References

• Sakakibara, K., Pair Hidden Markov Models on
  Tree Structures, Bioinformatics, 19232-240,
  2003
• Eddy, S., Computational Genomics of Noncoding
  RNA Genes, Cell, Vol 109137-140, 2002
• Szymanski, M., Barciszewski, J., Beyond The
  Proteome Non-coding Regulatory RNAs