phylogenetic reconstruction based on rna secondary structural alignment
DESCRIPTION
Phylogenetic Reconstruction based on RNA Secondary Structural Alignment. Benny Chor, Tel-Aviv Univ. Joint work with Moran Cabili, Assaf Meirovich, and Metsada Pasmanik-Chor. Phylogenetic Trees Based on What ? Morphology (1800 - ) Single gene sequence (DNA or AA) (1960 - ). - PowerPoint PPT PresentationTRANSCRIPT
Phylogenetic Reconstruction based on RNA Secondary
Structural Alignment
Benny Chor, Tel-Aviv Univ.
Joint work with Moran Cabili, Assaf Meirovich, and Metsada Pasmanik-Chor
Phylogenetic Trees Based on What ?
• Morphology (1800 - )
• Single gene sequence (DNA or AA)
(1960 - )
Phylogenetic Trees Based on What ?
• Whole genomes (2002 - )
1. Find a reliable metric between pairs of objects.
2. Design / choose / modify a good algorithm for determining metric (pairwise distances).
3. Compute distance matrix.
4. Construct a Neighbor Joining tree from the distance matrix.
5. As a sanity check, compare resulting tree to
“standard & accepted” ones.
NJ
More Sources to Base Phylogeny On?A Proposed, Metric Induced Approach
Metric Induced ApproachWas already applied (fairly successfully), e.g.
for constructing phylogenies based on whole
genomes/proteomes (Burstein et al., 2005),
and others, based on metabolic networks
(Tuller et al., 2006).
Of course distances that are
appropriate to each domain must
be applied (or especially designed).
NJ
Can phylogenetic reconstruction be based on RNA secondary structures ?
Our Question
Answer: Yes, And Even Quite Well
Archaea
Eukarya
Bacteria
Our tree, based on secondary structs.of 16s rRNA from 91 species
1. Find an efficient alignment algorithm (similarity based) pair-wise RNA secondary structures.
2. Transform similarity to distance.
3. Use RNA databases to get the RNA molecules
and structures. Apply the algorithm to compute
the distance for each pair of molecules.
4. Run NJ to produce trees.
Metric Induced Approach: Specifics
- We chose to use RSmatch: A sophisticated dynamic programming algorithm, based on the “dot bracket” representation of the secondary structure. J. Liu , J.T. Wang , J. Hu , B. Tian. BMC Bioinformatics 2005 , 6:89.
- RSmatch sorts each dot and bracket to components, and then compares components according to their order in the secondary structure.
- RSmatch employs both sequences and structures.
- Complexity: O(nm), where n and m are the lengths of the two
RNA molecules that are compared.
TAATTATCGGAAGCAGTGCCTTCCATAATTA
( ( ( ( ( ( ( . ( ( ( ( ( . . . . . . ) ) ) ) ) ) ) ) ) ) ) )
The Alignment Algorithm Chosen
From Similarity to Distance
In transforming the scoring matrix from similarity to distance, we tried to preserve the ratios between mismatches values, and of course lower similarity should imply higher distance.
Distance metric requirements:
Symmetry, Δ inequality, non negativity, self distance=0
Actual Distance Matrices: Higher Mismatch Penalties at “Dots”
AU CG GC GU UA UG
AU 0 1 1 0.5 0.5 0.5
CG 1 0 0.5 1 1 1
GC 1 0.5 0 1 1 1
GU 0.5 1 1 0 0.5 0.5
UA 0.5 1 1 0.5 0 0.5
UG 0.5 1 1 0.5 0.5 0
A C G U
A 0 2 2 2
C 2 0 2 2
G 2 2 0 2
U 2 2 2 0
- Gap cost : 3 per nucleotide involved.
- Δ inequality : mismatch < 2* gap cost
DBs of Reliable Secondary Struc.
• RNaseP DB:http://www.mbio.ncsu.edu/RNaseP/
Sequences length: ~300 - 400 (+/-) nucleotides
DBs constructed with manual intervention
RNaseP function:
Cleaves off an extra, or precursor, sequence of RNA on tRNA molecules.
• 16S rRNA:Comparative RNA Web Site: http://www.rna.icmb.utexas.edu/
Sequences length: ~1,500 (+/-) nucleotides
16S function:
In charge of tRNA binding and formation of peptide bonds during translation.
Our results …ahhm… trees
RNaseP Tree, 51 SpeciesSecondary structure based tree
• Good partition to 3 kingdoms.• Bacteria (characterized by Bxy) also look good.
RNaseP 51 SpeciesSequence based tree
Eukarya
Bacteria
Archaea
Eukaryotes are not monophyletic (yeast external).
16s rRNA – 20 Species Secondary structure based
tree
Fungi
Bacillariophyta
Viridaeplanatae
Mammalia
Amphibia
16s rRNA –91 SpeciesSecondary structure based tree
Eukarya
Bacteria
Archaea
After completing this project, we discovered a related, earlier work from David Penny’s group. When determining evolutionary relationships between some catalytic RNA molecules, they constructed a 16S rRNA tree based on a similar “distance approach”.
We compared our results to
the trees published in their article
(using a different distance algorithm,
RNAdistance, by Shapiro & Zhang).
Collins et al., 2000
Collins et al., 2000.
Collins’ 16s rRNA sequence based tree
Collins’ 16s r RNA secondary struct based tree
16 Species
Bacteria
Archaea
Bacteria
Archaea
Our Tree, 13 Out of 16 Collins’ Species
Secondary structure based treeArchaea
Bacteria
A Close Look at the Trees
Collins’ 16s rRNA seq based tree
Our 16s second. struct. tree
Collins’ 16s second. struct. based tree
outgroups
A Close Look at Sec. Strucs. Supports a “Thermoplasma Outgroup” Theory
Methanobacteruim Methanococcus Thermoplasma
Conclusions
1. Encouraging results
2. Accuracy of structure based trees is comparable to sequence based trees.
3. Warning: Reliable secondary structures
are crucial for accurate tree reconstruction.