dna assembly with gaps: simulating sequence evolution

DNA Assembly with Gaps: Simulating Sequence Evolution

Reed A. CartwrightDepartment of GeneticsUniversity of Georgia

3.12.2005 RA Cartwright [email protected] - http://scit.us/

2

Synopsis

Explain the importance of simulations.

Introduce Dawg, a new sequence simulation program.

Example usage of Dawg.


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Why Simulate Phylogenies?

Biologists use many techniques to reconstruct phylogenies based on biological data.

However, true phylogenies are unknown, except for a few instances.

How then can we test the accuracy of these reconstruction methods?

Use simulations.


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Why Simulate Phylogenies?

Techniques are often based on certain models of evolution.

Simulating sequence evolution based on these models produces an ideal situation to test the techniques.

Using other models can test how robust a technique is.


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Testing Procedure

A B C DA AATTCTTTGAGTTAAB AATTCTTTGAGTTAAC AATTCTTAAAGTTAAD AATTCTTAAAGTTAA

A AAAAGATAAAGCAAA--AB GAAAGATAAAGCAAA--AC GAAAGATAAAGAAAAACAD GAAAGATAAAGAAAAACA

A B C D

A B C D

1. Start with a “known” tree.

2. Simulate sequencesets based on the tree.

3. Estimate the treesof the simulated data.

4. Compare estimated treesto the original tree.


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Simulating Evolution

Proper simulation of molecular evolution should include both substitutions and indels.

However, existing programs either do not include indels or use an unjustified model of indel formation.

Dawg was created to address this gap.


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What is Dawg?

Dawg stands for “DNA Assembly with Gaps.”

A portable and robust program for simulating molecular evolution.

Development Website: http://scit.us/dawg/


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Comparing Software

Feature Seq-Gen Evolver Rose Dawg

Indels Yes Yes

Indel Parameter Estimator

Yes

Recombination Yes Yes

Substitution GTR GTR PAM GTR

Rate Heterogeneity Γ+I Γ Γ+I Γ+I

Input Format Switch File File File

Unix Yes Yes Yes Yes

Mac OS X Yes Yes Yes Yes

Win32 Yes Yes Yes


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Parameters Tree phylogeny TreeScale coefficient to scale branch lengths by Sequence root sequences Length length of generated root sequences Rates rate of evolution of each root nucleotide Model model of evolution: GTR|JC|K2P|K3P|HKY|F81|F84|TN Freqs nucleotide (ACGT) frequencies Params parameters for the model of evolution Width block width for indels and recombination Scale block position scales Gamma coefficients of variance for rate heterogeneity Alpha shape parameters Iota proportions of invariant sites GapModel models of indel formation: NB|PL|US Lambda rates of indel formation GapParams parameter for the indel model Reps number of data sets to output File output file Format output format: Fasta|Nexus|Phylip|Clustal GapSingleChar output gaps as a single character GapPlus distinguish insertions from deletions in alignment LowerCase output sequences in lowercase Translate translate outputed sequences to amino acids NexusCode text or file to include between datasets in Nexus format Seed PRNG seed (integers)


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Sample Input File# example.dawgTree = ((AY727331:0.001359,AY727330:0.001359):0.084512,

(AY727327:0.006116,AY727326:0.006116):0.079756);Model = "GTR"Params = {1.08031, 2.45581, 0.44452, 1.09145, 4.06519, 1.00000}Freqs = {0.353470, 0.143681, 0.178206, 0.324643}Length = 300Lambda = 0.143120GapModel = "NB"GapParams = {1, 0.753247}Format = "Clustal"File = "example.aln"Seed = 1981


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CLUSTAL multiple sequence alignment (Created by DAWG Version 1.0.0)

AY727326 TTCGAAAATATGTTAGTACTCAATATGAATTCTTTGAGTTAAAAAAGATAAAGCAAA--AAY727327 TTCGAAAATATGTTAGTACTCAATATGAATTCTTTGAGTTAAGAAAGATAAAGCAAA--AAY727330 TTCAAAAATATGCTAGGACTGAATATGAATTCTTAAAGTTAAGAAAGATAAAGAAAAACAAY727331 TTCAAAAATATGCTAGGACTGAATATGAATTCTTAAAGTTAAGAAAGATAAAGAAAAACA

AY727326 ATACATAATGTGATTTCAATATTCCAATTACCTAACAATACGGCTATCAATTAAACGATTAY727327 ATACATAATGTGATTTCAATATTCCAATTACCTAACAATACGGCTATCAATTAAACGATTAY727330 GTACATAATGTAAA----TTATTGCAA---------AAAACGGCTAACAATTAGACGATTAY727331 GTACATAATGTAAA----TTATTGCAA---------AAAACGGCTAACAATTAGACGATT

AY727326 TTAGGATTACACCGACAAATATTAGGCCGATATGAATTTAACATCATGTTGTATTTAGATAY727327 TTAGGATTACACCGACAAATATTAGGCCGATATGAATTTACCATCATGTTGTATTTAGATAY727330 TTAGGATTACGCTGACAAATATTAGGATGATATTAATTTA------TCTTGTATTTAGATAY727331 TTAGGATTACGCTGACAAATATTAGGATGATATTAATTTA------TCTTGTATTTAGAT

AY727326 GCTGTCTTTTATTAACATTCATCATTAAAT-TTGGAACCTTTTGCATTTAAGAAGTACATAY727327 GCTGTCTTTTATTAACATTCATCATTAAAT-TTGGAACCTTTTGTATTTAAGAAGTACATAY727330 GCTGTCTTTTATCAACATTCATCACTAGATATTGGAACCTATTGCATCTAAGAAGTACATAY727331 GCTGTCTTTTATCAACATTCATCACTAGATATTGGAACCTATTGCATCTAAGAAGTACAT

AY727326 GTTTAATAGTGTTTAAAA-TATATATGAAATTGATCATAAGGA---TCTATAAATGCGGTAY727327 GTTTAATAGTGTTTATAA-TATATATGAAATTGATCGTAAGGA---TCTATAAATGCAGTAY727330 GTTTAATAGGGTT-AAAACTATATATGAAGTCGATTATAAGGAATTTCTATAAATGTAGCAY727331 GTTTAATAGGGTT-AAAACTATATATGAAGTCGATTATAAGGAATTTCTATAAATGTAGC

AY727326 TCTTCAATTTCTTGAY727327 TCTTCAATTTCTTGAY727330 TCTTCAATTTCCTAAY727331 TCTTCAATTTCCTA


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Estimating Indel Rate

Dawg would be of little benefit if biologists could not estimate parameters of indel formation from real data.

Dawg’s indel model allows such estimation, which is implemented in a Perl script, lambda.pl.


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Example Usage:Confidence Interval of Indel Rate

I aligned the sequences of chloroplast trnK introns from two Hibiscus and two Prunus species.

Using Paup*, I estimated the phylogeny and substitution parameters.

Using lambda.pl, I estimated the indel formation parameters.


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Example Usage

From these estimated parameters of evolution, I constructed an input file for Dawg.

From the input file Dawg produced a thousand simulated sequence sets.

The rate of indel formation was estimated for each of the simulated sequences.


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Results

The estimated rate of indel formation was 0.143120.

Bootstrapping gave a 95% CI of 0.078530 to 0.213560.

Biologically this is 8 to 21 indels per 100 substitutions.


16

Synopsis

Explain the importance of simulations.

Introduce Dawg, a new sequence simulation program.

Example usage of Dawg.


17

Thanks

Marjorie Asmussen Wyatt Anderson John Avise Jim Hamrick Ron Pulliam Paul Schliekelman

Jeff Ross-Ibarra Beth Dakin Douglas Theobald Yong-Kyu Kim

dna assembly with gaps: simulating sequence evolution

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