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MBE Advance Access originally published online on August 3, 2009
Molecular Biology and Evolution 2009 26(11):2581-2593; doi:10.1093/molbev/msp174
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© 2009 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Research Articles

Biological Sequence Simulation for Testing Complex Evolutionary Hypotheses: indel-Seq-Gen Version 2.0

Cory L. Strope*, Kevin Abel*, Stephen D. Scott* and Etsuko N. Moriyama{dagger},{ddagger}

* Department of Computer Science and Engineering, University of Nebraska
{dagger} School of Biological Sciences, University of Nebraska
{ddagger} Center for Plant Science Innovation, University of Nebraska

E-mail: emoriyama2{at}unl.edu.

Accepted for publication July 29, 2009.

Sequence simulation is an important tool in validating biological hypotheses as well as testing various bioinformatics and molecular evolutionary methods. Hypothesis testing relies on the representational ability of the sequence simulation method. Simple hypotheses are testable through simulation of random, homogeneously evolving sequence sets. However, testing complex hypotheses, for example, local similarities, requires simulation of sequence evolution under heterogeneous models. To this end, we previously introduced indel-Seq-Gen version 1.0 (iSGv1.0; indel, insertion/deletion). iSGv1.0 allowed heterogeneous protein evolution and motif conservation as well as insertion and deletion constraints in subsequences. Despite these advances, for complex hypothesis testing, neither iSGv1.0 nor other currently available sequence simulation methods is sufficient. indel-Seq-Gen version 2.0 (iSGv2.0) aims at simulating evolution of highly divergent DNA sequences and protein superfamilies. iSGv2.0 improves upon iSGv1.0 through the addition of lineage-specific evolution, motif conservation using PROSITE-like regular expressions, indel tracking, subsequence-length constraints, as well as coding and noncoding DNA evolution. Furthermore, we formalize the sequence representation used for iSGv2.0 and uncover a flaw in the modeling of indels used in current state of the art methods, which biases simulation results for hypotheses involving indels. We fix this flaw in iSGv2.0 by using a novel discrete stepping procedure. Finally, we present an example simulation of the calycin-superfamily sequences and compare the performance of iSGv2.0 with iSGv1.0 and random model of sequence evolution.

Key Words: protein superfamily • sequence simulation • domains • motifs • indels

Sudhir Kumar, Associate Editor


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