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Towards more biological mutation operators in gene regulation studies

Towards more biological mutation operators in gene regulation studies
Towards more biological mutation operators in gene regulation studies
Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network level mutations. This paper analyses three such sequence level mutations (single-point mutation, transposition and gene duplication) for their frequency and effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.
gene regulatory networks, artificial genome, point mutation, sequence mutation, simulation
239-248
Watson, J.
b980aa6b-8b23-41f0-879c-3b6fc20e8d71
Geard, N.L.
b40f3147-322b-462f-9815-64576764fbba
Wiles, J.
4b566453-d3c4-441a-97bd-404c378d1f67
Watson, J.
b980aa6b-8b23-41f0-879c-3b6fc20e8d71
Geard, N.L.
b40f3147-322b-462f-9815-64576764fbba
Wiles, J.
4b566453-d3c4-441a-97bd-404c378d1f67

Watson, J., Geard, N.L. and Wiles, J. (2004) Towards more biological mutation operators in gene regulation studies. Biosystems, 76 (1-3), 239-248. (doi:10.1016/j.biosystems.2004.05.016).

Record type: Article

Abstract

Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network level mutations. This paper analyses three such sequence level mutations (single-point mutation, transposition and gene duplication) for their frequency and effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.

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More information

Published date: August 2004
Keywords: gene regulatory networks, artificial genome, point mutation, sequence mutation, simulation
Organisations: Electronics & Computer Science

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Local EPrints ID: 264053
URI: http://eprints.soton.ac.uk/id/eprint/264053
PURE UUID: 35fc119f-d31d-4dc4-b79c-a140c8905c65

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Date deposited: 23 May 2007
Last modified: 09 Dec 2019 20:12

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