Design of a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations

A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. This architecture is significant for Royal Road class fitness functions. Two real-life Systems Biology problems with such fitness functions are implemented here: evolution of the bacterial promoter rrnPl and of the enhancer of the Drosophila even-skipped gene. The effectiveness of the approach compared to standard GA is demonstrated on several benchmark and real-life tasks.

[1]  Donald H. Burke,et al.  Evolutionary Landscapes for the Acquisition of New Ligand Recognition by RNA Aptamers , 2003, Journal of Molecular Evolution.

[2]  J. Crutchfield,et al.  Optimizing Epochal Evolutionary Search: Population-Size Dependent Theory , 1998, Machine-mediated learning.

[3]  F. Varela,et al.  Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life , 1992 .

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  J. Whisstock,et al.  The Evolution of Enzyme Specificity in Fasciola spp. , 2003, Journal of Molecular Evolution.

[6]  W. Stemmer.  DNA shuffling by random fragmentation and reassembly: in vitro recombination for molecular evolution. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[7]  James P. Crutchfield,et al.  Statistical Dynamics of the Royal Road Genetic Algorithm , 1999, Theor. Comput. Sci..

[8]  L. Booker.  Foundations of genetic algorithms. 2: L. Darrell Whitley (Ed.), Morgan Kaufmann, San Mateo, CA, 1993, ISBN 1-55860-263-1, 322 pp., US$45.95 , 1994 .

[9]  W. Stemmer.  Rapid evolution of a protein in vitro by DNA shuffling , 1994, Nature.

[10]  Michael I. Jordan,et al.  Advances in Neural Information Processing Systems 30 , 1995 .

[11]  W. Fontana.  Modelling 'evo-devo' with RNA. , 2002, BioEssays : news and reviews in molecular, cellular and developmental biology.

[12]  J. Crutchfield,et al.  Optimizing Epochal Evolutionary Search: Population-Size Dependent Theory , 1998, Machine Learning.

[13]  Georges R. Harik,et al.  Foundations of Genetic Algorithms , 1997 .

[14]  S Bullock,et al.  Modelling the evolution of genetic regulatory networks. , 2006, Journal of theoretical biology.

[15]  Sio-Iong Ao,et al.  Advances in Computational Algorithms and Data Analysis , 2008 .

[16]  M. Negroni,et al.  Mechanisms of retroviral recombination. , 2001, Annual review of genetics.

[17]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[18]  D. Stern.  PERSPECTIVE: EVOLUTIONARY DEVELOPMENTAL BIOLOGY AND THE PROBLEM OF VARIATION , 2000, Evolution; international journal of organic evolution.

[19]  J. Crutchfield,et al.  Metastable evolutionary dynamics: Crossing fitness barriers or escaping via neutral paths? , 1999, Bulletin of mathematical biology.

[20]  Shumeet Baluja,et al.  Advances in Neural Information Processing , 1994 .

[21]  N. Patel,et al.  Evidence for stabilizing selection in a eukaryotic enhancer element , 2000, Nature.

[22]  M. Kimura,et al.  The neutral theory of molecular evolution. , 1983, Scientific American.

[23]  M. Ludwig,et al.  Functional evolution of noncoding DNA. , 2002, Current opinion in genetics & development.

[24]  J. Donelson,et al.  Mechanisms of Antigenic Variation in Borrelia hermsii and African Trypanosomes (*) , 1995, The Journal of Biological Chemistry.

[25]  R. Forman,et al.  Modeling the precision and robustness of Hunchback border during Drosophila embryonic development. , 2008, Journal of theoretical biology.

[26]  S. Aiyar,et al.  Contributions of UP Elements and the Transcription Factor FIS to Expression from the Seven rrn P1 Promoters inEscherichia coli , 2001, Journal of bacteriology.

[27]  S. Carroll.  Endless Forms The Evolution of Gene Regulation and Morphological Diversity , 2000, Cell.

[28]  A. Peirce.  Computer Methods in Applied Mechanics and Engineering , 2010 .

[29]  R. Rosenfeld.  Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[30]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[31]  V. Hakim,et al.  Design of genetic networks with specified functions by evolution in silico. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[32]  M. Kimura.  The role of compensatory neutral mutations in molecular evolution , 1985, Journal of Genetics.

[33]  R. Gourse,et al.  Control of rRNA expression in Escherichia coli. , 2003, Current opinion in microbiology.

[34]  J. Costas,et al.  Turnover of binding sites for transcription factors involved in early Drosophila development. , 2003, Gene.

[35]  Max B. Cooper,et al.  The evolutionary influence of binding site organisation on gene regulatory networks , 2009, Biosyst..

[36]  Max B. Cooper,et al.  Evolutionary modelling of feed forward loops in gene regulatory networks , 2008, Biosyst..

[37]  C. Glover,et al.  Gene expression profiling for hematopoietic cell culture , 2006 .

[38]  Melanie Mitchell,et al.  An introduction to genetic algorithms , 1996 .