Title: A novel strategy for plant breeding based on simulations of gene network models

Authors: X. Cai; S. Das; S.M. Welch

Addresses: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, PR China ' Electrical and Computer Engineering Department, Kansas State University, Manhattan, KS 66506, USA ' Agronomy Department, Kansas State University, Manhattan, KS 66506, USA

Abstract: This paper describes a new computational method to make predictions on the outcome of pair-wise crosses of plant lines limiting expensive laboratory breeding experiments to carry out crosses of the most promising pairs of lines. Compared to the well-known marker assisted breeding, the proposed approach approximates plant gene regulatory networks to estimate outcomes of all possible crossovers, thereby taking into account epistatic relationships between alleles. The proposed method is tested and compare with various breeding approaches on artificial NK landscape models and an extensive synthetic model of Arabidopsis plant's flowering time system. The results show our method outperforms other breeding strategies.

Keywords: plant breeding; GRN; gene regulatory networks; NAS; network assisted selection; MAS; marker assisted selection; NK fitness landscape models; simulation; gene network models; modelling; bioinformatics; epistatic relationships; alleles.

DOI: 10.1504/IJBRA.2013.056084

International Journal of Bioinformatics Research and Applications, 2013 Vol.9 No.5, pp.517 - 533

Received: 04 Jul 2011
Accepted: 19 Aug 2011
Published online: 18 Sep 2014 *

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