title: Fast and accurate construction of ultra-dense consensus genetic maps using evolution strategy optimization.
abstract: Our aim was to develop a fast and accurate algorithm for constructing consensus genetic maps for chip-based SNP genotyping data with a high proportion of shared markers between mapping populations. Chip-based genotyping of SNP markers allows producing high-density genetic maps with a relatively standardized set of marker loci for different mapping populations. The availability of a standard high-throughput mapping platform simplifies consensus analysis by ignoring unique markers at the stage of consensus mapping thereby reducing mathematical complicity of the problem and in turn analyzing bigger size mapping data using global optimization criteria instead of local ones. Our three-phase analytical scheme includes automatic selection of ~100-300 of the most informative (resolvable by recombination) markers per linkage group, building a stable skeletal marker order for each data set and its verification using jackknife re-sampling, and consensus mapping analysis based on global optimization criterion. A novel Evolution Strategy optimization algorithm with a global optimization criterion presented in this paper is able to generate high quality, ultra-dense consensus maps, with many thousands of markers per genome. This algorithm utilizes "potentially good orders" in the initial solution and in the new mutation procedures that generate trial solutions, enabling to obtain a consensus order in reasonable time. The developed algorithm, tested on a wide range of simulated data and real world data (Arabidopsis), outperformed two tested state-of-the-art algorithms by mapping accuracy and computation time.
authors: Institute of Evolution, University of Haifa, Haifa, Israel.
authors: David
authors: D
authors: Mester
authors: Institute of Evolution, University of Haifa, Haifa, Israel.
authors: Yefim
authors: Y
authors: Ronin
authors: Center for Plant Genomics, Iowa State University, Ames, Iowa, United States of America.
authors: Patrick
authors: P
authors: Schnable
authors: Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, United State of America.
authors: Srinivas
authors: S
authors: Aluru
authors: Institute of Evolution, University of Haifa, Haifa, Israel.
authors: Abraham
authors: A
authors: Korol
mesh_terms: D000465:Algorithms; D016384:Consensus Sequence; D019143:Evolution, Molecular; D020641:Polymorphism, Single Nucleotide