AlphaSim: Software for Breeding Program Simulation

被引:77
作者
Faux, Anne-Michelle [1 ]
Gorjanc, Gregor [1 ]
Gaynor, R. Chris [1 ]
Battagin, Mara [1 ]
Edwards, Stefan M. [1 ]
Wilson, David L. [1 ]
Hearne, Sarah J. [2 ]
Gonen, Serap [1 ]
Hickey, John M. [1 ]
机构
[1] Univ Edinburgh, Sch Vet Studies, Roslin Inst & Royal Dick, Easter Bush, Midlothian, Scotland
[2] CIMMYT, Texcoco, Mexico
来源
PLANT GENOME | 2016年 / 9卷 / 03期
基金
英国生物技术与生命科学研究理事会;
关键词
GENOMIC SELECTION; QUANTITATIVE TRAITS; COMPUTER-SIMULATION; RIDGE-REGRESSION; POPULATIONS; PREDICTION; VALIDATION; IMPUTATION; DOMINANCE; GENOTYPES;
D O I
10.3835/plantgenome2016.02.0013
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding programs in a series of steps: (i) simulate haplotype sequences and pedigree; (ii) drop haplotypes into the base generation of the pedigree and select single-nucleotide polymorphism (SNP) and quantitative trait nucleotide (QTN); (iii) assign QTN effects, calculate genetic values, and simulate phenotypes; (iv) drop haplotypes into the burn-in generations; and (v) perform selection and simulate new generations. The program is flexible in terms of historical population structure and diversity, recent pedigree structure, trait architecture, and selection strategy. It integrates biotechnologies such as doubled-haploids (DHs) and gene editing and allows the user to simulate multiple traits and multiple environments, specify recombination hot spots and cold spots, specify gene jungles and deserts, perform genomic predictions, and apply optimal contribution selection. AlphaSim also includes restart functionalities, which increase its flexibility by allowing the simulation process to be paused so that the parameters can be changed or to import an externally created pedigree, trial design, or results of an analysis of previously simulated data. By combining the options, a user can simulate simple or complex breeding programs with several generations, variable population structures and variable breeding decisions over time. In conclusion, AlphaSim is a flexible and computationally efficient software package to simulate biotechnology enhanced breeding programs with the aim of performing rapid, low-cost, and objective in silico comparison of breeding technologies.
引用
收藏
页数:14
相关论文
共 29 条
[1]  
Bernardo R., 2010, Breeding for Quantitative Traits in Plants
[2]   Prospects for genomewide selection for quantitative traits in maize [J].
Bernardo, Rex ;
Yu, Jianming .
CROP SCIENCE, 2007, 47 (03) :1082-1090
[3]   The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes [J].
Clark, Samuel A. ;
Hickey, John M. ;
Daetwyler, Hans D. ;
van der Werf, Julius H. J. .
GENETICS SELECTION EVOLUTION, 2012, 44 :4
[4]   Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting, and Benchmarking [J].
Daetwyler, Hans D. ;
Calus, Mario P. L. ;
Pong-Wong, Ricardo ;
de los Campos, Gustavo ;
Hickey, John M. .
GENETICS, 2013, 193 (02) :347-+
[5]   Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations [J].
Gorjanc, Gregor ;
Jenko, Janez ;
Hearne, Sarah J. ;
Hickey, John M. .
BMC GENOMICS, 2016, 17
[6]   Reliability of pedigree-based and genomic evaluations in selected populations [J].
Gorjanc, Gregor ;
Bijma, Piter ;
Hickey, John M. .
GENETICS SELECTION EVOLUTION, 2015, 47
[7]   Potential of genotyping-by-sequencing for genomic selection in livestock populations [J].
Gorjanc, Gregor ;
Cleveland, Matthew A. ;
Houston, Ross D. ;
Hickey, John M. .
GENETICS SELECTION EVOLUTION, 2015, 47
[8]   Genomic Selection for Crop Improvement [J].
Heffner, Elliot L. ;
Sorrells, Mark E. ;
Jannink, Jean-Luc .
CROP SCIENCE, 2009, 49 (01) :1-12
[9]  
Henderson CR, 1984, APPL LINEAR MODELS A
[10]   Imputation of Single Nucleotide Polymorphism Genotypes in Biparental, Backcross, and Topcross Populations with a Hidden Markov Model [J].
Hickey, John M. ;
Gorjanc, Gregor ;
Varshney, Rajeev K. ;
Nettelblad, Carl .
CROP SCIENCE, 2015, 55 (05) :1934-1946