Abstract
Making decisions on plant breeding programs require plant breeders to be able to test different breeding strategies by taking into account all the crucial factors affecting crop genetic improvement. Due to the complexity of the decisions, computer simulation serves as an important tool for researchers and plant breeders. This paper describes ADAM-plant, which is a computer software that models breeding schemes for self-pollinated and cross-pollinated crop plants using stochastic simulation. The program simulates a population of plants and traces the genetic changes in the population under different breeding scenarios. It takes into account different population structures, genomic models, selection (strategies and units) and crossing strategies. It also covers important features e.g., allowing users to perform genomic selection (GS) and speed breeding, simulate genotype-by-environment interactions using multiple trait approach, simulate parallel breeding cycles and consider plot sizes. In addition, the software can be used to simulate datasets produced from very complex breeding program in order to test new statistical methodology to analyze such data. As an example, three wheat-breeding strategies were simulated in the current study: (1) phenotypic selection, (2) GS, and (3) speed breeding with genomic information. The results indicate that the genetic gain can be doubled by GS compared to phenotypic selection and genetic gain can be further increased considerably by speed breeding. In conclusion, ADAM-plant is an important tool for comparing strategies for plant breeding and for estimating the effects of allocation of different resources to the breeding program. In the current study, it was used to compare different methodologies for utilizing genomic information in cereal breeding programs for selection of best-fit breeding strategy as per available resources.
Highlights
The goal of most plant breeding programs is to hybridize and select best elite lines or varieties with the best combination of desired characteristics, viz., yield-attributing traits, quality traits, and insect and pest resistance (Collard and Mackill, 2008)
This paper describes the simulation method and working process of ADAM-plant in different plant breeding applications with an emphasis on its main characteristics, component elements and computational performance using a couple of examples of wheat-breeding programs
In the first seven cycles, the genome of the 20 parental lines were randomly sampled from the 988 stored genomes without replacement and these 20 parental lines were used for crossing
Summary
The goal of most plant breeding programs is to hybridize and select best elite lines or varieties with the best combination of desired characteristics, viz., yield-attributing traits, quality traits, and insect and pest resistance (Collard and Mackill, 2008). In addition to applying GS, there are many other factors, which affect the genetic gain in a plantbreeding program These factors include breeding objectives, experimental design (e.g., plot size and number of replicates per family), selection strategy (e.g., individual/family selection and recurrent selection) and biological aspects (e.g., mode of pollination, self-incompatibility, heritability and genotype– environment interactions). The advantage of stochastic simulation in this situation is that, it can be used to simulate an entire population of individual plants, so that one can mimic the actual artificial plant breeding programs in any detail desired This enables stochastic simulation to be able to provide very precise prediction of consequence of alternatives. A tool that is capable of simulating a large range of practical breeding programs with sufficient feasibility and flexibility needs to be developed
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