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SimpleMating: R-package for prediction and optimization of breeding crosses using genomic selection.

Marco Antônio Peixoto^1,2, Rodrigo Rampazo Amadeu^3,4, Leonardo Lopes Bhering¹

¹Laboratório de Biometria, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.

The Plant Genome

|November 27, 2024

Summary

This summary is machine-generated.

A new R package, SimpleMating, optimizes breeding crosses to maximize genetic gain and maintain diversity. This computational tool aids plant breeders in designing crosses for long-term genetic improvement and robust populations.

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Area of Science:

Plant breeding
Computational biology
Quantitative genetics

Background:

Parent and cross selection are crucial for successful breeding programs.
Designing crosses that maximize genetic gain while preserving population diversity is essential for long-term breeding applications.

Purpose of the Study:

To introduce SimpleMating, a novel, flexible, and open-source R package for computational mate allocation in breeding programs.
To provide a tool for predicting and optimizing breeding crosses across diverse reproductive systems and designs.

Main Methods:

SimpleMating estimates cross performance using criteria like mid-parental value and total genetic value.
An optimization algorithm maximizes target criteria while minimizing next-generation inbreeding.
Users can specify cross numbers, parent limits, and maximum relatedness for flexible mating plan generation.

Main Results:

SimpleMating generates mating plans based on single or multi-trait criteria.
Testing in a simulated maize breeding program demonstrated substantial genetic gain (up to 22% more than conventional genomic selection).
The tool also showed a reduced loss of genetic diversity over time compared to conventional methods.

Conclusions:

SimpleMating is a valuable tool for data-driven decision-making in breeding programs.
The package effectively enhances genetic gain and maintains genetic diversity in plant breeding applications.