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Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
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Designed diversity: from marker-assisted backcrossing to computationally optimised polygenic introgression.

Seema Yadav1, Lee T Hickey1, Meredith McNeil2

  • 1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Queensland 4072, Australia.

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|April 23, 2026
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Summary
This summary is machine-generated.

Modern crop breeding uses predictive, design-driven methods for trait introgression, moving beyond traditional backcrossing. This optimizes success, genome recovery, time, and resources for resilient, high-yielding crops.

Keywords:
Breeding-by-Designmulti-objective optimisationpredicted cross metricsrecombination engineeringspeed breedingtrait introgression

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Area of Science:

  • Agricultural Science
  • Genetics
  • Plant Breeding

Background:

  • Traditional crop breeding relied on empirical backcrossing for trait introgression.
  • This method focused on a limited number of target genetic loci.
  • A shift towards more predictive and large-scale strategies is underway.

Purpose of the Study:

  • To reframe trait introgression as a multi-objective optimization problem.
  • To balance key factors like success probability, elite genome recovery, time, and resource utilization.
  • To integrate advanced genomic tools and breeding accelerators into predictive frameworks.

Main Methods:

  • Utilizing computational tools like predicted cross value and look-ahead selection for cross prioritization.
  • Employing advanced genomic resources such as pan-genomes and introgressiomics.
  • Leveraging breeding accelerators including speed breeding and gene editing for precise allele stacking.

Main Results:

  • Development of a design-driven approach for trait introgression.
  • Optimization of multi-generation planning for breeding programs.
  • Expansion of the design space for precise allele stacking through technological integration.

Conclusions:

  • Predictive breeding frameworks, enhanced by new technologies, refine introgression pipelines.
  • Transformation of trial-and-error breeding programs into 'designed diversity' pipelines.
  • Enabling the development of more resilient and higher-yielding crop varieties.