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Analytical and Decision Support Tools for Genomics-Assisted Breeding.

Rajeev K Varshney1, Vikas K Singh2, John M Hickey3

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Genomics-assisted breeding (GAB) requires effective analytical and decision support tools (ADSTs) for crop improvement. These tools, leveraging next-generation sequencing (NGS), aid in selecting superior plants for next-generation crops.

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data managementdecision support toolsgenetic mappinggenomic selectiongenomics-assisted breedingmarker assisted selection

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Area of Science:

  • Agricultural Science
  • Genetics
  • Bioinformatics

Background:

  • Genomics-assisted breeding (GAB) is crucial for advancing crop improvement programs.
  • Next-generation sequencing (NGS) provides massive genomic data, necessitating advanced analytical tools.

Purpose of the Study:

  • To review the application and deployment of analytical and decision support tools (ADSTs) for GAB.
  • To discuss software and pipelines for marker-based approaches and data management in GAB.

Main Methods:

  • Review of existing ADSTs and software for GAB.
  • Integration of NGS data with marker-based and molecular breeding approaches.
  • Discussion of data management and phenotyping strategies.

Main Results:

  • Identification of essential ADSTs for evaluating and selecting plants in GAB.
  • Highlighting the role of NGS in generating large-scale genotypic and phenotypic data.
  • Demonstrating the potential of predicting allelic effects to enhance genetic gain.

Conclusions:

  • Effective ADSTs are indispensable for successful GAB implementation.
  • Combining reliable phenotyping with genomic data and information systems accelerates crop genetic gain.
  • Predictive approaches using genomic information offer new avenues for developing next-generation crops.