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IonBreeders: bioinformatics plugins toward genomics-assisted breeding.

Eri Ogiso-Tanaka1, Shiori Yabe1, Tsuyoshi Tanaka1

  • 1Institute of Crop Science, National Agriculture and Food Research Organization (NARO), 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan.

Breeding Science
|July 28, 2020
PubMed
Summary

IonBreeders is a new bioinformatics tool simplifying next-generation sequencing (NGS) data analysis for genome-wide marker-assisted breeding. It streamlines genotyping to genomic prediction, aiding researchers and breeders in utilizing large-scale genetic datasets.

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genomic predictiongenotypingnext-generation sequencingplugin

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Area of Science:

  • Genomics
  • Bioinformatics
  • Plant and Animal Breeding

Background:

  • Next-generation sequencing (NGS) generates vast amounts of polymorphism data crucial for genome-wide marker-assisted breeding.
  • Handling large-scale NGS datasets presents significant challenges for researchers and breeders.
  • There is a need for accessible and flexible bioinformatics tools for NGS data analysis in breeding programs.

Purpose of the Study:

  • To develop a user-friendly bioinformatics tool, IonBreeders, for comprehensive NGS data analysis in breeding.
  • To implement essential steps from genotyping to genomic prediction within a single software package.
  • To facilitate the application of genomic selection in practical breeding scenarios.

Main Methods:

  • IonBreeders consists of three integrated plugins: ABH for format conversion, IMPUTATION for data preprocessing and imputation, and GENOMIC PREDICTION for predictive modeling.
  • The ABH plugin standardizes genotyping data into the ABH format, compatible with various breeding software.
  • The IMPUTATION plugin filters markers and imputes missing genotypes, while GENOMIC PREDICTION offers four statistical methods for genomic selection.

Main Results:

  • IonBreeders provides a streamlined workflow for analyzing NGS genotyping data.
  • The tool enables efficient format conversion, data imputation, and the construction of genomic prediction models.
  • It supports various statistical approaches within the GENOMIC PREDICTION plugin, catering to different breeding objectives.

Conclusions:

  • IonBreeders offers a flexible and straightforward solution for managing and analyzing large-scale NGS data in breeding.
  • The tool empowers researchers and breeders to leverage genomic information for accelerated genetic gain.
  • IonBreeders enhances the application of marker-assisted breeding and genomic selection through accessible bioinformatics.