Analytical and decision support tools for genomics-assisted breeding

Rajeev K. Varshney, Vikas K. Singh, John M. Hickey, Xu Xun, David F. Marshall, Jun Wang, David Edwards, Jean Marcel Ribaut

Research output: Contribution to journalReview articlepeer-review

49 Citations (Scopus)


To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are ‘must haves’ to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approaches (markers/haplotypes), including large-scale genotypic and phenotypic, data management, and molecular breeding approaches. Although phenotyping remains expensive and time consuming, prediction of allelic effects on phenotypes opens new doors to enhance genetic gain across crop cycles, building on reliable phenotyping approaches and good crop information systems, including pedigree information and target haplotypes. Appropriate analytical and decision support tools (ADSTs) are critical for deploying genomics-assisted breeding. Development of breeder-friendly pipelines and/or tools will enhance the adoption of ADSTs and facilitate the rapid development of new breeding lines. Deployment of ADSTs in public breeding programs is the need of the hour. Advances in next-generation sequencing technologies have prompted geneticists and breeders to utilize more sophisticated tools for sequencing-based mapping and genome-wide selection for the development of new breeding lines. The availability of open-source and one-stop integrated platforms such as Integrated Breeding Platform (IBP) and their hubs across the world will facilitate the modernization of crop breeding programs.
Original languageEnglish
Pages (from-to)354-363
Number of pages10
JournalTrends in Plant Science
Issue number4
Early online date2 Dec 2015
Publication statusPrint publication - 1 Apr 2016
Externally publishedYes


  • data management
  • decision support tools
  • genetic mapping
  • genomic selection
  • genomics-assisted breeding
  • marker assisted selection


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