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Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics
Monday, 2021/07/05 | 08:40:20

Jacob I. MarshHaifei HuMitchell GillJacqueline Batley & David Edwards

Theoretical and Applied Genetics June 2021; vol. 134:1677–1690

Key message

Safeguarding crop yields in a changing climate requires bioinformatics advances in harnessing data from vast phenomics and genomics datasets to translate research findings into climate smart crops in the field.

Abstract

Climate change and an additional 3 billion mouths to feed by 2050 raise serious concerns over global food security. Crop breeding and land management strategies will need to evolve to maximize the utilization of finite resources in coming years. High-throughput phenotyping and genomics technologies are providing researchers with the information required to guide and inform the breeding of climate smart crops adapted to the environment. Bioinformatics has a fundamental role to play in integrating and exploiting this fast accumulating wealth of data, through association studies to detect genomic targets underlying key adaptive climate-resilient traits. These data provide tools for breeders to tailor crops to their environment and can be introduced using advanced selection or genome editing methods. To effectively translate research into the field, genomic and phenomic information will need to be integrated into comprehensive clade-specific databases and platforms alongside accessible tools that can be used by breeders to inform the selection of climate adaptive traits. Here we discuss the role of bioinformatics in extracting, analysing, integrating and managing genomic and phenomic data to improve climate resilience in crops, including current, emerging and potential approaches, applications and bottlenecks in the research and breeding pipeline.

 

See: https://link.springer.com/article/10.1007/s00122-021-03820-3

 

Figure 1: Key stages in proposed breeding research pipeline integrating next generation genomic and phenomic data with bioinformatics to identify climate adaptive traits and translate findings to the field

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