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The Future of Maize

  • Jeffrey L. Bennetzen

In the near future, maize will continue to expand and diversify as a research model, as an industrial resource and as a crop for feed and fuel. The generation of the first maize genome sequence, followed by great improvements in genome sequencing technology, will allow the exceptional genetic diversity of maize to be described in multiple sequenced genomes. Maize will become a premier plant system for association genetics, and reverse genetic tools will continue to improve to a point where the genetic basis of phenotypic variation can be comprehensively defined. As a model for gene function in a complex genomic environment, maize will be without peer, leading to a uniquely deep understanding of the dynamic relationship between chromosome packaging, chromatin structure, epigenetics and the evolution of genetic regulatory circuits. As a crop, maize production will continue to consume more acreage worldwide, with mixed benefits and problems. The relentless narrowing of the commercial maize gene pool and its increased use in borderline environments will enhance the potential for both local and worldwide crop failures as the environment changes and when new pathogen races jet through a susceptible global germplasm. The recent preciptious shift to maize grain as an ethanol source is a mistake driven by politics and profit. One hopes that wisdom will prevail in the near future. Moreover, it is vital that the current maize-to-ethanol boom will not obscure the long-term value of maize as an industrial feedstock. Maize already has many uses, from adhesives to plastics, and food scientists will continue to expand this cornucopia. The great diversity, ease of genetic study, and talented research community in maize will ensure its continued place in the first line of model systems for plant biology.

Keywords

Maize Genome Genome Sequencing Technology Nest Association Mapping Plant Science Research Nest Association Mapping Population 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of GeneticsUniversity of GeorgiaGeorgia

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