It is important to describe and fully exploit conserved syntenic relationships among species in Poaceae, Brassicaceae, Solanaceae, and Fabaceae so that any finely mapped qualitative or quantitative character in any member of the reference genomes can be easily bred into agronomically relevant cultivars. This effort includes the development of fine-structure genetic and physical maps of key species and the development of a comprehensive set of anchor markers. We anticipate that these tools will enable detailed characterization of the genes that contribute to specialized traits of agronomic interest, such as drought tolerance, salt tolerance, disease resistance, seed quality, and plant architecture.

To determine the genetic basis of traits of economic interest, it will be useful to map genetic variation with relatively high precision, including SNPs or simple, DNA-based, high-resolution introgression tools. Thus, it is important to have comprehensive BAC libraries for species of major agronomic interest and to use BACs for end- and low-pass draft sequencing to see which genes are in each “map bin.” Coupled with identification of a polymorphism for each BAC, this approach would provide powerful tools to assign genetic variation to a small set of candidate genes quickly. Such advances will facilitate translation from reference species to other crops.

TOOLS FOR TRANSLATIONAL AGRICULTURE

The following sections outline a variety of approaches that should be undertaken to develop tools for translational agriculture.

  1. Construction of genetic maps for key, carefully chosen species. We recommend identification of a set of several hundred conserved genes that can be used as anchor markers for comparative map construction and phylogenetic studies across relevant taxonomic distances. If possible, sets of conserved genes should be chosen on the basis of the biologic significance of the underlying genes and pathways and of genomic distribution; map positions should initially be defined in a reference genome. Comparative maps lay the foundation for high-resolution mapping of simply



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