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TitleGenetic, physical and informatics resources for maize: On the road to an integrated map
AuthorsKaren Cone, Michael McMullen, Irie Vroh Bi, Georgia Davis, Young-Sun Yim, Jack Gardiner, Mary Polacco, Hector Sanchez-Villeda, Zhiwei Fang, Steven Schroeder, Seth Havermann, John E. Bowers, Andrew H. Paterson, Carol Soderlund, Fred Engler, Rod Wing, and Edward Coe
PublicationPlant Physiol 128: 9-12
AbstractMaize (Zea mays L.) is among the most important crop plants in the world. For any crop plant, an integrated genetic and physical map serves as the foundation for numerous studies, especially those aimed at improving the agronomic characteristics of the plant. Once a phenotypically defined locus controlling a trait of interest has been mapped genetically, the integrated map facilitates isolating the underlying gene by positional cloning. Gene isolation is the prelude to studies aimed at first elucidating how the gene functions to contro the targeted trait and then applying this knowledge to crop improvement. The maize genome presents a complex challenge to the development of an integrated genetic and physical map. The genome is large, approximately 2,500 megabases (Arumuganathan and Earle, 1991); it is laden with numerous families of transposable elements, whose copy numbers can be in the tens of thousands (Bennetzen, 2000; Myers et al., 2001); and sequence information is limited. Previous large-scale mapping projects, driven by the goal of genome sequencing, were aimed at selecting a minimal tiling path of genomic clones; as clones were sequenced, they were useful in verifying and merging contigs (International Human Genome Mapping Consortium, 2001; Chen et al., 2002). To develop an integrated genetic and physical map resource for maize, we are using a comprehensive approach that includes three core components. The first is a highresolution genetic map that provides essential genetic anchor points for ordering the physical map and for utilizing comparative information from other smaller-genome plants. The physical map component consists of contigs assembled from clones from three deepcoverage genomic libraries. The third core component is a set of informatics tools designed to analyze, search and display the mapping data.

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