The Fabaceae (leguminosae) comprise the second largest family of flowering plants with 650 genera and 18000 species. The soybean is a member of the tribe Phaseoleae, the most economically important of the legume tribes. The soybean, Glycine max (L.) Merr. is the major source of vegetable oil and protein on earth. Soybean oil has garnered considerable recent attention due to its increased use for biodiesel production. The extensive genetic resources of soybean and the associated physiological tools available present a set of unique opportunities to study everything from seed development to the biology of polyploidization to a huge array of pathogenic and symbiotic plant-host interactions. The large plant size of soybean is an advantage for such studies, permitting the use of techniques not easy or possible with smaller plants. For these and additional reasons, soybean genomic research has seen major advances in recent years. Therefore, a book chronicling these advances and the potential for future discoveries would be timely. This is especially true given the very recent announcement that the Department of Energy, Joint Genome Institute will sequence the soybean genome. The soybean seed is unique in its accumulation of both high levels of protein and oil, which presents several opportunities for study. A typical soybean seed is 40% protein and 20% oil by weight. The somatic embryo methodology that exists for soybean is among the most advanced embryogenic systems available for any dicot and can be used to help study seed physiology and development. Furthermore, transgenic somatic embryos may be used to efficiently study seed genomics, without the need to recover an entire plant, by either over-expressing or suppressing embryo-specific genes. This book covers the recent progress on genome research in soybeans, including genetic map including classical, RFLP, SSR and SNP markers; genomic and cDNA libraries, functional genomics platforms (e.g., cDNA, Affymetrix and oligonucleotide based DNA microarrays); and genetic and physical maps, gene expression profiles.