First soybean genome assembly released to enable bioenergy researchJanuary 20th, 2008 - 2:40 pm ICT by admin
Washington, Jan 20 (ANI): The DOE Joint Genome Institute in California, USA, have released the first soybean genome assembly to the worldwide scientific community to enable bioenergy research.
The soybean genome project was initiated through the DOE JGI Community Sequencing Program (CSP), with support from the U.S. Department of Agriculture and the National Science Foundation.
This large-scale shotgun DNA sequencing project began in the middle of 2006 and will be completed in 2008.
The current assembly gene, set, and browser are collectively referred to as “Glyma0″.
Glyma0 is a preliminary release, based on a partial dataset. This is expected to be replaced with an improved, chromosome-scale “Glyma1″ version by the end of 2008.
Early users of this data are encouraged to track their favorite genes by saving local copies of the DNA sequences of these loci, and not by identifier or sequence coordinate, as these will change in future versions.
DOE JGI’s interest in sequencing the soybean stems from its role as a principal source of biodiesel, a renewable, alternative fuel with the highest energy content of any alternative fuel.
Detailed knowledge of the soybean genetic code will enable crop improvements for more effective application of this plant for clean bioenergy generation.
Knowing which genes control specific traits, researchers are able to change the type, quantity, and/or location of oil produced by the crop.
Through utilization of the sequence information generated by DOE JGI, it may be possible to develop a customized biomass production platform for combining oil seed production for biodiesel with enhanced vegetative growth for ethanol conversion–doubling the energy output of the crop. (ANI)
Tags: biomass production, crop improvements, dna sequences, dna sequencing, doe joint genome institute, energy content, energy output, highest energy, jgi, joint genome institute, national science foundation, oil seed, partial dataset, principal source, production platform, seed production, sequencing project, soybean genome, type quantity, vegetative growth