Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Bioinformatics for Crop ImprovementPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Pp. 773-778 in Proceedings of the World Congress of Computers in Agriculture and Natural Resources (13-15, March 2002, Iguacu Falls, Brazil) 701P0301.(doi:10.13031/2013.8410)Authors: M. C. Cutanda, P. Hernández-Acosta and F. A. Culiáñez-Macià Keywords: Computer, agriculture, bioinformatics, crop improvement, functional genomics, plant biotechnology Feeding the increasing world population is a challenge for modern plant biotechnology. Crop yields have increased during the last century and will continue to improve as agronomy re-assorting the enhanced breeding and develop new biotechnological-engineered strategies. The onset of genomics is providing massive information to improve crop phenotypes. The accumulation of sequence data allows detailed genome analysis by using-friendly database access and information retrieval. Genetic and molecular genome colinearity allow efficient transfer of data revealing extensive conservation of genome organisation between species. The genome research goal is the identification of the sequenced genes and the deduction of their functions by metabolic analysis and reverse genetic screens of gene knockouts. Over 20% of the predicted genes occur as cluster of related genes generating a considerable proportion of gene families. Multiple alignment provides a method to estimate the number of genes in gene families allowing the identification of previously undescribed genes. This information enables new strategies to study gene expression patterns in plants. Available information from news technologies, as the database stored DNA microarray expression data, will help plant biology functional genomics. Expressed sequence tags (ESTs) also give the opportunity to perform digital northern comparison of gene expression levels providing initial clues toward unknown regulatory phenomena. Crop plant networks collections of databases and bioinformatics resources for crop plants genomics have been built to harness the extensive work in genome mapping. This resource facilitates the identification of agronomically important genes, by comparative analysis between crop plants and model species, allowing the genetic engineering of crop plants selected by the quality of the resulting products. Bioinformatics resources have evolved beyond expectation, developing new nutritional genomics biotechnology tools to genetically modify and improve food supply, for an ever-increasing world population, and to solve unanswered research questions on the mechanisms of plant development. (Download PDF) (Export to EndNotes)
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