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ARS Home Northeast Area Geneva, New York Grape Genetics Research Unit (GGRU) Research Publications at this Location





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Title:   Author  item
                                            HYMA, KATIE - Cornell Universityitem
                                            Londo, Jasonitem
                                            BARBA, PAOLA - Cornell Universityitem
                                            REISCH, BRUCE - Cornell Universityitem
                                            Cadle-Davidson, Lanceitem
                                            SUN, QI - Cornell Universityitem
                                            ACHARYA, CHARLOTTE - Cornell Universityitem
                                            MITCHELL, SHARON - Cornell University
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 3/17/2014
                                    Publication  Date: 3/17/2014
                                    Citation: Hyma, K., Londo, J.P., Barba, P., Reisch, B., Cadle Davidson, L.E., Sun, Q., Acharya, C., Mitchell, S. 2014. Agricultural biodiversity in the post-genomics era. 2nd Annual World Congress of Biodiversity, Ecology and the Environment, Nanjing, China.Interpretive Summary:
                                Technical Abstract: The toolkit available for assessing and utilizing biological diversity within agricultural systems is rapidly expanding. In particular, genome and transcriptome re-sequencing as well as genome complexity reduction techniques are gaining popularity as the cost of generating short read sequence data decreases. Genome complexity reduction can reduce problems associated with ascertainment bias typically encountered with other genotyping platforms, and has the advantage of being highly repeatable and scalable. Through the use of customized bioinformatics approaches, biodiversity can be assessed quickly and accurately in many systems. By utilizing these genomic scale data to combine population genomics analyses with molecular breeding approaches, breeding and conservation efforts can be accelerated and improved. Here we present an overview of some of the technologies and applications.


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