394-1 Development and Utilization of the Alfalfa Breeder's Toolbox (ABT) for Practical Plant Breeding Applications.
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing General Oral
Wednesday, October 25, 2017: 1:34 PM
Tampa Convention Center, Room 37
Abstract:
The Alfalfa Breeder’s Toolbox (ABT) represents a platform to integrate genomic, genetic and phenotypic information to advance alfalfa cultivar improvement. The ABT was developed using Drupal, the Chado schema and Tripal as the construction toolkit. The genome sequences of Cultivated Alfalfa at the Diploid Level (CADL v1.0) and the model legume Medicago truncatula (v4.0) were used to anchor other datasets including molecular markers, gene models and RNA-sequencing reads. The CADL genome was annotated using the MAKER pipeline and SPADA to generate high-confidence gene models. Test case scenarios using key features of the ABT to address practical breeder-centric questions will be presented. These include: 1) query, search and blast the M. truncatula and alfalfa genome sequences; 2) search the predicted gene models and mine their expression profiles in response to abiotic stress conditions in the alfalfa gene expression atlas (GEA); 3) identify molecular markers associated with key traits to implement molecular breeding; 4) visual representations of shifts in allele frequencies at loci under selection from cycles of selection in alfalfa breeding populations; 5) access phenotypic data from various field trials and identify potential lines for targeted breeding programs. Additional datasets, functionalities and features to facilitate basic, translational and practical plant breeding applications continue to be integrated to enrich the ABT. The ultimate goal of the ABT is to facilitate the practical application of scientific discoveries to advance the alfalfa cultivar development pipeline.
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing General Oral
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