Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44060
Title: Automatic identification of DNA markers based on features reduction
Authors: Travieso, Carlos M. 
Solé-Casals, Jordi
Alonso, Jesús B. 
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Feature Reduction
Principal Component Analysis
Independent Components Analysis
Classification System
Deoxyribonucleic Acid (Dna)
Issue Date: 2010
Journal: BIOSIGNALS 2010 - Proceedings of the 3rd International Conference on Bio-inpsired Systems and Signal Processing, Proceedings
Conference: 3rd International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2010 
Abstract: Phytosanitary regulations and the provision of plant health certificates still rely mainly on long and laborious culture-based methods of diagnosis, which are frequently inconclusive. DNA-based methods of detection can circumvent many of the limitations of currently used screening methods, allowing a fast and accurate monitoring of samples. The genus Xanthomonas includes 13 phytopathogenic quarantine organisms for which improved methods of diagnosis are needed. In this work, we propose 21 new Xanthomonas-specific molecular markers, within loci coding for Xanthomonas-specific protein domains, useful for DNA-based methods of identification of xanthomonads. The specificity of these markers was assessed by a dot blot hybridization array using 23 non-Xanthomonas species, mostly soil dwelling and/or phytopathogens for the same host plants. In addition, the validation of these markers on 15 Xanthomonas spp. suggested species-specific hybridization patterns, which allowed discrimination among the different Xanthomonas species. Having in mind that DNA-based methods of diagnosis are particularly hampered for unsequenced species, namely, Xanthomonas fragariae, Xanthomonas axonopodis pv. phaseoli, and Xanthomonas fuscans subsp. fuscans, for which comparative genomics tools to search for DNA signatures are not yet applicable, emphasis was given to the selection of informative markers able to identify X. fragariae, X. axonopodis pv. phaseoli, and X. fuscans subsp. fuscans strains. In order to avoid inconsistencies due to operator-dependent interpretation of dot blot data, an image-processing algorithm was developed to analyze automatically the dot blot patterns. Ultimately, the proposed markers and the dot blot platform, coupled with automatic data analyses, have the potential to foster a thorough monitoring of phytopathogenic xanthomonads.
URI: http://hdl.handle.net/10553/44060
ISBN: 9789896740184
Source: Biosignals 2010: Proceedings Of The Third International Conference On Bio-Inspired Systems And Signal Processing, p. 347-352, (2010)
Appears in Collections:Actas de congresos
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