NDLI: Colorado Potato Beetle Resistance in Solanum oplocense X Solanum tuberosum Intercross Hybrids and Metabolite Markers for Selection

Content Provider	Springer Nature Link
Author	Tai, Helen H. Worrall, Kraig Koeyer, David Pelletier, Yvan Tai, George C. C. Calhoun, Larry
Copyright Year	2015
Abstract	S. oplocense Hawkes, a wild relative of the potato S. tuberosum L. and source of resistance against the Colorado potato beetle Leptinotarsa decemlineata (Say) (CPB), was intercrossed with S. tuberosum. Backcross clones carried varying levels of resistance. Differences in foliar metabolites between resistant and susceptible clones were analyzed using liquid chromatography-mass spectrometry (LC-MS). Supervised machine learning classification methods uncorrelated shrunken centroids (USC), k-nearest neighbor (KNN) and support vector machines (SVM) were applied to develop algorithms that can classify resistant and susceptible plants using the metabolite data. Five metabolites were found to have a low error rate of prediction of CPB resistance. The five metabolites included two glycoalkaloids previously associated with resistance and susceptibility to CPB, dehydrocommersonine and solanine, respectively. Resistance was associated with a change in composition of glycoalkaloids to higher ratios of dehydrocommersonine over solanine. S. oplocense Hawkes, un pariente silvestre de la papa S. tuberosum L., y fuente de resistencia contra el escarabajo de Colorado Leptinotarsa decemlineata (Say) (CPB), se intercruzó con S. tuberosum. Los clones de la retrocruza conservaron diversos niveles de resistencia. Se analizaron las diferencias en los metabolitos foliares entre los clones resistentes y susceptibles usando espectrometría de cromatografía líquida de masas (LC-MS). Métodos supervisados de clasificación de aprendizaje de máquina no correlacionados con centroides encogidos (USC), k-cercanía de vecinos (KNN) y máquinas de respaldo de vector (SVM) se aplicaron para desarrollar algoritmos que pueden clasificar plantas resistentes y susceptibles usando los datos de los metabolitos. Se encontró que cinco metabolitos tenían un nivel bajo de error de predicción de la resistencia al CPB. Los cinco metabolitos incluyeron dos glicoalcaloides asociados previamente con resistencia y susceptibilidad al CPB, la deshidrocommersonina y la solanina, respectivamente. La resistencia se asoció con un cambio en la composición de los glicoalcaloides a altas proporciones de deshidrocommersonina sobre la solanina.
Starting Page	684
Ending Page	696
Page Count	13
File Format	PDF
ISSN	1099209X
Journal	American Potato Journal
Volume Number	92
Issue Number	6
e-ISSN	18749380
Language	English
Publisher	Springer US
Publisher Date	2015-11-05
Publisher Institution	Potato Association of America
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Colorado potato beetle resistance Untargeted metabolite profiling Potato Solanum oplocense Supervised machine learning classification Plant Sciences Agriculture Plant Genetics & Genomics Plant Breeding/Biotechnology Plant Pathology
Content Type	Text
Resource Type	Article
Subject	Plant Science Agronomy and Crop Science

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