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GENETIC CONTROL OF POTATO TUBER COMPOSITION: A SYSTEMS BIOLOGY APPROACH

dc.contributor.authorLevina, Anna
dc.contributor.chairDe Jong, Walter S.
dc.contributor.committeeMemberMazourek, Michael
dc.contributor.committeeMemberPerry, Keith Lloyd
dc.date.accessioned2019-10-15T16:49:35Z
dc.date.available2020-08-29T06:00:41Z
dc.date.issued2019-08-30
dc.descriptionSupplemental file(s) description: SolCAP phenotypes, Metabolomics raw data, GWAS results for individual metabolites, metabolites module assignments, module gwas results
dc.description.abstractPlant improvement requires selection, which can be complicated when the genetic basis of a trait is complex or poorly understood. In an effort to better understand the genetic control of potato (Solanum tuberosum) tuber composition, we performed non-targeted metabolomic profiling to generate a deep (but largely anonymous) dataset, and analyzed the data with a combination of genetic and network approaches. Water/methanol extracts of cooked potato tuber cores from 185 clones that had previously been genotyped by the Solanaceae Coordinated Agricultural Project (SolCAP) were analyzed by LC/MS-MS; this resulted in the detection of 981 features that represent a mixture of primary metabolites, specialized metabolites and hydrolyzed fragments of abundant proteins. Using GWASpoly, an R package that considers gene dosage through a series of genetic models, 472 features could be associated with at least one single nucleotide polymorphism (SNP) marker, markedly increasing the number of marker-trait associations that have been made in potato to date. Unexpectedly, SNPs associated with features were not uniformly distributed throughout the genome, but were instead clustered on chromosomes 3, 7, and 8, with dozens of features associated with several small (~2 Mbp) regions. Also of note was that the most significant SNPs for several glycoalkaloids (α-chaconine, β-chaconine, and α-solamarine) – detected on chromosomes 2, 7, and 8 – are unlinked to any known glycoalkaloid biosynthetic genes. Network analysis condensed the 981 features into 44 modules, whose eigenvalues were then used to explore correlations with phenotype data collected by SolCAP, as well as for genetic mapping. Half of the modules were associated with at least one SNP according to GWAS; 11 of these were also significantly correlated with chip color. Loci associated with module eigenvalues were not evenly distributed throughout the genome, but like individual features, were instead clustered on chromosomes 3, 7 and 8. Unexpectedly, the features within modules were structurally disparate, suggesting that linkage disequilibrium confounds network analyses in potato. This research expanded the number of known marker-traits associations in potato by more than 50-fold, and identified potential selection targets to modify potato chip quality and glycoalkaloid content by identifying genetic markers correlated with these traits.
dc.identifier.doihttps://doi.org/10.7298/6shp-ea29
dc.identifier.otherLevina_cornellgrad_0058F_11641
dc.identifier.otherhttp://dissertations.umi.com/cornellgrad:11641
dc.identifier.otherbibid: 11050657
dc.identifier.urihttps://hdl.handle.net/1813/67673
dc.language.isoen_US
dc.subjectPotato
dc.subjectGenetics
dc.subjectPlant Breeding
dc.subjectNetwork Analysis
dc.subjectAgriculture
dc.subjectPlant sciences
dc.titleGENETIC CONTROL OF POTATO TUBER COMPOSITION: A SYSTEMS BIOLOGY APPROACH
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810
thesis.degree.disciplinePlant Breeding
thesis.degree.grantorCornell University
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh.D., Plant Breeding

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