eQTL regulating transcript levels associated with diverse biological processes in tomato

dc.contributor.authorRanjan, Aashish
dc.contributor.authorBudke, Jessica
dc.contributor.authorRowland, Steven D.
dc.contributor.authorChitwood, Daniel H
dc.contributor.authorKumar, Ravi
dc.contributor.authorCarriedo, Leonela G.
dc.contributor.authorIchihashi, Yasunori
dc.contributor.authorZumstein, Kristina
dc.contributor.authorMaloof, Julin N.
dc.contributor.authorSinha, Neelima R.
dc.date.accessioned2016-07-18T08:45:18Z
dc.date.available2016-07-18T08:45:18Z
dc.date.issued2016
dc.descriptionAccepted date: 11 July 2016en_US
dc.description.abstractVariation in gene expression, in addition to sequence polymorphisms, is known to influence developmental, physiological and metabolic traits in plants. Genetic mapping populations have facilitated identification of expression Quantitative Trait Loci (eQTL), the genetic determinants of variation in gene expression patterns. We used an introgression population developed from the wild desert-adapted Solanum pennellii and domesticated tomato Solanum lycopersicum to identify the genetic basis of transcript level variation. We established the effect of each introgression on the transcriptome, and identified ~7,200 eQTL regulating the steady state transcript levels of 5,300 genes. Barnes-Hut t-distributed stochastic neighbor embedding clustering identified 42 modules revealing novel associations between transcript level patterns and biological processes. The results showed a complex genetic architecture of global transcript abundance pattern in tomato. Several genetic hotspots regulating a large number of transcript level patterns relating to diverse biological processes such as plant defense and photosynthesis were identified. Important eQTL regulating transcript level patterns were related to leaf number and complexity, and hypocotyl length. Genes associated with leaf development showed an inverse correlation with photosynthetic gene expression but eQTL regulating genes associated with leaf development and photosynthesis were dispersed across the genome. This comprehensive expression QTL analysis details the influence of these loci on plant phenotypes, and will be a valuable community resource for investigations on the genetic effects of eQTL on phenotypic traits in tomato.en_US
dc.description.sponsorshipThis work is supported through a National Science Foundation grant (IOS-0820854) awarded to NRS and JNM. DHC was a fellow of the Life Sciences Research Foundation funded through the Gordon and Betty Moore Foundation. JMB is a recipient of Katherine Esau Postdoctoral Fellowship at UC Davis.en_US
dc.identifier.citationPlant Physiol., 172(1): 328-340en_US
dc.identifier.doihttp:/​/​dx.​doi.​org/​10.​1104/​pp.​16.​00289en_US
dc.identifier.issn1532-2548
dc.identifier.officialurlhttp://www.plantphysiol.org/content/early/2016/07/14/pp.16.00289.abstracten_US
dc.identifier.urihttp://172.16.0.77:8080/jspui/handle/123456789/666
dc.language.isoen_USen_US
dc.publisherAmerican Society of Plant Biologistsen_US
dc.subjectexpression Quantitative Trait Locien_US
dc.subjecteQTLen_US
dc.subjectTomatoen_US
dc.titleeQTL regulating transcript levels associated with diverse biological processes in tomatoen_US
dc.typeArticleen_US

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