PhD Dissertation: Naimat Ullah
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  • PhD Dissertation: Naimat Ullah

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COMPARATIVE METABOLITE PROFILING OF DROUGHT STRESS RESPONSIVE BIOCHEMICAL PATHWAYS IN ROOT AND LEAVES OF TRITICEAE SPECIES

 

NAIMAT ULLAH
Molecular Biology, Genetics and Bioengineering
, PhD Dissertation, 2017

 

Thesis Jury

Prof. Dr. Hikmet Budak (Thesis Advisor), Assoc. Prof. Levent Öztürk, Assist. Prof. Muhammad Faheem, Asist. Prof. Meltem Elitaş, Assist. Prof. Nazlı Keskin

 

 

Date & Time: June 16th, 2017 –  3:30 PM

Place: FENS L065

Keywords : Metabolomics, Organic acids, Biochemical pathway, Plant Genomics  

 

Abstract

 

An untargeted metabolite profiling was applied to modern wheat and wild relatives exposed to drought stress using Gas Chromatography-Mass Spectrometry technique. A total of 84 analytes were resolved in the wheat metabolome for which multivariate analyses including supervised (Principal Component Analyses) and unsupervised (Partial Least-Squares-Discriminant Analysis) provided significantly variable dataset under control and drought stress conditions. Around 45 significantly altered metabolites, with possible roles in drought stress, were identified in all species tested through the GC-MS study. The potential drought stress responsive metabolites were further investigated to track genes encoding the enzymes of selected biochemical pathways using FL-cDNA sequences and transcriptome data. It has been hypothesized that if the genes encoding the enzymes that control the biosynthesis of drought stress-specific metabolites have a significant role in tolerance, contrasting genotypes would have a variance in the metabolite content. A small proportion showed a reduction in the metabolite accumulation in the drought sensitive genotypes, indicating that selected genes are directly or indirectly engaged in metabolome-regulative biochemical pathways under water-limiting conditions. These results demonstrated that those specific genotypes with high drought tolerance skills, especially wild emmer wheat, could be genetic model systems for experiments to validate metabolomics–genomics networks.