|Title||Analysis of mRNA-seq data and metabolite profiles in five Brassica oleracea morphotypes|
|Group||Plant Breeding, Laboratory of|
|Supervisor(s)||Dr. Guusje Bonnema, Chengcheng Cai|
|Examiner(s)||Dr. Guusje Bonnema|
|Contact info||Guusje Bonnema (firstname.lastname@example.org), Chengcheng Cai (email@example.com)
|Description||Brassica oleracea is an economically important crop exhibiting enormous diversity in its appearance (ranging from cauliflower to kohlrabi and cabbage to kale) and uses (ranging from fodder to vegetables to ornamentals). Besides the diversity in appearance, Brassica crops also vary extensively in their metabolite content and composition, such as glucosinolates, flavonoids/anthocyanins, phenylpropanoids, amino acids, organic acids, sugers, etc.
In this project, we have generated comprehensive metabolite profiles of selected organs of five morphotypes (broccoli, cauliflower, kale, kohlrabi and white cabbage). This allows us to directly compare the metabolite variation across tissues and genotypes. To identify candidate genes related to specific metabolite, we have also generated mRNA-seq data of the selected organs of each genotype.
In the proposed thesis, the students will analyse both mRNA-Seq data and metabolite data, and then integrate them to identify candidate genes related to interested metabolites. This project offers the opportunity for students to work with real multi-omics dataset (transcriptomics, metabolomics and probably genomics), to strengthen their skills in bioinformatics and programming, to increase their understanding of genetic regulation of metabolite composition, etc
|Used skills||Bioinformatics, Statistics, Genomics, Programming, Linux|
|Requirements||BSc in plant science or equivalent, interest in bioinformatics, experience with at least one programming language (Python/R/Perl/C/Java, etc) and Linux system, preferably courses like Advanced Bioinformatics, Genomics and Advanced Statistics|