Project properties |
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Title | Studying the genomic basis of breeding traits in industrial crops |
Group | Plant Breeding, Laboratory of |
Project type | thesis |
Credits | 24-39 |
Supervisor(s) | Dr. Francesco Pancaldi, Prof. Dr. Luisa Trindade |
Examiner(s) | Prof. Dr. Luisa Trindade |
Contact info | luisa.trindade@wur.nl, francesco.pancaldi@wur.nl |
Begin date | 2023/09/01 |
End date | 2027/12/31 |
Description | The development of a bio-based economy requires the availability of crops and varieties that can supply biomass and bio-molecules in sufficient amounts and quality for economically-viable bio-based value chains. Non-food crops that are attractive for bio-based applications are often under-domesticated, and require breeding activities to reach acceptable levels of yield and quality of biomass and bio-molecules. However, doing breeding in under-domesticated crops with scarce availability of breeding tools (e.g. markers, maps, QTLs,…) is challenging. In this project, we aim at using translational genomics to develop breeding tools for under-domesticated industrial crops by translating knowledge on traits of interest from model species to new crops with an available genome sequence. Examples of research activities include inter-species mapping and translation of QTL regions, markers, and candidate genes; bioinformatic identification of alleles of interest in crop panels; analysis of genomic conservation of metabolic pathways of traits of interest by integrating diverse data (gene synteny, expression data, phylogenetic analysis). Regarding traits, the major focus is on complex traits as biomass yield and quality in lignocellulosic crops, fiber yield and quality in fiber crops, and oil yield and quality in oilseed species. The specific activities to be carried out can vary depending on the moment of thesis start. |
Used skills | Bioinformatics, statistical analysis |
Requirements | Compulsory: ABG-30306 Genomics,
Preferred: PBR-31306 Bioresources or PBR-37306 Advanced Bioresources. Clear interest in bioinformatics and statistics and experience with R/Python/Unix are a plus. |