Discovery and identification of favourable haplotypes for metabolic traits in tea germplasm

• Applicants: Professor Dr. Alisdair Fernie, Ph.D.; Professor Dr. Björn Usadel
• Subject Area: Plant Genetics and Genomics ; Plant Biochemistry and Biophysics
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 468870408

Within the project HAPLOTEA we will analyze the metabolic diversity in tea and couple metabolite content and genetic analyses. We believe that the lack of any observable domestication bottleneck and the high genetic diversity and heterozygosity in extant tea germplasm will be reflected in a strong metabolic diversity in tea. This hypothesis is in line with our current data on tea genetics suggesting a high degree of hybridization in tea accessions and based on the high importance of tea leaf processing on flavor in the tea beverage likely masking many genetic effects on flavor bestowing components.To investigate this hypothesis, we will generate deep metabolic profiles for an established collection of more than 200 tea accessions and will couple this with expression and genetic polymorphism data. Based on these joint data, we will link metabolite content to genetic regions using genome wide association studies and we will generate haplotype resolved genome assemblies for a selection of 15 tea accessions. This will allow to observe haplotype divergence and to link metabolite content to specific haplotypes and -using biochemical knowledge- underlying candidate genes. In on our previous work we could show the existence of two major allelic versions of an enzyme involved in catechin metabolism which showed markedly different catalytic properties when expressed in vitro. Hence, we will analyze up to 10 candidate genes for enzymatic differences in their different allelic forms to investigate if such catalytic enzyme differences are common in tea and are contributing to metabolic diversity.

• DFG Programme: Research Grants
• International Connection: China
• Partner Organisation: National Natural Science Foundation of China
• Cooperation Partner: Professorin Dr. Weiwei Wen