Towards systematic approaches for validation of biological parts and testing of functions in yeast

Synthetic genomics research heavily relies on rapidly advancing technologies for DNA sequencing ("reading"), DNA manipulation ("editing"), and DNA synthesis ("writing"). Synthetic biology approaches biology from an engineering perspective, emphasizing the importance of adapting them to high-throughput and automated systems. The increasing complexity of DNA constructs and the ability to work with large, pooled libraries in synthetic biology pose significant challenges for cost-effective sequencing validation. To address this, the first part of this thesis presents a highly scalable method for the rapid validation of amplified DNA sequences using long-read Nanopore sequencing. In combination with the developed automated analysis pipeline, efficient processing of sequencing data is achieved, resulting in easy-to-interpret reports. The second part aims to investigate the non-canonical role of the hetero-tetrameric tRNA splicing complex (SEN complex) known for tRNA splicing. However, studies in yeast suggest an additional, essential function of the SEN complex that remains unknown. To uncover this, a global approach was employed to identify RNA sequences bound to the SEN complex, providing new insights into both known and novel RNAs associated with this complex. These findings may help elucidate the SEN complex's unexplored role in yeast. During the study, challenges arose in modifying the essential genes of the SEN complex in yeast. To overcome this, the third part of the thesis describes the development of a modular approach to cluster SEN complex genes on a minichromosome. This strategy is expected to facilitate systematic studies of the SEN complex. Combined with the amplicon sequencing protocol and the identified SEN complex associated RNAome, this approach could enable the analysis of large combinatorial libraries, to decipher the unknown function of the SEN complex in yeast. This approach can also be applied to other complex cellular functions because functional clustering of genes simplifies complex genome engineering challenges and allows for systematic mechanistic studies.