Summary
This study adapted Plant STARR-seq to systematically characterise over 50,000 plant terminators from Arabidopsis and maize, revealing that terminator strength is determined by GC content, polyadenylation motif composition, and cleavage site probability. The authors developed a computational model to predict terminator activity and used it to design optimised synthetic terminators that outperform bacterial terminators commonly used in plant genetic engineering. The findings establish molecular principles governing plant 3' end processing and provide tools for improving gene expression in crop improvement.
Regional applicability
This research addresses fundamental molecular biology of plant gene expression in model and crop species (maize). Findings are applicable to United Kingdom crop breeding and genetic improvement programmes, particularly for enhancing transgene expression stability and predictability in cereal crops and other targets.
Key measures
Terminator activity (measured via Plant STARR-seq), GC content, polyadenylation motif composition, cleavage site probability, species-specific performance differences
Outcomes reported
The study measured terminator activity across over 50,000 sequences from Arabidopsis and maize using a massively parallel reporter assay, identifying sequence features (GC content, polyadenylation motifs, cleavage probability) that determine terminator strength and developing a predictive computational model.
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