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Massively parallel characterization of engineered transcript isoforms using direct RNA sequencing

Author

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  • Matthew J. Tarnowski

    (University of Bristol)

  • Thomas E. Gorochowski

    (University of Bristol
    University of Bristol)

Abstract

Transcriptional terminators signal where transcribing RNA polymerases (RNAPs) should halt and disassociate from DNA. However, because termination is stochastic, two different forms of transcript could be produced: one ending at the terminator and the other reading through. An ability to control the abundance of these transcript isoforms would offer bioengineers a mechanism to regulate multi-gene constructs at the level of transcription. Here, we explore this possibility by repurposing terminators as ‘transcriptional valves’ that can tune the proportion of RNAP read-through. Using one-pot combinatorial DNA assembly, we iteratively construct 1780 transcriptional valves for T7 RNAP and show how nanopore-based direct RNA sequencing (dRNA-seq) can be used to characterize entire libraries of valves simultaneously at a nucleotide resolution in vitro and unravel genetic design principles to tune and insulate termination. Finally, we engineer valves for multiplexed regulation of CRISPR guide RNAs. This work provides new avenues for controlling transcription and demonstrates the benefits of long-read sequencing for exploring complex sequence-function landscapes.

Suggested Citation

  • Matthew J. Tarnowski & Thomas E. Gorochowski, 2022. "Massively parallel characterization of engineered transcript isoforms using direct RNA sequencing," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28074-5
    DOI: 10.1038/s41467-022-28074-5
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    Cited by:

    1. Evangelos-Marios Nikolados & Arin Wongprommoon & Oisin Mac Aodha & Guillaume Cambray & Diego A. Oyarzún, 2022. "Accuracy and data efficiency in deep learning models of protein expression," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Simeon D. Castle & Michiel Stock & Thomas E. Gorochowski, 2024. "Engineering is evolution: a perspective on design processes to engineer biology," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

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