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From sequence to function and back – High-throughput sequence-function mapping in synthetic biology
Article
Höllerer, Simon, Desczyk, Charlotte, Muro, Ricardo Farrera and Jeschek, Markus
(2023)
From sequence to function and back – High-throughput sequence-function mapping in synthetic biology.
Current Opinion in Systems Biology 37, p. 100499.
DOI to cite this document: 10.5283/epub.55514
Abstract
How does genetic sequence give rise to biological function? Answering this question is key to our understanding of life and the construction of synthetic biosystems that fight disease, resource scarcity and climate change. Unfortunately, the virtually infinite number of possible sequences and limitations in their functional characterization limit our current understanding of sequence-function ...
How does genetic sequence give rise to biological function? Answering this question is key to our understanding of life and the construction of synthetic biosystems that fight disease, resource scarcity and climate change. Unfortunately, the virtually infinite number of possible sequences and limitations in their functional characterization limit our current understanding of sequence-function relationships. To overcome this dilemma, several high-throughput methods to experimentally link sequences to corresponding functional properties have been developed recently. While all of these share the goal to collect sequence-function data at large scale, they differ significantly in their technical approach, functional readout and application scope. Herein, we highlight recent developments in the aspiring field of high-throughput sequence-function mapping providing a critical assessment of their potential in synthetic biology.
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| Item type | Article | ||||
| Journal or Publication Title | Current Opinion in Systems Biology | ||||
| Publisher | Elsevier | ||||
| Open Access Type | Hybrid Open Acces | ||||
| Volume | 37 | ||||
| Page Range | p. 100499 | ||||
| Date | 13 December 2023 | ||||
| Date of publication | 02 Feb 2024 13:50 | ||||
| Institutions | Biology, Preclinical Medicine > Institut für Biochemie, Genetik und Mikrobiologie > Lehrstuhl für Mikrobiologie (Archaeenzentrum) | ||||
| Identification Number |
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| Keywords | Sequence-function mapping, Sequence-activity landscapes, Nextgeneration sequencing, DNA recording, DNA recorder, RNA-Seq, Flow- Seq, Sort-Seq, Recombinases, Integrases, Machine learning in biology, Data-driven modelling, Synthetic biology.. | ||||
| Dewey Decimal Classification | 500 Science > 570 Life sciences | ||||
| Status | Published | ||||
| Refereed | Yes, this version has been refereed | ||||
| Created at the University of Regensburg | Yes | ||||
| URN of the UB Regensburg | urn:nbn:de:bvb:355-epub-555143 | ||||
| Item ID | 55514 |
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