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Ultra-high-throughput mapping of genetic design space
Kshitij Rai1,2, Ronan W O'Connell1,3, Trenton C Piepergerdes1,3
1Department of Bioengineering, Rice University, Houston, TX, USA.
Nature
|January 14, 2026
Summary
CLASSIC is a new genetic screening platform that uses long- and short-read sequencing to analyze complex gene circuits. This enables high-throughput screening of thousands of designs, accelerating synthetic biology and revealing genetic part composability rules.
Area of Science:
- Synthetic Biology
- Genomics
- Molecular Biology
Background:
- High-throughput genetic screens are crucial for understanding sequence-to-function relationships.
- Current methods struggle with analyzing complex constructs containing multiple, long-range genetic elements.
- Accelerating synthetic biology requires high-throughput screening of diverse gene circuit designs.
Purpose of the Study:
- Introduce CLASSIC, a novel platform for high-throughput genetic screening of complex constructs.
- Enable quantitative assessment of gene circuit pools with diverse genetic part compositions.
- Reveal genetic part composability rules for data-driven design of complex genetic systems.
Main Methods:
- CLASSIC combines long- and short-read next-generation sequencing (NGS) modalities.
- Assesses pools of gene constructs with arbitrary lengths and diverse genetic part compositions.
- Measures expression profiles of over 10^5 gene circuit designs (5-20 kb) in human cells.
Main Results:
- CLASSIC enables quantitative assessment of thousands of gene circuit designs in a single experiment.
- Generated datasets facilitate machine learning models for accurate prediction of circuit behavior.
- Identified part composability rules governing circuit performance across expansive design landscapes.
Conclusions:
- CLASSIC significantly enhances the pace and scale of synthetic biology research.
- Establishes an experimental foundation for data-driven design of complex genetic systems.
- Overcomes limitations in analyzing multi-kb length scale genetic constructs.
