Multiplexed tracking of combinatorial genomic mutations in engineered cell populations.

Area of Science:

• Synthetic Biology
• Genomics
• Molecular Biology

Background:

• Generating genetic diversity is crucial for understanding gene function.
• Existing methods lack the ability to track complex, engineered mutations and their resulting phenotypes.

Purpose of the Study:

• To introduce a novel method, TRACE (Tracking Combinatorial Engineered Libraries), for high-resolution mapping of engineered genomes.
• To enable the linkage of genotype to phenotype in large-scale combinatorial libraries.

Main Methods:

• TRACE simultaneously maps millions of combinatorially engineered genomes at single-cell resolution.
• Genomic sites are assembled into DNA constructs compatible with next-generation sequencing.
• Applied to multiplexed genome engineering in *Escherichia coli* and human ES2 cells.

Main Results:

• TRACE achieved a 10^4-fold increase in depth for mapping *E. coli* combinatorial libraries.
• Successfully identified genotype-to-phenotype correlations.
• Mapped the evolutionary trajectory of individual combinatorial mutants and assessed combinatorial mutations in human cells.

Conclusions:

• TRACE completes the genome engineering cycle by enabling simultaneous tracking of mutations and phenotypes.
• Facilitates more sophisticated genome engineering approaches in both prokaryotic and eukaryotic systems.
• Opens new avenues for studying evolution and gene function through large-scale genetic manipulation.