GGAssembler: Economical Design of Gene Libraries with Precise Control over Mutations

Abstract Golden Gate (GG) assembly is an effective tool for the seamless assembly of genes from DNA fragments. Its use for generating combinatorial mutagenic libraries is much less developed. We describe a new method called GGAssembler for designing gene libraries that encode combinatorial mutations through GG gene assembly. GGAssembler uses a graph-theoretical approach to find the most cost-effective way to assemble diversity from DNA fragments. We demonstrate the accuracy, efficiency, low bias, and cost-effectiveness of GGAssembler by encoding hundreds of thousands of variants of camelid single-domain antibodies. We envision that GGAssembler will advance protein science and engineering by enabling the construction of diverse protein libraries with precise control over mutations. Source code is freely available at: https://github.com/Fleishman-Lab/GGAssembler .