Rational manipulation of large DNA constructs is a central challenge to current synthetic biology and genome engineering efforts. In recent years, a variety of technologies have been developed to address this challenge and increase the specificity and speed with which mutations can be generated. Additionally, adaptive mutations are a central driver of evolution, but their abundance and relative contribution to cellular phenotypes are poorly understood even in the most well-studied organisms. This can be attributed in large part to the technical challenges associated with observing and reconstructing these genotypes and correlating their presence with the phenotype of interest. For example, methods of genome editing that rely on random mutagenesis lead to complex genotypes consisting of many mutations, the relative contribution of each of which is difficult to deconvolute. Moreover, epistatic interactions between alleles are difficult to assign due to lack of information regarding the individual mutations.