For instance, specification AvoidChanges can be used as a constraint to forbid sequence modifications in a given region, or as an objective to simply penalize changes in that region. A specification can be either a hard constraint, which must be satisfied in the final sequence, or an optimization objective, whose score must be maximized. The framework can be used as a web application, a Python library, or a command-line application, making it suitable for a wide range of uses.Īn optimization problem is defined in DNA Chisel by a list of global or local specifications against which a starting sequence will be optimized. The D-tailor framework ( Guimaraes et al., 2014) introduced the possibility to combine different specifications via Python scripts, with a focus on the exploration of multi-objective problems.ĭNA Chisel improves on these approaches with new methods for constraints resolution and objective maximization, the possibility for researchers to provide design specifications via Genbank annotations, support for circular sequences, detailed output reports, and over 15 built-in classes of specifications (listed in Supplementary Section 1A) which can be freely composed to handle any combination of the optimization objectives mentioned above, and extended with user-defined specifications. However, these projects focus on specific objectives and predetermined sequence locations (such as coding regions), and are hard to integrate in a same workflow, as their optimizations may undo one another. Software solutions have been proposed to address various scenarios, including host-specific codon optimization or harmonization ( Richardson et al., 2012 Claassens et al., 2017), gene expression enhancement via CpG island enrichment ( Raab et al., 2010), the design of biologically neutral sequences ( Casini et al., 2014), or the removal of synthesis-impeding DNA patterns ( Oberortner et al., 2017). While a sequence’s primary purpose may be the study or engineering of an organism, its design may also account for manufacturability, host compatibility, and other practical requirements, resulting in complex multi-constrained optimization problems. Advances in DNA synthesis have made it possible for biologists to routinely order DNA constructs with custom nucleotide sequences ( Kosuri and Church, 2014).
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