DNA Chisel - a versatile sequence optimizer

DNA Chisel (complete documentation here) is a Python library for optimizing DNA sequences with respect to a set of constraints and optimization objectives. It can also be used via a command-line interface, or a web application.

The library comes with over 15 classes of sequence specifications which can be composed to, for instance, codon-optimize genes, meet the constraints of a commercial DNA provider, avoid homologies between sequences, tune GC content, or all of this at once! Users can also define their own specifications using Python, making the library suitable for a large range of automated sequence design applications, and complex custom design projects. 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. For more information, please see the publication.

Citation

DNA Chisel, a versatile sequence optimizer, Valentin Zulkower, Susan Rosser. Bioinformatics (2020) 36, 16, 4508–4509

Usage

Defining a problem via scripts

The example below will generate a random sequence and optimize it so that:

• It will be rid of BsaI sites (on both strands).
• GC content will be between 30% and 70% on every 50bp window.
• The reading frame at position 500-1400 will be codon-optimized for E. coli.

from dnachisel import *

# DEFINE THE OPTIMIZATION PROBLEM

problem = DnaOptimizationProblem(
    sequence=random_dna_sequence(10000),
    constraints=[
        AvoidPattern("BsaI_site"),
        EnforceGCContent(mini=0.3, maxi=0.7, window=50),
        EnforceTranslation(location=(500, 1400))
    ],
    objectives=[CodonOptimize(species='e_coli', location=(500, 1400))]
)

# SOLVE THE CONSTRAINTS, OPTIMIZE WITH RESPECT TO THE OBJECTIVE

problem.resolve_constraints()
problem.optimize()

# PRINT SUMMARIES TO CHECK THAT CONSTRAINTS PASS

print(problem.constraints_text_summary())
print(problem.objectives_text_summary())

# GET THE FINAL SEQUENCE (AS STRING OR ANNOTATED BIOPYTHON RECORDS)

final_sequence = problem.sequence  # string
final_record = problem.to_record(with_sequence_edits=True)

Defining a problem via Genbank features

You can also define a problem by annotating directly a Genbank as follows:

Note that constraints (colored in blue in the illustration) are features of type misc_feature with a prefix @ followed by the name of the constraints and its parameters, which are the same as in python scripts. Optimization objectives (colored in yellow in the illustration) use prefix ~. See the Genbank API documentation for more details.

Genbank files with specification annotations can be directly fed to the web application or processed via the command line interface:

# Output the result to "optimized_record.gb"
dnachisel annotated_record.gb optimized_record.gb

Or via a Python script:

from dnachisel import DnaOptimizationProblem
problem = DnaOptimizationProblem.from_record("my_record.gb")
problem.optimize_with_report(target="report.zip")

By default, only the built-in specifications of DNA Chisel can be used in the annotations, however it is easy to add your own specifications to the Genbank parser, and build applications supporting custom specifications on top of DNA Chisel.

Reports

DNA Chisel also implements features for verification and troubleshooting. For instance by generating optimization reports:

problem = DnaOptimizationProblem(...)
problem.optimize_with_report(target="report.zip")

Here is an example of summary report:

How it works

DNA Chisel hunts down every constraint breach and suboptimal region by recreating local version of the problem around these regions. Each type of constraint can be locally reduced and solved in its own way, to ensure fast and reliable resolution.

Below is an animation of the algorithm in action:

Installation

DNA Chisel requires Python 3, and can be installed via a pip command:

pip install dnachisel     # <= minimal install without reports support
pip install 'dnachisel[reports]' # <= full install with all dependencies

The full installation using dnachisel[reports] downloads heavier libraries (Matplotlib, PDF reports, sequenticon) for report generation, but is highly recommended to use DNA Chisel interactively via Python scripts. Also install GeneBlocks and its dependencies if you wish to include a plot of sequence edits in the report.

Alternatively, you can unzip the sources in a folder and type

python setup.py install

Optionally, also install Bowtie to be able to use AvoidMatches (which removes short homologies with existing genomes). On Ubuntu:

sudo apt-get install bowtie

License = MIT

DNA Chisel is an open-source software originally written at the Edinburgh Genome Foundry by Zulko and released on Github under the MIT licence (Copyright 2017 Edinburgh Genome Foundry). Everyone is welcome to contribute!

More biology software

DNA Chisel is part of the EGF Codons synthetic biology software suite for DNA design, manufacturing and validation.

Related projects

(If you would like to see a DNA Chisel-related project advertized here, please open an issue or propose a PR)

• Benchling uses DNA Chisel as part of its sequence optimization pipeline according to this webinar video.
• dnachisel-dtailor-mode brings features from D-tailor to DNA Chisel, in particular for the generation of large collection of sequences covering the objectives fitness landscape (i.e. with sequences with are good at some objectives and bad at others, and vice versa).