A Full-automatic Sequence Design Algorithm for Branched DNA Structures

Abstract

Production of various structures by self-assembling single stranded DNA molecules is a widely used technology in the filed of DNA nanotechnology. Base sequences of single strands do predict the shape of the resulting nanostructure. Therefore, sequence design is crucial for the successful structure fabrication. This paper presents a sequence design algorithm based on mismatch minimization that can be applied to every desired DNA structure. With this algorithm, junctions, loops, single as well as double stranded regions, and very large structures up to several thousand base pairs can be handled. Thereby, the algorithm is fast for the most structures. Algorithm is Java-implemented. Its implementation is called Seed and is available publicly. As an example for a successful sequence generation, this paper presents the fabrication of DNA chain molecules consisting of double-crossover (DX) tiles as well.

In vitro assembly of cubic RNA-based scaffolds designed in silico

“…The computational sequence optimization consists of sequence randomization and Monte Carlo optimization algorithms (Figure S1, Supporting Information (SI)). The objective function of the optimization is the weighted sum of three scores: (i) a rule-based score35,36, (ii) a score comparing the target secondary structure with RNAcofold37–39 predictions of all sequence pairs as well as with RNAfold37,40 predictions of all individual sequences, and (iii) a score evaluating a multi-sequence secondary structure prediction based on a trivial energy model34. Three different cube types were engineered: two cubes with and without dangling ends, each containing six strands of equal length, and a 10-stranded cube with dangling ends containing two different strand lengths (Figure 1).…”

EGNAS: an exhaustive DNA sequence design algorithm

“…Sets of sequences with defined properties can be achieved with the program Seed developed by Seiffert et al [10,11], as well as with the software tools DNASequenceGenerator and CANADA by Feldkamp et al [15,20,22,25]. These programs are freely available, work efficiently, provide satisfactory set sizes and meet the criteria of uniqueness among all sequences of a set concerning interstrand properties.…”

“…These are essential prerequisites to avoid secondary structures due to self-complementary sequences and hairpin formation. In contrast to the criton concept [2,3], as applied by Seiffert et al [10,11] and Feldkamp et al [15,20,22], the novel algorithm treats intrastrand properties separately. Below, we define the used terms and describe these properties.…”

“…On the one hand, the preassigned criton rules in Section “Intrastrand properties” are valid for the whole set of generated sequences. This holds for Seed [10,11], CANADA [25] and DNASequenceGenerator [15,20]. In this cases, we refer to “global criton rules” .…”

“…The operating system was a 32-bit Ubuntu 10.04 ( Linux ). The intra- and interstrand properties were verified by the analysis option of the software Seed [10,11]. …”