A Robust and Efficient DNA Storage Architecture Based on Modulation Encoding and Decoding

Abstract

Synthetic DNA has been widely considered an attractive medium for digital data storage. However, the random insertion−deletion−substitution (IDS) errors in the sequenced reads still remain a critical challenge to reliable data recovery. Motivated by the modulation technique in the communication field, we propose a new DNA storage architecture to solve this problem. The main idea is that all binary data are modulated into DNA sequences with the same AT/GC patterns, which facilitate the detection of indels in noisy reads. The modulation signal could not only satisfy the encoding constraints but also serve as prior information to detect the potential positions of errors. Experiments on simulation and real data sets demonstrate that modulation encoding provides a simple way to comply with biological constraints for sequence encoding (i.e., balanced GC content and avoiding homopolymers). Furthermore, modulation decoding is highly efficient and extremely robust, which can correct up to ∼40% of errors. In addition, it is robust to imperfect clustering reconstruction, which is very common in practice. Although our method has a relatively low logical density of 1.0 bits/nt, its high robustness may provide a wide space for developing low-cost synthetic technologies. We believe this new architecture may boost the early coming of large-scale DNA storage applications in the future.

Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval

“…To verify the effectiveness of the ECA-PCRAIR algorithm in addressing the nonspecific pairing constraint, we compared it against traditional TC [ 27 ], QC [ 28 ] algorithms, and the latest YYC [ 29 ], Modulation [ 30 ], and CAC [ 19 ] algorithms. We analyzed the frequency of consecutive 8-base nonspecific pairing between DNA sequences of different experimental files and the 3’ ends of primers under various coding algorithms.…”

“…Its theoretical storage density ranges from 2.14 to 3.67 bits/nt, as depicted in Figure 6 . In comparison, current coding algorithms achieve a theoretical density of 1 to 1.98 bits/nt [ 19 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. This demonstrates that the proposed algorithm significantly enhances storage capacity, thereby reducing the cost of DNA sequence synthesis and accelerating the adoption and application of DNA storage technology.…”

Storing Images in DNA via base128 Encoding

“…In DNA storage, because synthesis and sequencing make it difficult to achieve a single-molecule-level operation, one cannot avoid the uncertainty generated in the storage process by optimizing only the encoding scheme. Therefore, to improve the success rate of data decoding and reading accuracy, researchers must introduce error correction schemes. , Currently, two main types of error correction approaches exist. The first type involves performing logical operations on the original data and adding error correction codes such as Reed-Solomon (RS) and low-density parity-check (LDPC) at the end. − In 2015, Grass et al innovatively applied RS to DNA sequences, utilizing the logical redundancy of the data to achieve error detection and correction within sequences.…”