Error characterization and error correction approaches in combinatorial DNA-based storage
Data storage in DNA has recently emerged as a promising archival solution, offering space-efficient and long-lasting digital storage. Combinatorial DNA encoding enhances this potential by increasing the logical density through combinations of DNA shortmers, where each sequence position is represented by a set of predefined short DNA fragments, allowing more data to be encoded using fewer synthesis cycles. However, this method introduces unique synthesis and sequencing errors. In this study, we characterize errors in combinatorial DNA-based storage systems. We reveal that asymmetric combinatorial erasure errors, defined as the omission of a single shortmer from the set defining the combinatorial letter, are a prevalent error type, particularly in large-scale systems where read coverage is limited. In two previously published datasets, we observed a high frequency of erasure errors, where missing sequences obstruct the reconstruction of combinatorial letters. We conducted a large-scale experimental proof-of-concept and confirmed that erasure errors become increasingly prominent with reduced sequencing depth: below 50 reads per sequence, their frequency sharply increased. We developed an asymmetric error-correcting code for these errors, utilizing tensor-product codes to integrate standard erasure and substitution-correcting codes (such as Reed-Solomon (RS) codes) with asymmetric Varshamov-Tenengolts codes. We validated its performance in simulations and in a second large-scale experiment directly comparing it with the more straightforward 2D RS scheme. Our method consistently outperformed 2D RS, particularly in erasure-dominated scenarios, and demonstrated superior decoding accuracy under low coverage conditions where 2D RS struggled to decode the data. Our findings demonstrate the importance of error correction schemes tailored to the asymmetric nature of errors in combinatorial DNA.