# Image Storage in DNA by an Extensible Quaternary Codec System
## 5 Conclusions and Future Work  
Our research presents a true quaternary DNA storage encoding system, specifically designed for image files, which achieves high storage density and data integrity. By dividing color images into RGB channels and employing a lossless compression method combined with Reed-Solomon (RS) error correction codes, we ensured that decompressed images were identical to the originals. The ETQ demonstrated excellent performance in both in vitro and computational simulation experiments. In vitro experiments achieved a net storage density of 1.41 bits/nt, while in silico simulations surpassed the theoretical 2 bits/nt limit established by [PERSON] [10]. The system's modular design, centered on quaternary Huffman encoding and RS error correction, offers flexibility and extensibility, making it adaptable to other data types such as text or audio by omitting color channel processing steps. This work provides valuable insights into optimizing DNA digital storage systems and highlights the potential of quaternary encoding to overcome current storage density limitations. Future research on DNA storage should focus on developing efficient, quaternary-specific error correction codes to address unique challenges like insertions, deletions, and substitutions, while minimizing redundancy and cost. Advanced quaternary encoding methods, building on the ETQ framework, can refine mapping schemes for stable and efficient base combinations. Multi-layered encoding atop the quaternary Huffman framework could enhance storage density and error resilience. Biotechnological advancements in DNA synthesis and sequencing tailored for storage applications are crucial to reduce errors and improve performance. Additionally, the modular design of the ETQ enables seamless integration with other encoding or error correction strategies, paving the way for robust and versatile DNA storage solutions. We believe that the introduction of quaternary encoding has the potential to significantly enhance DNA storage systems, surpassing the 2 bits/nt storage density limit and enabling more efficient data storage. In the future, encoding systems that directly map data to nucleotide sequences are likely to replace the current paradigm of \"data \(\rightarrow\) binary data stream \(\rightarrow\) nucleotide sequence\", further advancing the field of DNA storage technology. And we will focus on advancing quaternary error correction algorithms, particularly those addressing the insertion-deletion-substitution (indel-sub) error correlation inherent to DNA storage systems. This includes developing machine learning-driven encoding optimization to counteract sequence synthesis biases and engineering enzymatic synthesis platforms for error-suppressed long-strand (>500 nt) production. Concurrent standardization efforts will prioritize establishing ethical guidelines and interoperability protocols for biologically embedded data within hybrid silicon-DNA storage hierarchies, ensuring secure transitions between molecular and electronic domains. Through algorithmic development and biotechnology co-advancement, this integrated strategy aims to resolve error propagation challenges while enabling scalable architectures for ultra-dense data preservation, ultimately contributing actionable solutions to the impending zettabyte-scale data storage crisis. Conceptualization, R.P., Y.D. and X.Z. ; methodology, R.P., Y.D. and X.Z. ; software, R.P. ; validation, R.P., Y.D. and X.Z. ; formal analysis, R.P. ; investigation, R.P., and Y.D. ; resources, X.Z. ; data curation, R.P. and Y.D. ; writing--original draft preparation, R.P. ; writing--review and editing, X.Z. ; visualization, R.P. ; supervision, X.Z. ; project administration, X.Z. ; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript. This work was funded by the National Natural Science Foundation of China under grant No. 62174107, the National Key R&D Program of China No. 2022 YFF1202000, and the National Natural Science Foundation of China under grant No. 62188102.