High molecular weight DNA extraction from mucilage rich zygnematophycean green algae for long read DNA sequencing

Zygnematophyceae green algae represent the closest living relatives of land plants. Adaptions to hydro-terrestrial environments are evident through the production of mucilage carbohydrates, which are secreted outside algal cell walls to retain water. However, the mucilage poses significant challenges for the extraction of high molecular weight (HMW) DNA. To address this, we have developed an efficient protocol optimized for algae nuclei isolation and HMW DNA extraction with modified CTAB method, facilitating the use of third-generation long read sequencing technologies, e.g., PacBio or Oxford Nanopore. Furthermore, we have benchmarked the performance of our method against eight established DNA extraction methods or commercial kits. Of the eight existing DNA extraction methods assessed, the PowerPlant DNeasy Kit, prominent for its use in plant DNA extraction, was the only protocol to successfully isolate DNA from Zygnema circumcarinatum algae. However, the DNA quality was insufficient for applications in PacBio or Oxford Nanopore sequencing. In contrast, our novel method not only yielded a high DNA concentration but also high purity with optimal A260/A230 and A260/A280 ratios suitable for long read DNA sequencing. Notably, the integrity of algal DNA obtained via our method surpassed that from commercial kits, demonstrating a significant increase in the length of extracted DNA, with a peak at 55.7 kb compared to 17.6 kb for the PowerPlant DNeasy Kit. Additionally, our method substantially reduced the organellar DNA, lowering it from 72.5% in the commercial kits to 9.6%, thereby enhancing the yield of nuclear genomic DNA. Our method represents a significant advancement in the extraction of DNA from challenging plants and algae characterized by high extracellular mucilage contents. Our protocol removes most organellar DNA, and thus substantially increases the proportion of nuclear DNA reads in the sequencing data to lower the cost for nuclear genome sequencing. Our cost-efficient method will facilitate the whole genome sequencing of mucilage-rich algae and plants.