Development of a High-Quality/Yield Long-Read Sequencing-Adaptable DNA Extraction Method for Crop Seeds

Genome sequencing is important for discovering critical genes in crops and improving crop breeding efficiency. Generally, fresh, young leaves are used for DNA extraction from plants. However, seeds, the storage form, are more efficient because they do not require cultivation and can be ground at room temperature. Yet, only a few DNA extraction kits or methods suitable for seeds have been developed to date. In this study, we introduced an improved (IMP) Boom method that is relatively low-cost, simple to operate, and yields high-quality DNA that can withstand long-read sequencing. The method successfully extracted approximately 8 µg of DNA per gram of seed weight from soybean seeds at an average concentration of 48.3 ng/µL, approximately 40-fold higher than that extracted from seeds using a common extraction method kit. The A_260/280 and A_260/230 values of the DNA were 1.90 and 2.43, respectively, which exceeded the respective quality thresholds of 1.8 and 2.0. The DNA also had a DNA integrity number value (indicating the degree of DNA degradation) of 8.1, higher than that obtained using the kit and cetyltrimethylammonium bromide methods. Furthermore, the DNA showed a read length N₅₀ of 20.96 kbp and a maximum read length of 127.8 kbp upon long-read sequencing using the Oxford Nanopore sequencer, with both values being higher than those obtained using the other methods. DNA extracted from seeds using the IMP Boom method showed an increase in the percentage of the nuclear genome with a decrease in the relative ratio of chloroplast DNA. These results suggested that the proposed IMP Boom method can extract high-quality and high-concentration DNA that can be used for long-read sequencing, which cannot be achieved from plant seeds using other conventional DNA extraction methods. The IMP Boom method could also be adapted to crop seeds other than soybeans, such as pea, okra, maize, and sunflower. This improved method is expected to improve the efficiency of various crop-breeding operations, including seed variety determination, testing of genetically modified seeds, and marker-assisted selection.