An Optimized Method for the Construction of a DNA Methylome from Small Quantities of Tissue or Purified DNA from Arabidopsis Embryo

• Published in: Molecules and cells 2021, 44(8), , pp.602-612
• Main Authors: Yoo, Hyunjin, Park, Kyunghyuk, Lee, Jaehoon, Lee, Seunga, Choi, Yeonhee
• Format: Article
• Language: English
• Subjects: Arabidopsis - embryology; Arabidopsis - genetics; DNA Methylation - genetics; DNA, Plant - isolation & purification; Molecular Biology - methods; Ribonuclease, Pancreatic - metabolism; Seeds - metabolism; 생물학
• ISSN: 1016-8478; 0219-1032
• DOI: 10.14348/molcells.2021.0084

DNA methylation is an important epigenetic mechanism affecting genome structure, gene regulation, and the silencing of transposable elements. Cell- and tissue-specific methylation patterns are critical for differentiation and development in eukaryotes. Dynamic spatiotemporal methylation data in these cells or tissues is, therefore, of great interest. However, the construction of bisulfite sequencing libraries can be challenging if the starting material is limited or the genome size is small, such as in Here, we describe detailed methods for the purification of embryos at all stages, and the construction of comprehensive bisulfite libraries from small quantities of input. We constructed bisulfite libraries by releasing embryos from intact seeds, using a different approach for each developmental stage, and manually picking single-embryo with microcapillaries. From these libraries, reliable methylome data were collected allowing, on average, 11-fold coverage of the genome using as few as five globular, heart, and torpedo embryos as raw input material without the need for DNA purification step. On the other hand, purified DNA from as few as eight bending torpedo embryos or a single mature embryo is sufficient for library construction when RNase A is treated before DNA extraction. This method can be broadly applied to cells from different tissues or cells from other model organisms. Methylome construction can be achieved using a minimal amount of input material using our method; thereby, it has the potential to increase our understanding of dynamic spatiotemporal methylation patterns in model organisms.