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Laser-Capture Microdissection RNA-Sequencing for Spatial and Temporal Tissue-Specific Gene Expression Analysis in Plants
Published on: August 5, 2020
Short Communication An efficient method for simultaneous extraction of high-quality RNA and DNA from various plant
R R Oliveira1, A J C Viana1, A C E Reátegui1
1Centro de Biologia Molecular e Engenharia Genética, Universidade Estadual de Campinas, Cidade Universitária Zeferino Vaz, Campinas, SP, Brasil.
Abstract:
Determination of gene expression is an important tool to study biological processes and relies on the quality of the extracted RNA. Changes in gene expression profiles may be directly related to mutations in regulatory DNA sequences or alterations in DNA cytosine methylation, which is an epigenetic mark. Correlation of gene expression with DNA sequence or epigenetic mark polymorphism is often desirable; for this, a robust protocol to isolate high-quality RNA and DNA simultaneously from the same sample is required. Although commercial kits and protocols are available, they are mainly optimized for animal tissues and, in general, restricted to RNA or DNA extraction, not both. In the present study, we describe an efficient and accessible method to extract both RNA and DNA simultaneously from the same sample of various plant tissues, using small amounts of starting material. The protocol was efficient in the extraction of high-quality nucleic acids from several Arabidopsis thaliana tissues (e.g., leaf, inflorescence stem, flower, fruit, cotyledon, seedlings, root, and embryo) and from other tissues of non-model plants, such as Avicennia schaueriana (Acanthaceae), Theobroma cacao (Malvaceae), Paspalum notatum (Poaceae), and Sorghum bicolor (Poaceae). The obtained nucleic acids were used as templates for downstream analyses, such as mRNA sequencing, quantitative real time-polymerase chain reaction, bisulfite treatment, and others; the results were comparable to those obtained with commercial kits. We believe that this protocol could be applied to a broad range of plant species, help avoid technical and sampling biases, and facilitate several RNA- and DNA-dependent analyses.
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