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Analysis of single- and double-stranded nucleic acids on polyacrylamide and agarose gels by using glyoxal and acridine orange.

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McMaster, G K, Carmichael, G G·1977·Proceedings of the National Academy of Sciences

Abstract

We have developed a simple and rapid system for the denaturation of nucleic acids and their subsequent analysis by gel electrophoresis. RNA and DNA are denatured in 1 M glyoxal (ethanedial) and 50% (vol/vol) dimethyl sulfoxide, at 50 degrees. The glyoxalated nucleic acids are then subjected to electrophoresis through either acrylamide or agarose gels in a 10 mM sodium phosphate buffer at pH 7.0. When glyoxalated DNA molecules of known molecular weights are used as standards, accurate molecular weights for RNA are obtained. Furthermore, we have employed the metachromatic stain acridine orange for visualization of nucleic acids in gels. This dye interacts differently with double- and single-stranded polynucleotides, fluorescing green and red, respectively. By using these techniques, native and denatured DNA and RNA molecules can be analyzed on the same slab gel.

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Authors
McMaster, G. K., & Carmichael, G. G.
Venue
Proceedings of the National Academy of Sciences
Published
1977-11
Volume
74
Issue
11
Pages
4835-4838
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2037957091
Cited by
2,348
References
0
FWCI
25.22
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Analysis of single- and double-stranded nucleic acids on polyacrylamide and agarose gels by using glyoxal and acridine orange. https://app.cochat.ai/papers/10.1073/pnas.74.11.4835
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McMaster, G. K., & Carmichael, G. G. (1977). Analysis of single- and double-stranded nucleic acids on polyacrylamide and agarose gels by using glyoxal and acridine orange. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.74.11.4835

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.