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A human beta-actin expression vector system directs high-level accumulation of antisense transcripts.

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Gunning, P, Leavitt, J, Muscat, G, Ng, S Y, Kedes, L·1987·Proceedings of the National Academy of Sciences

Abstract

We have constructed a mammalian expression vector consisting of 3 kilobases of the human beta-actin gene 5' flanking sequence plus 5' untranslated region and intervening sequence 1 linked at the 3' splice site to a short DNA polylinker sequence containing unique Sal I, HindIII, and BamHI restriction endonuclease sites followed by a simian virus 40 (SV40) polyadenylylation signal. Two derivatives, containing the selection markers obtained from pSV2gpt or pSV2neo, were also generated. We find that the promoter activity of this vector is a great or greater than that of the SV40 early promoter in a variety of human and rodent cells. The vector was used to generate gamma-actin and beta-tubulin antisense transcripts in human fibroblast cell lines. The antisense transcripts accumulate to levels comparable with that of the highly abundant gamma-actin and beta-tubulin mRNAs.

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Metadata

Authors
Gunning, P., Leavitt, J., Muscat, G., Ng, S. Y., & Kedes, L.
Venue
Proceedings of the National Academy of Sciences
Published
1987-07
Volume
84
Issue
14
Pages
4831-4835
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2089559330
Cited by
739
References
0
FWCI
8.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A human beta-actin expression vector system directs high-level accumulation of antisense transcripts. https://app.cochat.ai/papers/10.1073/pnas.84.14.4831
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Gunning, P., Leavitt, J., Muscat, G., Ng, S. Y., & Kedes, L. (1987). A human beta-actin expression vector system directs high-level accumulation of antisense transcripts. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.84.14.4831

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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.