ArticleRNA (New York, N.Y.)2005
Complete, gene-specific siRNA libraries: production and expression in mammalian cells.
Article in RNA (New York, N.Y.), 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 27 citations in OpenAlex.
- RNA Therapeutics: Delivery Problems and Solutions-A Review.Pharmaceutics · 2025Review
- Size unbiased representative enzymatically generated RNAi (SURER) library and application for RNAi therapeutic screens.Nucleic acid therapeutics · 2015Article
- RNAi: a potential new class of therapeutic for human genetic disease.Human genetics · 2011Review
- Association of ABCC2 and CDDP-Resistance in Two Sublines Resistant to CDDP Derived from a Human Nasopharyngeal Carcinoma Cell Line.Journal of oncology · 2010Article
- Amelioration of psoriasis by anti-TNF-alpha RNAi in the xenograft transplantation model.Molecular therapy : the journal of the American Society of Gene Therapy · 2009Article
- Single tube, high throughput cloning of inverted repeat constructs for double-stranded RNA expression.PloS one · 2009Article
- Lentivirus-mediated RNAi silencing targeting ABCC2 increasing the sensitivity of a human nasopharyngeal carcinoma cell line against cisplatin.Journal of translational medicine · 2008Article
- Large-scale production of dsRNA and siRNA pools for RNA interference utilizing bacteriophage phi6 RNA-dependent RNA polymerase.RNA (New York, N.Y.) · 2007Article
- RNA knockdown as a potential therapeutic strategy in Parkinson's disease.Gene therapy · 2006Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Short interfering RNAs (siRNAs) are widely used to silence the expression of specific genes. Current practice for designing effective siRNAs is to use algorithms based on sequence-efficacy correlations; however, there are many highly effective sequences that these algorithms do not anticipate. To ensure that the best siRNAs are identified, all possible gene-specific siRNA sequences of appropriate lengths should be screened in cell culture. Synthesizing and testing all such sequences individually is costly. A potentially much easier alternative is to prepare a mixture of all these sequences (a gene-specific library), express them in cells, select cells having the desired phenotype, and identify the siRNA contained within the selected cells. Here we describe two new methods for preparing and expressing such libraries. The first uses cloned Dicer or RNase III to digest gene-specific RNA duplexes to siRNAs, which are then converted to the corresponding DNA sequences by attaching RNA primers and performing reverse transcription-PCR. The second method involves partial DNase I digestion of gene-specific DNA, purification of a 20-30-bp fraction, and amplification by attaching DNA adapters followed by PCR. DNA libraries specific for TNF-alpha, DsRed, and part of the hepatitis C virus genome, generated by methods, were inserted into siRNA expression vectors between convergent human U6 and H1 promoters. Randomly selected clones from each library together with vectors expressing the corresponding target genes were cotransfected into 293FT cells and assayed for target gene inhibition. About 10%-20% of siRNAs represented in these libraries show significant inhibition of their target genes. Most of these inhibitory sequences are not predicted by existing algorithms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.