Evidence map›Paper›PMID 32161798›Full record

ArticleBiology methods & protocols2018

Single-round isolation of diverse RNA aptamers from a random sequence pool.

Masahiko Imashimizu, Masaki Takahashi, Ryo Amano, Yoshikazu Nakamura

Open access · goldAbstract read
In one paragraph

Article in Biology methods & protocols, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Masahiko ImashimizuInstitute of Medical Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan.
Masaki TakahashiInstitute of Medical Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan.
Ryo AmanoInstitute of Medical Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan.
Yoshikazu NakamuraInstitute of Medical Science, University of Tokyo, Minato-ku, Tokyo, 108-8639, Japan.
Tokyo University of Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aptamers are oligonucleotide ligands with specific binding affinity to target molecules. Generally, RNA aptamers are selected from an RNA pool with random sequences, using the technique termed SELEX, in which the target-binding RNA molecules are repeatedly isolated and exponentially amplified. Despite several advantages, SELEX often produces uncertain results during the iterative amplifications of the rare target-binding RNA molecules. Here, we develop a non-repeated, primer-less and target immobilization-free isolation method for generating RNA aptamers, which is robust to experimental noise. Uniquely, this method focuses on finding and removal of non-aptamer sequences from the RNA pool by RNase digestion leaving target-bound aptamer molecules, and thus is independent of aptamer types. The undigested RNA sequences remaining are so few in number that they must be mixed with a large excess of a known sequence for further manipulations and this sequence is then removed by restriction digestion followed by high-throughput sequencing analysis to identify aptamers. Using this method, we generated multiple RNA aptamers targeting α-thrombin and TGFβ1 proteins, independently. This method potentially generates thousands of sequences as aptamer candidates, which may enable us to predict a common average sequence or structural property of these aptamers that is different from input RNA.

Identifiers

PMID32161798
PMCPMC6994090
OpenAlexW2804400102

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.