Evidence map›Paper›PMID 22971421›Full record

ArticlePlant methods2012

Development of a rapid and inexpensive method to reveal natural antisense transcripts.

Silvio Collani, Gianni Barcaccia

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Silvio CollaniLaboratory of Plant Genetics and Genomics, DAFNAE - University of Padova, Campus of Agripolis, Viale dell'Università 16, 35020 Legnaro, PD, Italy. gianni.barcaccia@unipd.it.
Gianni Barcaccia
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNatural antisense transcripts (NATs) are a group of RNAs encoded within a cell that have transcript complementarity to other RNA transcripts. NATs have been identified in multiple eukaryotes, including humans, mice, yeast and several plants, and are known to play crucial roles in gene regulation and modification via RNA interference, alternative splicing and genomic imprinting. NATs are also involved in several human diseases.

resultsWe describe a novel method to detect the occurrence of target NATs in specific plant tissues. This method differs from the others currently used in molecular biology laboratories for a number of reasons, particularly the simplicity and versatility of application, low cost and lower material requirement. We demonstrate that NATs can be detected by using diluted cDNA, avoiding the need for a large amount of RNA, thus differing from basic techniques, such as Northern blot hybridisation and reverse-transcription PCR amplification. Furthermore, our method also allows the precise detection of long NATs and their cloning into plasmid vectors for downstream applications. We also reported the first case of a tissue-specific NAT occurring in Oleaceae family and, the antisense orientation of this transcript, allows the splicing of two introns otherwise impossible in the sense orientation.

conclusionsThis method is the first that combines the polymerisation and cleavage activity of DNA polymerase and exonuclease enzymes, respectively, to discover NATs in living organisms. It may simplify the discovery of NATs in plants providing a new strategy for an easy identification and characterization of this group of RNA molecules. Furthermore, since NATs are found in multiple eukaryotes, our method can be easily applied to a wide range of organisms, including human, mice and yeast.

Identifiers

PMID22971421
PMCPMC3490877
OpenAlexW2164114151

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.