Evidence map›Paper›PMID 23617936›Full record

ArticleBMC genomics2013

Prediction and identification of natural antisense transcripts and their small RNAs in soybean (Glycine max).

Hu Zheng, Jiang Qiyan, Ni Zhiyong, Zhang Hui

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 16 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

4 authors at 2 institutions in 1 country.

Hu ZhengThe National Key Facilities for Crop Genetic Resources and Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Jiang Qiyan
Ni Zhiyong
Zhang Hui
Chinese Academy of Agricultural Sciences · CNInstitute of Crop Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNatural antisense transcripts (NATs) are a class of RNAs that contain a sequence complementary to other transcripts. NATs occur widely in eukaryotes and play critical roles in post-transcriptional regulation. Soybean NAT sequences are predicted in the PlantNATsDB, but detailed analyses of these NATs remain to be performed.

resultsA total of 26,216 NATs, including 994 cis-NATs and 25,222 trans-NATs, were predicted in soybean. Each sense transcript had 1-177 antisense transcripts. We identified 21 trans-NATs using RT-PCR amplification. Additionally, we identified 179 cis-NATs and 6,629 trans-NATs that gave rise to small RNAs; these were enriched in the NAT overlapping region. The most abundant small RNAs were 21, 22, and 24 nt in length. The generation of small RNAs was biased to one stand of the NATs, and the degradation of NATs was biased. High-throughput sequencing of the degradome allowed for the global identification of NAT small interfering RNAs (nat-siRNAs) targets. 446 target genes for 165 of these nat-siRNAs were identified. The nat-siRNA target could be one transcript of a given NAT, or from other gene transcripts. We identified five NAT transcripts containing a hairpin structure that is characteristic of pre-miRNA. We identified a total of 86 microRNA (miRNA) targets that had antisense transcripts in soybean.

conclusionsWe globally identified nat-siRNAs, and the targets of nat-siRNAs in soybean. It is likely that the cis-NATs, trans-NATs, nat-siRNAs, miRNAs, and miRNA targets form complex regulatory networks.

Indexed as

Databases, Nucleic AcidGlycine maxMicroRNAsRNA, AntisenseRNA, PlantRNA, Small InterferingTranscriptomeMicroRNAsRNA, AntisenseRNA, PlantRNA, Small Interfering

Identifiers

PMID23617936
PMCPMC3643859
OpenAlexW2005026443

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.