Evidence map›Paper›PMID 23408149›Full record

ArticleMolecular biology reports2013

Characterization and expression profiling of selected microRNAs in tomato (Solanum lycopersicon) 'Jiangshu14'.

Nicholas Kibet Korir, Xiaoying Li, Sun Xin, Chen Wang, Song Changnian, Emrul Kayesh, Jinggui Fang

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Article in Molecular biology reports, 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
3.2field-weighted citation impact, top 9% 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, 10 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

7 authors at 1 institution in 2 countries.

Nicholas Kibet KorirCollege of Horticulture, Nanjing Agricultural University, Nanjing 210095, China. 2009204036@njau.edu.cn
Xiaoying Li
Sun Xin
Chen Wang
Song Changnian
Emrul Kayesh
Jinggui Fang
Nanjing Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Presence of selected tomato (Solanum lycopersicon) microRNAs (sly-miRNAs) was validated and their expression profiles established in roots, stems, leaves, flowers and fruits of tomato variety Jiangshu14 by quantitative RT-PCR (qRT-PCR). In addition conservation characteristics these sly-miRNAs were analyzed and target genes predicted bioinformatically. Results indicate that some of these miRNAs are specific to tomato while most are conserved in other plant species. Predicted sly-miRNA targets genes were shown to be targeted by either by a single or more miRNAs and are involved in diverse processes in tomato plant growth and development. All the 36 miRNAs were present in the cDNA of mixed tissues and qRT-PCR revealed that some of these sly-miRNAs are ubiquitous in tomato while others have tissue-specific expression. The experimental validation and expression profiling as well target gene prediction of these miRNAs in tomato as done in this study can add to the knowledge on the important roles played by these sly-miRNAs in the growth and development, environmental stress tolerance as well as pest and disease resistance in tomatoes and related species. In addition these findings broaden the knowledge of small RNA-mediated regulation in S. lycopersicon. It is recommended that experimental validation of the target genes be done so as to give a much more comprehensive information package on these miRNAs in tomato and specifically in the selected variety.

Indexed as

Gene Expression ProfilingComputational BiologyDNA, ComplementaryGene Expression Regulation, PlantMicroRNAsReproducibility of ResultsRNA, PlantSolanum lycopersicumDNA, ComplementaryMicroRNAsRNA, Plant

Identifiers

PMID23408149
OpenAlexW1998229106

What OpenQuestion holds

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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.