Evidence map›Paper›PMID 27501838›Full record

ArticleBMC genomics2016

Transcriptome profiling of drought responsive noncoding RNAs and their target genes in rice.

Pil Joong Chung, Harin Jung, Dong-Hoon Jeong, Sun-Hwa Ha, Yang Do Choi, Ju-Kon Kim

Open access · goldAbstract read
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Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
20.6field-weighted citation impact, top 1% 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

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3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 130 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

6 authors at 3 institutions in 1 country.

Pil Joong ChungGraduate School of International Agricultural Technology and Crop Biotechnology Institute/GreenBio Science & Technology, Seoul National University, Pyeongchang, 25354, Korea.
Harin JungGraduate School of International Agricultural Technology and Crop Biotechnology Institute/GreenBio Science & Technology, Seoul National University, Pyeongchang, 25354, Korea.
Dong-Hoon JeongDepartment of Life Science, Hallym University, Chuncheon, 24252, Korea.
Sun-Hwa HaDepartment of Genetic Engineering and Graduate School of Biotechnology, Kyung Hee University, Yongin, 17104, Korea.
Yang Do ChoiGraduate School of International Agricultural Technology and Crop Biotechnology Institute/GreenBio Science & Technology, Seoul National University, Pyeongchang, 25354, Korea.
Ju-Kon KimGraduate School of International Agricultural Technology and Crop Biotechnology Institute/GreenBio Science & Technology, Seoul National University, Pyeongchang, 25354, Korea. jukon@snu.ac.kr.
Seoul National University · KRHallym University · KRKyung Hee University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPlant transcriptome profiling has provided a tool for understanding the mechanisms by which plants respond to stress conditions. Analysis of genome-wide transcriptome will provides a useful dataset of drought responsive noncoding RNAs and their candidate target genes that may be involved in drought stress responses.

resultsHere RNA-seq analyses of leaves from drought stressed rice plants was performed, producing differential expression profiles of noncoding RNAs. We found that the transcript levels of 66 miRNAs changed significantly in response to drought conditions and that they were negatively correlated with putative target genes during the treatments. The negative correlations were further validated by qRT-PCR using total RNAs from both drought-treated leaves and various tissues at different developmental stages. The drought responsive miRNA/target pairs were confirmed by the presence of decay intermediates generated by miRNA-guided cleavages in Parallel Analysis of RNA Ends (PARE) libraries. We observed that the precursor miR171f produced two different mature miRNAs, miR171f-5p and miR171f-3p with 4 candidate target genes, the former of which was responsive to drought conditions. We found that the expression levels of the miR171f precursor negatively correlated with those of one candidate target gene, but not with the others, suggesting that miR171f-5p was drought-responsive, with Os03g0828701-00 being a likely target. Pre-miRNA expression profiling indicated that miR171f is involved in the progression of rice root development and growth, as well as the response to drought stress. Ninety-eight lncRNAs were also identified, together with their corresponding antisense transcripts, some of which were responsive to drought conditions.

conclusionsWe identified rice noncoding RNAs (66 miRNAs and 98 lncRNAs), whose expression was highly regulated by drought stress conditions, and whose transcript levels negatively correlated with putative target genes.

Indexed as

DroughtsGene Expression ProfilingGene Expression Regulation, PlantRNA, UntranslatedTranscriptomeAdaptation, BiologicalMicroRNAsOryzaPhenotypeRNA, AntisenseRNA InterferenceStress, PhysiologicalMicroRNAsRNA, AntisenseRNA, UntranslatedDrought stresslncRNAsmiRNANon-coding RNAOryza sativaPutative target genesRNA-seq

Identifiers

PMID27501838
PMCPMC4977689
OpenAlexW2492979942

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LicenceCC BY
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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.