Evidence map›Paper›PMID 30128600›Full record

ArticlePlanta2018

Circular RNA architecture and differentiation during leaf bud to young leaf development in tea (Camellia sinensis).

Wei Tong, Jie Yu, Yan Hou, Fangdong Li, Qiying Zhou, Chaoling Wei, Jeffrey L Bennetzen

Abstract read
PubMed Publisher
In one paragraph

Article in Planta, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

34 citing papers in PubMed, 91 citations in OpenAlex.

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  17. Identification and Characterization of Circular RNAs inInternational journal of molecular sciences · 2022
    Article
  18. Article
  19. Review
  20. Circular RNAs Repertoire and Expression Profile duringInternational journal of molecular sciences · 2021
    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

7 authors at 2 institutions in 2 countries.

Wei TongState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.
Jie YuState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.
Yan HouState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.
Fangdong LiState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.
Qiying ZhouState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.
Chaoling WeiState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China. weichl@ahau.edu.cn.ORCID http://orcid.org/0000-0003-0274-0910
Jeffrey L BennetzenState Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China. maize@uga.edu.
Anhui Agricultural University · CNXinyang Normal University · CN

Funding

China Postdoctoral Science Foundation 2016M601998China Postdoctoral Science Foundation 2017M612055China Postdoctoral Science Foundation 2017M621992Postdoctoral Science Foundation of Anhui Province, China 2017B189Special Innovative Province Construction in Anhui Province 15czs08032Special Project for Central Guiding Science and Technology Innovation of Region in Anhui Province 2016080503B024Top Talent Team Project of Anhui Agriculture University 03082021
6 · The paper itself

Abstract

MAIN

conclusionCircular RNA (circRNA) discovery, expression patterns and experimental validation in developing tea leaves indicates its correlation with circRNA-parental genes and potential roles in ceRNA interaction network. Circular RNAs (circRNAs) have recently emerged as a novel class of abundant endogenous stable RNAs produced by circularization with regulatory potential. However, identification of circRNAs in plants, especially in non-model plants with large genomes, is challenging. In this study, we undertook a systematic identification of circRNAs from different stage tissues of tea plant (Camellia sinensis) leaf development using rRNA-depleted circular RNA-seq. By combining two state-of-the-art detecting tools, we characterized 3174 circRNAs, of which 342 were shared by each approach, and thus considered high-confidence circRNAs. A few predicted circRNAs were randomly chosen, and 20 out of 24 were experimental confirmed by PCR and Sanger sequencing. Similar in other plants, tissue-specific expression was also observed for many C. sinensis circRNAs. In addition, we found that circRNA abundances were positively correlated with the mRNA transcript abundances of their parental genes. qRT-PCR validated the differential expression patterns of circRNAs between leaf bud and young leaf, which also indicated the low expression abundance of circRNAs compared to the standard mRNAs from the parental genes. We predicted the circRNA-microRNA interaction networks, and 54 of the differentially expressed circRNAs were found to have potential tea plant miRNA binding sites. The gene sets encoding circRNAs were significantly enriched in chloroplasts related GO terms and photosynthesis/metabolites biosynthesis related KEGG pathways, suggesting the candidate roles of circRNAs in photosynthetic machinery and metabolites biosynthesis during leaf development.

Indexed as

Alternative SplicingBinding SitesCamellia sinensisCell DifferentiationGene Expression ProfilingGene Regulatory NetworksMicroRNAsOrgan SpecificityPlant LeavesRNARNA, CircularRNA, MessengerRNA, PlantSequence Analysis, RNAMicroRNAsRNARNA, CircularRNA, MessengerRNA, PlantAlternative splicingcircRNAGene expression patternsmiRNANetwork

Identifiers

PMID30128600
OpenAlexW2888356635

What OpenQuestion holds

Textmetadata
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.