Evidence map›Paper›PMID 39622966›Full record

ArticleScientific reports2024

Full-length transcriptome sheds light into the molecular mechanism of tea leaf yellowing induced by red light.

Yaozong Shen, Xiao Han, Hui Wang, Jiazhi Shen, Litao Sun, Kai Fan, Yu Wang, Shibo Ding, Dapeng Song, Zhaotang Ding

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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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

10 authors.

Yaozong Shen *Tea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China.
Xiao Han *Tea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China.
Hui WangTea Research Institute, Rizhao Academy of Agricultural Sciences, Rizhao, China.
Jiazhi ShenTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China.
Litao SunTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China.
Kai FanTea Research Institute, Qingdao Agricultural University, Qingdao, China.
Yu WangTea Research Institute, Qingdao Agricultural University, Qingdao, China.
Shibo DingTea Research Institute, Rizhao Academy of Agricultural Sciences, Rizhao, China.
Dapeng SongTea Research Institute, Rizhao Academy of Agricultural Sciences, Rizhao, China.
Zhaotang DingTea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China. dzttea@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Light, as an energy source for plant photosynthesis, can not only affect the growth and development of plants, but also affect their leaf color. This study used white (WL), red (RL), and blue light (BL) to treat tea cuttings, aiming to investigate the effect of light quality on the color of tea leaves. The results showed that tea leaves turned yellow under red light, the SPAD and Fv/Fm values were significantly lower than WL and BL. Full-length transcriptome was analyzed, photosynthesis and chlorophyll biosynthesis related genes such as PsbS, Psb28, HemL, and POR had the lowest expression levels under RLCarotenoid biosynthesis related genes ZEP, ABA2, and CRTISO had the higher expression levels under RL. This study revealed the molecular mechanism of RL induced leaf yellowing in tea plants, providing new insights for the application of light quality in tea plants.

Indexed as

Camellia sinensisGene Expression Regulation, PlantLightPhotosynthesisPlant LeavesTranscriptomeChlorophyllGene Expression ProfilingPlant ProteinsRed LightTeaChlorophyllPlant ProteinsTeaCamellia sinensis(L.) O. KuntzeFull-length transcriptomeLeaf colorLight qualityTea cutting

Identifiers

PMID39622966
PMCPMC11612301

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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.