Evidence map›Paper›PMID 36557334›Full record

ArticleMetabolites2022

Integrated Analysis of Widely Targeted Metabolomics and Transcriptomics Reveals the Effects of Transcription Factor NOR-like1 on Alkaloids, Phenolic Acids, and Flavonoids in Tomato at Different Ripening Stages.

Xinyu Yang, Xiaodan Zhao, Daqi Fu, Ying Zhao

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

7 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.

Xinyu YangSchool of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Xiaodan ZhaoSchool of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Daqi FuLaboratory of Fruit Biology, College of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, China.ORCID 0000-0003-0073-0196
Ying ZhaoSchool of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Beijing Technology and Business University · CNChina Agricultural University · CN

Funding

National Natural Science Foundation of China 31972129
6 · The paper itself

Abstract

Tomato is abundant in alkaloids, phenolic acids, and flavonoids; however, the effect of transcription factor NOR-like1 on these metabolites in tomato is unclear. We used a combination of widely targeted metabolomics and transcriptomics to analyze wild-type tomatoes and CR-NOR-like1 tomatoes. A total of 83 alkaloids, 85 phenolic acids, and 96 flavonoids were detected with significant changes. Combined with a KEGG enrichment analysis, we revealed 16 differentially expressed genes (DEGs) in alkaloid-related arginine and proline metabolism, 60 DEGs were identified in the phenolic acid-related phenylpropane biosynthesis, and 30 DEGs were identified in the flavonoid-related biosynthesis pathway. In addition, some highly correlated differential-expression genes with differential metabolites were further identified by correlation analysis. The present research provides a preliminary view of the effects of NOR-like1 transcription factor on alkaloid, phenolic acid, and flavonoid accumulation in tomatoes at different ripening stages based on widely targeted metabolomics and transcriptomics in plants, laying the foundation for extending fruit longevity and shelf life as well as cultivating stress-resistant plants.

Indexed as

alkaloidsflavonoidsNOR-like1phenolic acidstomatotranscriptomicswidely targeted metabolomics

Identifiers

PMID36557334
PMCPMC9853326
OpenAlexW4312115262

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.