Evidence map›Paper›PMID 36904055›Full record

ArticlePlants (Basel, Switzerland)2023

Transcriptome Analysis Reveals a Major Gene Expression Pattern and Important Metabolic Pathways in the Control of Heterosis in Chinese Cabbage.

Ru Li, Shanshan Nie, Ning Zhang, Min Tian, Lugang Zhang

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Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Transcriptome Shock in Developing Embryos of aInternational journal of molecular sciences · 2023
    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

5 authors.

Ru LiState Key Laboratory of Crop Stress Biology for Arid Area, College of Horticulture, Northwest A&F University, Xianyang 712100, China.
Shanshan NieState Key Laboratory of Crop Stress Biology for Arid Area, College of Horticulture, Northwest A&F University, Xianyang 712100, China.
Ning ZhangState Key Laboratory of Crop Stress Biology for Arid Area, College of Horticulture, Northwest A&F University, Xianyang 712100, China.
Min TianState Key Laboratory of Crop Stress Biology for Arid Area, College of Horticulture, Northwest A&F University, Xianyang 712100, China.
Lugang ZhangState Key Laboratory of Crop Stress Biology for Arid Area, College of Horticulture, Northwest A&F University, Xianyang 712100, China.

Funding

the Key Research and Development Program of Shaanxi Province 2023-YBNY-078the Key Research and Development Program of Yangling Seed Innovative Center Ylzy-sc-04the National Key Research and Development Program of China 2017YFD0101802
6 · The paper itself

Abstract

Although heterosis is commonly used in Chinese cabbage, its molecular basis is poorly understood. In this study, 16Chinese cabbage hybrids were utilized as test subjects to explore the potential molecular mechanism of heterosis. RNA sequencing revealed 5815-10,252 differentially expressed genes (DEGs) (female parent vs. male parent), 1796-5990 DEGs (female parent-vs-hybrid), and 2244-7063 DEGs (male parent vs. hybrid) in 16 cross combinations at the middle stage of heading. Among of them, 72.83-84.20% DEGs conformed to the dominant expression pattern, which is the predominant expression pattern in hybrids. There were 13 pathways in which DEGs were significantly enriched in most cross combinations. Among them, the plant-pathogen interaction (ko04626) and circadian rhythm-plant (ko04712)were significantly enriched by DEGs in strong heterosis hybrids. WGCNA also proved that the two pathways were significantly related to heterosis in Chinese cabbage.

Indexed as

Chinese cabbagedifferentially expressed genesheterosismetabolic pathwaytranscriptome analysis

Identifiers

PMID36904055
PMCPMC10005390

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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.