Evidence map›Paper›PMID 38304458›Full record

ArticleFrontiers in plant science2023

Comparison of the transcriptome and metabolome of wheat (

Jia Shi, Lihong Wang, Zhong Wang, Jianfeng Li, Hongzhi Zhang, Xin Gao, Chunsheng Wang, Jianqiang Xia, Zhun Zhao, Zhenlong Wang and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2023. 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
3.0field-weighted citation impact, top 10% 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, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Commonalities and Specificities in Wheat (International journal of molecular sciences · 2024
    Article
  6. Review
  7. Review
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

14 authors at 1 institution in 1 country.

Jia ShiInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Lihong WangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zhong WangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Jianfeng LiInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Hongzhi ZhangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Xin GaoInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Chunsheng WangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Jianqiang XiaInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zhun ZhaoInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zhenlong WangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zhenyu YangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zihan XuInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Yueqiang ZhangInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Zheru FanInstitute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences/Xinjiang Key Laboratory of Crop Biotechnology/Crop Chemical Regulation Engineering Technology Research Center in Xinjiang, Urumqi, China.
Xinjiang Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Wheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour. Methods: To elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering. Results: Transcriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified. Discussion: This study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process.

Indexed as

glutenin contentmetabolometranscriptomeWGCNAwheat

Identifiers

PMID38304458
PMCPMC10830700
OpenAlexW4390980510

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.