Evidence map›Paper›PMID 42305606›Full record

ArticleiScience2026

Elucidation of sugar metabolic profiles and transcriptional regulatory networks during the developmental stages of sweet corn kernels.

Haiying Feng, Jianghua Guo, Cuirong Xu, Ziheng Li, Zhenhua Hu, Jin Zhu, Wenkang Chen, Fazhan Qiu, Changcheng Xu

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Haiying FengInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.
Jianghua GuoState Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China.
Cuirong XuInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.
Ziheng LiInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.
Zhenhua HuInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.
Jin ZhuInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.
Wenkang ChenKey Laboratory of Maize Biology and Genetic Breeding in Arid Areas of the Northwest Region, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712100, China.
Fazhan QiuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Hubei Hongshan Laboratory, Wuhan, Hubei 430070, China.
Changcheng XuInstitute of Vegetables, Wuhan Academy of Agricultural Sciences, Wuhan 430345, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sweet corn is highly valued by consumers due to its desirable taste, which is largely influenced by sugar metabolism within the kernels. Despite its importance, the genetic and transcriptional regulatory mechanisms underlying sugar metabolism in sweet corn remain inadequately characterized. In this study, targeted profiling of sugar metabolism was conducted at three critical developmental stages of sweet corn kernels-the blister, milky, and waxy stages-using gas chromatography-mass spectrometry. Simultaneously, the direct RNA sequencing was employed to explore the complexity of transcriptional regulation throughout kernel development at the transcriptomic level, facilitating the construction of a regulatory network for sugar metabolism-related genes. The results indicated that variations in polyadenylation tail length may modulate sugar metabolism during kernel development by influencing transcript abundance. This study elucidates potential transcriptional regulatory pathways governing sugar metabolites in sweet corn kernels and provides foundational data to support precision breeding strategies.

Indexed as

Agricultural plant productsPlant biochemistryPlant bioinformaticsPlant biologyPlant developmentPlant systematics

Identifiers

PMID42305606
PMCPMC13266126

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LicenceCC BY-NC-ND
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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.