Evidence map›Paper›PMID 42746061›Full record

ArticleFrontiers in plant science2026

Integrated transcriptomic and metabolomic analyses reveal the molecular mechanisms of sugar accumulation and yield trade-off in sugar beet.

Xiaoshan Bai, Sizhong Li, Abudukadier Kuerban, Hong Sha, Daoqian Yu, Xinjiu Dong, Jing Zhu, Xiaojing Liu, Jipeng Zhang, Ziming Wang and 7 more

Abstract read
In one paragraph

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

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

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

17 authors.

Xiaoshan BaiCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Sizhong LiCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Abudukadier KuerbanCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Hong ShaCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Daoqian YuCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Xinjiu DongCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Jing ZhuCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Xiaojing LiuCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Jipeng ZhangCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Ziming WangCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Zhengxing LiuAksu Regional Agricultural Technology Extension Center, Xinjiang Uygur Autonomous Region, Aksu, China.
Liya LvCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Teng MaXinjiang Uygur Autonomous Region Seed Industry Development Center (Xinjiang Uygur Autonomous Region Hainan Improved Seed Breeding Station), Sanya, China.
Liang MengXinjiang Uygur Autonomous Region Seed Industry Development Center (Xinjiang Uygur Autonomous Region Hainan Improved Seed Breeding Station), Sanya, China.
Hengyu PanXinjiang Uygur Autonomous Region Seed Industry Development Center (Xinjiang Uygur Autonomous Region Hainan Improved Seed Breeding Station), Sanya, China.
Huajun LiuCrop Research Institute, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi, China.
Zhimin WangCollege of Agronomy and Biotechnology, China Agricultural University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The negative correlation between taproot yield and sugar content remains a persistent challenge in sugar beet ( Methods: We integrated transcriptomic and widely-targeted metabolomic data across five developmental stages of taproots from two lines with contrasting phenotypes: a high-sugar/low-yield line (Group K) and a low-sugar/high-yield line (Group D). Results: Our analysis revealed that high sucrose accumulation is driven by minimized metabolic consumption rather than enhanced biosynthesis. While the high-yield line (Group D) sustained elevated expression of sucrose synthesis genes ( Conclusions: The yield-sugar trade-off in sugar beet appears to reflect differential carbon allocation between primary metabolic pathways and sucrose storage, associated with distinct transcriptional programs in the two lines. The identified transcription factor hubs may participate in regulating the balance between growth-associated carbon use and storage metabolism. These findings provide candidate molecular targets for future studies aimed at simultaneously improving yield and sugar content in sugar beet.

Indexed as

carbon partitioningmetabolism suppressionsugar beettranscription factor hubyield-sugar trade-off

Identifiers

PMID42746061
PMCPMC13574974

What OpenQuestion holds

Textmetadata
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.