Evidence map›Paper›PMID 41634580›Full record

ArticleBMC plant biology2026

Location and growth period influence the bioactive compounds of Angelica sinensis (Oliv.) diels: multi-omics insights.

Xiaofang Gong, Bao Chen, Ling Yang, Yong Zhang, Sijing Chang, Tao Yang, Yukun Chen, Ying Zhu, Zhiye Wang, Xinhua He and 1 more

Abstract read
In one paragraph

Article in BMC plant biology, 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

11 authors.

Xiaofang Gong *Institute of Biology, Key Laboratory of Microbial Resources Exploitation and Utilization in Gansu Province, Gansu Academy of Sciences, Lanzhou, 730000, China. gongxf789@163.com.
Bao Chen *Department of Orthopedics, Lanzhou University Second Hospital, Lanzhou, 730000, China.
Ling YangSchool of Biological and Pharmaceutical Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Yong ZhangCollege of Life Sciences and Engineering, Hexi University, Zhangye, Gansu, 734000, China.
Sijing ChangSchool of Biological and Pharmaceutical Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Tao YangInstitute of Biology, Key Laboratory of Microbial Resources Exploitation and Utilization in Gansu Province, Gansu Academy of Sciences, Lanzhou, 730000, China.
Yukun ChenInstitute of Biology, Key Laboratory of Microbial Resources Exploitation and Utilization in Gansu Province, Gansu Academy of Sciences, Lanzhou, 730000, China.
Ying ZhuInstitute of Biology, Key Laboratory of Microbial Resources Exploitation and Utilization in Gansu Province, Gansu Academy of Sciences, Lanzhou, 730000, China.
Zhiye WangInstitute of Biology, Key Laboratory of Microbial Resources Exploitation and Utilization in Gansu Province, Gansu Academy of Sciences, Lanzhou, 730000, China.
Xinhua HeSchool of Biological Sciences, University of Westen Australia, Perth, 6009, Australia. xinhua.he@uwa.edu.au.
Lingui XueSchool of Biological and Pharmaceutical Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China. xuelg62218@sina.com.

Funding

Intellectual Property Plan Project Gansu Province of China 22ZSCQ037the Natural Science Foundation of Gansu Province of China; the Outstanding Youth Fund of the Gansu Academy of Sciences 24JRRA1134; 2024YQ-04the Science and Technology Program of Gansu Province of China; the Young Scientists Fund Project of Gansu Academy of Sciences 24JRRA1137; 2024QN-13
6 · The paper itself

Abstract

Angelica sinensis, a traditional medicinal herb, exhibits significant variations in efficacy quality linked to geographical origin and rhizosphere microbiome composition. However, the microbial factors driving the synthesis of its bioactive compounds in authentic (historically recognized for superior quality geoherbs, Min County) and adjacent regions remain poorly understood. This study integrated transcriptomic profiling of plant tissues with 16 S rRNA (bacteria) and ITS (fungi) sequencing of rhizosphere soils over multiple growth stages in authentic and near-authentic regions (the latter characterized by a similar climate but differing soil ecology). By combining these data with targeted metabolomics and soil property analysis, substantial regional and temporal variations in bioactive compound levels and soil properties were identified. Specifically, 2,367 differentially expressed genes (DEGs), 417 bacterial amplicon sequence variants (ASVs), and 295 fungal ASVs were detected with significant abundance shifts. Key genera, including Vicinamibacter and Bacillus (bacteria), and Bisifusarium and Longitudinalis (fungi), were linked to secondary metabolite production. Functional differences, such as those related to chitinolysis and fermentation pathways, were also observed. Co-occurrence networks revealed correlations between plant genes and microbial communities. Notably, soil parameters, including organic matter, total nitrogen, and soil alkaline phosphatase, were identified as key factors influencing microbial community structure. The rhizosphere microbiome was further associated with nutrient absorption, potentially impacting bioactive compound accumulation. This multi-omics analysis highlights the role of regional and growth-period variations in A. sinensis quality, offering valuable insights for optimizing its cultivation and efficacy across diverse regions.

Indexed as

Angelica sinensisBacteriaFungiGene Expression ProfilingMicrobiotaMultiomicsPlant RootsRhizosphereSoil MicrobiologyTranscriptome16S rRNA sequencingAngelica sinensisITS sequencingMicrobiomeRhizosphereTranscriptome sequencing

Identifiers

PMID41634580
PMCPMC12958592

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.