Evidence map›Paper›PMID 40944398›Full record

ArticlePlant biotechnology journal2026

Metabolo-Transcriptomics Analyses Reveal Alfalfa Adaptation to Combined Saline-Alkali and Low-Temperature Stress in the Field.

Rui Guo, Lei Liu, Jiaqi Li, Hongyu Qu, Weileng Guo, Lishuang Zhang, Dihe Yang, Ruixin Wang, Changhong Guo

Abstract read
In one paragraph

Article in Plant biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Time-Course Transcriptomic Analysis IdentifiesPlants (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. The Ionic and Metabolic Response Mechanisms ofPlants (Basel, Switzerland) · 2025
    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

9 authors.

Rui GuoKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0007-5140-5373
Lei LiuKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0004-5002-4171
Jiaqi LiKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0006-1754-4372
Hongyu QuKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0007-7473-3433
Weileng GuoKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0000-0002-9499-9622
Lishuang ZhangKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0000-0002-4552-4751
Dihe YangKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0001-9140-0944
Ruixin WangKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0009-0005-5942-390X
Changhong GuoKey Laboratory of Molecular Cytogenetics and Genetic Breeding of Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.ORCID https://orcid.org/0000-0001-8543-2942

Funding

Graduate Innovation Fund of Harbin Normal University HSDBSCX2024-07National Natural Science Foundation of China U21A20182 31972507
6 · The paper itself

Abstract

Alfalfa (Medicago sativa L.) is known as the 'King of Forage' because of its high protein content and excellent palatability. Alfalfa productivity is adversely affected in cold regions with saline-alkali soils. However, the mechanisms underlying the response of alfalfa to combined saline-alkali and low-temperature stress under field conditions remain unknown. The resistance of two alfalfa cultivars (resistant, ZD; sensitive, BM) in saline-alkali soil during cold and freezing periods was investigated using transcriptomic and metabolomic analyses. Metabolomic analysis revealed specific accumulation of amino acids, organic acids, carbohydrates, fatty acids and flavonoids in ZD compared with that in BM. The core differential metabolites associated with ZD stress resistance included isoleucine, fumaric acid, raffinose, 2-hydroxydocosanoic acid and isovitexin. Transcriptomic analysis revealed that ZD enriched more upregulated differentially expressed genes in galactose, starch and sucrose metabolism and flavonoid biosynthesis pathways than BM. Integrated metabolo-transcriptomic analysis highlighted flavonoid, carbohydrate, glutathione and salicylic acid biosynthesis as key pathways in alfalfa stress response. WGCNA identified 10 hub genes responsive to combined stress, with MsBAM1 potentially regulating the carbohydrate synthesis pathway and its silencing impaired alfalfa resistance to combined saline-alkali and low-temperature stress.

Indexed as

Medicago sativaTranscriptomeAdaptation, PhysiologicalAlkaliesCold TemperatureGene Expression ProfilingGene Expression Regulation, PlantMetabolomeMetabolomicsStress, PhysiologicalAlkaliesalfalfacombined saline‐alkali and low‐temperature stressmetabolomeMsBAM1transcriptome

Identifiers

PMID40944398
PMCPMC12906809

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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 OpenQuestion graph.