Evidence map›Paper›PMID 40581894›Full record

ReviewPlant molecular biology2025

Decoding plant responses to waterlogging: from stress signals to molecular mechanisms and their future implications.

Muhammad Mudasir, Ali Shahzad

Abstract readReview
PubMed Publisher
In one paragraph

Review in Plant molecular biology, 2025. 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. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. 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

2 authors.

Muhammad MudasirDepartment of Plant Breeding and Genetics, Bahauddin Zakaria University Multan, Multan, 60800, Pakistan.
Ali ShahzadSanya Nanfan Research Institute of Hainan University, Sanya, 572025, China. ali.thathyala3212@outlook.com.ORCID http://orcid.org/0009-0007-5520-3760

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change and global warming drastically alter ecosystems, intensifying extreme weather events such as heavy rainfall and glacier melting, leading to increased soil flooding and threatening agriculture. Waterlogging, a direct consequence of prolonged soil saturation, severely affects plant growth by causing hypoxia, impaired nutrient uptake, photosynthesis inhibition, energy depletion, and microbiome disturbances, ultimately leading to plant mortality. Despite research progress in mitigating waterlogging stress, the molecular mechanisms underlying plant perception and their subsequent adaptive responses remain largely unclear. Recent advancements in molecular, biochemical, and multi-omics technologies have enabled significant progress in understanding the molecular mechanisms of plant responses to stress conditions. In this review, we highlight the metabolic pathways and key genes that could be targeted to enhance waterlogging tolerance and discuss how advanced techniques can be implemented to understand waterlogging responses and develop resistant cultivars. We review molecular insights into how ethylene and hypoxia signaling pathways trigger waterlogging responses and highlight key factors involved in energy metabolism and phytohormone signaling pathways, along with possible directions for further study.

Indexed as

Plant Physiological PhenomenaPlantsSignal TransductionStress, PhysiologicalClimate ChangeEthylenesFloodsGene Expression Regulation, PlantPlant Growth RegulatorsWaterethyleneEthylenesPlant Growth RegulatorsWaterCrop improvementHypoxiaMolecular mechanismsOmicsStress signalingWaterlogging stress

Identifiers

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.