Evidence map›Paper›PMID 42278532›Full record

ReviewInternational journal of molecular sciences2026

Multi-Omics Dissection of Drought Stress Responses in Crops: From Molecular Regulatory Networks to Climate-Resilient Breeding Applications.

Baber Ali, Zeeshan Khan, Nijat Imin, Tibor Janda, Fatemeh Gholizadeh

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
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  5. Article
  6. Review
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

5 authors.

Baber AliFaculty of Engineering, Computing and Science, Western Sydney University, Penrith, NSW 2751, Australia.
Zeeshan KhanAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
Nijat IminFaculty of Engineering, Computing and Science, Western Sydney University, Penrith, NSW 2751, Australia.
Tibor JandaDepartment of Plant Physiology and Metabolomics, Agricultural Institute, HUN-REN Centre for Agricultural Research, 2462 Martonvásár, Hungary.ORCID 0000-0002-8249-6585
Fatemeh GholizadehDepartment of Plant Physiology and Metabolomics, Agricultural Institute, HUN-REN Centre for Agricultural Research, 2462 Martonvásár, Hungary.ORCID 0000-0002-1518-4629

Funding

National Research, Development and Innovation Office TKP2021-NKTA-06
6 · The paper itself

Abstract

Drought stress is the most pervasive abiotic constraint on global crop productivity, with projected intensification under climate change threatening the yields of staple crops including wheat, rice, maize, and legumes. Conventional breeding approaches have delivered limited gains against drought tolerance, constrained by the polygenic and multifactorial nature of stress adaptation, the complexity of genotype-by-environment interactions, and the inadequacy of field-based phenotyping under variable stress conditions. Omics technologies, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics, have substantially advanced the molecular dissection of drought tolerance by enabling high-resolution characterization of stress-responsive genes, regulatory networks, adaptive proteins, and metabolic reprogramming pathways. Specific traits targeted include root system architecture and depth, osmotic adjustment capacity through proline and glycine betaine accumulation, antioxidant defense mechanisms, ABA-mediated stomatal regulation, LEA protein accumulation, epigenetic stress memory, and yield stability under water deficit. This review systematically examines omics-based strategies for drought stress mitigation across major crops, highlighting individual omics contributions, multi-omics integration frameworks, computational tools including machine learning and AI-driven predictive modelling, and translational breeding applications. Case studies in wheat, rice, maize, and legumes illustrate how omics-driven approaches accelerate precision breeding for drought resilience through marker-assisted selection, genomic selection, and CRISPR-based gene editing. Challenges including data integration complexity, high implementation costs, limited cross-species transferability, and the need for field-scale validation of microbiome-based strategies are critically addressed. Future perspectives encompassing single-cell and spatial omics, AI-driven predictive breeding, digital agriculture integration, and international data governance frameworks are discussed. By aligning with climate-smart agriculture principles, multi-omics approaches provide a robust and transformative foundation for developing drought-resilient crop cultivars suitable for water-limited production systems worldwide.

Indexed as

Crops, AgriculturalDrought ResistanceGene Regulatory NetworksPlant BreedingStress, PhysiologicalClimate ChangeDroughtsGene Expression Regulation, PlantGenomicsMultiomicsclimate-smart agriculturecrop resiliencedrought stressepigenomicsgenomicsmulti-omics integrationprecision breedingtranscriptomics

Identifiers

PMID42278532
PMCPMC13256899

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.