Evidence map›Paper›PMID 42348123›Full record

ArticlePlant, cell & environment2026

Systems-Level Developmental Reprogramming Under Waterlogging Stress in Cowpea Revealed by Integrated Phenotypic, Physiological, and Transcriptomic Analysis.

Mohammad A Ghanbari, Omolayo J Olorunwa, Mohit Verma, Sorina C Popescu, Ainong Shi, T Casey Barickman, George V Popescu

Abstract read
In one paragraph

Article in Plant, cell & environment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Mohammad A GhanbariInstitute for Genomics, Biocomputing & Biotechnology, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0009-0002-4011-7986
Omolayo J OlorunwaDepartment of Plant and Soil Sciences, Mississippi State University, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0002-0830-360X
Mohit VermaInstitute for Genomics, Biocomputing & Biotechnology, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0002-0438-5396
Sorina C PopescuDepartment of Biochemistry, Nutrition, and Health Promotion, Mississippi State University, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0001-5780-8252
Ainong ShiDepartment of Horticulture, University of Arkansas, Fayetteville, Arkansas, USA.
T Casey BarickmanDepartment of Plant and Soil Sciences, Mississippi State University, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0003-1915-5769
George V PopescuInstitute for Genomics, Biocomputing & Biotechnology, Mississippi State, Mississippi, USA.ORCID https://orcid.org/0000-0002-7580-6792

Funding

Mississippi Agricultural & Forestry Experiment Station 160000-SRUSDA-Agricultural Research Unit through the Big Data: Biocomputing, Bioinformatics, and Biological Discovery projects 59-6066-4-007USDA-Agricultural Research Unit through the Big Data: Biocomputing, Bioinformatics, and Biological Discovery projects 6066-21310-004-25SUSDA-National Institute of Food and Agriculture Hatch project MIS-145120
6 · The paper itself

Abstract

Cowpea (Vigna unguiculata (L.) Walp.) is a climate-resilient grain legume that contributes to nutritional and food safety in a variety of production regions around the world; however, many of these regions are becoming more vulnerable to climate-driven flooding and waterlogging, endangering productivity and seed quality. In this study, we used RNA-seq to assess transcriptional responses to waterlogging in different cowpea genotypes during the vegetative, flowering, and maturity stages. Using measured phenotypic/physiological, biochemical, yield, and seed-quality traits, RNA-seq expression profiles were combined with differential expression analysis, KEGG pathway enrichment/Pathview mapping, transcription factor profiling, weighted gene co-expression network analysis (WGCNA), and XGBoost-based machine-learning prediction. The tolerant genotype UCR369 demonstrated stronger physiological recovery and more dynamic transcriptional adjustment than EpicSelect.4, whereas flowering and maturity exhibited the clearest divergence in waterlogging responses, which were strongly stage- and genotype-dependent. Waterlogging caused stage-dependent alterations to soluble sugars, phenolics, flavonoids and seed-quality traits while decreasing pigment status, gas exchange, chlorophyll fluorescence, membrane stability, and yield components. Pathway analysis revealed four prominent response axes: phenylpropanoid biosynthesis, flavonoid/isoflavonoid biosynthesis, starch and sucrose metabolism, and cutin/suberin/wax biosynthesis. KEGG pathway and Pathview analyses revealed activation of antioxidant and wall-associated phenolic metabolism, carbohydrate reallocation, and surface-lipid/barrier remodelling in UCR369, with a stronger integration of these responses, particularly during flowering and maturation. Transcription factor expression dynamics exhibited stage-specific activation of the MYB, bHLH, ERF/AP2, WRKY, HD-ZIP, and HSF families, which is compatible with redox buffering, hormone-linked stress signalling, and membrane/cuticle protection. WGCNA detected 35 co-expression modules, with the top five modules as the most closely linked to phenolics/starch, sucrose, plastid/pigment functions, and membrane stability. These transcriptome-scale patterns were condensed by XGBoost into a compact collection of trait-linked predictors, with the strongest cross-layer support centred on LTP3, CER1/CER22, and CASPL1D1 for cuticle/barrier remodelling, NIA2/NR2, ICL, and SAG12 for carbohydrate and redox reprogramming, HSP21 for plastid protection, and ACS6 for ethylene-associated stress signalling. Additional recurrent predictors, such as Vigun07g271600 and Vigun08g155100, point to cytochrome P450 and HSP20-related stress-protective activities. These findings establish a trait-anchored, systems-level framework for cowpea waterlogging tolerance, as well as biologically grounded targets for marker development, functional validation, and breeding in waterlogging-prone regions.

Indexed as

Stress, PhysiologicalVignaGene Expression ProfilingGene Expression Regulation, PlantGenotypePhenotypeTranscriptomecowpeaKEGG enrichmentmachine learning modelstranscriptomicswaterlogging stressweighted gene vo‐expression network analysis (WGCNA)

Identifiers

PMID42348123
PMCPMC13436478

What OpenQuestion holds

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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.