Evidence map›Paper›PMID 39955705›Full record

ArticleFunctional & integrative genomics2025

Unraveling key genes and pathways involved in Verticillium wilt resistance by integrative GWAS and transcriptomic approaches in Upland cotton.

Majid Khan, Daowu Hu, Shuai Dai, Hongge Li, Zhen Peng, Shoupu He, Muhammad Awais, Xiongming Du, Xiaoli Geng

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In one paragraph

Article in Functional & integrative genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Integrative identification of key genes governingFrontiers in plant science · 2025
    Article
4 · The record

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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.

Majid KhanState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Daowu HuState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Shuai DaiState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Hongge LiState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Zhen PengState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Shoupu HeState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
Muhammad AwaisFaculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, 650500, China.
Xiongming DuState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. duxiongming@caas.cn.
Xiaoli GengState Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China. gengxiaoli@caas.cn.

Funding

Sanya Yazhou Bay Science and Technology City SCKJ-JYRC-2023-52
6 · The paper itself

Abstract

Verticillium dahliae Kleb, the cause of Verticillium wilt, is a particularly destructive soil-borne vascular disease that affects cotton, resulting in serious decline in fiber quality and causing significant losses in cotton production worldwide. However, the progress in identification of wilt-resistance loci or genes in cotton has been limited, most probably due to the highly complex genetic nature of the trait. Nevertheless, the molecular mechanism behind the Verticillium wilt resistance remains poorly understood. In the present study, we investigated the phenotypic variations in Verticillium tolerance and conducted a genome wide association study (GWAS) among a natural population containing 383 accessions of upland cotton germplasm and performed transcriptomic analysis of cotton genotypes with differential responses to Verticillium wilt. GWAS detected 70 significant SNPs and 116 genes associated with resistance loci in two peak signals on D02 and D11 in E1. The transcriptome analysis identified a total of 2689 and 13289 differentially expressed genes (DEGs) among the Verticillium wilt-tolerant (J46) and wilt-susceptible (J11) genotypes, respectively. The DEGs were predominantly enriched in metabolism, plant hormone signal transduction, phenylpropanoid pathway, MAPK cascade pathway and plant-pathogen interaction pathway in GO and KEGG analyses. The identified DEGs were found to comprise several transcription factor (TF) gene families, primarily including AP2/ERF, ZF, WRKY, NAC and MYB, in addition to pentatricopeptide repeat (PPR) proteins and Resistance (R) genes. Finally, by integrating the two results, 34 candidate genes were found to overlap between GWAS and RNA-seq analyses, associated with Verticillium-wilt resistance, including WRKY, MYB, CYP and RGA. This work contributes to our knowledge of the molecular processes underlying cotton responses to Verticillium wilt, offering crucial insights for additional research into the genes and pathways implicated in these responses and paving the way for developing Verticillium wilt-resistant cotton varieties through accelerated breeding by providing a plethora of candidate genes.

Indexed as

Disease ResistanceGossypiumPlant DiseasesTranscriptomeAscomycotaGene Expression Regulation, PlantGenome-Wide Association StudyPlant ProteinsPolymorphism, Single NucleotideVerticilliumPlant ProteinsCottonDEGGWASRNA-seqVerticillium wilt

Identifiers

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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.