Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance

Sunflower (<i>Helianthus annuus</i>) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. <i>Verticillium dahliae</i> is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to <i>V. dahliae</i> across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with <i>V. dahliae</i> resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by <i>V. dahliae</i>. This study also reveals the polygenic architecture of <i>V. dahliae</i> resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector.

Authors

Institutions

Publication Details

Journal
Plants
Published
2024-09-14
DOI
https://doi.org/10.3390/plants13182582
Citations
6
Primary Topic
Plant pathogens and resistance mechanisms
Type
article
Field-Weighted Citation Impact
3.60

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance

Loren H. Rieseberg, Zhao Jun, Yue Yu, Jian Zhang et al.
6 citations
Plants
Plant pathogens and resistance mechanisms
3.60
article

Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance

Loren H. Rieseberg, Zhao Jun, Yue Yu, Jian Zhang, Jianfeng Yang
article en
6 citations

Abstract

Sunflower (<i>Helianthus annuus</i>) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. <i>Verticillium dahliae</i> is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to <i>V. dahliae</i> across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with <i>V. dahliae</i> resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by <i>V. dahliae</i>. This study also reveals the polygenic architecture of <i>V. dahliae</i> resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector.

PlantsVol. 13(18)
Inner Mongolia Agricultural University (CN), University of British Columbia (CA)
China Scholarship Council, China Agricultural Research System, Natural Sciences and Engineering Research Council of Canada
Zero hunger
Openalex Percentile: Top 8%
Plant pathogens and resistance mechanisms
3.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.