ArticleBMC plant biology2025
Unveiling alfalfa root rot resistance genes through an integrative GWAS and transcriptome study.
Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Genome-Wide Association Identifies Candidate Genes for Salt Tolerance in Soybean at Emergence and Seedling Stages.Biology · 2026Article
- Genome-wide association studies reveal a functional SNP and candidate genes associated with alkali tolerance in alfalfa.Plant molecular biology · 2026Article
- Identifying candidate genes for grain protein content in wheat (Triticum aestivum L.) by integrated GWAS and transcriptome analysis.BMC plant biology · 2026Article
- Article
- Mendelian randomization reveals immune cell composition as a key determinant of cervical cancer prognosis.Discover oncology · 2025Article
- Harnessing the Potential of CRISPR/Cas in Targeted Alfalfa Improvement for Stress Resilience.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundRoot rot is a major disease affecting alfalfa (Medicago sativa L.), causing significant yield losses and economic damage. The primary pathogens include Fusarium spp., Rhizoctonia spp., Pythium spp., and Phytophthora spp., with Fusarium being particularly severe. Breeding disease-resistant varieties is crucial for mitigating these losses.
resultsUnder conditions of inoculation with Fusarium oxysporum, we conducted a statistical analysis of six phenotypic traits in alfalfa. Significant phenotypic variation was observed among different alfalfa varieties. Correlation analysis revealed significant relationships among traits such as relative yield, relative plant height (PH), and relative root number (NR), indicating potential synergistic roles of these traits in disease resistance. Through GWAS analysis, we identified 41 significant single nucleotide polymorphisms (SNP) associated with root rot resistance across eight chromosomes. The transcriptome analysis identified multiple differentially expressed genes (DEGs) associated with root rot stress, including transcription factors such as WRKY, NAC, AP2, GRAS, HLH, B3, MYB, and ARF. By integrating GWAS and transcriptome data, we identified four key DEGs significantly associated with root rot resistance, offering valuable insights for developing disease-resistant alfalfa varieties and enhancing overall crop resilience.
conclusionOur study identified significant phenotypic variation and key correlations among traits under root rot stress in alfalfa. We pinpointed 41 significant SNPs associated with root rot resistance across eight chromosomes and identified several key DEGs, including WRKY, NAC, and MYB transcription factors. The integration of GWAS and RNA-Seq data identified four key DEGs associated with root rot resistance, providing valuable insights for breeding disease-resistant alfalfa varieties and enhancing crop resilience.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.