ArticleScientific reports2025
Integrating phenotypic, molecular, and bioinformatics approaches for developing drought-tolerant sesame.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Genome-wide variation analysis of two Salvia hispanica L. genotypes and implication for associations with metabolic and adaptive traits.Journal, genetic engineering & biotechnology · 2026Article
- Exploring the genetic landscape of sesame: whole genome sequencing reveals distinct Egyptian lineages and SNP variability.Molecular genetics and genomics : MGG · 2026Article
- Uracil-DNA Glycosylase fromInternational journal of molecular sciences · 2025Article
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4 authors.
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Abstract
Breeding climate-resilient crops with high tolerance to abiotic and biotic stresses represents a major challenge in responding to climate change. The present study evaluated new sesame lines under drought conditions, which required the implementation of multi-environment experiments (MET) with the aim of identifying the most productive and stable sesame lines combining phenotypic evaluation, SCoT-PCR markers, and bioinformatics analysis. Seed yield was assessed across 18 limited irrigation environments, revealing significant genotype-by-environment interactions. Four stable, high-yielding lines (C5-8, C6-9, C6-11, and C9-3) were identified under optimal and drought conditions using parametric and non-parametric statistics, AMMI, and GGE biplot analysis. SCoT-PCR analysis revealed a reasonable level of genetic diversity among the genotypes, with primer SCoT-21 showing the highest polymorphism (88.24%). Bioinformatics analysis of SCoT-21 and 28 amplified regions identified potential genes associated with drought tolerance, including a DNA repair helicase XPD gene and a malonyl-coenzyme: anthocyanin 5-O-glucoside-6'''-O-malonyl transferase-like gene. These findings provide valuable insights for developing drought-resistant sesame varieties and highlight the power of integrating phenotypic, molecular, and Bioinformatics approaches in crop improvement.
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