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<p>Understanding the genetic basis of spike-related traits under rain-fed conditions is vital for identifying candidate genes that enhance bread wheat productivity in environmentally variable production systems. Hence, the objective of this study was to identify stable loci associated with spike-related traits in bread wheat populations. This study employed a SNP-based multi-locus genome-wide association study (ML-GWAS) using 22,962 polymorphic SNPs and six ML-GWAS models in 220 bread wheat populations sourced from CIMMYT, ICARDA, and the Ethiopian bread wheat research programs. A field experiment was conducted across three environments using alpha lattice design with two replications. The combined analysis revealed highly significant (P &lt; 0.001) among the genotypes of the studied traits. The ML-GWAS identified five stable quantitative trait nucleotides (QTNs) significantly associated with spike related traits. Multi-locus GWAS identified extensive polygenic control of spike architecture traits. False negatives were minimized using False Discovery Rate correction (FDR &lt; 0.05). The average genomic inflation factor (λ = 1.04) reflected substantial polygenic architectures across traits. A total of ten genes surrounding five QTNs were detected across 21 chromosomes. Genes encoding key proteins like <i>TF-B3</i> domain protein, <i>Zinc finger GRF-type</i> protein, Protein kinase domain protein, Cytochrome <i>P450,</i> Zinc finger <i>GRF</i>-type domain-containing protein, and DNA-binding transcription factor activity; <i>IPR001471-AP2/ERF</i> domain were identified. These genes could be key in supporting optimal growth in bread wheat under rain-fed agricultural conditions. A validation experiment conducted in a similar environment confirmed the stability of these QTNs. These findings provide critical insights that guide the designing of breeding strategies aimed at enhancing grain yield through the accumulation of favorable SNP alleles that work best under moisture stressed conditions, thereby enabling crops to maintain productivity under rain-fed environment.</p>

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Dissecting the genetics of wheat spike traits: GWAS reveals targets for yield improvement

  • 期刊论文

  • 发表日期：

    2026年2月11日

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  • Sefawdin Berta,
  • Zerihun Tadesse,
  • Techale Birhan,
  • Yishak Beniam,
  • Temesgen Matiwos Menamo,
  • Abush Tesfaye Abebe

摘要

Understanding the genetic basis of spike-related traits under rain-fed conditions is vital for identifying candidate genes that enhance bread wheat productivity in environmentally variable production systems. Hence, the objective of this study was to identify stable loci associated with spike-related traits in bread wheat populations. This study employed a SNP-based multi-locus genome-wide association study (ML-GWAS) using 22,962 polymorphic SNPs and six ML-GWAS models in 220 bread wheat populations sourced from CIMMYT, ICARDA, and the Ethiopian bread wheat research programs. A field experiment was conducted across three environments using alpha lattice design with two replications. The combined analysis revealed highly significant (P < 0.001) among the genotypes of the studied traits. The ML-GWAS identified five stable quantitative trait nucleotides (QTNs) significantly associated with spike related traits. Multi-locus GWAS identified extensive polygenic control of spike architecture traits. False negatives were minimized using False Discovery Rate correction (FDR < 0.05). The average genomic inflation factor (λ = 1.04) reflected substantial polygenic architectures across traits. A total of ten genes surrounding five QTNs were detected across 21 chromosomes. Genes encoding key proteins like TF-B3 domain protein, Zinc finger GRF-type protein, Protein kinase domain protein, Cytochrome P450, Zinc finger GRF-type domain-containing protein, and DNA-binding transcription factor activity; IPR001471-AP2/ERF domain were identified. These genes could be key in supporting optimal growth in bread wheat under rain-fed agricultural conditions. A validation experiment conducted in a similar environment confirmed the stability of these QTNs. These findings provide critical insights that guide the designing of breeding strategies aimed at enhancing grain yield through the accumulation of favorable SNP alleles that work best under moisture stressed conditions, thereby enabling crops to maintain productivity under rain-fed environment.