ArticleThe plant genome2025
Assessing the utility of genomic selection to breed for durable Ascochyta blight resistance in chickpea.
Article in The plant genome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Integrated Breeding Approaches for Ascochyta Blight Resistance in Chickpea.International journal of molecular sciences · 2026Review
- Accelerating genetic gain through integrated genomic selection in crop plants.Journal of applied genetics · 2026Review
- Genomic prediction for grain yield and biotic stress resistance in field pea (Frontiers in plant science · 2026Article
- Article
- Assessing the utility of genomic selection to breed for durable Ascochyta blight resistance in chickpea.The plant genome · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
Ascochyta blight (AB) is one of the most devastating fungal diseases of chickpea (Cicer arietinum L.). Conventional breeding has focused on exploiting and introgressing major genes (qualitative effect) to improve AB resistance in released varieties. However, such approaches are time-consuming and prone to the breakdown of disease resistance due to the fast evolution of AB pathogen. Genomic selection (GS) offers a promising alternative by predicting breeding values using genome-wide single nucleotide polymorphisms (SNPs), regardless of major or minor effects. To our knowledge, this is the first study to develop and implement GS to improve AB resistance in chickpea. Over 4 years, 2790 chickpea lines, representing a broad range of germplasm collections primarily sourced from the Australian Grains Genebank, were evaluated for AB disease response in the field and in an outdoor pot-based facility. Plants were genotyped with the Illumina multispecies pulse 30K SNP array, resulting in 23,239 high-quality SNPs distributed across the genome. Intermediate-to-high genomic prediction accuracies (0.40-0.90) were achieved across validation scenarios. Bayesian modeling identified six major QTL explaining 33% of the genetic variance for AB resistance, with the remaining variance explained by minor effect genes. Using genomic estimated breeding values (GEBVs), 462 lines of the 2790 lines were predicted to have higher resistance compared to the released check varieties, revealing the potential of further improvement of AB resistance for the industry. The desirable genomic prediction accuracy obtained in the study supports the applicability of GS to breed for AB resistance in chickpea.
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