Wheat and Barley Genetics and Pathology Open access

Haplotype-based insights into the genetic architecture of net blotch resistance in barley

Dan Liu, Xuechen Zhang, Lislé Snyman, Tara Garrard and 10 more

bioRxiv (Cold Spring Harbor Laboratory) | Jul 24, 2026

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This study provides a comprehensive haplotype-level framework for understanding net blotch resistance and delivers practical insights for breeding barley cultivars with durable and broad-spectrum resistance to both NFNB and SFNB.

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Net blotch, caused by Pyrenophora teres, is a major constraint to barley production worldwide and occurs as two epidemiologically distinct forms: net form net blotch (NFNB) and spot form net blotch (SFNB). Although numerous resistance loci have been reported in recent years, their genetic relationship remains poorly understood, and the effective deployment of resistance is constrained by the complex genetic architecture of net blotch resistance. In this study, we used a haplotype-based mapping approach to dissect the genetic basis of resistance to NFNB and SFNB in a diverse panel of 950 barley accessions from the Australian Grains Genebank (AGG). Disease responses were evaluated across 13 experiments, and a total of 40 quantitative trait loci (QTL) were identified, including 26 associated with NFNB, 29 with SFNB, and 15 common for both diseases. Most loci co-localized with previously reported QTL, while six putative novel haploblocks highlighted untapped genetic diversity within the AGG collection. Correlation analyses across phenotypic, genetic and haploblock levels revealed a partial but incomplete overlap in resistance mechanisms between NFNB and SFNB. Among the 4,497 haploblocks, approximately 60% of them showed positive local genetic correlations between the two diseases, suggesting shared genomic contributions to resistance. Haplotype composition analysis further identified a resistant haplotype group, mainly comprising accessions of Asian origin, that exhibited high levels of resistance to both forms of net blotch. Through in-silico haplotype stacking simulations, we demonstrated the cumulative genetic potential achievable by combining favourable haplotypes. When the breeding objective was to improve resistance to both NFNB and SFNB, dual-disease stacking strategies outperformed single-disease approaches, highlighting the value of prioritising haplotypes with positive pleiotropic effects. Overall, this study provides a comprehensive haplotype-level framework for understanding net blotch resistance and delivers practical insights for breeding barley cultivars with durable and broad-spectrum resistance to both NFNB and SFNB.

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Researchers on this paper

Dan Liu

first | The University of Queensland | ORCID 0000-0002-3611-3520

Xuechen Zhang

middle | New South Wales Department of Primary Industries | ORCID 0000-0001-9121-4802

Lislé Snyman

middle | New South Wales Department of Primary Industries

Tara Garrard

middle | South Australian Research and Development Institute | ORCID 0000-0002-9853-9893

H. Wallwork

middle | South Australian Research and Development Institute | ORCID 0000-0002-9200-3254

Hari Dadu

middle | South Australian Research and Development Institute

M D Maclean

middle | Agriculture Victoria

Jingyang Tong

middle | The University of Queensland | ORCID 0000-0002-6653-4916

Chensong Chen

middle | The University of Queensland | ORCID 0000-0002-4276-8865

Dilani Jambuthenne

middle | The University of Queensland | ORCID 0000-0002-0744-3790

Sambasivam Periyannan

middle | University of Southern Queensland | ORCID 0000-0002-5421-2872

Lee T. Hickey

middle | The University of Queensland | ORCID 0000-0001-6909-7101

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Citation

BibTeX

@article{Liu2026Haplotype,
  title = {Haplotype-based insights into the genetic architecture of net blotch resistance in barley},
  author = {Dan Liu and Xuechen Zhang and Lislé Snyman and Tara Garrard and H. Wallwork and Hari Dadu and M D Maclean and Jingyang Tong and Chensong Chen and Dilani Jambuthenne and Sambasivam Periyannan and Lee T. Hickey and Ben J. Hayes and Eric Dinglasan},
  journal = {bioRxiv (Cold Spring Harbor Laboratory)},
  year = {2026},
  doi = {10.64898/2026.07.23.740211},
  url = {https://doi.org/10.64898/2026.07.23.740211}
}

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