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      The genetic architecture of resistance to septoria tritici blotch in French wheat cultivars

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          Abstract

          Background

          Septoria tritici blotch (STB) is one of the most damaging wheat diseases worldwide, and the development of resistant cultivars is of paramount importance for sustainable crop management. However, the genetic basis of the resistance present in elite wheat cultivars remains largely unknown, which limits the implementation of this strategy. A collection of 285 wheat cultivars originating mostly from France was challenged with ten Zymoseptoria tritici isolates at the seedling stage. The collection was further evaluated in seven field trials across France using artificial inoculation.

          Results

          Genome-wide association study resulted in the detection of 57 wheat QTL, among which 40 were detected at the seedling stage. Three quarters of these QTL were in genomic regions previously reported for to confer resistance to Z. tritici, but 10 QTL are novel and may be of special interest as new sources of resistance. Some QTL colocalise with major Stb resistance genes, suggesting their presence in the French elite winter wheat germplasm. Among them, the three QTL with the strongest effect colocalize with Stb6, Stb9 and Stb18. There was minimal overlap between the QTL detected at the seedling and adult plant stages, with only 1 out of 20 seedling QTL also being detected in field trials inoculated with the same isolate. This suggests that different resistance genes are involved at the seedling and adult plant stages.

          Conclusion

          This work reveals the highly complex genetic architecture of French wheat resistance to STB and provides relatively small QTL intervals, which will be valuable for identifying the underlying causative genes and for marker-assisted selection.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12870-024-05898-5.

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          Most cited references82

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          Shifting the limits in wheat research and breeding using a fully annotated reference genome

          An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.
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            Least-Squares Means: TheRPackagelsmeans

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              Mixed linear model approach adapted for genome-wide association studies.

              Mixed linear model (MLM) methods have proven useful in controlling for population structure and relatedness within genome-wide association studies. However, MLM-based methods can be computationally challenging for large datasets. We report a compression approach, called 'compressed MLM', that decreases the effective sample size of such datasets by clustering individuals into groups. We also present a complementary approach, 'population parameters previously determined' (P3D), that eliminates the need to re-compute variance components. We applied these two methods both independently and combined in selected genetic association datasets from human, dog and maize. The joint implementation of these two methods markedly reduced computing time and either maintained or improved statistical power. We used simulations to demonstrate the usefulness in controlling for substructure in genetic association datasets for a range of species and genetic architectures. We have made these methods available within an implementation of the software program TASSEL.
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                Author and article information

                Contributors
                cyrille.saintenac@inrae.fr
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                19 December 2024
                19 December 2024
                2024
                : 24
                : 1212
                Affiliations
                [1 ]Université Clermont Auvergne, INRAE, UMR GDEC, ( https://ror.org/01a8ajp46) Clermont-Ferrand, France
                [2 ]Université Paris Saclay, INRAE, UR BIOGER, ( https://ror.org/03xjwb503) Palaiseau, France
                [3 ]Present address: RAGT Semences, Druelle, 12510 France
                Article
                5898
                10.1186/s12870-024-05898-5
                11657422
                39701973
                7f506f12-8235-4c3a-8b78-b13576d707bf
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 20 August 2024
                : 29 November 2024
                Funding
                Funded by: French fund to support breeding research
                Award ID: FSOV-2018-DivR
                Award ID: FSOV-2018-DivR
                Award ID: FSOV-2018-DivR
                Award ID: FSOV-2018-DivR
                Award ID: FSOV-2018-DivR
                Award ID: FSOV-2018-DivR
                Funded by: French Research National Agency, PIA BREEDWHEAT
                Award ID: ANR-10-BTBR-03
                Award ID: ANR-10-BTBR-03
                Award ID: ANR-10-BTBR-03
                Award ID: ANR-10-BTBR-03
                Award ID: ANR-10-BTBR-03
                Funded by: FranceAgriMer
                Award ID: 2013-0544
                Award ID: 2013-0544
                Award ID: 2013-0544
                Award ID: 2013-0544
                Award ID: 2013-0544
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Plant science & Botany
                septoria tritici blotch,gwas,qtl,resistance,stb,markers
                Plant science & Botany
                septoria tritici blotch, gwas, qtl, resistance, stb, markers

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