Historic recombination in a durum wheat breeding panel enables high-resolution mapping of Fusarium head blight resistance quantitative trait loci.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
05 05 2020
Historique:
received: 20 01 2020
accepted: 15 04 2020
entrez: 7 5 2020
pubmed: 7 5 2020
medline: 1 12 2020
Statut: epublish

Résumé

The durum wheat line DT696 is a source of moderate Fusarium head blight (FHB) resistance. Previous analysis using a bi-parental population identified two FHB resistance quantitative trait loci (QTL) on chromosome 5A: 5A1 was co-located with a plant height QTL, and 5A2 with a major maturity QTL. A Genome-Wide Association Study (GWAS) of DT696 derivative lines from 72 crosses based on multi-environment FHB resistance, plant height, and maturity phenotypic data was conducted to improve the mapping resolution and further elucidate the genetic relationship of height and maturity with FHB resistance. The Global Tetraploid Wheat Collection (GTWC) was exploited to identify durum wheat lines with DT696 allele and additional recombination events. The 5A2 QTL was confirmed in the derivatives, suggesting the expression stability of the 5A2 QTL in various genetic backgrounds. The GWAS led to an improved mapping resolution rendering the 5A2 interval 10 Mbp shorter than the bi-parental QTL mapping interval. Haplotype analysis using SNPs within the 5A2 QTL applied to the GTWC identified novel haplotypes and recombination breakpoints, which could be exploited for further improvement of the mapping resolution. This study suggested that GWAS of derivative breeding lines is a credible strategy for improving mapping resolution.

Identifiants

pubmed: 32372012
doi: 10.1038/s41598-020-64399-1
pii: 10.1038/s41598-020-64399-1
pmc: PMC7200731
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

7567

Références

Stępień, Ł. & Chełkowski, J. Fusarium head blight of wheat: pathogenic species and their mycotoxins. World Mycotoxin J. 3, 107–119 (2010).
doi: 10.3920/WMJ2009.1193
Sari, E. et al. High-density genetic mapping of Fusarium head blight resistance QTL in tetraploid wheat. PlosOne 13, e0204362 (2018).
doi: 10.1371/journal.pone.0204362
Clarke, J. M. et al. Brigade durum wheat. Can. J. Plant Sci. 89, 505–509 (2009).
doi: 10.4141/CJPS08168
Singh, A. K. et al. Transcend durum wheat. Can. J. Plant Sci. 92, 809–813 (2012).
doi: 10.4141/cjps2011-255
Brar, G. S. Characterization of resistance to Fusarium head blight in bread and durum wheat. Ph.D. thesis, Department of Plant Sciences, the University of Saskatchewan (2019).
Buerstmayr, H. et al. Molecular mapping of QTLs for Fusarium head blight resistance in spring wheat. I. Resistance to fungal spread (Type II resistance). Theor. Appl. Genet. 104, 84–91 (2002).
pubmed: 12579431 doi: 10.1007/s001220200009
Buerstmayr, H. et al. Variation for resistance to head blight caused by Fusarium graminearum in wild emmer in wild emmer (Triticum dicoccoides) originating from Israel. Euphytica 130, 17–23 (2003).
doi: 10.1023/A:1022324727780
Buerstmayr, M. et al. Mapping of QTL for Fusarium head blight resistance and morphological and developmental traits in three backcross populations derived from Triticum dicoccum × Triticum durum. Theor. Appl. Genet. 125, 1751–1765 (2012).
pubmed: 22926291 pmcid: 3493669 doi: 10.1007/s00122-012-1951-2
Buerstmayr, M. & Buerstmayr, H. The semi-dwarfing alleles Rht-D1b and Rht-B1b show marked differences in their associations with anther-retention in wheat heads and with Fusarium head blight susceptibility. Phytopathology 106, 1544–1552 (2016).
pubmed: 27452901 doi: 10.1094/PHYTO-05-16-0200-R
He, X. et al. Dwarfing genes Rht-B1b and Rht-D1b are associated with both Type I FHB susceptibility and low anther extrusion in two bread wheat populations. PLoSOne 11, e0162499 (2016).
doi: 10.1371/journal.pone.0162499
Buerstmayr, M., Lemmens, M., Steiner, B. & Buerstmayr, H. Advanced backcross QTL mapping of resistance to Fusarium head blight and plant morphological traits in a Triticum macha × T. aestivum population. Theor. Appl. Genet. 123, 293–306 (2011).
pubmed: 21479934 pmcid: 3114081 doi: 10.1007/s00122-011-1584-x
Buerstmayr, M. & Buerstmayr, H. Comparative mapping of quantitative trait loci for Fusarium head blight resistance and anther retention in the winter wheat population Capo × Arina. Theor. Appl. Genet. 128, 1519–1530 (2015).
pubmed: 25982129 pmcid: 4477076 doi: 10.1007/s00122-015-2527-8
Steiner, B. et al. Fine-mapping of the Fusarium head blight resistance QTL Qfhs.ifa-5A identifies two resistance QTL associated with anther extrusion. Theor. Appl. Genet. 132, 2039–2053 (2019).
pubmed: 30949717 pmcid: 6588648 doi: 10.1007/s00122-019-03336-x
Handa, H., Namiki, N., Xu, D. & Ban, T. Dissecting of the FHB resistance QTL on the short arm of wheat chromosome 2D using a comparative genomic approach: from QTL to candidate gene. Mol. Breed. 22, 71–84 (2008).
doi: 10.1007/s11032-008-9157-7
Ghavami, F. et al. Mixed model association mapping for Fusarium head blight resistance in Tunisian-derived durum wheat populations. Genetics 1, 209–218 (2011).
Steiner, B. et al. Exploring and exploiting the genetic variation of Fusarium head blight resistance for genomic-assisted breeding in the elite durum wheat gene pool. Theor. Appl. Genet. 132, 969–988 (2019).
pubmed: 30506523 doi: 10.1007/s00122-018-3253-9
Rawat, N. et al. Wheat Fhb1 encodes a chimeric lectin with agglutinin domains and a pore-forming toxin-like domain conferring resistance to Fusarium head blight. Nat. Genet. 48, 1576–1580 (2016).
pubmed: 27776114 doi: 10.1038/ng.3706
Su, Z., Jin, S., Zhang, D. & Bai, G. Development and validation of diagnostic markers for Fhb1 region, a major QTL for Fusarium head blight resistance in wheat. Theor. Appl. Genet. 131, 2371–2380 (2018).
pubmed: 30136107 doi: 10.1007/s00122-018-3159-6
Su, Z. et al. A deletion mutation in TaHRC confers Fhb1 resistance to Fusarium head blight in wheat. Nat. Genet. 51, 1099–1105 (2019).
pubmed: 31182809 doi: 10.1038/s41588-019-0425-8
Schweiger, W. et al. Transcriptomic characterization of two major Fusarium resistance quantitative trait loci (QTLs), Fhb1 and Qfhs.ifa-5A, identifies novel candidate genes. Mol. Plant Pathol. 14, 772–785 (2013).
pubmed: 23738863 pmcid: 3902993 doi: 10.1111/mpp.12048
Dhokane, D., Karre, S., Kushalappa, A. C. & McCartney, C. Integrated metabolo-transcriptomics reveals Fusarium head blight candidate resistance genes in wheat QTL-Fhb2. PLoSOne 11, 1–27 (2016).
doi: 10.1371/journal.pone.0155851
Long, X. et al. Expression profiling identifies differentially expressed genes associated with the Fusarium head blight resistance QTL 2DL from the wheat variety Wuhan-1. Physiol. Mol. Plant Pathol. 90, 1–11 (2015).
doi: 10.1016/j.pmpp.2015.02.002
Wang, S. et al. Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotechnol. J. 12, 787–796 (2014).
pubmed: 24646323 pmcid: 4265271 doi: 10.1111/pbi.12183
Maccaferri, M. et al. A high-density, SNP-based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding. Plant Biotechnol. J. 13, 648–663 (2015).
pubmed: 25424506 doi: 10.1111/pbi.12288
Clark, A. J. et al. Identifying rare FHB-resistant segregants in intransigent backcross and F
pubmed: 27014202 pmcid: 4779889 doi: 10.3389/fmicb.2016.00277
Korzun, V., Röder, M. S., Ganal, M. W., Worland, A. J. & Law, C. N. Genetic analysis of the dwarfing gene (Rht8) in wheat. Part I. Molecular mapping of Rht8 on the short arm of chromosome 2D of bread wheat (Triticum aestivum L.). Theor. Appl. Genet. 96, 1104–1109 (1998).
doi: 10.1007/s001220050845
Maccaferri, M. et al. A genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.). G3. 5, 449–465 (2015).
pubmed: 25609748 doi: 10.1534/g3.114.014563
Kovalchuk, I. et al. Pathogen-induced systemic plant signal triggers DNA rearrangements. Nature 423, 760 (2003).
pubmed: 12802336 doi: 10.1038/nature01683
Boyko, A., Hudson, D., Bhomkar, P., Kathiria, P. & Kovalchuk, I. Increase of homologous recombination frequency in vascular tissue of Arabidopsis plants exposed to salt stress. Plant Cell Physiol. 47, 736–742 (2006).
pubmed: 16608867 doi: 10.1093/pcp/pcj045
Balcárková, B. et al. A high-resolution radiation hybrid map of wheat chromosome 4A. Front. Plant Sci. 7, 2063 (2017).
pubmed: 28119729 pmcid: 5222868 doi: 10.3389/fpls.2016.02063
Lande, R. & Thompson, R. Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124, 743–756 (1990).
pubmed: 1968875 pmcid: 1203965
Miedaner, T., Moldovan, M. & Ittu, M. Comparison of spray and point inoculation to assess resistance to Fusarium head blight in a multi-environment wheat trial. Phytopathology 93, 1068–1072 (2003).
pubmed: 18944089 doi: 10.1094/PHYTO.2003.93.9.1068
Imathiu, S., Edwards, S., Ray, R. & Back, M. Artificial inoculum and inoculation techniques commonly used in the investigation of Fusarium head blight in cereals. Acta Phytopathol. Entomol. Hungarica 49, 129–139 (2014).
doi: 10.1556/APhyt.49.2014.2.1
Somers, D. J., Fedak, G., Clarke, J. & Cao, W. Mapping of FHB resistance QTLs in tetraploid wheat. Genome 49, 1586–1593 (2006).
pubmed: 17426773 doi: 10.1139/g06-127
Zhao, M. et al. Molecular mapping of Fusarium head blight resistance in the spring wheat Line ND2710. Phytopathology 108, 972–979 (2018).
pubmed: 29561710 doi: 10.1094/PHYTO-12-17-0392-R
Cavanagh, C. R. et al. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc. Natl. Acad. Sci. 110, 8057–8062 (2013).
pubmed: 23630259 doi: 10.1073/pnas.1217133110
Appels, R. et al. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361, 6403 (2018).
Maccaferri, M. et al. Durum wheat genome highlights past domestication signatures and future improvement targets. Nat. Genet. 51, 885–895 (2019).
pubmed: 30962619 doi: 10.1038/s41588-019-0381-3
Avni, R. et al. Wild emmer genome architecture and diversity elucidate wheat evolution and domestication. Science 357, 93–97 (2017).
doi: 10.1126/science.aan0032
Kurtz, S. et al. Versatile and open software for comparing large genomes. Genome Biol. 5, R12 (2004).
pubmed: 14759262 pmcid: 395750 doi: 10.1186/gb-2004-5-2-r12
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
pubmed: 17701901 pmcid: 17701901 doi: 10.1086/519795
Ramirez-Gonzalez, R. H., Uauy, C. & Caccamo, M. PolyMarker: A fast polyploid primer design pipeline. Bioinformatics 31, 2038–2039 (2015).
pubmed: 25649618 pmcid: 4765872 doi: 10.1093/bioinformatics/btv069
Milne, I. et al. Flapjack—graphical genotype visualization. Bioinformatics 26, 3133–3134 (2010).
pubmed: 20956241 pmcid: 2995120 doi: 10.1093/bioinformatics/btq580
Bradbury, P. J. et al. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635 (2007).
pubmed: 17586829 doi: 10.1093/bioinformatics/btm308
Raj, A., Stephens, M. & Pritchard, J. K. fastSTRUCTURE: Variational inference of population structure in large SNP data sets. Genetics 197, 573–589 (2014).
pubmed: 24700103 pmcid: 4063916 doi: 10.1534/genetics.114.164350
Barrett, J. C., Fry, B., Maller, J. & Daly, M. J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).
pubmed: 15297300 doi: 10.1093/bioinformatics/bth457
Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nat. Genet. 42, 355–360 (2010).
pubmed: 20208535 pmcid: 2931336 doi: 10.1038/ng.546
Wang, Q., Tian, F., Pan, Y., Buckler, E. S. & Zhang, Z. A SUPER powerful method for genome wide association study. PLoSOne 9, e107684 (2014).
doi: 10.1371/journal.pone.0107684
Lipka, A. E. et al. GAPIT: genome association and prediction integrated tool. Bioinformatics 28, 2397–2399 (2012).
pubmed: 22796960 doi: 10.1093/bioinformatics/bts444

Auteurs

Ehsan Sari (E)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.
Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada.

Ron E Knox (RE)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada. ron.knox@canada.ca.

Yuefeng Ruan (Y)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada. yuefeng.ruan@canada.ca.

Maria Antonia Henriquez (MA)

Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada.

Santosh Kumar (S)

Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada.

Andrew J Burt (AJ)

Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada.

Richard D Cuthbert (RD)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada.

David J Konkin (DJ)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.

Sean Walkowiak (S)

Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada.
Canadian Grain Commission, Winnipeg, MB, Canada.

Heather L Campbell (HL)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada.

Asheesh K Singh (AK)

Department of Agronomy, Iowa State University, Ames, Iowa, United States of America.

Jay Ross (J)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada.

Prabhath Lokuruge (P)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada.

Emma Hsueh (E)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.

Kerry Boyle (K)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.

Christine Sidebottom (C)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.

Janet Condie (J)

Aquatic and Crop Resource Development Centre, National Research Council, Saskatoon, SK, Canada.

Shawn Yates (S)

Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada.

Curtis J Pozniak (CJ)

Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada.

Pierre R Fobert (PR)

Aquatic and Crop Resource Development Centre, National Research Council, Ottawa, ON, Canada.

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