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Molecular Breeding

, 38:139 | Cite as

QTL-seq and marker development for resistance to Fusarium oxysporum f. sp. niveum race 1 in cultivated watermelon

  • Sandra E. Branham
  • W. Patrick Wechter
  • Shaunese Lambel
  • Laura Massey
  • Michelle Ma
  • Julie Fauve
  • Mark W. Farnham
  • Amnon Levi
Article
  • 8 Downloads

Abstract

Fusarium wilt, caused by the fungus Fusarium oxysporum f. sp. niveum (Fon), is one of the predominant diseases of watermelon. Resistance to Fon race 1 is conferred by a single major quantitative trait locus (QTL), Fo-1.1, but resolution of this region has been poor due to low marker density. In this study, a combination of whole genome resequencing of bulked segregants (QTL-seq analysis) followed by QTL mapping with kompetitive allele specific PCR (KASP) markers developed across Fo-1.1 successfully increased the resolution from 2.03 to 1.56 Mb and 315 kb, respectively. The linkage of the KASP markers to Fon race 1 resistance across a wide range of watermelon germplasm was validated in a set of elite watermelon cultivars. The linked markers described here provide a breeder-friendly toolkit immediately available for high-throughput genotyping in large-scale breeding programs for fine mapping and incorporation of Fon race 1 resistance in watermelon.

Keywords

Disease resistance QTL-seq Fusarium wilt Watermelon Resequencing KASP 

Notes

Funding information

This study was funded by the National Institute of Food and Agriculture, project no. 6080-21000-018-08.

Compliance with ethical standards

USDA is an equal opportunity provider and employer. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. The experiment conducted complies with the laws of the United States.

This research project was developed through a non-funded cooperative agreement (ARS Number: 58-6659-8-102) between USDA-ARS and HM.CLAUSE Seed Company.

This research was supported by a grant from USDA National Institute of Food and Agriculture Specialty Crop Research Initiative (2015-51181-24285).

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11032_2018_896_MOESM1_ESM.xlsx (21 kb)
Online resource 1 Sequence information for the Kompetitive Allele-Specific PCR markers, including: SNP ID, physical position of the SNP, primer sequences, SNP flanking sequence, and nucleotides of the resistant (R) and susceptible (S) alleles (XLSX 21 kb)
11032_2018_896_MOESM2_ESM.xlsx (5.5 mb)
Online resource 2 Results of the QTL-seq analysis of Fon race 1 resistance in a F2:3 watermelon population, including: SNP location (chromosome and position), quality information, read density, base calls, SNP index for each bulk, delta-SNP index and the lower (L) and upper (U) bounds of the 95% and 99% confidence intervals. All variant calls are relative to the susceptible parent reference genome. (XLSX 5646 kb)
11032_2018_896_MOESM3_ESM.png (933 kb)
Online resource 3 Scatterplots of the delta-SNP index values of association with Fon race 1 resistance. The red lines represent the results of a sliding window analysis with a 1 Mb interval and a window size of 10 kb. Regions lacking a red line had less than 10 SNPs per window and were excluded from analysis. Confidence intervals were calculated based on a null hypothesis of no QTL (p < 0.05 = green; p < 0.01 = orange) (PNG 933 kb)
11032_2018_896_MOESM4_ESM.xlsx (3.2 mb)
Online resource 4 Results of a sliding window analysis (1 Mb interval and a window size of 10 kb) of the delta-SNP index of association with Fon race 1 resistance. Each row corresponds to a window and includes the following information: chromosome, position (bp) of the center point of the window, width of the window, read depth and SNP index value for each bulk, the delta-SNP index, the upper and lower bounds of the 95% and 99% confidence intervals, and the number of SNPs in the window (XLSX 3291 kb)
11032_2018_896_MOESM5_ESM.png (855 kb)
Online resource 5 Scatterplots of the SNP-index for the Fon race 1 susceptible bulk. The red lines represent the results of a sliding window analysis with a 1 Mb interval and a window size of 10 kb (PNG 855 kb)
11032_2018_896_MOESM6_ESM.png (1012 kb)
Online resource 6 Scatterplots of the SNP-index for the Fon race 1 resistant bulk. The red lines represent the results of a sliding window analysis with a 1 Mb interval and a window size of 10 kb (PNG 1012 kb)
11032_2018_896_MOESM7_ESM.xlsx (20 kb)
Online resource 7 Genes located within the 1.5-LOD interval of QTLs significantly associated with Fon race 1 resistance in watermelon. Gene annotation information was obtained from the 97103 v1 genome (Guo et al. 2013), including: gene ID, chromosome (CS), start position (bp), stop position (bp), and functional description. The conserved domains and features were obtained from an NCBI conserved domain search (XLSX 20 kb)
11032_2018_896_MOESM8_ESM.xlsx (16 kb)
Online resource 8 List of cultivars included in the validation study of the Fon race 1 KASP markers. Seed company, seed lot, and date of receipt are reported for each cultivar, if known (XLSX 15 kb)

References

  1. Antoniw JF, Ritter CE, Pierpoint WS, Van Loon LC (1980) Comparison of three pathogenesis-related proteins from plants of two cultivars of tobacco infected with TMV. J Gen Virol 47(1):79–87CrossRefGoogle Scholar
  2. Berrocal-Lobo M, Molina A (2004) Ethylene response factor 1 mediates Arabidopsis resistance to the soilborne fungus Fusarium oxysporum. Mol Plant-Microbe Interact 17(7):763–770CrossRefGoogle Scholar
  3. Branham SE, Levi A, Farnham MW, Patrick Wechter W (2017) A GBS-SNP-based linkage map and quantitative trait loci (QTL) associated with resistance to Fusarium oxysporum f. sp. niveum race 2 identified in Citrullus lanatus var. citroides. Theor Appl Genet 130:319–330.  https://doi.org/10.1007/s00122-016-2813-0 CrossRefPubMedGoogle Scholar
  4. Broman KW, Sen S (2009) A guide to QTL mapping with R/qtl (Vol. 46). Springer, New YorkCrossRefGoogle Scholar
  5. Broman KW, Speed T (2002) A model selection approach for the identification of quantitative trait loci in experimental crosses (with discussion). J R Stat Soc B 64(641–656):731–775Google Scholar
  6. Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889–890.  https://doi.org/10.1093/bioinformatics/btg112 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Catanzariti AM, Lim GTT, Jones DA (2015) The tomato I-3 gene: a novel gene for resistance to fusarium wilt disease. New Phytol 207:106–118.  https://doi.org/10.1111/nph.13348 CrossRefPubMedGoogle Scholar
  8. Chambers JM, Freeny A, Heiberger RM (1992) Analysis of variance; designed experiments. Chapter 5 of Statistical models in S, eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/ColeGoogle Scholar
  9. Cole SJ, Diener AC (2013) Diversity in receptor-like kinase genes is a major determinant of quantitative resistance to Fusarium oxysporum f.sp matthioli. New Phytol 200:172–184.  https://doi.org/10.1111/nph.12368 CrossRefPubMedGoogle Scholar
  10. Collard BCY, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc B Biol Sci 363:557–572.  https://doi.org/10.1098/rstb.2007.2170 CrossRefGoogle Scholar
  11. Elshire RJ, Glaubitz JC, Sun Q et al (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6:e19379.  https://doi.org/10.1371/journal.pone.0019379 CrossRefPubMedPubMedCentralGoogle Scholar
  12. FAOSTAT: Food and Agriculture Organization of the United Nations (2017) http://www.fao.org/faostat/en/#search/watermelon. Accessed 7/2/2018
  13. Girhepuje PV, Shinde GB (2011) Transgenic tomato plants expressing a wheat endochitinase gene demonstrate enhanced resistance to Fusarium oxysporum f. sp. lycopersici. Plant Cell Tiss Org Cult 105(2):243–251CrossRefGoogle Scholar
  14. Guo S, Zhang J, Sun H et al (2013) The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions. Nat Genet 45:51–58.  https://doi.org/10.1038/ng.2470 CrossRefPubMedGoogle Scholar
  15. Jabeen N, Chaudhary Z, Gulfraz M, Rashid H, Mirza B (2015) Expression of rice chitinase gene in genetically engineered tomato confers enhanced resistance to fusarium wilt and early blight. Plant Pathol J 31(3):252–258CrossRefGoogle Scholar
  16. Keinath AP, Hassell RL, Everts KL, Zhou XG (2010) Cover crops of hybrid common vetch reduce fusarium wilt of seedless watermelon in the eastern United States. Plant Health Progress Online publication doi: https://doi.org/10.1094/PHP-2010-0914-01-RS CrossRefGoogle Scholar
  17. Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugenics 12:172–175.  https://doi.org/10.1111/j.1469-1809.1943.tb02321.x CrossRefGoogle Scholar
  18. Kosugi S, Natsume S, Yoshida K et al (2013) Coval: improving alignment quality and variant calling accuracy for next-generation sequencing data. PLoS One.  https://doi.org/10.1371/journal.pone.0075402 CrossRefGoogle Scholar
  19. Lambel S, Lanini B, Vivoda E et al (2014) A major QTL associated with Fusarium oxysporum race 1 resistance identified in genetic populations derived from closely related watermelon lines using selective genotyping and genotyping-by-sequencing for SNP discovery. Theor Appl Genet 127:2105–2115.  https://doi.org/10.1007/s00122-014-2363-2 CrossRefPubMedGoogle Scholar
  20. Levi A, Thomas CE, Wehner TC, Zhang X (2001) Low genetic diversity indicates the need to broaden the genetic base of cultivated watermelon. HortScience 36:1096–1101.Google Scholar
  21. Li H, Durbin R (2009) Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics 25:1754–1760.  https://doi.org/10.1093/bioinformatics/btp324 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079.  https://doi.org/10.1093/bioinformatics/btp352 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Li N, Wang J, Shang J, Li N, Xu Y, Ma S (2017) Fine-mapping of QTL and development of InDel markers for Fusarium oxysporum race 1 resistance in watermelon. Sci Agric Sin 50:131–141.  https://doi.org/10.3864/j.issn.0578-1752.2017.01.012 CrossRefGoogle Scholar
  24. Manichaikul A, Moon JY, Sen Ś et al (2009) A model selection approach for the identification of quantitative trait loci in experimental crosses, allowing epistasis. Genetics 181:1077–1086.  https://doi.org/10.1534/genetics.108.094565 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Marchler-Bauer A, Bryant SH (2004) CD-search: protein domain annotations on the fly. Nucleic Acids Res 32:327–331.  https://doi.org/10.1093/nar/gkh454 CrossRefGoogle Scholar
  26. Marchler-Bauer A, Bo Y, Han L et al (2017) CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Res 45:D200–D203.  https://doi.org/10.1093/nar/gkw1129 CrossRefPubMedGoogle Scholar
  27. Martyn RD, Bruton BD (1989) An initial survey of the United States for races of Fusarium oxysporum f. sp. niveum. HortSci 24:696–698Google Scholar
  28. Martyn RD, Netzer D (1991) Resistance to races 0, 1, and 2 of fusarium wilt of watermelon in Citrullus sp. PI-296341-FR. HortSci 26:429–432Google Scholar
  29. Meru G, McGregor C (2016) Genotyping by sequencing for SNP discovery and genetic mapping of resistance to race 1 of Fusarium oxysporum in watermelon. Sci Hortic 209:31–40.  https://doi.org/10.1016/j.scienta.2016.06.005 CrossRefGoogle Scholar
  30. Michelmore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci 88:9828–9832.  https://doi.org/10.1073/pnas.88.21.9828 CrossRefPubMedGoogle Scholar
  31. Moosa A, Farzand A, Sahi ST, Khan SA (2017) Transgenic expression of antifungal pathogenesis-related proteins against phytopathogenic fungi–15 years of success. Israel J Plant Sci.  https://doi.org/10.1080/07929978.2017.1288407
  32. Mundt CC (2014) Durable resistance: a key to sustainable management of pathogens and pests. Infect Genet Evol 27:446–455.  https://doi.org/10.1016/j.meegid.2014.01.011 CrossRefPubMedGoogle Scholar
  33. Netzer D, Weintall CH (1980) Inheritance of resistance in watermelon to race 1 of Fusarium oxysporum f. sp. niveum. Plant Dis 64:853–854CrossRefGoogle Scholar
  34. Nimmakayala P, Levi A, Abburi L, Abburi VL, Tomason YR, Saminathan T, Vajja VG, Malkaram S, Reddy R, Wehner TC, Mitchell SE, Reddy UK (2014) Single nucleotide polymorphisms generated by genotyping by sequencing to characterize genome-wide diversity, linkage disequilibrium, and selective sweeps in cultivated watermelon. BMC Genomics 15:767.  https://doi.org/10.1186/1471-2164-15-767 CrossRefGoogle Scholar
  35. R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  36. Ren Y, Jiao D, Gong G et al (2015) Genetic analysis and chromosome mapping of resistance to Fusarium oxysporum f. sp. niveum (FON) race 1 and race 2 in watermelon (Citrullus lanatus L.). Mol Breed 35:1–9.  https://doi.org/10.1007/s11032-015-0375-5 CrossRefGoogle Scholar
  37. Sekhwal M, Li P, Lam I et al (2015) Disease resistance gene analogs (RGAs) in plants. Int J Mol Sci 16:19248–19290.  https://doi.org/10.3390/ijms160819248 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Sen S, Churchill GA (2001) A statistical framework for quantitative trait mapping. Genetics 159:371–387.  https://doi.org/10.1126/science.1242429 CrossRefPubMedPubMedCentralGoogle Scholar
  39. Singh D, Haicour R, Sihachakr D, Rajam MV (2015) Expression of rice chitinase gene in transgenic eggplant confers resistance to fungal wilts. Indian J Biotechnol 14:233–240Google Scholar
  40. Takagi H, Abe A, Yoshida K et al (2013) QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J 74:174–183.  https://doi.org/10.1111/tpj.12105 CrossRefPubMedGoogle Scholar
  41. United States Environmental Protection Agency (2017) International Actions - The Montreal Protocol on Substances that Deplete the Ozone Layer. https://www.epa.gov/ozone-layer-protection/international-actions-montreal-protocol-substances-deplete-ozone-layer
  42. Van Loon LC, Van Strien EA (1999) The families of pathogenesis-related proteins, their activities, and comparative analysis of PR-1 type proteins. Physiol Mol Plant Pathol 55(2):85–97CrossRefGoogle Scholar
  43. Van Loon LC, Pierpoint WS, Boller TH, Conejero V (1994) Recommendations for naming plant pathogenesis-related proteins. Plant Mol Biol Report 12(3):245–264CrossRefGoogle Scholar
  44. Wechter WP, Kousik C, McMillan M, Levi A (2012) Identification of resistance to Fusarium oxysporum f. sp. niveum race 2 in Citrullus lanatus var. citroides plant introductions. HortSci 47:334–338.  https://doi.org/10.1002/ird.1717 CrossRefGoogle Scholar
  45. Xu Y (2014) SNP loci linked with blight resistant gene Fon-1 in watermelon, and markers thereof. Patent CN103146691B. 02 April 2014Google Scholar
  46. Zeng ZB, Kao CH, Basten CJ (1999) Estimating the genetic architecture of quantitative traits. Genet Res 74:279–289.  https://doi.org/10.1017/S0016672399004255 CrossRefPubMedGoogle Scholar
  47. Zhou XG, Everts KL, Bruton BD (2010) Race 3, a new and highly virulent race of Fusarium oxysporum f. sp. niveum causing fusarium wilt in watermelon. Plant Dis 94:92–98CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  • Sandra E. Branham
    • 1
  • W. Patrick Wechter
    • 1
  • Shaunese Lambel
    • 2
  • Laura Massey
    • 1
  • Michelle Ma
    • 2
  • Julie Fauve
    • 2
  • Mark W. Farnham
    • 1
  • Amnon Levi
    • 1
  1. 1.USDA, ARS, U.S. Vegetable LaboratoryCharlestonUSA
  2. 2.HM.CLAUSEDavisUSA

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