Genetic analysis of drought response of wheat following either chemical desiccation or the use of a rain-out shelter

  • Rasha A. Tarawneh
  • Fruzsina Szira
  • Istvan Monostori
  • Annika Behrens
  • Ahmad M. Alqudah
  • Stefanie Thumm
  • Ulrike Lohwasser
  • Marion S. Röder
  • Andreas Börner
  • Manuela NagelEmail author
Plant Genetics • Original Paper


Simulating drought stress during the breeding process has been proposed as a way to select varieties under naturally non-stressful conditions. The aim of the study was to characterise the genetic basis of the response of 111 spring wheat (Triticum aestivum L.) varieties and landraces to chemical desiccation and to rain-out shelter drought. The effect of the rain-out shelter was a 15% reduction in plant height, spike length and thousand seed weight (TSW); in contrast, the desiccant treatment induced a 15% reduction in seed number, a 35–72% loss in TSW and a reduction in subsequent germination of 12%. A genome-wide association analysis revealed 263 significant marker-trait associations (MTAs), of which 246 involved days to anthesis, plant height, spike length, number of spikelets, seed number, TSW and germination from the non-treated plants. Only four and five MTAs involved TSW from plants grown under the rain-out shelter and the chemical desiccation, respectively, and harboured the Sugar-Dependent6 gene. Seven MTAs involved seed number for chemical desiccated plants. Both, chemical desiccation and rain-out shelter drought identified same tolerant genotypes. Concluding, both approaches are suitable to simulate different drought scenarios. However, there was a strong environmental impact for chemical desiccation which may increase the complexity of this tolerance mechanism.


Abiotic stress Drought simulation Genetic mapping GWAS Phenotyping 



Anna Marthe, Allah Bakhsh, Sibylle Pistrick, Annett Marlow, Peter Schreiber, Philip Kouria and the past and current staff of the IPK gene bank as well as Freta K. Balladona and Farhadz Fadhillah Sandi are gratefully acknowledged for their technical support and Wolfgang Link for statistical advice.

Author contributions statement

MN, AB and UL designed the work; RT, MN, FS, IM, AMA, ST and MR acquired and analysed the data; RT and MN wrote the original draft of the manuscript and AMA, AB, RT and MN critically revised the content. All authors read and approved the manuscript.


This study was funded by the DAAD (Rasha Tarawneh).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

13353_2019_494_MOESM1_ESM.docx (3.5 mb)
ESM 1 (DOCX 3.50 mb)


  1. Bhargava S, Sawant K (2013) Drought stress adaptation: metabolic adjustment and regulation of gene expression. Plant Breed 132:21–32. CrossRefGoogle Scholar
  2. Blum A (1998) Improving wheat grain filling under stress by stem reserve mobilisation (reprinted from wheat: prospects for global improvement, 1998). Euphytica 100:77–83. CrossRefGoogle Scholar
  3. Blum A, Poiarkova H, Golan G, Mayer J (1983) Chemical desiccation of wheat plants as a simulator of post-anthesis stress. 1. Effects on translocation and kernel growth. Field Crop Res 6:51–58. CrossRefGoogle Scholar
  4. de Carvalho MAAP, Bebeli PJ, Bettencourt E, Costa G, Dias S, Dos Santos TMM, Slaski JJ (2013) Cereal landraces genetic resources in worldwide GeneBanks. A review. Agron Sustain Dev 33:177–203. CrossRefGoogle Scholar
  5. Dong Y et al (2016) Genome-wide association of stem water soluble carbohydrates in bread wheat. PLoS One 11:e0164293. CrossRefGoogle Scholar
  6. Farooq M, Hussain M, Siddique KHM (2014) Drought stress in wheat during flowering and grain-filling periods. Crit Rev Plant Sci 33:331–349. CrossRefGoogle Scholar
  7. Fischer RA, Maurer R (1978) Drought resistance in spring wheat cultivars. 1. Grain yield responses. Aust J Agric Res 29:897–912CrossRefGoogle Scholar
  8. Gahlaut V, Jaiswal V, Tyagi BS, Singh G, Sareen S, Balyan HS, Gupta PK (2017) QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments. PLoS One 12.
  9. Gupta P, Rustgi S, Kulwal P (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485. CrossRefGoogle Scholar
  10. Haley SD, Quick JS (1998) Methodology for evaluation of chemical desiccation tolerance in winter wheat. Cereal Res Commun 26:73–79Google Scholar
  11. ISTA (2014) International rules for seed testing. International Seed Testing Association, BassersdorfGoogle Scholar
  12. Ma J et al (2017) Transcriptomics analyses reveal wheat responses to drought stress during reproductive stages under field conditions. Front Plant Sci 8.
  13. Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12:57–63. CrossRefGoogle Scholar
  14. Mwadzingeni L, Shimelis H, Rees DJG, Tsilo TJ (2017) Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions. PLoS One 12.
  15. Nasehzadeh M, Ellis RH (2017) Wheat seed weight and quality differ temporally in sensitivity to warm or cool conditions during seed development and maturation. Ann Bot-London 120:479–493. CrossRefGoogle Scholar
  16. Nezhad KZ et al (2012) QTL analysis for thousand-grain weight under terminal drought stress in bread wheat (Triticum aestivum L.). Euphytica 186:127–138. CrossRefGoogle Scholar
  17. Nicolas ME, Turner NC (1993) Use of chemical desiccants and senescing agents to select wheat lines maintaining stable grain size during post-anthesis drought. Field Crop Res 31:155–171. CrossRefGoogle Scholar
  18. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genet 38:904–909. CrossRefGoogle Scholar
  19. Quettier A-L, Shaw E, Eastmond PJ (2008) SUGAR-DEPENDENT6 encodes a mitochondrial flavin adenine dinucleotide-dependent glycerol-3-P dehydrogenase, which is required for glycerol catabolism and postgerminative seedling growth in Arabidopsis. Plant Physiol 148:519–528. CrossRefGoogle Scholar
  20. Royo C, Blanco R (1998) Use of potassium iodide to mimic drought stress in triticale. Field Crop Res 59:201–212. CrossRefGoogle Scholar
  21. Salem KFM, Röder MS, Börner A (2007) Identification and mapping quantitative trait loci for stem reserve mobilisation in wheat (Triticum aestivum L.). Cereal Res Commun 35:1367–1374. CrossRefGoogle Scholar
  22. Samarah N, Alqudah A (2011) Effects of late-terminal drought stress on seed germination and vigor of barley (Hordeum vulgare L.). Arch Agron Soil Sci 57:27–32. CrossRefGoogle Scholar
  23. Sawhney V, Singh DP (2002) Effect of chemical desiccation at the post-anthesis stage on some physiological and biochemical changes in the flag leaf of contrasting wheat genotypes. Field Crop Res 77:1–6. CrossRefGoogle Scholar
  24. Storey JD (2003) The positive false discovery rate: a Bayesian interpretation and the q-value. Ann Stat 31:2013–2035. CrossRefGoogle Scholar
  25. Su ZQ, Hao CY, Wang LF, Dong YC, Zhang XY (2011) Identification and development of a functional marker of TaGW2 associated with grain weight in bread wheat (Triticum aestivum L.). Theor Appl Genet 122:211–223. CrossRefGoogle Scholar
  26. Trnka M, Rotter RP, Ruiz-Ramos M, Kersebaum KC, Olesen JE, Zalud Z, Semenov MA (2014) Adverse weather conditions for European wheat production will become more frequent with climate change. Nat Clim Chang 4:637–643. CrossRefGoogle Scholar
  27. Varshney RK et al (2012) Genome wide association analyses for drought tolerance related traits in barley (Hordeum vulgare L.). Field Crop Res 126:171–180. CrossRefGoogle Scholar
  28. Vishwakarma K et al (2017) Abscisic acid signaling and abiotic stress tolerance in plants: a review on current knowledge and future prospects. Front Plant Sci 8.
  29. VSN International (2013) GenStat for Windows, 17th edn. VSN International, Hemel Hempstead Web page: Google Scholar
  30. Wang S et al (2014) Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796. CrossRefGoogle Scholar
  31. Wickham H (2009) ggplot2: elegant graphics for data analysis. Springer, New YorkCrossRefGoogle Scholar
  32. Wilcox J, Makowski D (2014) A meta-analysis of the predicted effects of climate change on wheat yields using simulation studies. Field Crop Res 156:180–190. CrossRefGoogle Scholar
  33. Yamasaki Y, Gaol F, Jordan MC, Ayele BT (2017) Seed maturation associated transcriptional programs and regulatory networks underlying genotypic difference in seed dormancy and size/weight in wheat (Triticum aestivum L.). BMC Plant Biol 17.
  34. Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421. CrossRefGoogle Scholar

Copyright information

© Institute of Plant Genetics, Polish Academy of Sciences, Poznan 2019

Authors and Affiliations

  • Rasha A. Tarawneh
    • 1
  • Fruzsina Szira
    • 2
  • Istvan Monostori
    • 2
  • Annika Behrens
    • 1
  • Ahmad M. Alqudah
    • 1
  • Stefanie Thumm
    • 1
  • Ulrike Lohwasser
    • 1
  • Marion S. Röder
    • 1
  • Andreas Börner
    • 1
  • Manuela Nagel
    • 1
    Email author
  1. 1.Genebank DepartmentLeibniz-Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben)SeelandGermany
  2. 2.Hungarian Academy of SciencesAgricultural InstituteMartonvásárHungary

Personalised recommendations