Theoretical and Applied Genetics

, Volume 125, Issue 8, pp 1647–1661 | Cite as

Genetic dissection of the temperature dependent emergence processes in sorghum using a cumulative emergence model and stability parameters

  • Karin FiedlerEmail author
  • Wubishet A. Bekele
  • Wolfgang Friedt
  • Rod Snowdon
  • Hartmut Stützel
  • Arndt Zacharias
  • Ralf Uptmoor
Original Paper


Among the major limitations for cultivating biomass sorghum in temperate regions is low temperature in spring that results in low and non-uniform emergence. The adaptation of sorghum to tropical and subtropical highlands gives hint of genetic variation in cold tolerance during emergence. The objective of the present study was to detect marker–trait associations for parameters describing the emergence process under different temperature regimes. A diversity set comprising 194 genotypes was tested in nine controlled environments with temperatures ranging from 9.4 to 19.9 °C. The genotypes were fingerprinted with 171 DArT markers. A piecewise linear regression model carried out on cumulative emergence was used to estimate genotype mean performance across environments and to carry out stability analysis on the parameters of the regression model. Base temperature (T b) and thermal time required for emergence (E TS) were determined based on median time to emergence data. Identified QTL positions were compared to marker–trait associations for final emergence percentages under low (FEPcold) and normal (FEPnormal) temperatures. QTL for mean final emergence percentage (FEP), FEPcold and FEPnormal, T b and E TS were detected on SBI-01. Other QTL-rich regions were located on SBI-03, SBI-04, SBI-06, SBI-08, and SBI-09. Marker–trait associations for T b and E TS co-localized to QTL for the across environment stability of FEP and the median time to emergence or emergence rate, respectively. We conclude that genome regions on six chromosomes highly influencing cold tolerance during emergence are promising for regional association studies and for the development of stable markers for marker-assisted selection.


Quantitative Trait Locus Sorghum Cold Tolerance Quantitative Trait Locus Region DArT Marker 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Katharina Meyer for excellent technical assistance and gratefully acknowledge the German Federal Ministry of Education and Research (BMBF) for funding the project (BioEnergie 2021, Project No. 03154211). The authors would like to thank the anonymous reviewers for the helpful comments on the manuscript.

Supplementary material

122_2012_1941_MOESM1_ESM.pdf (106 kb)
Supplementary material 1 (PDF 105 kb)
122_2012_1941_MOESM2_ESM.pdf (352 kb)
Supplementary material 2 (PDF 351 kb)


  1. Afzal I, Basra SMA, Shahid M, Farooq M, Salem M (2008) Priming enhances germination of spring maize (Zea mays L.) under cool conditions. Seed Sci Technol 36:497–503Google Scholar
  2. Anda A, Pinter L (1994) Sorghum germination and development as influenced by soil-temperature and water-content. Agron J 86:621–624CrossRefGoogle Scholar
  3. Bhosale SU, Stich B, Rattunde HFW, Weltzien E, Haussmann BIG, Hash CT, Melchinger AE, Parzies HK (2011) Population structure in sorghum accessions from West Africa differing in race and maturity class. Genetica 139:453–463PubMedCrossRefGoogle Scholar
  4. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635PubMedCrossRefGoogle Scholar
  5. Brar GS, Stewart BA (1994) Germination under controlled temperature and field emergence of 13 sorghum cultivars. Crop Sci 34:1336–1340CrossRefGoogle Scholar
  6. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177PubMedCrossRefGoogle Scholar
  7. Brown RF, Mayer DG (1988a) Representing cumulative germination.1. A critical analysis of single-value germination indexes. Ann Bot 61:117–125Google Scholar
  8. Brown RF, Mayer DG (1988b) Representing cumulative germination. 2. The use of the Weibull function and other empirically derived curves. Ann Bot 61:127–138Google Scholar
  9. Burow G, Burke J, Xin ZG, Franks C (2011) Genetic dissection of early-season cold tolerance in sorghum (Sorghum bicolor (L.) Moench). Mol Breed 28:391–402CrossRefGoogle Scholar
  10. Casa AM, Pressoir G, Brown PJ, Mitchell SE, Rooney WL, Tuinstra MR, Franks CD, Kresovich S (2008) Community resources and strategies for association mapping in sorghum. Crop Sci 48:30–40CrossRefGoogle Scholar
  11. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971PubMedGoogle Scholar
  12. Crossa J, Burgueno J, Dreisigacker S, Vargas M, Herrera-Foessel SA, Lillemo M, Singh RP, Trethowan R, Warburton M, Franco J, Reynolds M, Crouch JH, Ortiz R (2007) Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure. Genetics 177:1889–1913PubMedCrossRefGoogle Scholar
  13. Dumur D, Pilbeam CJ, Craigon J (1990) Use of the Weibull function to calculate cardinal temperatures in faba bean. J Exp Bot 41:1423–1430CrossRefGoogle Scholar
  14. El Soda M, Nadakuduti SS, Pillen K, Uptmoor R (2010) Stability parameter and genotype mean estimates for drought stress effects on root and shoot growth of wild barley pre-introgression lines. Mol Breed 26:583–593CrossRefGoogle Scholar
  15. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620PubMedCrossRefGoogle Scholar
  16. Finlay KW, Wilkinson GN (1963) Analysis of adaptation in a plant-breeding programme. Aus J Agric Res 14:742–754CrossRefGoogle Scholar
  17. Flint-Garcia SA, Thornsberry JM, Buckler ES (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374PubMedCrossRefGoogle Scholar
  18. Franks CD, Burow GB, Burke JJ (2006) A comparison of US and Chinese sorghum germplasm for early season cold tolerance. Crop Sci 46:1371–1376CrossRefGoogle Scholar
  19. Hamblin MT, Mitchell SE, White GM, Gallego W, Kukatla R, Wing RA, Paterson AH, Kresovich S (2004) Comparative population genetics of the panicoid grasses: sequence polymorphism, linkage disequilibrium and selection in a diverse sample of Sorghum bicolor. Genetics 167:471–483PubMedCrossRefGoogle Scholar
  20. Hill J, Becker HC, Tigerstedt PMA (1998) Quantitative and ecological aspects of plant breeding. Chapman and Hall, LondonGoogle Scholar
  21. Hsu FH, Nelson CJ, Chow WS (1984) A mathematical-model to utilize the logistic function in germination and seedling growth. J Exp Bot 35:1629–1640CrossRefGoogle Scholar
  22. Hund A, Fracheboud Y, Soldati A, Frascaroli E, Salvi S, Stamp P (2004) QTL controlling root and shoot traits of maize seedlings under cold stress. Theor Appl Genet 109:618–629PubMedCrossRefGoogle Scholar
  23. Ji SL, Jiang L, Wang YH, Zhang WW, Liu X, Liu SJ, Chen LM, Zhai HQ, Wan JM (2009) Quantitative trait loci mapping and stability for low temperature germination ability of rice. Plant Breed 128:387–392CrossRefGoogle Scholar
  24. Kanemasu ET, Bark DL, Chinchoy E (1975) Effect of soil temperature on sorghum emergence. Plant Soil 43:411–417CrossRefGoogle Scholar
  25. Kempenaar C, Schnieders BJ (1995) A method to obtain fast and uniform emergence of weeds for field experiments. Weed Res 35:385–390CrossRefGoogle Scholar
  26. Kim JS, Klein PE, Klein RR, Price HJ, Mullet JE, Stelly DM (2005) Chromosome identification and nomenclature of Sorghum bicolor. Genetics 169:1169–1173PubMedCrossRefGoogle Scholar
  27. Knoll J, Ejeta G (2008) Marker-assisted selection for early-season cold tolerance in sorghum: QTL validation across populations and environments. Theor Appl Genet 116:541–553PubMedCrossRefGoogle Scholar
  28. Knoll J, Gunaratna N, Ejeta G (2008) QTL analysis of early-season cold tolerance in sorghum. Theor Appl Genet 116:577–587PubMedCrossRefGoogle Scholar
  29. Kotowski F (1926) Temperature relations to germination of vegetable seed. Proc Am Soc Hortic Sci 23:176–184Google Scholar
  30. Kraakman ATW, Niks RE, Van den Berg P, Stam P, Van Eeuwijk FA (2004) Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics 168:435–446PubMedCrossRefGoogle Scholar
  31. Lacaze X, Hayes PM, Korol A (2009) Genetics of phenotypic plasticity: QTL analysis in barley, Hordeum vulgare. Heredity 102:163–173PubMedCrossRefGoogle Scholar
  32. Li M, Sun PL, Zhou HJ, Chen S, Yu SB (2011) Identification of quantitative trait loci associated with germination using chromosome segment substitution lines of rice (Oryza sativa L.). Theor Appl Genet 123:411–420PubMedCrossRefGoogle Scholar
  33. Limami AM, Rouillon C, Glevarec G, Gallais A, Hirel B (2002) Genetic and physiological analysis of germination efficiency in maize in relation to nitrogen metabolism reveals the importance of cytosolic glutamine synthetase. Plant Physiol 130:1860–1870PubMedCrossRefGoogle Scholar
  34. Liu JB, Fu ZY, Xie HL, Hu YM, Liu ZH, Duan LJ, Xu SZ, Tang JH (2011) Identification of QTLs for maize seed vigor at three stages of seed maturity using a RIL population. Euphytica 178:127–135CrossRefGoogle Scholar
  35. Mace ES, Jordan DR (2011) Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement. Theor Appl Genet 123:169–191PubMedCrossRefGoogle Scholar
  36. Mace ES, Xia L, Jordan DR, Halloran K, Parh DK, Huttner E, Wenzl P, Kilian A (2008) DArT markers: diversity analyses and mapping in Sorghum bicolor. BMC Genomics 9:26PubMedCrossRefGoogle Scholar
  37. Cisse ND, Ejeta G (2003) Genetic variations and relationships among seedling vigor traits in sorghum. Crop Sci 43:824–828CrossRefGoogle Scholar
  38. Neumann K, Kobiljski B, Denčić S, Varshney R, Börner A (2010) Genome-wide association mapping: a case study in bread wheat. Mol Breed 27:37–58CrossRefGoogle Scholar
  39. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  40. Pswarayi A, van Eeuwijk FA, Ceccarelli S, Grando S, Comadran J, Russell JR, Pecchioni N, Tondelli A, Akar T, Al-Yassin A, Benbelkacem A, Ouabbou H, Thomas WTB, Romagosa I (2008) Changes in allele frequencies in landraces, old and modern barley cultivars of marker loci close to QTL for grain yield under high and low input conditions. Euphytica 163:435–447CrossRefGoogle Scholar
  41. Reymond M, Muller B, Leonardi A, Charcosset A, Tardieu F (2003) Combining quantitative trait loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit. Plant Physiol 131:664–675PubMedCrossRefGoogle Scholar
  42. Schimpf DJ, Flint SD, Palmblad IG (1977) Representation of germination curves with logistic function. Ann Bot 41:1357–1360Google Scholar
  43. Shehzad T, Iwata H, Okuno K (2009) Genome-wide association mapping of quantitative traits in sorghum (Sorghum bicolor (L.) Moench) by using multiple models. Breed Sci 59:217–227CrossRefGoogle Scholar
  44. Shepard HL, Naylor REL, Stuchbury T (1996) The influence of seed maturity at harvest and drying method on the embryo, alpha-amylase activity and seed vigour in sorghum (Sorghum bicolor (L) Moench) Seed. Sci Technol 24:245–259Google Scholar
  45. Snapp S, Price R, Morton M (2008) Seed priming of winter annual cover crops improves germination and emergence. Agron J 100:1506–1510CrossRefGoogle Scholar
  46. Sorkheh K, Malysheva-Otto LV, Wirthensohn MG, Tarkesh-Esfahani S, Martinez-Gomez P (2008) Linkage disequilibrium, genetic association mapping and gene localization in crop plants. Genet Mol Biol 31:805–814CrossRefGoogle Scholar
  47. Srinivas G, Satish K, Madhusudhana R, Nagaraja Reddy R, Murali Mohan S, Seetharama N (2009) Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum. Theor Appl Genet 118:1439–1454PubMedCrossRefGoogle Scholar
  48. Stich B, Mohring J, Piepho HP, Heckenberger M, Buckler ES, Melchinger AE (2008) Comparison of mixed-model approaches for association mapping. Genetics 178:1745–1754PubMedCrossRefGoogle Scholar
  49. Timson J (1965) New method of recording germination data. Nature 207:216–217CrossRefGoogle Scholar
  50. Tiryaki I, Andrews DJ (2002) Germination and seedling cold tolerance in sorghum: I. Evaluation of rapid screening methods. Agron J 94:389CrossRefGoogle Scholar
  51. Tiryaki I, Buyukcingil Y (2009) Seed priming combined with plant hormones: influence on germination and seedling emergence of sorghum at low temperature. Seed Sci Technol 37:303–315Google Scholar
  52. Trudgill DL, Squire GR, Thompson K (2000) A thermal time basis for comparing the germination requirements of some British herbaceous plants. New Phytol 145:107–114CrossRefGoogle Scholar
  53. Vanhala TK, Stam P (2006) Quantitative trait loci for seed dormancy in wild barley (Hordeum spontaneum c. Koch). Genet Resour Crop Evol 53:1013–1019CrossRefGoogle Scholar
  54. Ventelon M, Deu M, Garsmeur O, Doligez A, Ghesquiere A, Lorieux M, Rami JF, Glaszmann JC, Grivet L (2001) A direct comparison between the genetic maps of sorghum and rice. Theor Appl Genet 102:379–386CrossRefGoogle Scholar
  55. Vieth E (1989) Fitting piecewise linear-regression functions to biological responses. J Appl Physiol 67:390–396PubMedGoogle Scholar
  56. Wade LJ, Hammer GL, Davey MA (1993) Response of germination to temperature amongst diverse sorghum hybrids. Field Crop Res 31:295–308CrossRefGoogle Scholar
  57. Weibull W (1951) A statistical distribution function of wide applicability. J Appl Mech 18:293–297Google Scholar
  58. Whitkus R, Doebley J, Lee M (1992) Comparative genome mapping of sorghum and maize. Genetics 132:1119–1130PubMedGoogle Scholar
  59. Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208PubMedCrossRefGoogle Scholar
  60. Zhang ZH, Su L, Li W, Chen W, Zhu YG (2005) A major QTL conferring cold tolerance at the early seedling stage using recombinant inbred lines of rice (Oryza sativa L.). Plant Sci 168:527–534CrossRefGoogle Scholar
  61. Zhang ZW, Ersoz E, Lai CQ, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu JM, A.Arnett DK, Ordovas JM, Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Karin Fiedler
    • 1
    Email author
  • Wubishet A. Bekele
    • 2
  • Wolfgang Friedt
    • 2
  • Rod Snowdon
    • 2
  • Hartmut Stützel
    • 1
  • Arndt Zacharias
    • 3
  • Ralf Uptmoor
    • 1
    • 4
  1. 1.Institute of Biological Production SystemsLeibniz Universität HannoverHannoverGermany
  2. 2.Department of Plant BreedingJustus-Liebig-University GiessenGiessenGermany
  3. 3.KWS Saat AGEinbeckGermany
  4. 4.Department of AgronomyUniversity of RostockRostockGermany

Personalised recommendations