Skip to main content
Log in

Stability of genome-wide QTL effects on malt α-amylase activity in a barley doubled-haploid population

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

Pre-harvest sprouting (PHS) can be a problem in malting barley (Hordeum vulgare L.) production as it results in lower yield and reduced grade. The presence of PHS is often associated with increased activity of α-amylase, a key enzyme for breakdown of starch into simple sugars. It is difficult to measure α-amylase activity (AA) associated with PHS however, and the same quantitative trait loci (QTL) may be responsible for both PHS AA and malt AA. The objective of this paper was to investigate co-occurrence and stability of QTL controlling malt AA in a barley doubled-haploid (DH) population that was evaluated in eight environments across North America. This population consisted of 150 DH lines developed from a cross between two barley varieties (Steptoe × Morex) for the North American Barley Genome Mapping Project. Malt AA was measured on a composite 400 g sample of each DH line and parent. There were a total of 223 restriction fragment length polymorphism markers covering a total genetic distance of 1221.9 cM across the entire genome. We used an empirical Bayesian method for detecting single QTLs and epistatic QTLs for individual environments. A common QTL was counted if it co-occurred in a pair of environments. Thus, the level of QTL × environment interaction was assessed based on the total frequency of co-occurred QTLs for all possible pairs of eight environments [(8 × 7)/2 = 28]. Heritability estimates (0.62–0.89) for individual environments were moderate to high. Genetic correlations between co-occurred additive and epistatic effects are essentially zero for most environment pairs. These results indicated strong QTL × environment interaction for malt AA. While the efficacy of genome-wide selection for PHS is still unknown especially in the presence of QTL × environment interaction, using the Bayesian approach may help us better understand appropriate methods for measuring and selecting for this trait.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Bonnardeaux Y, Li C, Lance R, Zhang XQ, Sivasithamparam K, Appels R (2008) Seed dormancy in barley: identifying superior genotypes through incorporating epistatic interactions. Aus J Agric Res 59:517–526

    Article  Google Scholar 

  • Davies NL (1992) A new malting index: prediction of malting quality by endosperm hydration. J Inst Brew 98:43–46

    Google Scholar 

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Longman Group Ltd, Edinburgh

    Google Scholar 

  • Fisher RA (1918) The correlation between relatives on the supposition of mendelian inheritance. Trans Roy Soc Edinburgh 52:339–433

    Google Scholar 

  • Glennie-Holmes M (1990) Relationships between pearling resistances of barleys and the extract potential of the subsequent malts. J Inst Brew 96:123–124

    Google Scholar 

  • Ham BJ, Spaner D, Rahman MH, Yeh FC, Yang R-C (2010) Analysis of genotype–environment interactions from a genome-wide survey of quantitative trait loci in a barley population. Curr Top Genet 4:21–32

    Google Scholar 

  • Han F, Romagosa I, Ullrich SE, Jones BL, Hayes PM, Wesenberg DM (1997) Molecular marker-assisted selection for malting quality traits in barley. Mol Breed 3:427–437

    Article  CAS  Google Scholar 

  • Hayes PM, Liu BH, Knapp SJ, Chen F, Jones B, Blake T, Franckowiak J, Rasmusson D, Sorrells M, Ullrich SE, Wesenberg D, Kleinhofs A (1993) Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor Appl Genet 87:392–401

    Article  Google Scholar 

  • Heffner EL, Sorrells ME, Jannink J-L (2009) Genomic selection for crop improvement. Crop Sci 49:1–12

    Article  CAS  Google Scholar 

  • Henry RJ (1985) Evaluation of barley and malt quality using near-infrared reflectance techniques. J Inst Brew 91:393–396

    Google Scholar 

  • Huang G, Varriano-Marston E (1980) α-Amylase activity and preharvest sprouting damage in kansas hard white wheat. J Agric Food Chem 28:509–512

    Article  PubMed  CAS  Google Scholar 

  • Kaeppler HF, Rasmusson DC (1991) Heritability, heterosis, and maternal effects of alpha-amylase activity in barley. Crop Sci 31:1452–1455

    Article  CAS  Google Scholar 

  • Kleinhofs A, Kilian A, Saghai-Maroof MA, Biyashev RM, Hayes PM, Chen FQ, Lapitan N, Fenwick A, Blake T, Kanazin V, Ananiev E, Dahleen LS, Kudrna D, Bollinger J, Knapp SJ, Liu B, Sorrells M, Heun M, Franckowiak J, Hoffman DL, Skadsen R, Steffenson BJ (1993) A molecular, isozyme and morphological map of barley (Hordeum vulgare) genome. Theor Appl Genet 86:705–712

    Article  CAS  Google Scholar 

  • Li CD, Tarr A, Lance RC, Harasymow S, Uhlmann J, Westcot S, Young KJ, Grime CR, Cakir M, Broughton S, Appels R (2003) A major QTL controlling seed dormancy and pre-harvest sprouting/grain α-amylase in two-rowed barley (Hordeum vulgare L.). Aus J Agric Res 54:1303–1313

    Article  CAS  Google Scholar 

  • Lorenz AJ, Chao S, Asoro FG, Heffner EL, Hayashi T, Iwata H, Smith KP, Sorrells ME, Jannink J-L (2011) Genomic selection in plant breeding: knowledge and prospects. Adv Agron 110:77–123

    Article  Google Scholar 

  • Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland

    Google Scholar 

  • Megazyme (2007) AMYLAZYME: Alpha-amylase assay procedure T-AMZ200 06/07. Megazyme International Ireland Limited

  • Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    PubMed  CAS  Google Scholar 

  • Morgan AG, Gothard PG (1981) A rapid test for identifying potential malting quality in the early generations of a barley breeding program. J Sci Food Agric 32:333–338

    Article  Google Scholar 

  • Otto SP, Jones CD (2000) Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 156(4):2093–2107

    PubMed  CAS  Google Scholar 

  • Rae SJ, Macaulay M, Ramsay L, Leigh F, Matthews D, O’Sullivan DM, Donini P, Morris PC, Powell W, Marshall DF, Waugh R, Thomas WTB (2007) Molecular barley breeding. Euphytica 158:295–303

    Article  CAS  Google Scholar 

  • Schwarz P, Henson C, Horsley R (2004) Preharvest sprouting in the 2002 Midwestern barley crop: occurrence and assessment of methodology. J Am Soc Brew Chem 62:147–154

    CAS  Google Scholar 

  • Ullrich SE, Clancy JA, del Blanco IA, Lee H, Jitkov VA, Han F, Kleinhofs A, Matsui K (2008) Genetic analysis of preharvest sprouting in a six-row barley cross. Mol Breed 21:249–259

    Article  Google Scholar 

  • Xu S (2003) Estimating polygenic effects using markers of the entire genome. Genetics 163:789–801

    PubMed  CAS  Google Scholar 

  • Xu S (2007) An empirical bayes method for estimating epistatic effects of quantitative trait loci. Biometrics 63:513–521

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We thank Dr. Pat Juskiw and two anonymous reviewers for helpful comments. This research was supported in part by the Natural Sciences and Engineering Research Council of Canada Grant OGP0183983 to R-CY.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R.-C. Yang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yang, RC., Ham, B.J. Stability of genome-wide QTL effects on malt α-amylase activity in a barley doubled-haploid population. Euphytica 188, 131–139 (2012). https://doi.org/10.1007/s10681-012-0680-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10681-012-0680-6

Keywords

Navigation