Skip to main content
SpringerLink
Log in

Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection

  • Review
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Key message

Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process.

Abstract

Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40–0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Akdemir D, Sanchez JI, Jannink JL (2015) Optimization of genomic selection training populations with a genetic algorithm. Genet Sel Evol 47:38–47

    Article  PubMed  PubMed Central  Google Scholar 

  • Albrecht T, Wimmer V, Auinger H-J, Erbe M, Knaak C, Ouzunova M, Simianer H, Schön C-C (2011) Genome-based prediction of testcross values in maize. Theor Appl Genet 123:339–350

    Article  PubMed  Google Scholar 

  • Browning SR, Browning BL (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084–1097

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Butler D (2009) ASReml R package version 3.0. https://www.vsni.co.uk/de/software/asreml/

  • Calińskia T, Harabasza J (1974) A dendrite method for cluster analysis. Commun Stat 3:1–27

    Article  Google Scholar 

  • Chiapparino E, Donini P, Reeves J, Tuberosa R, O’Sullivan D (2006) Distribution of β-amylase I haplotypes among European cultivated barleys. Mol Breed 18:341–354

    Article  CAS  Google Scholar 

  • Close TJ, Bhat PR, Lonardi S, Wu Y, Rostoks N, Ramsay L, Druka A, Stein N, Svensson JT, Wanamaker S, Bozdag S, Roose ML, Moscou MJ, Chao S, Varshney RK, Szucs P, Sato K, Hayes PM, Matthews DE, Kleinhofs A, Muehlbauer GJ, DeYoung J, Marshall DF, Madishetty K, Fenton RD, Condamine P, Graner A, Waugh R (2009) Development and implementation of high-throughput SNP genotyping in barley. BMC Genomics 10:852

  • Comadran J, Kilian B, Russell J, Ramsay L, Stein N, Ganal M, Shaw P, Bayer M, Thomas W, Marshall D, Hedley P, Tondelli A, Pecchioni N, Francia E, Korzun V, Walther A, Waugh R (2012) Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley. Nat Genet 44:1388–1392

    Article  PubMed  CAS  Google Scholar 

  • Desta ZA, Ortiz R (2014) Genomic selection: genome-wide prediction in plant improvement. Trends Plant Sci 19:592–601

    Article  PubMed  CAS  Google Scholar 

  • Endelman JB (2011) Ridge regression and other Kernels for genomic selection with R package rrBLUP. Plant Genome 4:250–255

    Article  Google Scholar 

  • Endelman JB, Atlin GN, Beyene Y, Semagn K, Zhang X, Sorrells ME, Jannink J-L (2014) Optimal design of preliminary yield trials with genome-wide markers. Crop Sci 54:48–59

    Article  Google Scholar 

  • Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33:1–22

    Article  PubMed  PubMed Central  Google Scholar 

  • Frisch M (2015) SelectionTools. http://www.fb09-pg-s207agraruni-giessende/~frisch-m/. R-Library 15.1.1

  • Graner A, Streng S, Kellermann A, Schiemann A, Bauer E, Waugh R, Pellio B, Ordon F (1999) Molecular mapping and genetic fine-structure of the rym5 locus encoding resistance to different strains of the Barley Yellow Mosaic Virus complex. Theor Appl Genet 98:285–290

    Article  CAS  Google Scholar 

  • Gutiérrez L, Cuesta-Marcos A, Castro AJ, von Zitzewitz J, Schmitt M, Hayes PM (2011) Association mapping of malting quality quantitative trait loci in winter Barley: positive signals from small germplasm arrays. Plant Genome 4:256–272

    Article  Google Scholar 

  • Haley CS, Visscher PM (1998) Strategies to utilize marker-quantitative trait loci associations. J Dairy Sci 81:85–97

    Article  PubMed  CAS  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 

  • Heffner EL, Jannink J-L, Iwata H, Souza E, Sorrells ME (2011) Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci 51:2597–2606

    Article  Google Scholar 

  • Henryon M, Berg P, Sørensen AC (2014) Animal-breeding schemes using genomic information need breeding plans designed to maximise long-term genetic gains. Livest Sci 166:38–47

    Article  Google Scholar 

  • Heslot N, Jannink J-L, Sorrells ME (2015) Perspectives for genomic selection applications and research in plants. Crop Sci 55:1–12

    Article  Google Scholar 

  • Hickey JM, Dreisigacker S, Crossa J, Hearne S, Babu R, Prasanna BM, Grondona M, Zambelli A, Windhausen VS, Mathews K, Gorjanc G (2014) Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation. Crop Sci 54:1476–1488

    Article  Google Scholar 

  • Hofmann K, Silvar C, Casas AM, Herz M, Buttner B, Gracia MP, Contreras-Moreira B, Wallwork H, Igartua E, Schweizer G (2013) Fine mapping of the Rrs1 resistance locus against scald in two large populations derived from Spanish barley landraces. Theor Appl Genet 126:3091–3102

  • Isidro J, Jannink J-L, Akdemir D, Poland J, Heslot N, Sorrells ME (2015) Training set optimization under population structure in genomic selection. Theor Appl Genet 128:145–158

    Article  PubMed  PubMed Central  Google Scholar 

  • Islamovic E, Obert D, Budde A, Schmitt M, Brunick R II, Kilian A, Chao S, Lazo G, Marshall J, Jellen E, Maughan P, Hu G, Klos K, Brown R, Jackson E (2014) Quantitative trait loci of barley malting quality trait components in the Stellar/01Ab8219 mapping population. Mol Breed 34:59–73

    Article  CAS  Google Scholar 

  • Jia Y, Jannink J-L (2012) Multiple-trait genomic selection methods increase genetic value prediction accuracy. Genetics 192:1513–1522

    Article  PubMed  PubMed Central  Google Scholar 

  • König J, Kopahnke D, Steffenson BJ, Przulj N, Romeis T, Röder MS, Ordon F, Perovic D (2012) Genetic mapping of a leaf rust resistance gene in the former Yugoslavian barley landrace MBR1012. Mol Breed 30:1253–1264

    Article  Google Scholar 

  • Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756

    PubMed  CAS  PubMed Central  Google Scholar 

  • Lorenzana R, Bernardo R (2009) Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor Appl Genet 120:151–161

    Article  PubMed  Google Scholar 

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

    PubMed  CAS  PubMed Central  Google Scholar 

  • Miedaner T, Korzun V (2012) Marker-assisted selection for disease resistance in wheat and barley breeding. Phytopathology 102:560–566

    Article  PubMed  Google Scholar 

  • Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’ Hara RB, Simpson GL, Solymos P, Henry M, Stevens H, Wagner H (2014) Vegan: community ecology package. http://www.CRANR-projectorg/package=vegan. R package version 2.2-1

  • Poland J, Endelman J, Dawson J, Rutkoski J, Wu S, Manes Y, Dreisigacker S, Crossa J, Sánchez-Villeda H, Sorrells M, Jannink J-L (2012) genomic selection in wheat breeding using genotyping-by-sequencing. Plant Genome 5:103–113

    Article  CAS  Google Scholar 

  • Potokina E, Caspers M, Prasad M, Kota R, Zhang H, Sreenivasulu N, Wang M, Graner A (2004) Functional association between malting quality trait components and cDNA array based expression patterns in barley (Hordeum vulgare L.). Mol Breed 14:153–170

    Article  CAS  Google Scholar 

  • Rincent R, Laloë D, Nicolas S, Altmann T, Brunel D, Revilla P, Rodríguez VM, Moreno-Gonzalez J, Melchinger A, Bauer E, Schoen CC, Meyer N, Giauffret C, Bauland C, Jamin P, Laborde J, Monod H, Flament P, Charcosset A, Moreau L (2012) Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.). Genetics 192:715–728

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Rostoks N, Ramsay L, MacKenzie K, Cardle L, Bhat PR, Roose ML, Svensson JT, Stein N, Varshney RK, Marshall DF, Graner A, Close TJ, Waugh R (2006) Recent history of artificial outcrossing facilitates whole-genome association mapping in elite inbred crop varieties. Proc Natl Acad Sci 103:18656–18661

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Schmid KJ, Thorwarth P (2014) Genomic Selection in Barley Breeding. In: Kumlehn J, Stein N (eds) Biotechnological approaches to barley improvement. Springer, Berlin, pp 367–378

    Google Scholar 

  • Shewry PR, Ullrich SE (2014) Barley: Chemistry and Technology, 2nd edn. AACC International

  • Spindel J, Begum H, Akdemir D, Virk P, Collard B, Redoña E, Atlin G, Jannink JL, McCouch SR (2015) Genomic selection and association mapping in rice Oryza sativa: effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS Genet 11:e1004982

    Article  PubMed  PubMed Central  Google Scholar 

  • Utz HF (2011) PLABSTAT - Ein Computerprogramm zur statistischen Analyse von pflanzenzüchterischen Experimenten. Saatgutforschungund Populationsgenetik, Universität Hohenheim, Stuttgart, Institut für Pflanzenzüchtung

    Google Scholar 

  • Wang Y, Mette MF, Miedaner T, Gottwald M, Wilde P, Reif JC, Zhao Y (2014) The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years. BMC Genom 15:556

    Article  Google Scholar 

  • Werner K, Friedt W, Ordon F (2007) Localisation and combination of resistance genes against soil-borne viruses of barley (BaMMV, BaYMV) using doubled haploids and molecular markers. Euphytica 158:323–329

    Article  CAS  Google Scholar 

  • Wimmer V, Albrecht T, Auinger H-J, Schoen C-C (2012) synbreed: a framework for the analysis of genomic prediction data using R. Bioinformatics 28:2086–2087

    Article  PubMed  CAS  Google Scholar 

  • Zhao Y, Gowda M, Liu W, Würschum T, Maurer H, Longin F, Ranc N, Reif J (2012) Accuracy of genomic selection in European maize elite breeding populations. Theor Appl Genet 124:769–776

    Article  PubMed  Google Scholar 

  • Zhong S, Dekkers JCM, Fernando RL, Jannink J-L (2009) Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study. Genetics 182:355–364

    Article  PubMed  CAS  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors greatly thank Professor Mark E. Sorrells (Cornell University, USA) and Dr. Edward Henry Byrne (KWS UK Ltd., UK) for careful reading and providing useful comments for this manuscript. This research was supported by Grant (FKZ 0315960) from the Bundesministerium Bildung und Forschung (BMBF) within the framework of the PLANT 2030 program.

Author information

Authors and Affiliations

  1. KWS LOCHOW GMBH, Ferdinand-von-Lochow-Straße 5, 29303, Bergen, Germany

    Malthe Schmidt, Sonja Kollers, Anja Maasberg-Prelle, Jörg Großer, Burkhard Schinkel, Alexandra Tomerius & Viktor Korzun

  2. AIB Dr. Alexandra Tomerius, Saffeweg 32, 38304, Wolfenbüttel, Germany

    Alexandra Tomerius

  3. Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Stadt Seeland, Germany

    Andreas Graner

Authors
  1. Malthe Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sonja Kollers
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anja Maasberg-Prelle
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jörg Großer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Burkhard Schinkel
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexandra Tomerius
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Andreas Graner
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Viktor Korzun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Viktor Korzun.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Communicated by D. E. Mather.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 214 kb)

Supplementary material 2 (PDF 21 kb)

Supplementary material 3 (PDF 20 kb)

122_2015_2639_MOESM4_ESM.jpg

Supplementary Figure S1: Distribution of minor allele frequency of spring barley (left) and winter barley (right) over all chromosomes and also unmapped markers (JPEG 53 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schmidt, M., Kollers, S., Maasberg-Prelle, A. et al. Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection. Theor Appl Genet 129, 203–213 (2016). https://doi.org/10.1007/s00122-015-2639-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-015-2639-1

Keywords

Search

Navigation