Skip to main content
SpringerLink
Log in

Identification of wild barley derived alleles associated with plant development in an Australian environment

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

The objective of this study was to explore wild barley as a potential source of alleles controlling plant development that can be used to improve the adaptation of barley to the Australian environment. The HEB-25 population was evaluated in field conditions at Strathalbyn (South Australia) in 2015 and 2016 and phenotyped for five traits related to plant development, in addition to plant height and ear number. GWAS identified QTL for all traits, of which many co-localised with known phenology genes. In the Australian environment, it was found that the Gibberellic acid (GA)-dependant pathway is important in regulating key development stages including shooting, flowering and maturing compared to the photoperiod and vernalisation pathway. Beneficial alleles from wild barley were identified, such as at the QTL tightly linked to the swd1 locus belonging to the GA-dependant pathway, wild alleles from five subfamilies increased EAR by up to 2.23 ears per m2. At the identified QTL, a wide range of effects was observed due to the wild barley alleles thus providing new genetic diversity that can be utilised to fine-tune the adaptation of barley to the Australian environment.

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
Fig. 3

Similar content being viewed by others

References

  • ABARES (2018) Agricultural commodity statistics 2018. Coarse grains. Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, ACT. http://www.agriculture.gov.au/abares/research-topics/agricultural-commodities/agricultural-commodities-trade-data#2018. Accessed 21 Jan 2019

  • Akar T, Avci M, Dusunceli F (2004) Barley: post-harvest operations, 2004. http://www.fao.org/fileadmin/user_upload/inpho/docs/Post_Harvest_Compendium_-_BARLEY.pdf. Accessed 21 Jan 2019

  • Alqudah AM, Sharma R, Pasam RK, Graner A, Kilian B, Schnurbusch T (2014) Genetic dissection of photoperiod response based on GWAS of pre-anthesis phase duration in spring barley. PLoS ONE 9:e113120

    PubMed  PubMed Central  Google Scholar 

  • Alqudah AM, Koppolu R, Wolde GM, Graner A, Schnurbusch T (2016) The genetic architecture of barley plant stature. Front Genet 7:117

    PubMed  PubMed Central  Google Scholar 

  • Bélanger S, Paquet-Marceau S, Díaz Lago JE, Belzile F (2018) QTL mapping uncovers a semi-dwarf 1 (sdw1) allele in the barley (Hordeum vulgare) ND23049 line. Genome 61:429–436

    PubMed  Google Scholar 

  • Boden SA, Weiss D, Ross JJ, Davies NW, Trevaskis B, Chandler PM, Swain SM (2014) EARLY FLOWERING3 regulates flowering in spring barley by mediating gibberellin production and FLOWERING LOCUS T expression. Plant Cell 114:123794

    Google Scholar 

  • BOM (Bureau of Meteorology) (2019) Climate statistics for Australian locations. Summary statistics Strathalbyn. http://www.bom.gov.au/jsp/ncc/cdio/cvg/av?p_stn_num=023747&p_prim_element_index=0&p_comp_element_index=0&redraw=null&p_display_type=statistics_summary&normals_years=1981-2010&tablesizebutt=normal. Accessed 16 May 2019

  • Bradley D, Carpenter R, Copsey L, Vincent C, Rothstein S, Coen E (1996) Control of inflorescence architecture in Antirrhinum. Nature 379:791–797

    CAS  PubMed  Google Scholar 

  • Butler DG, Cullis BR, Gilmour AR, Gogel BJ (2018) ASReml-R reference manual (version 4). School of Mathematics and Applied Statistics, University of Wollongong

  • Campoli C, von Korff M (2014) Chapter five: genetic control of reproductive development in temperate cereals. In: Fornara F (ed) Advances in botanical research, vol 72. Academic Press, London, pp 131–158

    Google Scholar 

  • Campoli C, Shtaya M, Davis SJ, von Korff M (2012) Expression conservation within the circadian clock of a monocot: natural variation at barley Ppd-H1affects circadian expression of flowering time genes, but not clock orthologs. BMC Plant Biol 12:97

    CAS  PubMed  PubMed Central  Google Scholar 

  • Campoli C, Pankin A, Drosse B, Casao CM, Davis SJ, von Korff M (2013) HvLUX1 is a candidate gene underlying the early maturity 10 locus in barley: phylogeny, diversity, and interactions with the circadian clock and photoperiodic pathways. New Phytol 199:1045–1059

    CAS  PubMed  PubMed Central  Google Scholar 

  • Cantalapiedra CP, Boudiar R, Casas AM, Igartua E, Contreras-Moreira B (2015) BARLEYMAP: physical and genetic mapping of nucleotide sequences and annotation of surrounding loci in barley. Mol Breed 35(1):13

    Google Scholar 

  • Colmsee C, Beier S, Himmelbach A, Schmutzer T, Stein N, Scholz U, Mascher M (2015) BARLEX: the barley draft genome explorer. Mol Plant 8:964–966

    CAS  PubMed  Google Scholar 

  • Comadran J et al (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

    CAS  PubMed  Google Scholar 

  • Coventry S, Barr A, Eglinton J, McDonald G (2001) Characterisation of mapping parents and identification of genes involved in the yield and grain weight of barley (Hordeum vulgare L.) grown under Mediterranean environments. In: Proceedings of the 10th Australian barley technical symposium

  • Cuesta-Marcos A, Szucs P, Close TJ, Filichkin T, Muehlbauer GJ, Smith KP, Hayes PM (2010) Genome-wide SNPs and re-sequencing of growth habit and inflorescence genes in barley: implications for association mapping in germplasm arrays varying in size and structure. BMC Genom 11:707

    CAS  Google Scholar 

  • Cullis BR, Smith AB, Coombes NE (2006) On the design of early generation variety trials with correlated data. J Agric Biol Environ Stat 11:381

    Google Scholar 

  • Deppermann A, Balkovič J, Bundle SC, Di Fulvio F, Havlik P, Leclère D, Lesiv M, Prishchepov AV, Schepaschenko D (2018) Increasing crop production in Russia and Ukraine—regional and global impacts from intensification and recultivation. Environ Res Lett 13:025008

    Google Scholar 

  • Doyle MR et al (2002) The ELF4 gene controls circadian rhythms and flowering time in Arabidopsis thaliana. Nature 419:74

    CAS  PubMed  Google Scholar 

  • Dubcovsky J, Chen C, Yan L (2005) Molecular characterization of the allelic variation at the VRN-H2 vernalization locus in barley. Mol Breed 15:395–407

    CAS  Google Scholar 

  • Dwivedi SL, Scheben A, Edwards D, Spillane C, Ortiz R (2017) Assessing and exploiting functional diversity in germplasm pools to enhance abiotic stress adaptation and yield in cereals and food legumes. Front Plant Sci 8:1461

    PubMed  PubMed Central  Google Scholar 

  • Faure S, Turner AS, Gruszka D, Christodoulou V, Davis SJ, von Korff M, Laurie DA (2012) Mutation at the circadian clock gene EARLY MATURITY 8 adapts domesticated barley (Hordeum vulgare) to short growing seasons. Proc Natl Acad Sci 109:8328–8333

    CAS  PubMed  PubMed Central  Google Scholar 

  • Garrick DJ, Taylor JF, Fernando RL (2009) Deregressing estimated breeding values and weighting information for genomic regression analyses. Genet Sel Evol 41:55

    PubMed  PubMed Central  Google Scholar 

  • Gottwald S, Bauer P, Komatsuda T, Lundqvist U, Stein N (2009) TILLING in the two-rowed barley cultivar ‘Barke’ reveals preferred sites of functional diversity in the gene HvHox1. BMC Res Notes 2:258

    PubMed  PubMed Central  Google Scholar 

  • Gumedze FN, Welham SJ, Gogel BJ, Thompson R (2010) A variance shift model for detection of outliers in the linear mixed model. Comput Stat Data Anal 54:2128–2144

    Google Scholar 

  • Habte E, Müller LM, Shtaya M, Davis SJ, Von Korff M (2014) Osmotic stress at the barley root affects expression of circadian clock genes in the shoot. Plant Cell Enviro 37:1321–1337

    CAS  Google Scholar 

  • Hemming MN, Peacock WJ, Dennis ES, Trevaskis B (2008) Low-temperature and daylength cues are integrated to regulate FLOWERING LOCUS T in barley. Plant Physiol 147:355–366

    CAS  PubMed  PubMed Central  Google Scholar 

  • Herrero E et al (2012) EARLY FLOWERING4 recruitment of EARLY FLOWERING3 in the nucleus sustains the Arabidopsis circadian clock. Plant Cell 24:428–443

    CAS  PubMed  PubMed Central  Google Scholar 

  • Herzig P et al (2018) Contrasting genetic regulation of plant development in wild barley grown in two European environments revealed by nested association mapping. J Exp Bot 69:1517–1531

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hill CB, Li C (2016) Genetic architecture of flowering phenology in cereals and opportunities for crop improvement. Front Plant Sci 7:1906

    PubMed  PubMed Central  Google Scholar 

  • Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70

    Google Scholar 

  • James VA, Neibaur I, Altpeter F (2008) Stress inducible expression of the DREB1A transcription factor from xeric, Hordeum spontaneum L in turf and forage grass (Paspalum notatum Flugge) enhances abiotic stress tolerance. Trans Res 17:93–104

    CAS  Google Scholar 

  • Jiang K, Liberatore KL, Park SJ, Alvarez JP, Lippman ZB (2013) Tomato yield heterosis is triggered by a dosage sensitivity of the florigen pathway that fine-tunes shoot architecture. PLoS Genet 9:e1004043

    PubMed  PubMed Central  Google Scholar 

  • Karsai I et al (2005) The Vrn-H2 locus is a major determinant of flowering time in a facultative × winter growth habit barley (Hordeum vulgare L.) mapping population. Theor Appl Genet 110:1458–1466

    CAS  PubMed  Google Scholar 

  • Kikuchi R, Kawahigashi H, Ando T, Tonooka T, Handa H (2009) Molecular and functional characterization of PEBP genes in barley reveal the diversification of their roles in flowering. Plant Physiol 149:1341–1353

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kole C (2011) Wild Crop relatives: genomic and breeding resources: industrial crops. Springer, New York

    Google Scholar 

  • Laidig F, Piepho HP, Drobek T, Meyer U (2014) Genetic and non-genetic long-term trends of 12 different crops in German official variety performance trials and on-farm yield trends. Theor Appl Genet 127:2599–2617

    PubMed  PubMed Central  Google Scholar 

  • Liu W et al (2011) Association mapping in an elite maize breeding population. Theor Appl Genet 123:847–858

    PubMed  Google Scholar 

  • Loscos J, Igartua E, Contreras-Moreira B, Gracia MP, Casas AM (2014) HvFT1 polymorphism and effect—survey of barley germplasm and expression analysis. Front Plant Sci 5:251

    PubMed  PubMed Central  Google Scholar 

  • Maurer A et al (2015) Modelling the genetic architecture of flowering time control in barley through nested association mapping. BMC Genom 16:290

    Google Scholar 

  • Maurer A, Draba V, Pillen K (2016) Genomic dissection of plant development and its impact on thousand grain weight in barley through nested association mapping. J Exp Bot 67:2507–2518

    CAS  PubMed  PubMed Central  Google Scholar 

  • Maurer A, Sannemann W, Léon J, Pillen K (2017) Estimating parent-specific QTL effects through cumulating linked identity-by-state SNP effects in multiparental populations. Heredity 118:477–485

    CAS  PubMed  Google Scholar 

  • McMaster GS, Wilhelm WW (1997) Growing degree-days: one equation, two interpretations. Agric For Meteorol 87:291–300

    Google Scholar 

  • Mutasa-Göttgens E, Hedden P (2009) Gibberellin as a factor in floral regulatory networks. J Exp Bot 60:1979–1989

    PubMed  Google Scholar 

  • Nadolska-Orczyk A, Rajchel IK, Orczyk W, Gasparis S (2017) Major genes determining yield-related traits in wheat and barley. Theor Appl Genet 130(6):1081–1098

    CAS  PubMed  PubMed Central  Google Scholar 

  • Nice LM, Steffenson BJ, Blake TK, Horsley RD, Smith KP, Muehlbauer GJ (2017) Mapping agronomic traits in a wild barley advanced backcross–nested association mapping population. Crop Sci 57:1199–1210

    Google Scholar 

  • Nitcher R, Distelfeld A, Tan C, Yan L, Dubcovsky J (2013) Increased copy number at the HvFT1 locus is associated with accelerated flowering time in barley. Mol Genet Genom 288:261–275

    CAS  Google Scholar 

  • Nusinow DA et al (2011) The ELF4–ELF3–LUX complex links the circadian clock to diurnal control of hypocotyl growth. Nature 475:398

    CAS  PubMed  PubMed Central  Google Scholar 

  • Obsa BT, Eglinton J, Coventry S, March T, Guillaume M, Le TP, Hayden M, Langridge P, Fleury D (2017) Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment. PLoS ONE 12:e0178111–e0178111

    PubMed  PubMed Central  Google Scholar 

  • Pankin A et al (2014) Mapping-by-sequencing identifies HvPHYTOCHROME C as a candidate gene for the early maturity 5 locus modulating the circadian clock and photoperiodic flowering in barley. Genetics 114:165613

    Google Scholar 

  • Patterson HD, Thompson R (1971) Recovery of inter-block information when block sizes are unequal. Biometrika 58:545–554

    Google Scholar 

  • Pham A-T et al (2019) Genome-wide association of barley plant growth under drought stress using a nested association mapping population. BMC Plant Biol 19:134

    PubMed  PubMed Central  Google Scholar 

  • Punda I (2009) Barley malt beer food and agriculture organization of the United Nations. http://www.fao.org/fileadmin/user_upload/tci/docs/AH3_BarleyMaltBeer.pdf

  • R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/

  • Saade S et al (2016) Yield-related salinity tolerance traits identified in a nested association mapping (NAM) population of wild barley. Sci Rep 6:32586

    CAS  PubMed  PubMed Central  Google Scholar 

  • Sakuma S et al (2017) Extreme suppression of lateral floret development by a single amino acid change in the VRS1 transcription factor. Plant Physiol 175:1720–1731

    CAS  PubMed  PubMed Central  Google Scholar 

  • SAS Institute (2014) The SAS enterprise guide 7.1. SAS Institute, Cary, NC, USA

  • Schils R, Olesen JE, Kersebaum KC et al (2018) Cereal yield gaps across Europe. Eur J Agron 101:109–120

    Google Scholar 

  • Sharma R et al (2018) Genome-wide association of yield traits in a nested association mapping population of barley reveals new gene diversity for future breeding. J Exp Bot 69:3811–3822

    CAS  PubMed  PubMed Central  Google Scholar 

  • Shavrukov Y et al (2010) HvNax3—a locus controlling shoot sodium exclusion derived from wild barley (Hordeum vulgare ssp spontaneum). Funct Integr Genom 10:277–291

    CAS  Google Scholar 

  • Trevaskis B, Hemming MN, Peacock WJ, Dennis ES (2006) HvVRN2 responds to daylength, whereas HvVRN1 is regulated by vernalization and developmental status. Plant Physiol 140:1397–1405

    CAS  PubMed  PubMed Central  Google Scholar 

  • Turner A, Beales J, Faure S, Dunford RP, Laurie DA (2005) The pseudo-response regulator Ppd-H1 provides adaptation to photoperiod in barley. Science 310:1031–1034

    CAS  PubMed  Google Scholar 

  • Vatter T, Maurer A, Kopahnke D, Perovic D, Ordon F, Pillen K (2017) A nested association mapping population identifies multiple small effect QTL conferring resistance against net blotch (Pyrenophora teres f. teres) in wild barley. PLoS ONE 12:e0186803. https://doi.org/10.1371/journal.pone.0186803

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • von Zitzewitz J et al (2005) Molecular and structural characterization of barley vernalization genes. Plant Mol Biol 59:449–467

    CAS  Google Scholar 

  • Warschefsky E, Penmetsa RV, Cook DR, von Wettberg EJ (2014) Back to the wilds: tapping evolutionary adaptations for resilient crops through systematic hybridization with crop wild relatives. Am J Bot 101:1791–1800

    PubMed  Google Scholar 

  • Wiegmann M et al (2019) Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues. Sci Rep 9:6397. https://doi.org/10.1038/s41598-019-42673-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wilson RN, Heckman JW, Somerville CR (1992) Gibberellin is required for flowering in Arabidopsis thaliana under short days. Plant Physiol 100:403–408

    CAS  PubMed  PubMed Central  Google Scholar 

  • Xu Y, Jia Q, Zhou G, Zhang XQ, Angessa T, Broughton S, Yan G, Zhang W, Li C (2017) Characterization of the sdw1 semi-dwarf gene in barley. BMC Plant Biol 17(1):11

    PubMed  PubMed Central  Google Scholar 

  • Yan L et al (2006) The wheat and barley vernalization gene VRN3 is an orthologue of FT. Proc Natl Acad Sci 103:19581–19586

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yoshihara Y, Isogai T (2019) Does genetic diversity of grass improve yield, digestibility, and resistance to weeds, pests and disease infection? Arch Agron Soil Sci 65(12):1623–1629

    Google Scholar 

  • Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14(6):415–421

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank Trung Dzung Nguyen, Giang Truong Nguyen, Hoa Thanh Nguyen, Simon Schreiber, Pauline Delano for their technical assistance with measuring and phenotyping in both field and laboratory conditions.

Funding

This study was funded by the Grains Research and Development Corporation (Project UA00148).

Author information

Authors and Affiliations

  1. School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Urrbrae, SA, 5064, Australia

    Anh-Tung Pham & Timothy J. March

  2. Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120, Halle, Germany

    Andreas Maurer & Klaus Pillen

  3. Biometry Hub, Waite Campus, Urrbrae, SA, 5064, Australia

    Julian Taylor

  4. Australian Grain Technologies, 20 Leitch Road, Roseworthy, SA, 5371, Australia

    Stewart Coventry

  5. Sugar Research Australia, 71378 Bruce Highway, Gordonvale, QLD, 4865, Australia

    Jason K. Eglinton

Authors
  1. Anh-Tung Pham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andreas Maurer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Klaus Pillen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Julian Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stewart Coventry
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jason K. Eglinton
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Timothy J. March
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A-TP, SC, JE, TM carried out the experiments. A-TP, AM and JT analysed the data. KP provided seed material. JE, SC and TM provided crucial information for the design of the experiments. A-TP and TM wrote the manuscript. All authors read, revised and approved the final manuscript.

Corresponding author

Correspondence to Timothy J. March.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Availability of data and materials

Supporting data and sources used for this manuscript are provided in Online Resource 1: Figure S1, Online Resource 2: Fig. S2, Online Resource 3: Fig. S3, Online Resource 4: Tables S4. Raw data generated in this work (approximately 2 Mbytes of data) are available from the corresponding author on reasonable request.

Code availability

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Online Resource 1 (ESM_1)

. Table S1. Summary of simple statistics for the seven traits measured in the field trial in 2015 and 2016. (DOCX 14 kb)

Online Resource 2 (ESM_2)

. Fig. S1. Bar plots showing trait differences between the HEB-25 population and ten barley check varieties sown in the 2015 (A) and 2016 (B)’s experiments (TIFF 2919 kb)

Online Resource 3 (ESM_3)

. Fig. S2. Bar plots showing the difference between two experimental years in flowering time (HEA) in both Julian days (A) and growing degree days (GDD, B) for ten control barley varieties. Yellow and light blue color represents the year 2015 and 2016, respectively (DOCX 5244 kb)

Online Resource 4 (EMS_4)

. Table S2. Overview of all QTL and their significant effects on seven traits studied in 25 families of the HEB-25 population (XLSX 131 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pham, AT., Maurer, A., Pillen, K. et al. Identification of wild barley derived alleles associated with plant development in an Australian environment. Euphytica 216, 148 (2020). https://doi.org/10.1007/s10681-020-02686-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10681-020-02686-8

Keywords

Search

Navigation