Skip to main content

Identification and validation of QTL for spike fertile floret and fruiting efficiencies in hexaploid wheat (Triticum aestivum L.)

Abstract

Key message

This study identified and validated two QTL associated with spike fertile floret and fruiting efficiencies. They represent two new loci to use in MAS to improve wheat yield potential.

Abstract

The spike fruiting efficiency (FE—grains per unit spike dry weight at anthesis, GN/SDW) is a promising trait to improve wheat yield potential. It depends on fertile floret efficiency (fertile florets per unit SDW—FFE, FF/SDW) and grain set (grains per fertile floret—GST). Given its difficult measurement, it is often estimated as the grains per unit of nongrain spike dry weight at maturity (FEm). In this study, quantitative trait loci (QTL) were mapped using a double haploid population (Baguette 19/BIOINTA 2002, with high and low FE, respectively) genotyped with the iSelect 90 K SNP array and evaluated in five environments. We identified 37 QTL, but two were major with an R2 > 10% and stable for being at least present in three environments: the QFEm.perg-3A (on Chr. 3A, 51.6 cM, 685.12 Mb) for FEm and the QFFE.perg-5A (on Chr. 5A, 42.1 cM, 461.49 Mb) for FFE, FE and FEm. Both QTL were validated using two independent F2 populations and KASP markers. For the most promising QTL, QFFE.perg-5A, the presence of the allele for high FFE resulted in + 4% FF, + 9% GN, + 13% GST, + 16% yield gSDW−1 and + 5% yield spike−1. QFEm.perg-3A and QFFE.perg-5A represent two new loci to use in MAS to improve wheat yield potential.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Notes

  1. https://github.com/juancrescente/lmap.

Abbreviations

B19:

Baguette 19

B2002:

BIOINTA 2002

CH:

Chaff (no-grain spike dry weight at maturity, g spike1)

CN:

Compactness of the spike (mm node1)

DH:

Double haploid

E1 to E5:

Testing environments

FFE:

Fertile floret efficiency (florets gSDW1)

FE:

Fruiting efficiency (grains gSDW1)

FEm:

Fruiting efficiency at maturity (grains gCH1)

FF:

Fertile florets per spike (n° spike1)

FFFS:

Fertile florets per fertile spikelet (n° spikelet1)

FS:

Fertile spikelets per spike (n° spike1)

GN:

Grain number per spike (n° spike1)

GST:

Grain set (n° grains floret1)

GW:

Grain weight (g)

Pop 1:

F2 population showing segregation for the QFFE.perg-5A

Pop 2:

F2 population showing segregation for the QFEm.perg-3A

SDW:

Spike dry weight at anthesis (g spike1)

SL:

Spike length (mm)

TS:

Total spikelets per spike (n° spike1)

References

  • Abbate PE, Andrade FH, Lázaro L, Bariffi JH, Berardocco HG, Inza VH, Marturano F (1998) Grain yield increase in recent Argentine wheat cultivars. Crop Sci 38:1203–1209

    Google Scholar 

  • Acreche MM, Briceño-Félix G, Martín Sanchez JA, Slafer GA (2008) Physiological bases of genetic gains in Mediterranean bread wheat yield in Spain. Eur J Agron 28(3):162–170

    Google Scholar 

  • Alonso MP, Panelo J, Mirabella NE, Pontaroli AC (2018) Selection for high spike fertility index increases genetic progress in grain yield and stability in bread wheat. Euphytica 214:112

    Google Scholar 

  • Appels R, Eversole K, Feuillet C et al (2018) Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361:6403

    Google Scholar 

  • Basile SML, Ramirez IA, Crescente JM, Conde MB, Demichelis M, Abbate PE, Rogers WJ, Pontaroli AC, Helguera M, Vanzetti LS (2019) Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation. BMC Plant Biol 19:553

    Google Scholar 

  • Beales J, Turner A, Griffiths S, Snape JW, Laurie DA (2007) A pseudo-response regulator is misexpressed in the photoperiod insensitive Ppd-D1a mutant of wheat (Triticum aestivum L.). Theor Appl Genet 115(5):721–733

    CAS  PubMed  Google Scholar 

  • Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889–890

    CAS  PubMed  Google Scholar 

  • Calderini DF, Slafer GA (1998) Changes in yield and yield stability in wheat during the 20th century. Field Crop Res 57:335–347

    Google Scholar 

  • Calderini DF, Savin R, Abeledo LG, Reynolds MP, Slafer GA (2001) The importance of the period immediately preceding anthesis for grain weight determination in wheat. Euphytica 119:199–204

    Google Scholar 

  • Chand R (2009) Challenges to ensuring food security through wheat. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour 4:1–13

    Google Scholar 

  • Chen H, Iqbal M, Yang RC, Spaner D (2016) Effect of Lr34/Yr18 on agronomic and quality traits in a spring wheat mapping population and implications for breeding. Mol Breed 36:5

    Google Scholar 

  • Chen H, Semagn K, Iqbal M, Moakhar NP, Haile T, N’Diaye A, Yang R-C, Hucl P, Pozniak C, Spaner D (2017) Genome-wide association mapping of genomic regions associated with phenotypic traits in Canadian western spring wheat. Mol Breed 37:141

    Google Scholar 

  • Cheng R, Doerge RW, Borevitz J (2017) Novel resampling improves statistical power for multiple-trait QTL mapping. G3-Genes Genom Genet 7:813

    Google Scholar 

  • Dao HQ, Byrne PF, Reid SD, Haley SD (2017) Validation of quantitative trait loci for grain quality-related traits in a winter wheat mapping population. Euphytica 213:5

    Google Scholar 

  • De Buyser J, Henry Y (1980) Comparison of different media used in culturing anthers in vitro in soft wheat. Can J Bot 58:997–1000

    Google Scholar 

  • Del Pozo A, Mathus I, Serret MD, Araus JL (2014) Agronomic and physiological traits associated with breeding advances of wheat under high productive Mediterranean conditions. The case of Chile. Environ Exp Bot 130:180–189

    Google Scholar 

  • Deng Z, Cui Y, Han Q, Fang W, Li J, Tian J (2017) Discovery of consistent QTLs of wheat spike-related traits under nitrogen treatment at different development stages. Front Plant Sci 8:2120

    PubMed  PubMed Central  Google Scholar 

  • Di Rienzo JA, Casanoves F, Balzarini MG, Gonzalez L, Tablada M, Robledo CW (2016) Grupo InfoStat. FCA, Universidad Nacional de Córdoba, Córdoba

    Google Scholar 

  • Elía M, Savin R, Slafer GA (2016) Fruiting efficiency in wheat: physiological aspects and genetic variation among modern cultivars. Field Crop Res 191:83–90

    Google Scholar 

  • Evans LT (1996) Crop evolution, adaptation and yield. Cambridge University Press, Cambridge

    Google Scholar 

  • Falconer DS (1960) Introduction to quantitative genetics. Ronald Press Co, New York

    Google Scholar 

  • Fischer RA (1975) Yield potential in a dwarf spring wheat and the effect of shading 1. Crop Sci 15:607–613

    Google Scholar 

  • Fischer RA (1983) Wheat. Potential productivity of field crops under different environments. International Rice Research Institute, Los Banos, pp 129–154

    Google Scholar 

  • Fischer RA (1985) Number of kernels in wheat crops and the influence of solar radiation and temperature. J Agric Sci 105:447–461

    Google Scholar 

  • Fischer RA (2007) Understanding the physiological bases of yield potential in wheat. J Agric Sci 145:99–113

    Google Scholar 

  • Fischer RA (2011) Wheat physiology: a review of recent developments. Crop Pasture Sci 62:95–114

    Google Scholar 

  • Fischer RA, Edmeades GO (2010) Breeding and cereal yield progress. Crop Sci 50:S-85–S-98

    Google Scholar 

  • Fischer RA, Stockman YM (1980) Kernel number per spike in wheat (Triticum Aestivum L.): responses to preanthesis shading. Aust J Plant Physiol 7:169–180

    CAS  Google Scholar 

  • Fischer RA, Rebetzke GJ (2018) Indirect selection for potential yield in early-generation, spaced plantings of wheat and other small-grain cereals: a review. Crop Pasture Sci 69(5):439

    Google Scholar 

  • Fu D, Szűcs P, Yan L, Helguera M, Skinner JS, von Zitzewitz J, Hayes PM, Dubcovsky J (2005) Large deletions within the first intron in VRN-1 are associated with spring growth habit in barley and wheat. Mol Genet Genom 273:54–65

    CAS  Google Scholar 

  • Gerard GS, Alqudah A, Lohwasser U, Börner A, Simón MR (2019) Uncovering the genetic architecture of fruiting efficiency in bread wheat: a viable alternative to increase yield potential. Crop Sci 59:1–17

    Google Scholar 

  • Ghiglione HO, Gonzalez FG, Serrago R, Maldonado SB, Chilcott C, Cura JA, Miralles DJ, Zhu T, Casal JJ (2008) Autophagy regulated by daylength sets the number of fertile florets in wheat. Plant J 55:1010–1024

    CAS  PubMed  Google Scholar 

  • González FG, Slafer GA, Miralles DJ (2003) Grain and floret number in response to photoperiod during stem elongation in fully and slightly vernalized wheats. Field Crop Res 81:17–27

    Google Scholar 

  • González FG, Miralles DJ, Slafer GA (2011a) Wheat floret survival as related to pre-anthesis spike growth. J Exp Bot 62:4889–4901

    PubMed  Google Scholar 

  • González F, Terrile I, Falcón MO (2011b) Spike fertility and duration of stem elongation as promising traits to improve potential grain number (and yield): variation in modern Argentinean wheats. Crop Sci 51:1693

    Google Scholar 

  • Guo Z, Chen D, Alqudah AM, Röder MS, Ganal MW, Schnurbusch T (2017) Genome-wide association analyses of 54 traits identified multiple loci for the determination of floret fertility in wheat. New Phytol 214:257–270

    CAS  PubMed  Google Scholar 

  • Kirby EJM (1988) Analysis of leaf, stem and ear growth in wheat from terminal spikelet stage to anthesis. Field Crop Res 18:127–140

    Google Scholar 

  • Langer RHM, Hanif M (1973) A study of floret development in wheat (Triticum aestivum L.). Ann Bot 37:743–751

    Google Scholar 

  • Lo Valvo PJ, Miralles DJ, Serrago RA (2018) Genetic progress in Argentine bread wheat varieties released between 1918 and 2011: changes in physiological and numerical yield components. Field Crop Res 221:314–321

    Google Scholar 

  • Mahibbur RM, Govindarajulu Z (1997) A modification of the test of Shapiro and Wilk for normality. J Appl Stat 24(2):219–236

    Google Scholar 

  • Martino DL, Abbate PE, Cendoya MG, Gutheim F, Mirabella NE, Pontaroli AC, Saranga Y (2015) Wheat spike fertility: inheritance and relationship with spike yield components in early generations. Plant Breed 134(3):264–270

    Google Scholar 

  • Mirabella NE, Abbate PE, Ramirez IA, Pontaroli AC (2016) Genetic variation for wheat spike fertility in cultivars and early breeding materials. J Agric Sci 154(1):13–22

    Google Scholar 

  • Mo Y, Vanzetti LS, Hale I, Spagnolo EJ, Guidobaldi F, Al-Oboudi J, Odle N, Pearce S, Helguera M, Dubcovsky J (2019) Identification and characterization of Rht25, a locus on chromosome arm 6AS affecting wheat plant height, heading time, and spike development. Theor Appl Genet 131(10):2021–2035

    Google Scholar 

  • Perry MW, D’Antuono MF (1989) Yield improvement and associated characteristics of some Australian spring wheat cultivars introduced between 1860 and 1982. J Agric Res 40:457–472

    Google Scholar 

  • Pflüger LA, D’Ovidio R, Margiotta B, Peña R, Mujeeb-Kazi A, Lafiandra D (2001) Characterization of high- and low-molecular weight glutenin subunits associated to the D genome of Aegilops tauschii in a collection of synthetic hexaploid wheats. Theor Appl Genet 103:1293–1301

    Google Scholar 

  • Pretini N, Terrile II, Gazaba LN, Donaire G, Arisnabarreta S, Vanzetti LS, González FG (2020) A comprehensive study of spike fruiting efficiency in wheat. Crop Sci. https://doi.org/10.1002/csc2.20143

    Article  Google Scholar 

  • Quraishi UM, Murat F, Abrouk M, Pont C, Confolent C, Oury FX, Ward J, Boros D, Gebruers K, Delcour JA, Courtin CM, Bedo Z, Saulnier L, Guillon F, Balzergue S, Shewry PR, Feuillet C, Charmet G, Salse J (2011) Combined meta-genomics analyses unravel candidate genes for the grain dietary fiber content in bread wheat (Triticum aestivum L.). Funct Integr Genom 11:71–83

    CAS  Google Scholar 

  • Ramirez-Gonzalez RH, Uauy C, Caccamo M (2015) PolyMarker: a fast polyploid primer design pipeline. Bioinformatics 31:2038–2039

    CAS  PubMed  PubMed Central  Google Scholar 

  • Reynolds M, Foulkes MJ, Slafer GA, Berry P, Parry MAJ, Snape JW, Angus WJ (2009) Raising yield potential in wheat. J Exp Bot 60:1899–1918

    CAS  PubMed  Google Scholar 

  • Reynolds M, Foulkes J, Furbank R, Griffiths S, King J, Murchie E, Parry M, Slafer G (2012) Achieving yield gains in wheat. Plant Cell Environ 35:1799–1823

    PubMed  Google Scholar 

  • Sakuma S, Golan G, Guo Z et al (2019) Unleashing floret fertility in wheat through the mutation of a homeobox gene. Proc Natl Acad Sci USA 116:5182

    CAS  PubMed  PubMed Central  Google Scholar 

  • Siddique KHM, Kirby EJM, Perry MW (1989) Ear: stem ratio in old and modern wheat varieties; relationship with improvement in number of grains per ear and yield. Field Crop Res 21:59–78

    Google Scholar 

  • Slafer GA (2003) Genetic basis of yield as viewed from a crop physiologist’s perspective. Ann Appl Biol 142:117–128

    Google Scholar 

  • Slafer GA, Andrade FH (1989) Genetic improvement in bread wheat (Triticum aestivum) yield in Argentina. Field Crop Res 21:289–296

    Google Scholar 

  • Slafer GA, Andrade FH (1993) Physiological attributes related to the generation of grain yield in bread wheat cultivars released at different eras. Field Crop Res 31:351–367

    Google Scholar 

  • Slafer GA, Araus JL (2007) Physiological traits for improving wheat yield under a wide range of conditions. In: Spiertz JHJ, Struik PC, van Laar HH (eds) Scale and complexity in plant systems research: gene-plant-crop relations. Springer, The Nethelands, pp 147–156

    Google Scholar 

  • Slafer GA, Elía M, Savin R, García G, Terrile I, Ferrante A, Miralles DJ (2015) Fruiting efficiency: an alternative trait to further raise wheat yield. Food Energy Secur 4(2):92–109

    Google Scholar 

  • Snape JW, Moore G (2007) Reflections and opportunities: gene discovery in the complex wheat genome. In: Buck HT, Nisi JE, Salomón N (eds) Wheat production in stressed environments. Springer, Dordrecht, pp 677–684

    Google Scholar 

  • Stapper M, Fischer RA (1990) Genotype, sowing date and plant spacing influence on high-yielding irrigated wheat in southern New South Wales. II. Growth, yield and nitrogen use. Aust J Agric Res 41(6):1021–1041

    Google Scholar 

  • Stockman YM, Fischer RA, Brittain EG (1983) Assimilate supple and floret development within the spike of wheat (Triticum aestivum L.). Aust J Plant Physiol 10:585–594

    Google Scholar 

  • Stone BF (1968) A formula for determining degree of dominance in cases of monofactorial inheritance of resistance to chemicals. Bull World Health Organ 38(2):325–326

    CAS  PubMed  PubMed Central  Google Scholar 

  • Terrile II, Miralles DJ, González FG (2017) Fruiting efficiency in wheat (Triticum aestivum L): trait response to different growing conditions and its relation to spike dry weight at anthesis and grain weight at harvest. Field Crop Res 201:86–96

    Google Scholar 

  • Tweeten L, Thompson SR (2008) Long-term global agricultural output supply-demand balance and real farm and food prices. Working paper AEDE-WP0044-08. Ohio State University. Columbus, OH

  • Waddington SR, Cartwright PM, Wall PC (1983) A quantitative scale of spike initial and pistil development in barley and wheat. Ann Bot 51:119–130

    Google Scholar 

  • Waddington SR, Ransom JK, Osmanzai M, Saunders DA (1986) Improvement in the yield potential of bread wheat adapted to northwest Mexico. Crop Sci 26(4):698–703

    Google Scholar 

  • Wang S, Basten CJ, Zeng ZB (2012) Windows QTL cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC. https://statgen.ncsu.edu/qtlcart/WQTLCart.htm

  • Wang S, Wong D, Forrest K 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

    CAS  PubMed  PubMed Central  Google Scholar 

  • Xu YF, Li SS, Li LH, Ma FF, Fu XY, Shi ZL, Xu HX, Ma PT, An DG (2017) QTL mapping for yield and photosynthetic related traits under different water regimes in wheat. Mol Breed 37:34

    Google Scholar 

  • Yan L, Helguera M, Kato K, Fukuyama S, Sherman J, Dubcovsky J (2004) Allelic variation at the VRN-1 promoter region in polyploid wheat. Theor Appl Genet 109:1677–1686

    CAS  PubMed  Google Scholar 

  • Yu M, Mao SL, Hou DB, Chen GY, Pu ZE, Li W, Lan XJ, Jiang QT, Liu YX, Deng M, Wei YM (2018) Analysis of contributors to grain yield in wheat at the individual quantitative trait locus level. Plant Breed 137:35–49

    CAS  Google Scholar 

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

    Google Scholar 

  • Zhai H, Feng Z, Du X et al (2018) A novel allele of TaGW2-A1 is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (Triticum aestivum L.). Theor Appl Genet 131:539–553

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The present work was funded by the National Agency of Scientific and Technical Promotion of Argentina (PICT 2012-1198, PICT 2014-1283), the National Institute of Agricultural and Husbandry Technology (INTA, PNCYO 1127042), Argentina, the Monsanto Beachell-Bourlag Scholarship, the Northwest University of Buenos Aires Province (UNNOBA, SIB 2015, SIB 2017, SIB 2019), Argentina, and the EU FP7 Funding (ADAPATWHEAT 289842). NP is a research fellow of the National Scientific and Technical Research Council (CONICET) at the Center for Research and Transfer of Northwest Buenos Aires (CITNOBA).

Author information

Authors and Affiliations

Authors

Contributions

FGG identified the parental lines for developing the populations. FGG, IIT and AB generated the DH populations. IIT, JP, MG and MR helped with the initial genotyping and mapping of the populations. NP and LSV improved and set the final genetic map. IIT and FGG carried out the phenotyping experiments for 2012 and 2013. NP, IIT and FGG carried out the phenotyping experiments for 2015 and 2016. LSV, NP and FGG designed the validation experiments. NP and LSV conducted the F2 genotyping and the QTL analyses. NP wrote the first manuscript with revision from LSV and FGG. FGG designed and coordinated the project.

Corresponding author

Correspondence to Nicole Pretini.

Ethics declarations

Conflict of interest

The authors declare that there are no conflicts of interest. This study does not include human or animal subjects.

Additional information

Communicated by Takao Komatsuda.

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.

Supplementary file1 (PDF 192 kb)

Supplementary file2 (PDF 597 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pretini, N., Vanzetti, L.S., Terrile, I.I. et al. Identification and validation of QTL for spike fertile floret and fruiting efficiencies in hexaploid wheat (Triticum aestivum L.). Theor Appl Genet 133, 2655–2671 (2020). https://doi.org/10.1007/s00122-020-03623-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-020-03623-y