Skip to main content
SpringerLink
Log in

Genome-wide association analysis of root system architecture features and agronomic traits in durum wheat

  • Published:
Molecular Breeding Aims and scope Submit manuscript

Abstract

Root system architecture (RSA) has positive effects on wheat growth and its yield performance. As root features are difficult to manipulate through conventional breeding strategies, marker-trait association (MTA) could be helpful for the improvement of RSA. In the present study, 112 durum wheat genotypes were investigated for several root system features as well as some agronomic traits. The population was genotyped using a 15K SNP and a total of 3321 markers were used in the association analysis. A total of 581 significant marker-trait associations were identified in all of the 14 chromosomes. The percentages of phenotypic variation (R2) of measured traits varied between 8.76 and 24.81%. Out of 581 associated markers, 125 loci were linked with multiple traits. The most significant associations on measured traits were detected for genome B compared to genome A (61% vs 39%). Also, major associated loci existed on chromosomes 1A, 1B, 2B, 3B, and 5B, which could be considered in the future breeding programs to manipulate relevant traits using marker-assisted selection procedures. Among associated SNP markers, most markers were related to the number of days to spike heading (181), anthesis (53), booting (69), physiological maturity (41), water use efficiency (109), and transpiration efficiency (24). Furthermore, the large number of QTLs (167 in total) for RSA and agronomic traits were detected. The highest numbers of QTLs were related to WUE (23), DAS (23), DB (21), and DA (20) than other traits. Among the detected QTLs, 16 QTLs for RSA overlapped with different agronomic traits, as well as 6 QTLs co-located with other RSA traits in at last one trait. These results are helpful for better understanding the genetic basis of root system features and agronomic traits. Furthermore, these results could be valuable for facilitating pyramiding of the ideal alleles using the MAS approach for favorable plant-type and high water use efficiency in the future durum wheat breeding programs.

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

  • Ahmadi J, Pour-Aboughadareh A, Fabriki-Ourang S, Mehrabi AA, Siddique KHM (2018a) Screening wild progenitors of wheat for salinity stress at early stages of plant growth: insight into potential sources of variability for salinity adaptation in wheat. Crop Pasture Sci 69:649–658

    CAS  Google Scholar 

  • Ahmadi J, Pour-Aboughadareh A, Fabriki-Ourang S, Mehrabi AA, Siddique KHM (2018b) Screening wheat germplasm for seedling root architectural traits under contrasting water regimes: potential sources of variability for drought adaptation. Arch Agron Soil Sci 64:1351–1365

    Google Scholar 

  • Ahmadi J, Pour-Aboughadareh A, Ourang SF, Mehrabi AA, Siddique KHM (2018c) Wild relatives of wheat: Aegilops–Triticum accessions disclose differential antioxidative and physiological responses to water stress. Acta Physiol Plant 40:90

    Google Scholar 

  • Alahmad S, El Hassouni K, Bassi FM, Dinglasan E, Youssef C, Quarry G, Aksoy A, Mazzucotelli E, Juhasz A, Able JA, Christopher J, Voss-Fels KP, Hickey LT (2019) A major root architecture QTL responding to water limitation in durum wheat. Front Plant Sci 10:436

    PubMed  PubMed Central  Google Scholar 

  • Bai C, Liang Y, Hawkesford MJ (2013) Identification of QTLs associated with seedling root traits and their correlation with plant height in wheat. J Exp Bot 64:1745–1753

    CAS  PubMed  PubMed Central  Google Scholar 

  • Baloch FS, Alsaleh A, Shahid MQ, Çiftçi V, E. Sáenz de Miera L, Aasim M, Nadeem MA, Aktaş H, Özkan H, Hatipoğlu R (2017) A whole genome DArTseq and SNP analysis for genetic diversity assessment in durum wheat from central Fertile Crescent. PLoS One 12:e0167821

    PubMed  PubMed Central  Google Scholar 

  • Bashiri H, Cheghamirza K, Arji I, Mahmodi N (2017) Assessing genetic diversity of Pyrus spp. in the central Zagros mountains based on morphological characters. Genet Resour crop Evol 64:391

  • Blum A (2009) Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress. Field Crop Res 112:119–123

    Google Scholar 

  • Bodner G, Leitner D, Nakhforoosh A, Sobotik M, Moder K, Kaul HP (2013) A statistical approach to root system classification. Front Plant Sci 4:2–15

    Google Scholar 

  • Boukid F, Dall’Asta M, Bresciani L, Mena P, Del Rio D (2019) Phenolic profile and antioxidant capacity of landraces, old and modern Tunisian durum wheat. Eur Food Res Technol 245:73–82

    CAS  Google Scholar 

  • 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 23:2633–2635

    CAS  PubMed  Google Scholar 

  • Bramley H, Turner NC, Siddique KHM (2013) Water use efficiency. In: Kole C (ed) Genomics and breeding for climate resilient crops. Springer Science & Business Media, pp 225–269

  • Cane MA, Maccaferri M, Nazemi G, Salvi S, Frncisa R, Colalongo C, Tuberosa R (2014) Association mapping for root architectural traits in durum wheat seedlings as related to agronomic performance. Mol Breeding 34:1629–1645

    Google Scholar 

  • Christopher J, Christopher M, Jennings R, Jones S, Fletcher S, Borrell A, Manschadi AM, Jordan D, Mace E, Hammer G (2013) QTL for root angle and number in a population developed from bread wheats (Triticum aestivum) with contrasting adaptation to water-limited environments. Theor Appl Genet 126:1563–1574

    CAS  PubMed  Google Scholar 

  • Debibakas S, Rocher S, Garsmeur O, Toubi L, Roques D, D’Hont A, Hoarau JY, Daugrois JH (2014) Prospecting sugarcane resistance to sugarcane yellow leaf virus by genome-wide association. Theor Appl Genet 127:1719–1732

    CAS  PubMed  PubMed Central  Google Scholar 

  • Deschamps S, Campbell M (2010) Utilization of next-generation sequencing platforms in plant genomics and genetic variant discovery. Mol Breed 25:553–570

    CAS  Google Scholar 

  • Doyle JJ, Doyle JL (1990) Isolation of plant DNA from fresh tissue. Focus 12:13–15

    Google Scholar 

  • Earl DA, vonHoldt BM (2012) Structure Harvester: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361

    Google Scholar 

  • Edae EA, Byrne PF, Manmathan H, Haley SD, Moragues M, Lopes MS, Reynolds MP (2013) Association mapping and nucleotide sequence variation in five drought tolerance candidate genes in spring wheat. Plant Genome 6:1–13

    CAS  Google Scholar 

  • Ehdaie B, Mohammadi SA, Nouraein M (2016) QTLs for root traits at mid-tillering and for root and shoot traits at maturity in a RIL population of spring bread wheat grown under well-watered conditions. Euphytica 211:17–38

    Google Scholar 

  • El Hassouni K, Alahmad B, Belkadi B, Filali-Maltouf L, Hickey LT, Bassi FM (2018) Root system architecture and its association with yield under different water regimes in durum wheat. Crop Sci 58:1–16

    Google Scholar 

  • Fitter A (2002) Characteristics and functions of root systems. In: Waisel Y, Eshel A, Beeckman T, Kafkafi U (eds) Plant roots: the hidden half, CRC Press, pp 15–32

  • Flint-Garcia SA, Thornsberry JM, Buckler ES (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374

    CAS  PubMed  Google Scholar 

  • Gao Y, Duan A, Qiu X, Liu Z, Sun J, Zhang J, Wang H (2010) Distribution of roots and root length density in a maize/soybean strip intercropping system. Agric Water Manag 98:199–212

    Google Scholar 

  • Giunta F, Pruneddu G, Motzo R (2019) Grain yield and grain protein of old and modern durum wheat cultivars grown under different cropping systems. Field Crop Res 230:107–120

    Google Scholar 

  • Gould SH (1955) The methods of Archimedes. Am Math Mon 62:473–476

    Google Scholar 

  • Graziani M, Maccaferri M, Royo C, Salvatorelli F, Tuberosa R (2014) QTL dissection of yield components and morphophysiological traits in a durum wheat elite population tested in contrasting thermo-pluviometric conditions. Crop & Pasture Sci 65:80–95

    Google Scholar 

  • Gurung S, Mamidi S, Bonman JM, Xiong M, Brown-Guedira G, Adhikari TB (2014) Genome-wide association study reveals novel quantitative trait loci associated with resistance to multiple leaf spot diseases of spring wheat. PLoS One 9:e108179

    PubMed  PubMed Central  Google Scholar 

  • Hajabbasi MA (2001) Tillage effects on soil compactness and wheat root morphology. J Agric Sci Technol 3:67–77

    Google Scholar 

  • House MA, Griswold CK, Lukens LN (2014) Evidence for selection on gene expression in cultivated rice (Oryza sativa). Mol Biol Evol 31:1514–1525

    CAS  PubMed  Google Scholar 

  • Hu X, Ren J, Ren X, Huang S, Sabiel SAI, Luo M, Nevo E, Fu C, Peng J, Sun D (2015) Association of agronomic traits with SNP markers in durum wheat (Triticum turgidum L. durum (Desf.)). PLoS One 10:e0130854

    PubMed  PubMed Central  Google Scholar 

  • Huang S, Sun L, Hu X, Wang Y, Zhang Y, Nevo E, Peng J, Sun D (2018) Associations of canopy leaf traits with SNP markers in durum wheat (Triticum turgidum L. durum (Desf.)). PLoS One 13:e0206226

    PubMed  PubMed Central  Google Scholar 

  • Hwang EY, Song Q, Jia G, Specht JE, Hyten DL, Costa J, Cregan PB (2014) A genome-wide association study of seed protein and oil content in soybean. BMC Genome 15:1

    Google Scholar 

  • IBPGR (1985) Revised descriptor list for wheat (Triticum spp.). International Board for Plant Genetic Resources. Rome, Italy

  • Ju C, Zhang W, Liu Y, Gao Y, Wang X, Yan J, Yang X, Li J (2018) Genetic analysis of seedling root traits reveals the association of root trait with other agronomic traits in maize. BMC Plant Biol 18:171

    PubMed  PubMed Central  Google Scholar 

  • Khalili M, Pour Aboughadareh A, Naghavi MR (2013) Screening of drought tolerant cultivars in barley using morpho-physiological traits and integrated selection index under water deficit stress condition. Advanced Crop Science 3:462–471

    Google Scholar 

  • Le Gouis J, Bordes J, Ravel C, Heumez E, Faure S, Praud S, Galic N, Remoue C, Balfourier F, Allard V, Rousset M (2012) Genome-wide association analysis to identify chromosomal regions determining components of earliness in wheat. Theor Appl Genet 124:597–611

    PubMed  Google Scholar 

  • Lewien M, Carter A, Pumphrey M, Talbert L, Akhunov E (2016) Nested association mapping of water use efficiency in spring wheat (Triticum aestivum L.) using carbon isotope discrimination analysis and remote sensing traits. International Annual Meetings, 6-9 November, Phoenix, Arizona

  • Ma J, Luo W, Zhang H, Zhou XH, Qin NN, Wei YM, Liu YX, Jiang QT, Chen GY, Zheng YL, Lan XJ (2017) Identification of quantitative trait loci for seedling root traits from Tibetan semi-wild wheat (Triticum aestivum subsp. tibetanum). Genome 60:1068–1075

    CAS  PubMed  Google Scholar 

  • Maccaferri M, El-Feki W, Nazemi G, Salvi S, Angela Cane M, Colalongo MC, Stefanelli S, Tuberosa R (2016) Prioritizing quantitative trait loci for root system architecture in tetraploid wheat. J Exp Bot 67:1161–1178

    CAS  PubMed  PubMed Central  Google Scholar 

  • Maccaferri M, Sanguineti MC, Corneti S, Ortega JLA, Salem MB, Bort J, DeAmbrogio E, del Moral LFG, Demontis A, el-Ahmed A, Maalouf F, Machlab H, Martos V, Moragues M, Motawaj J, Nachit M, Nserallah N, Ouabbou H, Royo C, Slama A, Tuberosa R (2008) Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 178:489–511

    PubMed  PubMed Central  Google Scholar 

  • Maccaferri M, Sanguineti MC, Demontis A, El-Ahmed A, del Moral LG, Maalouf F, Nachit M, Nserallah N, Ouabbou H, Rhouma S, Royo C, Villegas D, Tuberosa R (2011) Association mapping in durum wheat grown across a broad range of water regimes. J Exp Bot 62:409–438

    CAS  PubMed  Google Scholar 

  • Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends Plant Sci 12:57–63

    CAS  PubMed  Google Scholar 

  • Mahanta D, Rai RK, Mishra SD, Raja A, Purakayastha TJ, Varghese E (2014) Influence of phosphorus and biofertilizers on soybean and wheat root growth and properties. Field Crop Res 166:1–9

    Google Scholar 

  • Maulana F, Ayalew H, Anderson JD, Kumssa TT, Huang W, Ma XF (2018) Genome-wide association mapping of seedling heat tolerance in winter wheat. Front Plant Sci 9:1272

    PubMed  PubMed Central  Google Scholar 

  • Mwadzingeni L, Shimelis H, Rees DJG, Tsilo TJ (2017) Genome-wide association analysis of agronomic traits in wheat under drought stressed and non-stressed conditions. PLoS One 12:e0171692

    PubMed  PubMed Central  Google Scholar 

  • Newman EI (1966) A method for estimating the total length of roots in a sample. J Appl Ecol 3:139–145

    Google Scholar 

  • Paula P, Pausas JG (2011) Root traits explain different foraging strategies between resprouting life histories. Oecologia 165:321–331

    PubMed  Google Scholar 

  • Peng J, Sun D, Nevo E (2011) Wild emmer wheat, Triticum dicoccoides, occupies a pivotal position in wheat domestication process. Aust J Crop Sci 5:1127–1143

    Google Scholar 

  • Phung NTP, Mai CD, Hoang GT, Truong HTM, Lavarenne J, Gonin M (2016) Genome-wide association mapping for root traits in a panel of rice accessions from Vietnam. BMC Plant Biol 16:64

    PubMed  PubMed Central  Google Scholar 

  • Pierret A, Moran CJ, Mclachlan CB, Kirby JM (2000) Measurement of root length density in intact samples using x-radiography and image analysis. Image Anal Stereol 19:145–149

    Google Scholar 

  • Pour-Aboughadareh A, Ahmadi J, Mehrabi AA, Etminan A, Moghaddam M, Siddique KHM (2017) Physiological responses to drought stress in wild relatives of wheat: implications for wheat improvement. Acta Physiol Plant 39:106

    Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ren Y, Qian Y, Xu Y, Zou C, Liu D, Zhao X, Zhang A, Tong Y (2017) Characterization of QTLs for root traits of wheat grown under different nitrogen and phosphorus supply levels. Front Plant Sci 8:2096

    PubMed  PubMed Central  Google Scholar 

  • Robredo A, Perez-Lopez U, de la Maza HS, Gonzalez-Moro B, Lacuesta M, Mena-Petite A, Munzo-Rueda A (2007) Elevated CO2 alleviates the impact of drought on barley improving water status by lowering stomatal conductance and delaying its effects on photosynthesis. Environ Exp Bot 59:252–263

    CAS  Google Scholar 

  • Ruiz M, Giraldo P, Gonzalez JM (2018) Phenotypic variation in root architecture traits and their relationship with eco-geographical and agronomic features in a core collection of tetraploid wheat landraces (Triticum turgidum L.). Euphytica 214:54

    Google Scholar 

  • Ryser P (2006) The mysterious root length. Plant Soil 286:1–6

    CAS  Google Scholar 

  • Sabiel SAI, Huang S, Hu X, Ren X, Fu C, Peng J, Sun D (2017) SNP-based association analysis for seedling traits in durum wheat (Triticum turgidum L. durum (Desf.)). Breed Sci 67:83–94

    CAS  PubMed  PubMed Central  Google Scholar 

  • Schenk MK, Barber SA (1979) Root characteristics of corn genotypes as related to P uptake. Agron J 71:921–927

    CAS  Google Scholar 

  • Siosemardeh A, Osmani Z, Bahraminejad B, Vahabi K, Roohi E (2012) Identification of AFLP markers associated with stress tolerance index in Sardari wheat ecotypes. J Agr Sci Tech 14:629–643

    CAS  Google Scholar 

  • Sukumaran S, Reynolds MP, Sansaloni C (2018) Genome-wide association analyses identify QTL hotspots for yield and component traits in durum wheat grown under yield potential, drought, and heat stress environments. Front Plant Sci 9:81

    PubMed  PubMed Central  Google Scholar 

  • Sun X, Du Z, Ren J, Amombo E, Hu T, Fu J (2015) Association of SSR markers with functional traits from heat stress in diverse tall fescue accessions. BMC Plant Biol 15:116–149

    PubMed  PubMed Central  Google Scholar 

  • Trebbi D, Maccaferri M, de Heer P, Sorensen A, Giuliani S, Salvi S, Sanguineti MC, Massi A, va der Vossen EA, Tuberosa R (2011) High-throughput SNP discovery and genotyping in durum wheat (Triticum durum Desf.). Theor Appl Genet 123:555–569

  • Varshney RK, Spurthi N, Nayak S, May GD, Jackson SA (2009) Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends Biotechnol 27:522–530

    CAS  PubMed  Google Scholar 

  • Wahl S, Ryser P (2000) Root tissue structure is linked to ecological strategies of grasses. New Phytol 148:459–471

    PubMed  Google Scholar 

  • Waines JG, Ehdaie B (2007) Domestication and crop physiology: roots of green-revolution wheat. Ann Bot 100:991–998

    PubMed  PubMed Central  Google Scholar 

  • Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing Consortium, Lillemo M, Mather D, Appels R, Dolferus R, Brown-Guedira G, Korol A, Akhunova AR, Feuillet C, Salse J, Morgante M, Pozniak C, Luo MC, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards KJ, Hayden M, Akhunov E (2014) Characterization of polyploidy wheat genomic diversity using a high-density 90000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796

    CAS  PubMed  PubMed Central  Google Scholar 

  • Wehner G, Balko C, Ordon F (2016) QTL for water use related traits in juvenile barley. Agronomy 6:62

    Google Scholar 

  • XLSTAT (2017) Data analysis and statistical solution for Microsoft excel. Addinsoft; Paris

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

    Google Scholar 

  • Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20

    CAS  Google Scholar 

Download references

Acknowledgments

The authors sincerely thank the Department of Gene Bank, Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Germany for making the genotypic data. Also, the authors are grateful to Dr. Marion Roder, from the Leibniz Institute of Plant Genetics and Crop Plant, for her fruitful comments on the manuscript.

Author information

Authors and Affiliations

  1. Department of Agronomy and Plant Breeding, Ilam University, Ilam, Iran

    Ali Ashraf Mehrabi & Sajjad Mansouri

  2. Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

    Alireza Pour-Aboughadareh

  3. Department of Water Resources Engineering, Ilam University, Ilam, Iran

    Alireza Hosseini

Authors
  1. Ali Ashraf Mehrabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alireza Pour-Aboughadareh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sajjad Mansouri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alireza Hosseini
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceived and designed the experiments: AAM and AP; methodology: AAM, AP, and AH; investigation: AAM and SM. Software: AM and AP; writing—original draft: AAM and AP; writing—review and editing: AAM, AP, SM and AH.

Corresponding author

Correspondence to Ali Ashraf Mehrabi.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

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

Electronic supplementary material

Table S1

Pearson’s correlation matrix for 26 root and agronomic traits in 112 durum wheat genotypes (DOCX 22 kb)

Table S2

Variable loading scores of 26 root and agronomic traits and the proportion of variation of each principal component (DOCX 15 kb)

Table S3

Significant trait-SNP marker association pairs for measured root and agronomic traits in 112 durum wheat genotypes (XLSX 47 kb)

Table S4

The SNP marker loci associated with multiple traits in durum wheat genotypes (XLSX 18 kb)

Fig. S1

Frequency distribution of the measured traits. (A) number of seminal roots, (B) length of maximum seminal root, (C) average of seminal root length, (D) sum of seminal root length, (E) root fresh weight, (F) root dry weight, (G) root length, (H) root surface area, (I) root fineness, (J) root diameter, (K) root surface density, (L) specific root length (PNG 1191 kb)

High resolution image (TIF 142 kb)

Fig. S2

Frequency distribution of the measured traits. (A) root length density, (B) root tissue density, (C) root volume, (D) days to appearance of spike, (E) days to anthesis, (F) days to booting, (G) days to physiological maturity, (H) grain filling period, (I) number of grains per spike, (J) root diameter, (K) 100-grains weight, (L) grain yield (PNG 1279 kb)

High resolution image (TIF 145 kb)

Fig. S3

Frequency distribution of the measured traits. (A) water use efficiency and (B) transpiration efficiency (PNG 208 kb)

High resolution image (TIF 25 kb)

Fig. S4

Genome LD decay of whole genome (PNG 358 kb)

High resolution image (TIF 63 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mehrabi, A.A., Pour-Aboughadareh, A., Mansouri, S. et al. Genome-wide association analysis of root system architecture features and agronomic traits in durum wheat. Mol Breeding 40, 55 (2020). https://doi.org/10.1007/s11032-020-01136-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11032-020-01136-6

Keywords

Search

Navigation