Skip to main content

Advertisement

Log in

Variability in Indian bread wheat (Triticum aestivum L.) varieties differing in nitrogen efficiency as assessed by microsatellite markers

  • Original Article
  • Published:
Protoplasma Aims and scope Submit manuscript

Abstract

Wheat (Triticum aestivum L.) is a staple food for half of the world. Its productivity and agronomical practices, especially for nitrogen supplementation, is governed by the nitrogen efficiency (NE) of the genotypes. We analyzed 16 popular cultivated Indian varieties of wheat for their NE and variability estimates using a set of 21 simple sequence repeat (SSR) markers, derived from each wheat chromosome. These genotypes were categorized into three groups, viz., low, moderate, and high nitrogen efficient. Of these 16 genotypes, we have reported six, eight, and two genotypes in high, moderate, and low NE categories, respectively. The differential NE in these genotypes was supported by nitrogen uptake and assimilation parameters. The values of average polymorphic information content and marker index for these SSR markers were estimated to be 0.32 and 0.59, respectively. The genetic similarity coefficient for all possible pairs of varieties ranged from 0.41 to 0.76, indicating the presence of considerable range of genetic diversity at molecular level. The dendrogram prepared on the basis of unweighted pair-group method of arithmetic average algorithm grouped the 16 wheat varieties into three major clusters. The clustering was strongly supported by high bootstrap values. The distribution of the varieties in different clusters and subclusters appeared to be related to their variability in NE parameter that was scored. Genetically diverse parents were identified that could potentially be used for their desirable characteristics in breeding programs for improvement of NE in wheat.

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

Similar content being viewed by others

Abbreviations

N:

nitrogen

NUE:

nitrogen use efficiency

NE:

nitrogen efficiency

SSR:

simple sequence repeat

PIC:

polymorphic information content

NR:

nitrate reductase

Km :

Michaelis-Menten constant

MI:

marker index

ANOVA:

one-way analysis of variance

LSD:

Fisher’s least significant difference

HNE:

high N efficient

LNE:

low N efficient

MNE:

moderate N efficient

UPGMA:

unweighted pair group method with arithmetic mean

CTAB:

cetyl trimethylammonium bromide

GWM:

gatersleben wheat microsatellite

AICWIP:

all India coordinated wheat improvement project

References

  • Abdin MZ, Kumar PA, Abrol YP (1992) Biochemical basis of variability in nitrate reductase activity in wheat (Triticum aestivum L.). Plant Cell Physiol 33:951–956

    CAS  Google Scholar 

  • Abdin MZ, Dwivedi RK, Abrol YP (2004) Nitrogen and agriculture. In: Singh RP, Shankar N, Jaiwal PK (eds) Nitrogen nutrition and plant productivity. Studium Press, Houston, pp 23–46

    Google Scholar 

  • Abrol YP, Chatterjee SR, Kumar PA, Jain V (1999) Improvement in nitrogenous fertilizer utilization—physiological and molecular approaches. Curr Sci 76:1357–1364

    Google Scholar 

  • Agarwal M, Shrivastava N, Padh H (2008) Advances in molecular marker techniques and their applications in plant sciences. Plant Cell Rep 27:617–631

    Article  PubMed  CAS  Google Scholar 

  • Ahmad A, Abdin MZ (1999) NADH: nitrate reductase and NAD (P) H: nitrate reductase activity in mustard seedlings. Plant Sci 143:1–8

    Article  CAS  Google Scholar 

  • Ahmad A, Khan I, Anjum NA, Abrol YP, Iqbal M (2005) Role of sulphate transporter systems in sulphur efficiency of mustard genotypes. Plant Sci 169:842–846

    Article  CAS  Google Scholar 

  • Ahmad A, Khan I, Abrol YP, Iqbal M (2008) Genotypic variation of nitrogen use efficiency in Indian mustard. Environ Pollut 154:462–466

    Article  PubMed  CAS  Google Scholar 

  • Aslam M, Travis RL, Huffaker RC (1992) Comparative kinetics and reciprocal inhibition of nitrate and nitrite uptake in roots of uninduced and induced barley (Hordeum vulgare L.) seedlings. Plant Physiol 99:1124–1133

    Article  PubMed  CAS  Google Scholar 

  • Bertin P, Gallais A (2000) Physiological and genetic basis of nitrogen use efficiency in maize: II. QTL detection and coincidences. Maydica 45:67–80

    Google Scholar 

  • Bohn M, Utz HF, Melchinger AE (1999) Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs, and SSRs and their use for predicting progeny variance. Crop Sci 39:228–237

    CAS  Google Scholar 

  • Bredemeijer GMM, Arens P, Wouters D, Visser D, Vosman B (1998) The use of semi-automated fluorescent microsatellite analysis for tomato cultivar identification. Theor Appl Genet 97:584–590

    Article  CAS  Google Scholar 

  • Evans HJ, Nason A (1953) Pyridine nucleotide-nitrate reductase from extracts of higher plants. Plant Physiol 28:233–254

    Article  PubMed  CAS  Google Scholar 

  • Fageria NK, Baligar VC (1999) Phosphorus use efficiency in wheat genotypes. J Plant Nutr 22:331–340

    Article  CAS  Google Scholar 

  • Fahima T, Roder MS, Grama A, Nevo E (1998) Microsatellite DNA polymorphism divergence in Triticum dicoccoides accessions highly resistant to yellow rust. Theor Appl Genet 96:187–195

    Article  CAS  Google Scholar 

  • FAI (2008) Fertiliser statistics 2007-08. Fertilizer Association of India, New Delhi

    Google Scholar 

  • Gourley CJP, Allan DL, Ruselle MP (1994) Plant nutrient efficiency. A comparison of definitions and suggested improvement. Plant Soil 15:29–37

    Article  Google Scholar 

  • Gupta S, Prasad M (2009) Development and characterization of geneic SSR-markers in Medicago truncatula and their transferability in leguminous and non-leguminous species. Genome 52:761–771

    Article  PubMed  CAS  Google Scholar 

  • Gupta PK, Varshney RK (2000) The development and use of microsatellites markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphytica 113:163–185

    Article  CAS  Google Scholar 

  • Hirel B, Bertin P, Isabella Q, Bourdoncle W, Attagnant C, Dellay C, Gouy A, Cadiou S, Retailliau C, Falque M, Gallis A (2001) Towards better understanding of the genetic and physiological basis for nitrogen use efficiency in maize. Plant Physiol 125:1258–1270

    Article  PubMed  CAS  Google Scholar 

  • Hokanson SC, Szewc-Mcfadden AK, Lamboy WF, Mcferson JR (1998) Microsatellite (SSR) markers reveal genetic identities, genetic diversity and relationships in a Malus domestica borkh. core subset collection. Theor Appl Genet 67:671–683

    Article  Google Scholar 

  • Huang XQ, Börner A, Röder MS, Ganal MW (2002) Assessing genetic diversity of wheat (Triticum aestivum L.) germplasm using microsatellite markers. Theor Appl Genet 105:699–707

    Article  PubMed  CAS  Google Scholar 

  • Jaccard P (1908) Nouvelles recherché sur to distribution florale. Bulletin Society Vaud Sc Nat 44:223–270

    Google Scholar 

  • Kronzucker HJ, Siddiqi MY, Class ADM (1995) Kinetics of NO, influx in Spruce. Plant Physiol 109:319–326

    PubMed  CAS  Google Scholar 

  • Kumar PA, Krusse E, Andriesse X, Weisbeek P, Kloppstech K (1993) Integration of a cyanobacterial protein involved in nitrate reduction (narB) into isolated Synechococcus but not into pea thylakoid membranes. Eur J Biochem 214:533–537

    Article  PubMed  CAS  Google Scholar 

  • Lian X, Xing Y, Yan H, Xu C, Li X, Zhang Q (2005) QTLs for low nitrogen tolerance at seedling stage identified using a recombinant inbred line population derived from an elite rice hybrid. Theor Appl Genet 112:85–96

    Article  PubMed  CAS  Google Scholar 

  • Merdinoglu D, Butterlin G, Bevilacqua L, Chiquet V, Adam-Blondon’ AF, Decroocq S (2005) Develpoment and characterization of a large set of microsatellite markers in grapevine (Vitis vinifera L.) suitable for multiplex PCR. Mol Breed 15:349–366

    Article  CAS  Google Scholar 

  • Mir RR, Rustgi S, Sharma S, Singh R, Goyal A, Kumar J, Gaur A, Tyagi AK, Khan H, Sinha M, Balyan HS, Gupta PK (2008) A preliminary genetic analysis of fibre traits and the use of new genomic SSRs for genetic diversity in jute. Euphytica 161:413–427

    Article  CAS  Google Scholar 

  • Mohammadi SA, Khodarahmi M, Jamalirad S, Jalal Kamali MR (2009) Genetic diversity in a collection of old and new bread wheat cultivars from Iran as revealed by simple sequence repeat based analysis. Ann Appl Biol 154:67–76

    Article  CAS  Google Scholar 

  • Moll RH, Kamprath EJ, Jackson WA (1982) Analysis and interpretation of factors which contribute to efficiency of nitrogen utilization. Agron J 74:562–564

    Article  Google Scholar 

  • Moll RH, Kamprath EJ, Jackson WA (1987) Development of N efficient prolific hybrids of maize. Crop Sci Madison 27:181–186

    Article  CAS  Google Scholar 

  • Oscarson P, Ingemarsson B, Larsson CM (1989) Growth and nitrate uptake properties of plants grown with different relative rates of nitrogen supply. II. Activity and affinity of the nitrate uptake system in Pisum and Lemna in relation to nitrogen availability and N demand. Plant Cell Environ 12:787–794

    Article  Google Scholar 

  • Pathak RR, Ahmad A, Lochab S, Raghuram N (2008) Molecular physiology of plant nitrogen use efficiency and biotechnological options for its enhancement. Curr Sci 94:1394–1403

    CAS  Google Scholar 

  • Plaschke J, Ganal MW, Roder MS (1995) Detection of genetic diversity in closely related bread wheat using microsatellite markers. Theor Appl Genet 102:689–694

    Google Scholar 

  • Powell W, Marchray GC, Provan J (1996) Polymorphism revealed by simple sequence repeats. Trends Plant Sci 1:215–222

    Google Scholar 

  • Prasad M, Varshney RK, Roy JK, Balyan HS, Gupta PK (2000) The use of microsatellites for detecting DNA polymorphism, genotype identification and genetic diversity in wheat. Theor Appl Genet 100:584–592

    CAS  Google Scholar 

  • Raghuram N, Pathak RR, Sharma P (2006) Signalling and the molecular aspects of N-use efficiency in higher plants. In: Singh RP, Jaiwal PK (eds) Biotechnological approaches to improve nitrogen use efficiency in plants. Studium Press, Houston, pp 19–40

    Google Scholar 

  • Rengel Z, Graham RD (1995) Wheat genotypes differ in zinc efficiency when grown in the chelate-buffered nutrient solution. Plant Soil 176:307–316

    Article  Google Scholar 

  • Röder MS, Korzun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal MW (1998) A microsatellite map of wheat. Genetics 149:2007–2023

    PubMed  Google Scholar 

  • Röder MS, Plaschke J, König SU, Börner A, Sorells ME, Tanksley SD, Ganal MW (1995) Abundance, variability and chromosomal location of microsatellites in wheat. Mol Gen Genet 246:327–333

    Article  PubMed  Google Scholar 

  • Rohlf FJ (1992) NTSYSpc: numerical taxonomy and multivariate system, version 2.02e. Exeter Software, New York

    Google Scholar 

  • Roldán-Ruiz I, Van Eeuwijk FA, Gilliland TJ, Dubreuil P, Dillmann J, Lalemand M, De Loose M, Baril CP (2001) A comparative study of molecular and morphological methods of describing relationships between perennial ryegrass (Lolium perenne L.) varieties. Theor Appl Genet 103:1138–1150

    Article  Google Scholar 

  • Russel J, Fuller J, Young G, Thomas B, Taramino G, Macaulay M, Waugh R, Powell W (1997) Discriminating between barley genotypes using microsatellite markers. Genome 40:442–450

    Article  Google Scholar 

  • Saghai-Maroof MA, Biyaschev RM, Yang GP, Zhang Q, Allard RW (1984) Extaordinary polymorphism microsatellite DNA in barley: species diversity, chromosomal location and population dynamics. Proc Natl Acad Sci USA 91:5466–5470

    Article  Google Scholar 

  • Salem KFM, El-Zanaty AM, Esmail RM (2008) Assessing wheat (Triticum aestivum L.) genetic diversity using morphological characters and microsatellite markers. World J Agril Sci 4:538–544

    Google Scholar 

  • Song MT, Lee JH, Cho YS, Jeon YH, Lee SB, Ku JH, Choi SH, Hwang HG (2002) Narrow genetic background of Korean rice germplasm as revealed by DNA fingerprinting with SSR markers and their pedigree information. Korean Journal of Genetics 24:397–403

    CAS  Google Scholar 

  • Tsegave S, Tesemma T, Belay G (1996) Relationships among tetraploid wheat (Triticum turgidum L.) landraces population revealed by isozyme markers and agronomic traits. Theor Appl Genet 93:600–605

    Article  Google Scholar 

  • UNEP (1999) Global environment outlook 2000. United Nations Environment Programme, Nairobi

    Google Scholar 

  • Yap IP, Nelson R (1995) Win Boot: A programm for performing boot strap analysis of binary data to determine the confidence limits of UPGMA-based dendrograms. IPRI Discussion Paper series

  • Zhu ZL, Chen DL (2002) Nitrogen fertilizer use in China contributions to food production, impacts on the environment and best management strategies. Nutr Cycl Agroecosyst 63:117–127

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We are thankful to the Director of the Indian Agricultural Research Institute, Pusa, New Delhi for providing the seed material; to Drs. M. Röder and M. Ganal, IPK, Gatersleben, Germany for providing DNA aliquots of some of the unpublished SSR primers and Dr. Pankaj Kaushal for helpful discussions. Grateful thanks are also due to the Director of the National Institute of Plant Genome Research, and Head, Department of Botany, Jamia Hamdard, New Delhi, India for providing facilities. We also gratefully acknowledge the financial support from the Department of Biotechnology, Department of Science and Technology, and University Grants Commission, Government of India for carrying out the present study. We would like to thank the reviewers for their critical comments.

Conflicts of interest statement

The authors declare that they have no conflicts of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Manoj Prasad.

Additional information

Ruby Chandna and Sarika Gupta contributed equally to this paper.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Table ESM 1

Identification of 16 wheat cultivars using seven microsatellite markers. (DOC 187 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chandna, R., Gupta, S., Ahmad, A. et al. Variability in Indian bread wheat (Triticum aestivum L.) varieties differing in nitrogen efficiency as assessed by microsatellite markers. Protoplasma 242, 55–67 (2010). https://doi.org/10.1007/s00709-010-0122-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00709-010-0122-z

Keywords

Navigation