, 214:75 | Cite as

Identification of QTLs for agronomic traits using association mapping in lentil

  • Jitendra Kumar
  • Sunanda Gupta
  • Debjyoti Sen Gupta
  • Narendra Pratap Singh


A diverse panel of 96 genotypes of lentil was used in this study to identify QTL for nine agronomic traits through marker-trait association analysis. This study showed significant genetic variability among the lentil genotypes for nine agronomic traits and had medium to large broad sense heritability estimates (h2 = 0.58–0.95). Screening of 534 SSR markers resulted in 266 polymorphic loci that generated 697 alleles ranging from 2 to 16 alleles per locus across the genotypes. The model-based population structure analysis identified two distinct subpopulations among lentil genotypes and each subpopulation did not show any admixture. Marker trait association (MTA) analysis following ML model resulted in the identification of 24 MTAs for nine traits at P < 0.01. The per cent of phenotypic variation explained by each associated marker with particular agronomic trait ranged from 7.3 to 25.8%. The highest proportion of total phenotypic variation (23.1–25.8%) was explained by the QTLs controlling the primary branches/per plant. In the present study, few EST-SSR markers showed significant association with days to maturity, pods/plant, secondary branches/plant, 100 seed weight, yield/plant and reproductive duration and explained large phenotypic variation (7.3–23.8%). Hence, these markers can be used as functional markers in lentil breeding program for developing improved cultivars.


Lentil Agronomic traits Population structure Association mapping QTL Functional markers 



Authors thanks to Indian Council of Agricultural Research, New Delhi for research support. This work is partially funded by Department of Agriculture Corporation and Framers Welfare (DAC & FW), Government of India, New Delhi and Department of Biotechnology (BT/PR10921/AG11/106/943/2014), Govt. of India.

Author contributions

The experimental work was done by Sunanda Gupta. The data analysis and manuscript was written by Jitendra Kumar, Debjyoti Sen Gupta and Narendra Pratap Singh helped to revise the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Jitendra Kumar
    • 1
  • Sunanda Gupta
    • 1
  • Debjyoti Sen Gupta
    • 1
  • Narendra Pratap Singh
    • 2
  1. 1.Division of Crop ImprovementICAR-Indian Institute of Pulses ResearchKanpurIndia
  2. 2.Division of BiotechnologyICAR-Indian Institute of Pulses ResearchKanpurIndia

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