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Journal of Genetics

, Volume 93, Issue 3, pp 775–784 | Cite as

Population structure and association mapping studies for important agronomic traits in soybean

  • BHUPENDER KUMAR
  • AKSHAY TALUKDAREmail author
  • INDU BALA
  • KHUSHBU VERMA
  • SANJAY KUMAR LAL
  • RAMESH LAL SAPRA
  • B. NAMITA
  • SUBHASH CHANDER
  • RESHU TIWARI
RESEARCH ARTICLE

Abstract

The present study was carried out with a set of 96 diverse soybean genotypes with the objectives of analysing the population structure and to identify molecular markers associated with important agronomic traits. Large phenotypic variability was observed for the agronomic traits under study indicating suitability of the genotypes for association studies. The maximum values for plant height, pods per plant, seeds per pod, 100-seed weight and seed yield per plant were approximately two and half to three times more than the minimum values for the genotypes. Seed yield per plant was found to be significantly correlated with pods per plant (r = 0.77), 100-seed weight (r = 0.35) and days to maturity (r = 0.23). The population structure studies depicted the presence of seven subpopulations which nearly corresponded with the source of geographical origin of the genotypes. Linkage disequilibrium (LD) between the linked markers decreased with the increased distance, and a substantial drop in LD decay values was observed between 30 and 35 cM. Genomewide marker-traits association analysis carried out using general linear (GLM) and mixed linear models (MLM) identified six genomic regions (two of them were common in both) on chromosomes 6, 7, 8, 13, 15 and 17, which were found to be significantly associated with various important traits viz., plant height, pods per plant, 100-seed weight, plant growth habit, average number of seeds per pod, days to 50% flowering and days to maturity. The phenotypic variation explained by these loci ranged from 6.09 to 13.18% and 4.25 to 9.01% in the GLM and MLM studies, respectively. In conclusion, association mapping (AM) in soybean could be a viable alternative to conventional QTL mapping approach.

Keywords

phenotypic variation agronomic traits population structure linkage disequilibrium general linear model mixed linear model. 

Notes

Acknowledgement

First author sincerely acknowledges PG School, IARI, for providing the fellowship during post-graduate study.

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Copyright information

© Indian Academy of Sciences 2014

Authors and Affiliations

  • BHUPENDER KUMAR
    • 1
  • AKSHAY TALUKDAR
    • 2
    Email author
  • INDU BALA
    • 3
  • KHUSHBU VERMA
    • 2
  • SANJAY KUMAR LAL
    • 2
  • RAMESH LAL SAPRA
    • 2
  • B. NAMITA
    • 2
  • SUBHASH CHANDER
    • 2
  • RESHU TIWARI
    • 2
  1. 1.Cummings’s Laboratory, Directorate of Maize ResearchNew DelhiIndia
  2. 2.Indian Agricultural Research InstituteNew DelhiIndia
  3. 3.Molecular Cytogenetics and Tissue Culture Laboratory, Department of Crop ImprovementCSK Himachal Pradesh Agricultural UniversityPalampurIndia

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