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Theoretical and Applied Genetics

, Volume 128, Issue 5, pp 839–850 | Cite as

QTL for seed protein and amino acids in the Benning × Danbaekkong soybean population

  • C. V. Warrington
  • H. Abdel-Haleem
  • D. L. Hyten
  • P. B. Cregan
  • J. H. Orf
  • A. S. Killam
  • N. Bajjalieh
  • Z. Li
  • H. R. Boerma
Original Paper

Abstract

Key message

We identified QTL associated with protein and amino acids in a soybean mapping population that was grown in five environments. These QTL could be used in MAS to improve these traits.

Abstract

Soybean, rather than nitrogen-containing forages, is the primary source of quality protein in feed formulations for domestic swine, poultry, and dairy industries. As a sole dietary source of protein, soybean is deficient in the amino acids lysine (Lys), threonine (Thr), methionine (Met), and cysteine (Cys). Increasing these amino acids would benefit the feed industry. The objective of the present study was to identify quantitative trait loci (QTL) associated with crude protein (cp) and amino acids in the ‘Benning’ × ‘Danbaekkong’ population. The population was grown in five southern USA environments. Amino acid concentrations as a fraction of cp (Lys/cp, Thr/cp, Met/cp, Cys/cp, and Met + Cys/cp) were determined by near-infrared reflectance spectroscopy. Four QTL associated with the variation in crude protein were detected on chromosomes (Chr) 14, 15, 17, and 20, of which, a QTL on Chr 20 explained 55 % of the phenotypic variation. In the same chromosomal region, QTL for Lys/cp, Thr/cp, Met/cp, Cys/cp and Met + Cys/cp were detected. At these QTL, the Danbaekkong allele resulted in reduced levels of these amino acids and increased protein concentration. Two additional QTL for Lys/cp were detected on Chr 08 and 20, and three QTL for Thr/cp on Chr 01, 09, and 17. Three QTL were identified on Chr 06, 09 and 10 for Met/cp, and one QTL was found for Cys/cp on Chr 10. The study provides information concerning the relationship between crude protein and levels of essential amino acids and may allow for the improvement of these traits in soybean using marker-assisted selection.

Keywords

Quantitative Trait Locus Crude Protein Single Nucleotide Polymorphism Quantitative Trait Locus Analysis Segregation Distortion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This research was supported by funds allocated to the Georgia Agricultural Experiment Stations and grants from the United Soybean Board.

Conflict of interest

The authors declare that they have no conflicts of interests.

Ethical standards

All experiments described in this manuscript comply with the current laws of the country in which they were performed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • C. V. Warrington
    • 1
    • 6
  • H. Abdel-Haleem
    • 1
    • 2
  • D. L. Hyten
    • 3
    • 7
  • P. B. Cregan
    • 3
  • J. H. Orf
    • 5
  • A. S. Killam
    • 5
  • N. Bajjalieh
    • 4
  • Z. Li
    • 1
  • H. R. Boerma
    • 1
  1. 1.Institute of Plant Breeding, Genetics and GenomicsUniversity of GeorgiaAthensUSA
  2. 2.Arid Land Agricultural Research Center, US Department of AgricultureAgricultural Research ServiceMaricopaUSA
  3. 3.Soybean Genomics and Improvement LaboratoryUS Department of Agriculture, Agricultural Research ServiceBeltsvilleUSA
  4. 4.Integrative Nutrition, Inc.DecaturUSA
  5. 5.Department of Agronomy and Plant GeneticsUniversity of MinnesotaSt. PaulUSA
  6. 6.Schillinger Genetics, Inc.QueenstownUSA
  7. 7.DuPont PioneerJohnstonUSA

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