Theoretical and Applied Genetics

, Volume 131, Issue 3, pp 555–568 | Cite as

Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map

  • Zhandong Cai
  • Yanbo Cheng
  • Zhuwen Ma
  • Xinguo Liu
  • Qibin Ma
  • Qiuju Xia
  • Gengyun Zhang
  • Yinghui Mu
  • Hai Nian
Original Article

Abstract

Key message

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively.

Abstract

Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8–10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171–39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37–59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

Abbreviations

cv.

Cultivar

CIM

Composite interval mapping method

LOD

Log-likelihood

QTL

Quantitative trait loci

RIL

Recombinant inbred line

RAD-seq

Restriction site-associated DNA sequencing

SLAF-seq

Specific length amplified fragment sequencing

SNP

Single nucleotide polymorphism

MAS

Marker-assisted selection

Notes

Acknowledgements

We wish to thank Professor Junming Sun (Chinese Academy of Agricultural Sciences, People’s Republic of China) for kindly supplying the 12 standards of isoflavone components. This work was supported by the National Natural Sciences Foundation of China (31401398); the China Agricultural Research System (CARS-04-PS09); the Project of Molecular Design Breeding for Major Economic Crops (2016yfd0101901) and the Research Project of the State Key Laboratory of Agricultural and Biological Resources Protection and Utilization in Subtropics.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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Supplementary material 1 (XLSX 75 kb)
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Supplementary material 2 (EPS 78861 kb)
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Supplementary material 3 (EPS 78208 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Zhandong Cai
    • 1
    • 2
    • 3
  • Yanbo Cheng
    • 1
    • 2
    • 3
  • Zhuwen Ma
    • 1
    • 2
    • 4
  • Xinguo Liu
    • 1
    • 2
  • Qibin Ma
    • 1
    • 2
    • 3
  • Qiuju Xia
    • 5
  • Gengyun Zhang
    • 5
  • Yinghui Mu
    • 1
    • 2
    • 3
  • Hai Nian
    • 1
    • 2
    • 3
  1. 1.The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresourcesSouth China Agricultural UniversityGuangzhouPeople’s Republic of China
  2. 2.The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of AgricultureSouth China Agricultural UniversityGuangzhouPeople’s Republic of China
  3. 3.Shofine Seed Technology Co., Ltd.JiaxiangPeople’s Republic of China
  4. 4.Guangdong Provincial Key Laboratory of Crops Genetics and Improvement, Crops Research InstituteGuangdong Academy of Agricultural SciencesGuangzhouPeople’s Republic of China
  5. 5.Beijing Genomics Institute (BGI)-ShenzhenShenzhenPeople’s Republic of China

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