Theoretical and Applied Genetics

, Volume 128, Issue 9, pp 1813–1825 | Cite as

Fine mapping of qGW1, a major QTL for grain weight in sorghum

  • Lijie Han
  • Jun Chen
  • Emma S. Mace
  • Yishan Liu
  • Mengjiao Zhu
  • Nana Yuyama
  • David R. Jordan
  • Hongwei Cai
Original Paper


Key message

We detected seven QTLs for 100-grain weight in sorghum using an F 2 population, and delimited qGW1 to a 101-kb region on the short arm of chromosome 1, which contained 13 putative genes.


Sorghum is one of the most important cereal crops. Breeding high-yielding sorghum varieties will have a profound impact on global food security. Grain weight is an important component of grain yield. It is a quantitative trait controlled by multiple quantitative trait loci (QTLs); however, the genetic basis of grain weight in sorghum is not well understood. In the present study, using an F2 population derived from a cross between the grain sorghum variety SA2313 (Sorghum bicolor) and the Sudan-grass variety Hiro-1 (S. bicolor), we detected seven QTLs for 100-grain weight. One of them, qGW1, was detected consistently over 2 years and contributed between 20 and 40 % of the phenotypic variation across multiple genetic backgrounds. Using extreme recombinants from a fine-mapping F3 population, we delimited qGW1 to a 101-kb region on the short arm of chromosome 1, containing 13 predicted gene models, one of which was found to be under purifying selection during domestication. However, none of the grain size candidate genes shared sequence similarity with previously cloned grain weight-related genes from rice. This study will facilitate isolation of the gene underlying qGW1 and advance our understanding of the regulatory mechanisms of grain weight. SSR markers linked to the qGW1 locus can be used for improving sorghum grain yield through marker-assisted selection.


Phenotypic Variation Sorghum Simple Sequence Repeat Marker Cetyl Trimethyl Ammonium Bromide Sorghum Genome 
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.


Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

122_2015_2549_MOESM1_ESM.docx (13 kb)
Supplementary material 1 (DOCX 13 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Lijie Han
    • 1
    • 2
  • Jun Chen
    • 1
    • 2
  • Emma S. Mace
    • 3
  • Yishan Liu
    • 1
    • 2
  • Mengjiao Zhu
    • 1
    • 2
  • Nana Yuyama
    • 4
  • David R. Jordan
    • 5
  • Hongwei Cai
    • 1
    • 2
    • 4
  1. 1.Department of Plant Genetics and Breeding, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
  2. 2.Beijing Key Laboratory of Crop Genetic Improvement and Genome, Ministry of AgricultureBeijingChina
  3. 3.Department of Agriculture and Fisheries (DAF)WarwickAustralia
  4. 4.Forage Crop Research InstituteJapan Grassland Agricultural and Forage Seed AssociationNasushiobaraJapan
  5. 5.Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandWarwickAustralia

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