Identification and validation of QTLs controlling multiple traits in sorghum
Hai-Lian Wang A , Hua-Wen Zhang A , Rui-Heng Du B , Gui-Ling Chen A , Bin Liu A , Yan-Bing Yang A , Ling Qin A , Er-Ying Cheng A , Qiang Liu C and Yan-An Guan A D
+ Author Affiliations
- Author Affiliations
A Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
B Millet Research Institute, Hebei Academy of Agro-forestry Sciences, Shijiazhuang, 050000, China.
C Maize Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250100, China.
D Corresponding author. Email: yguan65@163.com
Crop and Pasture Science 67(2) 193-203 https://doi.org/10.1071/CP15239
Submitted: 18 July 2015 Accepted: 2 November 2015 Published: 29 February 2016
Abstract
Sweet sorghum (Sorghum bicolor L. Moench) is a promising crop for biofuel and forage production, having strong resilience to multiple stresses and being capable of thriving on marginal land. The main goals in sweet sorghum improvement are to increase biomass and sugar yield. We validated quantitative trait loci (QTLs) controlling plant height, biomass, juice weight and Brix with 181 recombinant inbred lines derived from a cross between Shihong137, a dwarf grain sorghum, and L-Tian, a tall sweet sorghum, under four environments. Seven QTLs for plant height, stem and leaf fresh weight, stem fresh weight and juice weight could be repeatedly identified across four environments. However, three of those major QTLs, qPH7-2, qSLFW9 and qSFW9, had strong epistatic effect. Many QTLs related to biomass production were co-localised with previously known height QTLs, suggesting that plant height is a major trait regulating biomass production. However, qSFW1-2, qSLFW6-1, and qSLFW6-2 were mapped to positions with no known height QTL. We also identified and validated stable qBrix2 across environments. This study provided a genetic basis for integrated approaches, including plant height, to improve sweet sorghum biomass and sugar production.
Additional keywords: Dw, F2 and F2:3 populations, genetic map, marker-assisted selection.
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