Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE

Identification of quantitative trait loci underlying seed oil content of soybean including main, epistatic and QTL × environment effects in different regions of Northeast China

Weili Teng A C , Binbin Zhang A C , Qi Zhang A , Wen Li A , Depeng Wu A , Hui Yang A , Xue Zhao A , Yingpeng Han A B and Wenbin Li A B
+ Author Affiliations
- Author Affiliations

A Key Laboratory of Soybean Biology in Chinese Ministry of Education (Northeastern Key Laboratory of Soybean Biology and Genetics and Breeding in Chinese Ministry of Agriculture), Northeast Agricultural University, Harbin 150030, China.

B Corresponding authors. Email: hyp234286@aliyun.com, wenbinli@neau.edu.cn

C These authors contributed equally to this work.

Crop and Pasture Science 68(7) 625-631 https://doi.org/10.1071/CP17169
Submitted: 27 April 2017  Accepted: 17 July 2017   Published: 8 September 2017

Abstract

Oil content is a primary trait in soybean and determines the quality of soy food, feed and oil product. Increasing oil content is a major objective of soybean breeding. The aims of the present study were to identify quantitative trait loci (QTLs) and epistatic QTLs associated with oil content in soybean seed by using 129 recombinant inbred lines derived from a cross between cultivar Dongnong 46 (oil content 22.53%) and the semi-wild line L-100 (oil content 17.33%). Phenotypic data were collected from 10 tested environments including Harbin in the years 2012–15, Hulan in 2013–15 and Acheng in 2013–15. A genetic linkage map including 213 simple sequence repeat markers in 18 chromosomes (or linkage groups) was constructed, covering ~3623.39 cM. Seven QTLs, located on five chromosomes (or linkage groups), were identified to be associated with oil content, explaining 2.24–17.54% of the phenotypic variation in multi-environments. Among these identified QTLs, five (qOIL-2, qOIL-4, qOIL-5, qOIL-6 and qOIL-7) were detected in more than five environments. Seven QTLs had additive and/or additive × environment interaction effects. QTLs with higher additive effects were more stable in multi-environments than those with lower additive effects. Moreover, five epistatic, pairwise QTLs were identified in different environments. The findings with respect to genetic architecture for oil content could be valuable for marker-assisted selection in soybean breeding programs for high oil content.

Additional keywords: additive effect, epistatic effect.


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