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Articles

Mapping additive and epistatic QTLs for forage quality and yield in soybean [Glycine max (L.) Merri.] in two environments

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Pages 839-852 | Received 03 Feb 2021, Accepted 15 May 2021, Published online: 19 Aug 2021
 

Abstract

Soybean plants have high protein content and can be used as a supplementary source of high-protein feed. To map quantitative trait loci (QTL) for the content of crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and dry weight of plant (DWP) in R2 stage of soybean, two recombinant inbred lines, RIL3613 and RIL6013, containing 134 and 156 RILs, derived from the cross of Dongnong L13 × Heihe 36 and Dongnong L13 × Henong 60, were planted for two consecutive years. Based on a simple sequence repeat (SSR) linkage map, QTLs of CP, NDF, ADF and DWP were mapped by interval mapping (IM) and inclusive composite interval mapping method (ICIM) using additive effect, epistatic effect and environmental interaction model. The variance components of genotype, environment and genotype × environment (G × E) interaction for quality and yield traits in the two RIL populations were significant under multiple environmental conditions. Eighteen additive effect QTLs on 10 of 20 soybean chromosomes explained 7.02%–15.67% and 2.13%–11.42% of the phenotypic variation in RIL3613 and RIL6013, respectively. Three epistatic QTL pairs related to CP and six ones for DWP were identified. Eight additive effect QTLs for CP, eight ones for NDF, three ones for ADF, and another three ones for DWP were identified by genotype × environment interaction analysis. One epistatic QTL for CP, 11 epistatic QTL pairs for ADF and 38 ones for NDF were identified. These results can provide better understanding of the genetic basis of soybean feed quality and yield.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

The data that support the findings reported in this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This research was financially supported by Hundredthousand and Million Project of Heilongjiang Province for Engineering and Technology Science (2019ZX16B01) to Hailong Ning.