Identification of QTL, QTL-by-environment interactions, and their candidate genes for resistance HG Type 0 and HG Type 1.2.3.5.7 in soybean using 3VmrMLM

Front Plant Sci. 2023 Apr 21:14:1177345. doi: 10.3389/fpls.2023.1177345. eCollection 2023.

Abstract

Introduction: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is an important disease affecting soybean yield in the world. Potential SCN-related QTLs and QTL-by-environment interactions (QEIs) have been used in SCN-resistant breeding.

Methods: In this study, a compressed variance component mixed model, 3VmrMLM, in genome-wide association studies was used to detect QTLs and QEIs for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7 in 156 different soybean cultivars materials.

Results and discussion: The results showed that 53 QTLs were detected in single environment analysis; 36 QTLs and 9 QEIs were detected in multi-environment analysis. Based on the statistical screening of the obtained QTLs, we obtained 10 novel QTLs and one QEI which were different from the previous studies. Based on previous studies, we identified 101 known genes around the significant/suggested QTLs and QEIs. Furthermore, used the transcriptome data of SCN-resistant (Dongnong L-10) and SCN-susceptible (Suinong 14) cultivars, 10 candidate genes related to SCN resistance were identified and verified by Quantitative real time polymerase chain reaction (qRT-PCR) analysis. Haplotype difference analysis showed that Glyma.03G005600 was associated with SCN HG Type 0 and HG Type 1.2.3.5.7 resistance and had a haplotype beneficial to multi-SCN-race resistance. These results provide a new idea for accelerating SCN disease resistance breeding.

Keywords: 3VmrMLM; GWAS; QTL; candidate genes; soybean cyst nematode.

Grants and funding

This study was conducted in the Key Laboratory of Soybean Biology of the Chinese Education Ministry, Soybean Research and Development Center (CARS), and the Key Laboratory of Northeastern Soybean Biology and Breeding/Genetics of the Chinese Agriculture Ministry and was financially supported by the Natural Science Foundation of Heilongjiang Province (JD22A015, ZD2022C002), National Key Research and Development Project (2021YFD1201604, 2021YFF1001204), the Chinese National Natural Science Foundation (31971967, U22A20473), the Youth Leading Talent Project of the Ministry of Science and Technology in China (2015RA228), The National Ten-thousand Talents Program, Postdoctoral Fund in Heilongjiang Province (LBH-Q20004), The national project (CARS-04-PS06).