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Further insight into decreases in seed glucosinolate content based on QTL mapping and RNA-seq in Brassica napus L

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Abstract

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The QTL hotspots determining seed glucosinolate content instead of only four HAG1 loci and elucidation of a potential regulatory model for rapeseed SGC variation.

Abstract

Glucosinolates (GSLs) are amino acid-derived, sulfur-rich secondary metabolites that function as biopesticides and flavor compounds, but the high seed glucosinolate content (SGC) reduces seed quality for rapeseed meal. To dissect the genetic mechanism and further reduce SGC in rapeseed, QTL mapping was performed using an updated high-density genetic map based on a doubled haploid (DH) population derived from two parents that showed significant differences in SGC. In 15 environments, a total of 162 significant QTLs were identified for SGC and then integrated into 59 consensus QTLs, of which 32 were novel QTLs. Four QTL hotspot regions (QTL-HRs) for SGC variation were discovered on chromosomes A09, C02, C07 and C09, including seven major QTLs that have previously been reported and four novel major QTLs in addition to HAG1 loci. SGC was largely determined by superimposition of advantage allele in the four QTL-HRs. Important candidate genes directly related to GSL pathways were identified underlying the four QTL-HRs, including BnaC09.MYB28, BnaA09.APK1, BnaC09.SUR1 and BnaC02.GTR2a. Related differentially expressed candidates identified in the minor but environment stable QTLs indicated that sulfur assimilation plays an important rather than dominant role in SGC variation. A potential regulatory model for rapeseed SGC variation constructed by combining candidate GSL gene identification and differentially expressed gene analysis based on RNA-seq contributed to a better understanding of the GSL accumulation mechanism. This study provides insights to further understand the genetic regulatory mechanism of GSLs, as well as the potential loci and a new route to further diminish the SGC in rapeseed.

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Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was financially supported by National Key R&D Program of China (2016YFD0101300) and National Natural Science Foundation of China (31871656 and 32001583).

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Authors and Affiliations

  1. School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, China

    Hongbo Chao & Jinyong Huang

  2. Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Huaixin Li, Shuxiang Yan, Weiguo Zhao, Kang Chen, Nadia Raboanatahiry & Maoteng Li

  3. Hybrid Rapeseed Research Center of Shaanxi Province, Shaanxi Rapeseed Branch of National Centre for Oil Crops Genetic Improvement, Yangling, 712100, China

    Weiguo Zhao & Hao Wang

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  7. Nadia Raboanatahiry
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  8. Jinyong Huang
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  9. Maoteng Li
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Contributions

HC carried out QTL analysis, transcriptome analysis and wrote the manuscript. HL and SY participated in the field experiment and collected data. WZ and KC performed the data processing, detection and modifying of pictures. HW and NR provided many guidelines for the paper and revised the manuscript. JH and ML designed, led and coordinated the overall study.

Corresponding authors

Correspondence to Jinyong Huang or Maoteng Li.

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The authors declare that they have no conflict of interest.

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The authors declare that the experiments comply with the current laws of the country in which they were performed.

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Communicated by Isobel AP Parkin.

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Supplementary Information

Below is the link to the electronic supplementary material.

122_2022_4161_MOESM1_ESM.tif

Supplementary file1 Fig. S1 Collinearity of the updated high-density genetic map and the previous high-density map Chao et al., (2017) constructed with the ‘Darmor-bzh’ reference genome. Outer and inner circles represent 19 genetic linkage groups of the genetic map and 19 chromosomes of the reference genome. The arrows with same color indicate the inferior collinearity regions in previous high-density map and its corresponding collinearity regions in the current updated high-density map when comparison to the reference genome. (TIF 8383 kb)

122_2022_4161_MOESM2_ESM.jpg

Fig. S2 QTL hotspot identified on chromosome A09 and candidate genes within the QTL hotspot. The identified QTLs for SGC in different environments are shown by curves above the line of the linkage group, and corresponding additive effects are display in curves of the same color below the linkage group. The short-terms localization in the middle represent identified QTL detected at the corresponding position, and subsequently are integrated into consensus QTL showed by brown term with yellow line near the peak, and the name of major QTL are displayed in red fonts. At the bottom, corresponding part of the reference genome ‘Darmor-bzh’ and ‘ZS11’, candidate gene within this region and collinearity are shown.

Fig. S3 The relative expression difference of some candidate genes in leaf and silique.

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Supplementary file4 Fig S4 Statistics of differentially expressed genes between Ken-C8 and N53-2 in leaf and seed. (TIF 107 kb)

Fig. S5 GO enrichment analysis of different expression genes in leaf (A) and seed (B).

Fig. S6 KEGG enrichment of different expression genes in leaf (A) and seed (B).

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Supplementary file7 Fig. S7 The relative expression level of BnaC02. MYB34 and BnaC09. MYB34 (A) and seed indole GSLs content in the two parents (B). I3M: Indol-3-yl-methy-GSL; 4MTI3M: 4-methoxyindol-3-yl-methy-GSL; 1MTI3M: 1- methoxyindol-3-yl-methy-GSL. (TIF 225 kb)

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Fig. S8 Verifying the gene expression difference from RNA-Seq analysis by qRT-PCR. The level of differential expression on the left side was calculated by FPKM value from RNA-Seq, and the right side by qRT-PCR.

Supplementary file9 (XLSX 450 kb)

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Chao, H., Li, H., Yan, S. et al. Further insight into decreases in seed glucosinolate content based on QTL mapping and RNA-seq in Brassica napus L. Theor Appl Genet 135, 2969–2991 (2022). https://doi.org/10.1007/s00122-022-04161-5

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