甘蓝型油菜菌核病抗性基因和调控途径鉴定

发布时间：2023-06-01 04:24

　　菌核病(SSR)是甘蓝型油菜的主要病害之一,可造成10-20%的产量损失,在侵染严重的田间甚至达到80%。SSR不仅会导致产量下降,而且引起含油量降低。因此,鉴定抗菌核病的遗传资源对培育抗性品种具有重要意义。在本研究中,我们结合三种技术对由抗病亲本和感病亲本构建的双单倍体(DH)系,进行了抗病基因和相关调控途径的鉴定。我们对181个DH株系进行了数量性状位点(QTL)分析,并在QTL区域内对2个极端抗病和感病的DH系进行了比较转录组和代谢组学分析。综合分析抗病系和感病系的所有差异基因和差异代谢物的表达情况,从中鉴定到了一些参与SSR抗病的相关基因和调控途径。利用单核苷酸多态性(SNP)标记和接种后的表型,我们在三个不同年份鉴定到了17个参与SSR抗性的QTL。没有检测到3年共同的QTL,但发现3个QTL能够在两年里检测到,分别为SRA9a、SRC2a和SRC3a,它们可解释两年内的表型变异分别为14.75%和11.57%,7.49%和10.38%,和7.73%和6.81%。开花时间与抗病性呈负相关,即早开花的材料更加容易感病。茎秆宽度对抗病性只有微弱的影响。考虑到开花期对抗病性状的影响...

【文章页数】：178 页

【学位级别】：博士

【文章目录】：
ABSTRACT
摘要
List of Abbreviations
1.REVIEW OF LITERATURE
    1.1 General Introduction
    1.2 Factors hindering the potential production of B.napus
    1.3 Diseases of B.napus
    1.4 Sclerotinia sclerotiorum impact on B.napus
    1.5 Control of S.sclerotiorum in B.napus
        1.5.1 Chemical control
        1.5.2 Biological control
        1.5.3 Cultural control
        1.5.4 Genetic control
    1.6 Impact of flowering time on SSR resistance in B.napus
    1.7 Aims and objectives
2.MATERIALS AND METHODS
    2.1 Plant material
    2.2 Phenotyping measurements and statistical analysis
    2.3 SNP array genotyping
    2.4 Linkage mapping and QTL map construction
    2.5 Sampling for RNA-seq analysis and metabolites profiling
    2.6 RNA quantification and qualification,cDNA library construction and sequencing
    2.7 Quality control and reads mapping to the reference genome
    2.8 Differential gene expression quantification
    2.9 qRT-PCR analysis for the validation of RNA-seq data
    2.10 Map Man analysis for biotic stress genes
    2.11 GO and KEGG enrichment analysis of differentially expressed genes
    2.12 Metabolites Extraction
    2.13 UHPLC-MS/MS Analysis
    2.14 Database search for metabolites
    2.15 Data Analysis of metabolites
3.RESULTS
    3.1 Phenotyping SSR resistance in the DH population
        3.1.1 Correlation among stem width and lesion length
        3.1.2 Correlation between flowering time and disease resistance
    3.2 QTL mapping
    3.3 Integration of QTLs for SSR resistance
    3.4 Phenotype of the lines used for RNA-seq and metabolomics profiling
    3.5 RNA sequencing and differential gene expression
    3.6 Identification of putative candidate genes within QTL regions
    3.7 DEGs related to biotic stress in RNA-seq analysis
    3.8 GO enrichment analysis of DEGs from RNA-seq data
    3.9 KEGG enrichment analysis of DEGs from RNA-seq data
    3.10 Metabolites profiling
    3.11 KEGG enrichment analysis of DEMs from metabolites profiling
    3.12 Overlapping Pathways from transcriptomic and metabolomics studies
4.DISCUSSION
    4.1 Avoiding the role of flowering in identification of resistant genes and pathways
    4.2 Classification and functions of identified genes within QTL regions
    4.3 Important pathways involved in resistance
        4.3.1 The role of phenylpropanid biosynthesis pathway
        4.3.2 The role of biosynthesis of amino acids
        4.3.3 The role of arginine biosynthesis
    4.4 Validation of genes and pathways involved in resistance
5.SUMMARY
    5.1 Future Directions
    5.2 Innovations
    5.3 Future Directions
REFERENCES
APPENDICES
    Appendix A.List of Primers Used in this Study
    Appendix B.GO Categories in different comparisons
        Appendix B-1.List of Significantly Enriched GO categories in R24 vs R-mock
        Appendix B-2.List of Significantly Enriched GO categories in R24 vs S24
        Appendix B-3.List of Significantly Enriched GO categories in R48 vs R-mock
        Appendix B-4.List of Significantly Enriched GO categories in R96 vs R-mock
        Appendix B-5.List of Significantly Enriched GO categories in R96 vs S96
    Appendix C.Enriched KEGG pathways in RNA-sequencing
        Appendix C-1.Enriched KEGG pathways in R24 vs R-mock
        Appendix C-2.Enriched KEGG pathways in R24 vs S24
        Appendix C-3.Enriched KEGG pathways in R48 vs R-mock
        Appendix C-4.Enriched KEGG pathways in R48 vs S48
        Appendix C-5.Enriched KEGG pathways in R96 vs R-mock
        Appendix C-6.Enriched KEGG pathways in R96 vs S96
        Appendix C-7.Enriched KEGG pathways in S24 vs S-mock
        Appendix C-8.Enriched KEGG pathways in S48 vs S-mock
        Appendix C-9.Enriched KEGG pathways in S96 vs S-mock
    Appendix D.Significantly Enriched KEGG pathways in Metabolomics profiling
    Appendix E.DEGS for the identified KEGG pathways
        Appendix E-1.DEGs in different comparisons for phenylpropanoid biosynthesis pathway
        Appendix E-2.DEGs in different comparisons for biosynthesis of amino acids pathway
        Appendix E-3.DEGs in different comparisons for arginine biosynthesis pathway
    Appendix F.List of Publications
ACKNOWLEGEMENTS



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