Identification Of Resistant Genes And Pathways Involved In Resistance For Sclerotinia Stem Rot In Brassica Napus

Sclerotinia stem rot(SSR)is a major disease in Brassica napus that causes yield losses of 10-20% and reaching 80% in severely infected fields.SSR not only causes yield reduction but also lower oil content.There is a need to identify resistant genetic sources with functional significance for the breeding of SSR-resistant cultivars.In this study,we have put three forward genetics techniques together on the double haploid(DH)lines developed from a resistant and susceptible parent to identify the genes and pathways involved in resistance.We carried a quantitative trait locus(QTL)analysis using 181 DH lines and identified putative candidate genes within QTL regions using comparative transcriptomic of two extreme resistant and susceptible DH lines.We also studied metabolomics profiling from the same samples for RNA sequencing(RNA-seq).Integrated studies of the differential expression of all the genes and metabolites from the resistant and susceptible lines thus identified some pathways involved in SSR resistance.We identified 17 QTL regions involved in SSR resistance in three different seasons using single nucleotide polymorphism(SNP)markers and disease lesion development after artificial inoculation.There were no common QTLs in all three years,but there were three QTLs that appeared in two seasons covering all seasons with a shared QTL.The QTLs identified in the two years were SRA9 a,SRC2a and SRC3 a with phenotypic effect variances of 14.75% and 11.57% for SRA9 a,7.49% and 10.38% for SRC3 a and 7.73% and 6.81% for SRC2 a in their two years,respectively.The flowering time was also found to have a negative correlation with disease resistance,i.e.,early-maturing lines were more susceptible to disease.The stem width has shown a notably weak effect on disease development.Given that flowering time is an important factor in disease resistance,we used comparative RNA-seq analysis of resistant(R)and susceptible(S)lines with consistent performance in three years with almost the same flowering time to identify the resistance genes directly involved in resistance within the QTL regions.Overall,there were more genes differentially expressed in R line(19,970)than in S line(3936)compared to their mock-inoculated lines,demonstrating their tendency to cope with disease.We identified 36 putative candidate genes from our QTL regions that were upregulated in R line compared to resistant mock(R-mock)and S line that might be involved in resistance to SSR.We also studied all differentially expressed genes(DEGs)at three time points in R line compared to R-mock and S lines and look for the genes related to biotic stress and pathways that might cause resistance.A total of 11,917 DEGs were there in the R vs Rmock comparison,6682 DEGs in the R vs S comparison,and 8053 genes were expressed mutually in both comparisons at all time points.We looked for the DEGs and KEGG annotated pathways,which were enriched significantly at different time points in RNAseq analysis.Biosynthesis of amino acids and phenylpropanoid biosynthesis along with others were enriched significantly in R line compare to R-mock and S line at different time points.Maximum number of the significantly enriched pathways were there at 96 hours post inoculation(hpi)in R line.Using the same samples used for RNA seq,we also identified 447 metabolites from our samples and looked for the differentially expressed metabolites(DEMs)at each time point in same comparisons as RNA seq.There were more DEMs in R line compared to S line(107)than in R line compared to R-mock(56).Most of the metabolites differentially expressed were flavonoids,phenolic compounds and amino acids.KEGG annotation identified metabolites and pathways that were enriched significantly in R line.The phenylpropanoid biosynthesis at 24 hpi and biosynthesis of amino acids at 48 hpi were enriched significantly in R line compared to R-mock and S line.Biosynthesis of secondary metabolites and Arginine biosynthesis were significantly enriched in R line compared to S line at all-time points.Overlapping the results from overall RNA seq and metabolites profiling we identified the role of biosynthesis of amino acids and phenylpropanoid biosynthesis in resistance trait.Additionally,we identified the role of arginine biosynthesis in R line compared to S line in both transcriptomic and metabolomics data.The arginine biosynthesis was significantly enriched in R line compared to S line at all time points in metabolomics data and was also enriched in R line compared to S line at all time points in transcriptomic data.This differential expression of arginine biosynthesis at all time points emphasis its role for resistance in R line.However,the role of biosynthesis of amino acids and phenylpropanoid biosynthesis was obvious in our study as we also identified the genes related to these pathways from our QTL regions.