Comparative transcriptome analysis of Powdery mildew Resistance between two Melon (Cucumis melo L) with Different Thickness Peel

Melon (Cucumis melo L.) is wildly planted in the world and China is a major producer of muskmelon. Powdery mildew is one of the most common fungal diseases in the world and this disease frequently affects melon (Cucumis melo L.) and due to the reduction of melon yield. In this study, one material GanTianmi with thin peel and another material XueLianHua with thick peel were selected. After inoculating the powdery mildew, both materials were used to do the RNA-Seq. In total two RNA-seq libraries were constructed and sequenced separately. The reads per kilobase per Million mapped reads (RPKM) values of all the genes in the two materials were calculated and there were 13828 genes were expressed in the material G and 13944 genes were expressed in the material S (RPKM>1). The differentially expression gene (DEG) analysis result suggested that total 769 the DEGs between the two materials were identified. All the DEGs were annotated with several database and the transcript factors (TFs) that related to disease resistance such as MYB, ERF and WRKY among the DEGs were also identified. This research could not only provide the information about understanding the mechanism of powdery mildew infection but also help researchers breed the varieties with powdery mildew resistance.


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affects melon (Cucumis melo L.) and due to the reduction of melon yield. In this study, one material 1 1 GanTianmi with thin peel and another material XueLianHua with thick peel were selected. After 1 2 inoculating the powdery mildew, both materials were used to do the RNA-Seq. In total two RNA-seq 1 3 libraries were constructed and sequenced separately. The reads per kilobase per Million mapped reads 1 4 (RPKM) values of all the genes in the two materials were calculated and there were 13828 genes were 1 5 expressed in the material G and 13944 genes were expressed in the material S (RPKM>1). The 1 6 1 0 0 less than 0.05 and the log2 (Fold_change) (log2 (FC)) more than one or less than -1 could be 1 0 1 considered as DEGs. The genes that with log2 (FC) more than one were up-regulated genes while ones 1 0 2 with log2 (FC) less than negative one were down-regulated genes.

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Different expressed genes annotation and transcription factor analysis 1 0 4 The GO annotation information of the candidate genes was got from the GO databases 1 0 5  (Table S1).

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In the alignment analysis, the proportion of clean data was mapped to the genome of Cucumis melo. Cucumis melo and 80435970 of them could be mapped to genes (99.59% in exon) (Table S2).

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The expression level of the genes 1 2 8 From the RNA sequencing, all the expression levels of the genes in the Cucumis melo genome were 1 2 9 calculated. For the materials G, total 7222 genes were not expressed as the RPKM of these genes were 1 3 0 zero; total 6377 genes were low expressed as the RPKM of these genes were between zero and one; 1 3 1 total 8944 genes were medium expressed as the RPKM of these genes were between one and ten; total 1 3 2 4884 genes were high expressed as the RPKM of these genes were more than 10; For the materials H, 1 3 3 total 7275 genes were not expressed; total 6237 genes were low expressed; total 9103 genes were 1 3 4 medium expressed a; total 4841 genes were high expressed (Table S3, Table 1, Figure 1).

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For the no expressed genes there were 6549 genes (82.7%) that could be detected in both materials, 673  Figure 1).

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The different expression genes 1 4 4 To find out the different expression genes between the two materials G and H, the software 1 4 5 Deseq2 were used and the genes with the absolute value of log2FC more than one and Q_value 1 4 6 less than 0.05 could be considered as different expression genes. In this research, there were 769 1 4 7 different expression genes. Among them, 726 were up-regulation genes and the other 43 were 1 4 8 down-regulation genes (Table S4, Figure 2). 1 4 9 The annotation with different expression gene 1 5 0 All the different expression genes were annotated with GO, KEEG and KOG. For the GO 1 5 1 annotation, all the DEGs could be annotated into 968 GO terms as one DEG maybe annotated into 1 5 2 more than one GO term. Among the 968 GO terms, 326 belonged to the category of molecular 1 5 3 function; 146 belonged to the category of cellular component and 496 belonged to the category of 1 5 4 biological process. The GO term nucleus harbored the most number of DEGs (143), and followed 1 5 5 with the GO term molecular function, biological process and cytoplasm, harbored 125 116 and 1 5 6 114 DEGs respectively (Table S5, Figure 2). For the KEGG analysis, all the DEGs were annotated 1 5 7 into 76 KEGG pathways. Among them, "Metabolic pathways", "Biosynthesis of secondary 1 5 8 metabolite" and "Ribosome" harbored the most DEGs (76, 53 and 14) respectively (Table S6, 1 5 9 Figure 2); For the KOG analysis, all the DEGs were located into 21 KOG baskets. Among them, 1 6 0 the basket "Signal transduction mechanisms", "Lipid transport and metabolism" and "Energy 1 6 1 In our research, these DEGs were related to disease resistance and could be considered as 2 0 4 candidate genes. But whether these DEGs could make some contributions to increase the disease 2 0 5   Table S5. The detail GO annotation information of DESs between the materials G and H 3 1 5 Table S6. The detail KEGG annotation information of DESs between the materials G and H 3 1 6 Table S7. The detail KOG annotation information of DESs between the materials G and H 3 1 7