Cucumber (Cucumis sativus L.) is an economically important vegetable cultivated all over the world. Grafting can produce bloomless or sparse-bloom cucumber, which is welcomed by increasing consumers. Bloom granule is tine glandular hair, which is hard and rare studied on its formation and related genes. Mutifunctional RNA-seq is a recently developed analytical approach for transcriptome profiling via high-throughput sequencing and has been recently applied to a wide variety of organisms, which provide us reliable technical means detect bloom formation and related genes. In this study, we chose a cucumber inbred line (Shannong No.5) and two pumpkin rootstock lines as materials, and constructed four tested cucumbers, grew plants in “Yamazaki cucumber nutrient solution formula” prepared by deionized water, treated plants with or without 1.7mM potassium silicate 2 hours before collecting pericarp. Each treatment were duplicated twice.16 cDNA libraries were constructed from pericarp of a cucumber inbred line (own-rooted cucumber), C/C (self-grafted cucumber), M/C (More bloom, cucumber grafted onto “3225” rootstock) and L/C(Less bloom, cucumber grafted onto “3212” rootstock). We obtained 17,215,769~17,529,047 high quality reads, and 18,804~19,358 genes from each sample. All reads can be mapped to the cucumber genome (Version 2). By RPKM comparing, we got 38 comparing combinations with differentially expressed genes (DEGs), obtained 38 significantly expressed combinations by FDR≤0.001 and the absolute value of log2Ratio≥1 as the thresholds. These results suggest that there are many differences and genes expression mode among effects of grafting or added silicon. This study addresses a preliminary analysis and offers a foundation for future genomic research in the bloom formation of cucumber.
Overall design: Own-rooted cucumber,self-grafted cucumber and cucumber grafted onto two pumpkin rootstock lines, cultivated by deionized water nutrient solution with 1.7mM silicon added or not; RNA-Seq on cucumbers pericarp, analyse the data, and get differencially expressed genes
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