Dataset Information

Identification of candidate genes related to astringency in cucumber via RNA-seq based transcriptome profiling

ABSTRACT: Cucumber (Cucumis sativus L.) is one of the most important fruit vegetable crops and is widely grown worldwide (FAO STAT 2016, http://faostat3.fao.org). Astringency greatly affects the flavor quality of cucumber fruits and can be irritating due to the unpleasant oral sensation it causes. However, there are no available report addressing the molecular mechanisms driving the development of cucumber fruit astringency at the transcriptome level. A few relatively basic research efforts have been carried out in our previous studies. In this study, genome-wide analysis of gene expression in the highly astringent cucumber inbred line ‘YB’ was performed using RNA-seq. The aims of this research were to identify the genes responsible for fruit astringency development and to provide new insights into the mechanism underlying the synthesis of astringent compounds in cucumber fruits.

ORGANISM(S): Cucumis sativus

PROVIDER: GSE112666 | GEO | 2018/12/01

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Purpose: Cucumber (Cucumis sativus L.) is an economically important vegetable crop worldwide, and cucumber fruit spine density has an important impact on the commercial value. However, little is known about the regulatory mechanism for the fruit spine formation.In this study, the transcriptome analyses of ovaries and pericarps from numerous-spine parent and few-spine parent were conducted to identify the gene regulatory networks involved in the formation and development of numerous fruit spines in cucumber. Methods: Cucumber mRNA profiles of ovaries and pericarps from numerous-spine parent and few-spine parent were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. Then, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly-N sequences and low-quality reads from the raw data. Simultaneously, the Q20, Q30 and GC contents of the clean data were calculated. All of the downstream analyses were based on the high-quality clean data. Clean paired-end reads were mapped to the reference genome using TopHat v2.0.12 (Trapnell et al. 2012). Then, the FPKM (fragments per kilobase of transcript sequence per million base pairs sequenced) value of each gene was calculated to estimate gene expression levels (Trapnell et al. 2010). Genes with an adjusted P-value < 0.05 identified by DESeq were assigned as differentially expressed genes(DEGs). Results: We generated 42.96-57.53 million raw reads from each library, and 39.85-54.02 million clean reads were obtained after the removal of low-quality reads and adapter sequences. Among the clean reads, 79.03-80.94% were mapped to the gene database . Based on the KEGG database, pathway enrichment analysis was performed to identify significantly enriched metabolic pathways or signal transduction pathways in DEGs. Plant hormone signal transduction was significantly enriched in up-regulated genes in both F_6DBF compared with M_6DBF and F_0DAA compared with M_0DAA. Conclusions: Based on the transcriptome analysis, we excavated possible biological regulatory networks involved in the formation and development of numerous fruit spines in cucumber. This work will promote the exploration of molecular mechanisms that regulate cucumber fruit spine density.

Dataset Information

Identification of candidate genes related to astringency in cucumber via RNA-seq based transcriptome profiling

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure