FINDINGS: We optimized the assembly of a Hevea bark transcriptome based on 16 Gb Illumina PE RNA-Seq reads using the Oases assembler across a range of k-mer sizes. We then assessed assembly quality based on transcript N50 length and transcript mapping statistics in relation to (a) known Hevea cDNAs with complete open reading frames, (b) a set of core eukaryotic genes and (c) Hevea genome scaffolds. This was followed by a systematic transcript mapping process where sub-assemblies from a series of incremental amounts of bark transcripts were aligned to transcripts from the entire bark transcriptome assembly. The exercise served to relate read amounts to the degree of transcript mapping level, the latter being an indicator of the coverage of gene transcripts expressed in the sample. As read amounts or datasize increased toward 16 Gb, the number of transcripts mapped to the entire bark assembly approached saturation. A colour matrix was subsequently generated to illustrate sequencing depth requirement in relation to the degree of coverage of total sample transcripts.
CONCLUSIONS: We devised a procedure, the "transcript mapping saturation test", to estimate the amount of RNA-Seq reads needed for deep coverage of transcriptomes. For Hevea de novo assembly, we propose generating between 5-8 Gb reads, whereby around 90% transcript coverage could be achieved with optimized k-mers and transcript N50 length. The principle behind this methodology may also be applied to other non-model plants, or with reads from other second generation sequencing platforms.
OBJECTIVES: The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene.
METHODS: The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of the pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. Highthroughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development.
RESULTS: In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene- driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from the most to the least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins.
CONCLUSION: The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines.