PURPOSE: In this study, we aimed to discover the role of oil palm phenolics (OPP) in influencing the gene expression changes caused by an atherogenic diet in mice.
METHODS: We fed mice with either a low-fat normal diet (14.6 % kcal/kcal fat) with distilled water, or a high-fat atherogenic diet (40.5 % kcal/kcal fat) containing cholesterol. The latter group was given either distilled water or OPP. We harvested major organs such as livers, spleens and hearts for microarray gene expression profiling analysis. We determined how OPP changed the gene expression profiles caused by the atherogenic diet. In addition to gene expression studies, we carried out physiological observations, blood hematology as well as clinical biochemistry, cytokine profiling and antioxidant assays on their blood sera.
RESULTS: Using Illumina microarrays, we found that the atherogenic diet caused oxidative stress, inflammation and increased turnover of metabolites and cells in the liver, spleen and heart. In contrast, OPP showed signs of attenuating these effects. The extract increased unfolded protein response in the liver, attenuated antigen presentation and processing in the spleen and up-regulated antioxidant genes in the heart. Real-time quantitative reverse transcription-polymerase chain reaction validated the microarray gene expression fold changes observed. Serum cytokine profiling showed that OPP attenuated inflammation by modulating the Th1/Th2 axis toward the latter. OPP also increased serum antioxidant activity to normal levels.
CONCLUSION: This study suggests that OPP may possibly attenuate atherosclerosis and other forms of cardiovascular disease.
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.