RESULTS: The present report is a continuing study from our previous published transcriptomic profiling of oil palm seedlings against G. boninense. We focused on identifying differentially expressed genes (DEGs) encoding transcription factors (TFs) from the same RNA-seq data; resulting in 106 upregulated and 108 downregulated TFs being identified. The DEGs are involved in four established defense-related pathways responsible for cell wall modification, reactive oxygen species (ROS)-mediated signaling, programmed cell death (PCD) and plant innate immunity. We discovered upregulation of JUNGBRUNNEN 1 (EgJUB1) during the fungal biotrophic phase while Ethylene Responsive Factor 113 (EgERF113) demonstrated prominent upregulation when the palm switches to defense against necrotrophic phase. EgJUB1 was shown to have a binding activity to a 19 bp palindromic SNBE1 element, WNNYBTNNNNNNNAMGNHW found in the promoter region of co-expressing EgHSFC-2b. Further in silico analysis of promoter regions revealed co-expression of EgJUB1 with TFs containing SNBE1 element with single nucleotide change at either the 5th or 18th position. Meanwhile, EgERF113 binds to both GCC and DRE/CRT elements promoting plasticity in upregulating the downstream defense-related genes. Both TFs were proven to be nuclear-localized based on subcellular localization experiment using onion epidermal cells.
CONCLUSION: Our findings demonstrated unprecedented transcriptional reprogramming of specific TFs potentially to enable regulation of a specific set of genes during different infection phases of this hemibiotrophic fungal pathogen. The results propose the intricacy of oil palm defense response in orchestrating EgJUB1 during biotrophic and EgERF113 during the subsequent transition to the necrotrophic phase. Binding of EgJUB1 to SNBE motif instead of NACBS while EgERF113 to GCC-box and DRE/CRT motifs is unconventional and not normally associated with pathogen infection. Identification of these phase-specific oil palm TFs is important in designing strategies to tackle or attenuate the progress of infection.
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.