IC4R005-RNA-Seq-2016-27228336

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Project Title

Phosphorus remobilisation from rice flag leaves during grain filling: an RNA-seq study

The Background of This Project

  • The loading of P into grains is of critical importance for the global P cycle because the accumulation of P in the grains of the major cereals, oilseed and pulse crops globally removes the equivalent of over 50% of the P applied as fertiliser each year. Provided seed germination and seedling vigour can be maintained (see Pariasca-Tanaka et al., 2015 and discussion therein), reducing the amount of P stored in the grains of major crops may be a viable option to reduce the amount of P lost from the P cycle within agricultural production systems
  • In this project, the researchers conducted an RNA-seq analysis of rice flag leaves during the pre-remobilisation phase (6 DAA) and when the leaves were acting as a P source (15 DAA),to test the hypothesis that a subset of genes involved in the P starvation response are involved in remobilisation of P from flag leaves to developing grains.

Plant Culture & Treatment

  • The rice plants were grown under controlled glasshouse conditions at Southern Cross University (Lismore, NSW, Australia) with a mean day/night air temperature of 29°C/21°C and relative humidity (RH) of 75%. Additional N (50 kg ha -1 as urea) was top dressed at tillering stage (60 days after transplanting) to ensure low soil N did not induce premature leaf senescence.
  • Individual panicles in each pot were tagged at anthesis, with anthesis defined as when 50% of florets on a panicle had flowered. This occurred at around 85 days after sowing (DAS). At anthesis, and every 3 DAA until maturity, panicles of the same age (excluding panicles of the main tiller) from three separate pots were harvested and separated into grain, husk, rachis, stem, flag leaf, and other leaves. This occurred until 33 DAA, when plants reached physiological maturity, with no plant sampled more than once.
  • RNA extraction was undertaken on flag leaf tissue samples from two time points selected from the P audit (above). Total RNA was extracted from rice flag leaf tissue using the RNeasy Mini Kit (Qiagen, Victoria, Australia) according to the manufacturer’s instructions.

Illumina Sequencing

  • The TruSeq mRNA stranded kit (Illumina, California, US) was used to prepare Illumina RNA-seq libraries for each sample from 1.3 μg of total RNA.
  • Library sequencing was undertaken with the Illumina Hi-Seq 2500 system (Illumina) at the Biomolecular Facility (BRF) at the John Curtin School for Medical Research (JCSMR), Australian National University (ANU), ACT, Australia.
  • Raw sequencing reads in FASTQ format were first filtered for quality using FASTQC (Andrews, 2010) followed by removal of adapter sequences, poly-N stretches and low quality reads using the BBDuk module of the BBMap software package . All subsequent analyses were based on high quality sequencing reads. Bowtie v2.2.4 was used to index the genome. Retained high quality paired-end reads were mapped against the rice genome IRGSP 1.0 using TopHat.
  • Cufflinks then used the TopHat generated alignment to assemble a set of reference based transcripts. Finally, the CuffDiff module of Cufflinks was used to identify differentially expressed genes between samples and CummeRbund R package was used for subsequent analyses.
Sg4-RNA-Seq-2016-27228336-1.png

Research Findings

  • Three biological replicates for each time point (6 DAA and 15 DAA) were analysed using RNA-seq. These six libraries generated 156 million 101 bp paired-end reads after quality control using FASTQC software; 83 million and 73 million from 6 DAA and 15 DAA, respectively. Reads were filtered for adapter sequences, poly N-stretches and low quality reads which resulted in 78 million (94%) and 70 million (95.6%) high quality reads from 6 DAA and 15 DAA respectively.

Figure 2. GO analysis of unigenes.

  • Using Parametric Analysis of Gene Set Enrichment (PAGE) 1,180 DEGs were mapped to the GO term database resulting in a total of 263 enriched GO terms. Upregulated DEGs within the biological process term were largely associated with P metabolism, protein modification and transport, which was congruent with upregulated DEGs within the molecular function term that were found to be associated with phosphotransferase, kinase or transport activity.
  • Downregulated DEGS within biological processes were associated with transcription and translation, while, congruently, downregulated DEGs under molecular functions were associated with RNA binding and ribosome constitution. Several genes related to photosynthesis and photosystems were downregulated, which was further reflected in a marked downregulation of cellular component genes associated with plastids and organelles.

Labs working on this Project

  • Southern Cross Plant Science, Southern Cross University, PO Box 57 Lismore NSW 2480,Australia
  • Southern Cross GeoScience, Southern Cross University, PO Box 57 Lismore NSW 2480,Australia
  • Instituto de Biotecnología, Universidad Nacional Autónoma de México, Apdo. Postal 510-3,Cuernavaca, Morelos, 62250, Mexico
  • Crop Production and Environment Division, Japan International Research Center for Agriculture Science, 1-1 Ohwashi, Tsukuba, Ibaraki 305-8686, Japan
  • Australian Centre for Plant Functional Genomics (ACPFG), Adelaide, SA 5064, Australi
  • Genotyping Services Laboratory, International Rice Research Institute (IRRI), 7777 Metro Manila, Philippines