IC4R018-RNA-Seq-2015-25447912

Project Title

• RNA-Seq analysis of differentially expressed genes in rice under varied nitrogen supplies

The Background of This Project

• Ammonium (NH4 +) and nitrate (NO3 −) are the two main forms of inorganic nitrogen (N) available for plant growth (Chen et al., 1998). In general, ammonium is the preferred nitrogen source for many plant species over nitrate because of its lower energy demand for metabolism.It's reported that ammonium ion is not only the primary nitrogen nutrient for rice growth and development in paddies of tropical Asia(Yu, 1985) but also the chief limiting factor for rice production.
• The Oryza sativa ammonium transporter,OsAMT1;1, more constitutive expression in shoots and roots, was a prominent member of the OsAMT1 gene family that involved in NH4 + transport in rice plants (Sonoda et al., 2003a). Meanwhile, NH4 + uptake had been reported to be subjected to negative feedback, supposedly from nitrogen metabolites (Lee and Rudge, 1986; Morgan and Jackson,1988; Sonoda et al., 2003b); the early intermediates of nitrogen metabolism such as glutamine might control the expression of ammonium transporter genes in rice and serve as indicators of both the environmental and the cytosolic nitrogen status in rice.
• With the rapid development of bioengineering and molecular biological technologies, transgenic approaches have broadly been applied to enhance nitrogen uptake and assimilation in rice by the overexpression of novel transgenes. Gene expression, the NH4 + permeability as well as the uptake rate in overexpressed OsAMT1;1 lines were much higher than wild type (WT), meanwhile, higher NH4 + contents also promoted higher expression levels of genes in the nitrogen assimilation pathway, resulting in greater nitrogen assimilates, chlorophyll, starch, sugars, and grain yield in transgenic lines than in the WT under both suboptimal and optimal nitrogen conditions, these results implicated that OsAMT1;1 had the potential to improve nitrogen use efficiency and grain yield in rice (Ranathunge et al., 2014).

Plant Culture & Treatment

• Rice seeds (O. sativa ssp. Japonica ‘Nipponbare’) were surfacesterilized with 2.5% NaClO for 30 min, rinsed thoroughly with distilled water, then soaked for 24 h in distilled water at 37 °C in the dark.Seeds were then transferred to a plastic mesh placed over the surface of distilled water (in a container of ca. 8 L capacity) and allowed to germinate for 6 days before providing light at 27 °C. Uniform seedlings were selected in batches of three and then transferred to a tank containing 8 L of IRRI nutrient solution (1.25 mM NH4NO3, 0.3 mM KH2PO4,0.35 mM K2SO4, 1 mM CaCl2·2 H2O, 1 mM MgSO4·7 H2O, 0.5 mM Na2SiO3, 20 μM NaFeEDTA, 20 μM H3BO3, 9 μM MnCl2·4 H2O, 0.32 μM CuSO4·5 H2O, 0.77 μM ZnSO4·7 H2O and 0.39 μM Na2MoO4·2 H2O, pH5.8). The outer walls and the bottom of the containers were painted black to prevent light from entering inside the tanks (to prevent algal growth). Plants were grown in a greenhouse at 27 °C/25 °C (day/night) for 10 days with a 16 h light/8 h dark regime (light intensity was 400 μmol m−2 s−1, the relative humidity was kept at 70%). The solution was exchanged every 2 days.
• Total RNA of each sample was isolated using the TRIzol total RNA extraction kit (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. RNA quality was characterized on an agarose gel electrophoresis and spectrophotometry. High quality RNA with 28S:18S more than 1.5 and absorbance 260/280 ratios between 1.8 and 2.2 was used for library construction and sequencing.
• The raw reads were filtered before data analysis, the adaptor contamination was removed, the reads were screened from the 39 to 59to trim the bases with a quality score of Q b 20 using 5 bp windows and the reads with final length less than 25 bp were removed using the cutadapt software and fastQC method. The remaining (clean) reads were mapped to the reference genome of Japonica variety Nipponbare (ftp://ftp.ensemblgenomes.org/pub/release-21/plants/fasta/oryza_sativa/dna/)using bowtie2 and tophat2 software(Trapnell et al., 2009). During mapping, mismatches of no more than two bases were allowed in the alignment. Gene structure information was obtained from Ensembl (http://www.ensembl.org/index.html) annotation. We used the RPKM (reads per kilo bases per million reads) method to calculate unique gene expression levels according to the equation: RPKM = total exonreads / mapped reads (millions) × exon length (kb). For functional annotation, the expressed genes were selected and compared against the reference genes from the Ensembl database (http://www.ensembl.org/index.html). Gene Ontology (GO) annotation analysis was performed using Blast2GO software (http://www.blast2go.org/), an automated tool for the assignment of GO terms. The annotation result was categorized with respect to biological process, molecular function, and cellular component.In order to gain an overview of gene pathway networks, KEGG analysis was performed using the online KEGG Automatic Annotation Server(KAAS) (http://www.genome.jp/tools/kaas/). EggNOG (evolutionary genealogy of genes: non-supervised orthologous groups) functional category analysis was carried out by online protein database (http://eggnog.embl.de/version_4.0.beta/).
• The R package DESeq (Anders and Huber, 2010) was performed to identify the differentially expressed genes. This method represents the widely accepted and accurate analysis approaches of RNA-Seq data.The researchers first mapped high-quality reads to the reference genome of Japonica variety Nipponbare (ftp://ftp.ensemblgenomes.org/pub/release-21/plants/fasta/oryza_sativa/dna/) to calculate the number of reads mapped to each gene in six samples. These raw read counts were then used as the input of DESeq to get the normalized signal for each gene,for this purpose we used the Tophat2 software, version 2.0.3 (Trapnell et al., 2009) with default settings. Aligned reads were assembled by the Cufflinks software (version 2.0.2) (Trapnell et al., 2010, 2012).Those with p-value b 0.05 were considered as significant differential expression, and a 2-fold variance was used to identify the genes differentially expressed between every two libraries (nitrogen-free compared to control and high ammonium compared to control, respectively).Then we performed GO (http://geneontology.org/) and KEGG (http://www.genome.jp/kegg/) function enrichment analysis to the differentially expressed genes (DEGs).
• Primers designed (Primer Premier 5 software) for each gene were given in Table S1. qRT-PCR was done with a BioRad CFX96™ Real-time System C1000 Thermal Cycler using SYBR® Premix Ex TaqTM (TliRNaseH Plus, TaKaRa, Japan) according to the manufacturer's protocol.

Illumina sequencing

• To obtain a comprehensive understanding of the genes that were affected by changes in ammonium availability, separate RNA samples were prepared respectively from roots and shoots subjected to nitrogen-free (0 mM) and high ammonium (10 mM) for 4 h with 1 mM ammonium as the control, and sequenced using the Illumina sequencing platform.

Research Findings

• EggNOG (evolutionary genealogy of genes: non-supervised orthologous groups) was used to classify orthologous gene products. The orthologous group genes in this database are annotated with functional description lines (derived by identifying a common denominator for the genes based on their various annotations), with functional categories (i.e. derived from the original cluster of orthologous groups categories) (Jensen et al., 2008). The identified sequences can be aligned to the eggNOG database to predict and classify their possible functions.However, only 311 among 165,411 putative proteins from 6 libraries were classified functionally into 21 molecular families according to eggNOG database (Fig. 1).

'Fig. 1. EggNOG annotations of identified proteins from six libraries under varied nitrogen supplies (0 mM NH4 +, 1 mM NH4 + and 10 mM NH4 +). Histogram presentation of the protein function category. All identified proteins were aligned to the eggNOG database and functionally classified into at least 21molecular families. The x-axis represented the function category the proteins belong to and the y-axis the protein numbers.'

• Based on sequence homology, 137,157 out of 165,411 genes were categorized into 53 functional groups that belong to the biological process, cellular component and molecular function clusters (Fig. 2).

'Fig. 2. Gene Ontology classification of the genes identified from six libraries under varied nitrogen supplies (0 mM NH4 +, 1 mM NH4 + and 10 mM NH4 +). Histogram presentation of the Gene Ontology classification. The results were summarized in the three main GO categories: biological process, cellular component and molecular function. The x-axis represented the functional category of the genes and the y-axis the gene numbers.'

• The results are derived from the differential expression analysis experiment between every two libraries (the nitrogen-free transcripts compared to the control and the high ammonium transcripts compared to the control, respectively). When compared the nitrogen-free transcripts with the control ones (1 mM), of 394 DEGs in root transcripts,143 DEGs were up-regulated and 251 DEGs were down-regulated, and of 468 DEGs in shoot transcripts, 119 DEGs were up-regulated and 349 DEGs were down-regulated respectively (Fig. 3a).

'Fig. 3. DEGs in rice roots and shoots under nitrogen-free (0 mM NH4 +) and high ammonium (10 mM NH4 +) conditions. a. DEGs in rice roots and shoots under nitrogen-free condition (0 mM NH4 +) compared to the control condition (1 mM NH4 +). Base on DESeq software, genes with p-value b 0.05 were considered as significantly differential expression,and a 2-foldvariancewas usedto identify the genes differentially expressedbetween every two libraries.'

• When transcripts from the high ammonium condition were compared with the control, 63 DEGs in roots and 115 DEGs in shoots were obtained respectively. In roots, 6 DEGs showed higher expression and 57 lower expression, and in shoots, 93 DEGs showed higher expression and 22 lower expression (Fig. 3b).

Fig. 3. DEGs in rice roots and shoots under nitrogen-free (0 mM NH4 +) and high ammonium (10 mM NH4 +) conditions. b. DEGs in rice roots and shoots under high ammonium condition (10 mM NH4 +) compared to the control condition (1 mM NH4 +). Base on DESeq software,genes with p-value b 0.05were consideredas significantly differential expression,anda 2-fold variance was used to identify the genes differentially expressed between every two libraries.

Labs working on this Project

• State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
• University of Chinese Academy of Sciences, Beijing 100049, China
• Institute of Horticulture, Jiangsu Academy of Agricultural Sciences, Nanjing 210008, China

Corresponding Author

• Shun-ying Yang: yhsu@issas.ac.cn