View source for IC4R003-lncRNA-2015-26734039

== Project Title ==
'''RNA-Seq Analysis of Rice Roots Reveals the Involvement of Post-Transcriptional Regulation in Response to Cadmium Stress '''

==The Background of This Project==
* Cadmium (Cd) is one of the most toxic heavy metals to organisms. Unlike some essential heavy metals, such as copper (Cu), zinc (Zn), manganese (Mn), and nickel (Ni) that are necessary for plant growth and development, Cd is considered a non-essential metal element for plants. Widely spread Cd pollution has significantly affected human health both in term so fits direct effect on crop production and its high accumulation in the edible part of crops such as rice. Previous studies have shown that excessive Cd in plants causes an accumulation of reactive oxygen species (ROS), lipid peroxidation, enzyme inactivation, and DNA and membrane damage, resulting in various toxicity phenotypes, such as chlorosis, wilting, growth reduction, and cell death. However,assignalingmolecules,ROS can be produced at controlled levels and can lead to tolerance responses.
* Plants have evolved several common mechanisms to prevent excess Cd effects, such as extracellular exudates, transport, chelation, and sequestration and repair of damaged proteins. By inhibiting toxic metal transport,plants can reduce to xic metal influx and enhanc emetal removal from the cytosol. Several transporters involved in the acquisition, distribution and home ostasis of Cd in plants have been identified, including heavy metal ATPases (HMA), ATP-binding cassette transporters (ABC), natural resistance-associated macrophage protein (Nramp), metal transporter proteins (MTPs), and low-affinity cation transporter (LCT). One recent study showed that Cd enter into rice root through OsNramp5, originally uptake transporter for essential element Mn, because of the unspecificity properties of this transporter. The HMAf amily transporter Os HMA2 and Os HMA3 playsroles in translocation of Cd into shoot and sequestration of Cd into vacuole,respectively. In mature stage, OsLCT1 regulates cadmium transport into rice grains. In Arabidopsis, the ABC transporter AtPDR8 is a cadmium extrusion pump conferring heavy metal resistance, whereas the phytochelatin transporters AtABCC1 and AtABCC2 mediate tolerance to cadmium and mercury. Cadmium-inducible expression of the ABC-type transporter AtABCC3 increases phytochelatin-mediated cadmium tolerance in Arabidopsis. Glutathione (GSH) and phytochelatins (PCs) chelating represent another detoxification strategy in plant cells.

==Plant Culture & Treatment==
* Rice (Oryza sativa spp. japonica cv. Nipponbare) seeds were sown on mesh floating in a 0.5mM calcium chloride (CaCl 2 ) solution and maintained for 2 days at 25–30 ◦ C in the dark, thereby inducing germination. Seedlings were transferred into Kimura B nutrient solution containing the macronutrients (mM): (NH 4 ) 2 SO 4 (0.18), MgSO 4 ·7H 2 O (0.27), KNO 3 (0.09), Ca(NO 3 ) 2 ·4H 2 O (0.18), and KH 2 PO 4 (0.09); and the micronutrients (µM): MnCl 2 ·4H 2 O (0.5), H 3 BO 3 (3), (NH 4 ) 6 Mo 7 O 24 ·4H 2 O (1), ZnSO 4 ·7H 2 O (0.4), Fe-EDTA (20), and 0.2µM CuSO 4 ·5H 2 O. The pH of the nutrient solution was adjusted to 5.5, and held under normal greenhouse conditions with illumination provided by cool-white fluorescent lamps. Growth conditions were as follows: 27/24 ◦ C day/night temperatures, 60–80% relative humidity, and a 14/10-h day/night photoperiod. Fifteen-day-old rice seedlings were treated with or without 10 and 100µM solutions of Cd (II) hydrochloride (CdCl 2 ) for 24h. Following Cd treatment, roots were harvested for RNA extraction and subsequent analysis. Samples were stored at −80 ◦ C if not immediately used for RNA isolation. All experiments were performed at least twice with three biological replicates each, and representative results of one experiment are shown.
[[File:IC4R003-lncRNA-2015-26734039-1.PNG|1000px|thumb|center|'''Figure 1''' '' Flowchart of our RNA-seq data analysis workflow.'']]

==Research Findings==
* To gain additional insight into the rice transcriptomic response to environmental Cd stress, 15-day-old rice seedlings were treated with 10 or 100µM solutions of Cd 2+ , or without Cd (control), for 24h, at which point root samples were harvested and labeled as Cd+, Cd++, and control, respectively. These samples were used for 101 bp paired-end (PE) deep sequencing on an Illumina HiSeq 2500 platform. After the adaptor and low-quality sequences of pair-end reads were trimmed, in total, ∼218 million clean reads (∼21.5 Gb) were obtained, with an average of ∼72.8 million reads (∼6.9Gb) per sample. Our workflow for analysis of RNA-Seq data is illustrated in '''Figure 1'''. An average of ∼68.9 million clean reads per sample, corresponding to ∼94.6% of the total clean reads per sample, were aligned to the Os-Nipponbare-Reference-IRGSP-1. 0 reference genome using TopHat2. Among the mapped reads per sample, ∼96.7% were uniquely aligned, and the remaining 3.3% were multiple mapped reads ('''Table 1'''). For each sample, the resulting aligned reads were then analyzed with Cufflinks, which assembles the aligned reads into transcripts. The assembled transcripts were further filtered based on greater than 0 FPKM (Fragments Per Kilobase Million) expression level. The remaining transcripts were processed separately by comparing our merged reference transcript annotation using Cuffcompare and further classified into four main categories: known reference transcript, novel isoform transcripts, antisense transcripts, and intergenic transcripts. An average 32.7% of 113,001 merged known reference transcript sper sample was expressed.Averagely, 8908 novel isoform transcripts, 157 antisense transcripts, and 754 intergenic transcripts for each sample were also detected('''Table 2''').
[[File:IC4R003-lncRNA-2015-26734039-2.PNG|500px|thumb|right|'''Table 1''' ''Statistics of the Read Alignments in the RNA-Seq study.'']]
[[File:IC4R003-lncRNA-2015-26734039-3.PNG|500px|thumb|right|'''Table 2''' ''Number of transcripts detected by annotation classification reported by Cufflinks and cuffcompare.'']]
* Differential expression genes (DEGs) were identified between Cd+ or Cd++ and control samples using DESeq. A total of 1169 DEGs of Oryza sativa in response to Cd stress from the RNA-Seq data were identified. Under Cd+ treatment, 214 were up-regulated while 22 were down-regulated. Under Cd++ treatment, 914 genes were up-regulated, and 248 were down-regulated. These results suggest that most up- and down-regulated genes are common under the two gradients of Cd treatment. 208 out of 214 regulated genes and 21 out of 22 repressed genes regulated by Cd+ treatment were also among the up- and down-regulated genes regulated by Cd++ treatment. In addition to the significantly increased number of up- and down-regulated genes after Cd++ compared with Cd+ treatment, the expression ratio also changed significantly between the two concentrations of Cd relative to the control, indicated by the Heatmap analysis. We compared these DEGs with results from a previous study that used an Agilent two-color Rice Oligo DNA Microarray 44K designed for RAP-DB genes. 89 (45.4%) out of 196 Cd+ up-regulated genes and 294 (35.2%) out of Cd++ 836 up-regulated genes identified in our RNA-Seq assay were also found in the microarray datasets, while in contrast, most of the down-regulated genes varied between the two assays (Figure 2D). In addition to the differences in culture conditions and the rice cultivars we used, the differences TABLE 2 | Number of transcripts detected by annotation classification reported by Cufflinks and cuffcompare. Cufflinks transcripts Control Cd + Cd ++ Total reference transcripts (T) 113,001 Known reference transcripts (K) (K/T%) 36,923 (32.7%) 37,028 (32.8%) 36,743 (32.5%) Novel isoform transcripts (N) 8906 8868 8950 Antisense transcripts (A) 166 175 157 Intergenic transcripts (I) 721 732 810 between two-color microarray and RNA-Seq technologies may also lead to the discrepancy on some DEGs results. Real-time qRT-PCR analysis was also performed to validate some up- and down-regulated genes expression data according to the RNA-Seq results.

== Labs working on this Project ==
* College of Life Sciences, Nanjing Agricultural University, Nanjing, China

==Corresponding Author==
* ''' Luqing Zheng '''(zhenglq@njau.edu.cn)