Microarrays revealed general-key genes responsive to implantation of low-energy N + ion beam in rice

Implantation with low-energy ion beam can induce various plant biological effects including stimulation, damage and mutation. But the adaptive mechanism altering gene expression in response to this stressor in plant is not fully understood. A highly thorough and comprehensive analysis to investigate the general-key genes responsive to implantation with low-energy ion beam in plant is important to understand the diverse mechanism. We used Agilent Rice Gene Expression Microarray to investigate the overlap differentially expressed genes between two independent implantation experiments underlying three ion fluences. Our microarray data showed that 26 up-regulated overlap genes and 6 down-regulated overlap genes were observed. The Gene Ontology terms analysis showed that genes with functions including kinase, transporter, acceptor, transcription regulation were involved in signaling and response biological processes in rice responding to the implantation with ion beam. Our data also implied that ABA signal transduction pathway is involved in response to ion-beam implantation in rice. The RiceNet co-expressed network analysis showed the direct and indirect coexpressed linkages among these up-regulated genes, which suggested some signal transduction pathways should be involved in this response and remained unclear. Our microarray data revealed the general and key genes responsive to the stress of implantation with low-energy ion beam during the rice germination. These data provide information on the candidate genes for further elucidation regarding the molecular mechanisms of the biological effects of ion-beam implantation and its application for improvement of corn.


INTRODUCTION
Low-energy ion beam as a new mutagen has been extensively applied to organisms for genetic transformation, breeding and creation of aneuploids (Feng et al., 2007).As a kind of environmental stress, it can induce various biological effects including growth stimulation, damage, lethality, mutation (Yu, 2007).Numerous adaptive mechanisms in cells alter gene expression in response to stressors.Many functional proteins, involved in signaling pathways are responsible for response to environmental stresses including salinity, drought, submergence, temperature extremes (high and low temperatures); and heavy metals are identified and recognized (Tardif et al., 2007;Zhu, 2002).However, the key genes and their network responsive to implantation with low-energy ion beam remain not fully elucidated because few of these genes need to be identified and recognized in plant.Recently, genome expression analysis was used to identify the key functional genes involved in response to abiotic stress for its high throughput detection, especially the whole-genome microarrays (Zhou et al., 2007;Walia et al., 2007;Wang et al., 2007).
Rice's (Oryza sativa) compact genome size (≈430 Mb), well-established methods for genetic transformation, availability of high density genetic maps and wholegenome microarrays (Jung et al., 2008), finished genome sequence (Matsumoto et al., 2005), and close relationships with other cereals, all make rice an ideal model system that studies plant physiology including tolerance of stress, development, agronomics, and genomics of grasses (Shimamoto and Kyozuka, 2002).In previous extensive studies, many research groups have been examining the effects of a wide variety of abiotic and biotic stresses in rice (Jwa et al., 2006).So, we selected the rice seeds as the experimental materials in this study.Previously, we focused on gene expression profiles in promoted-growth rice with germination stage from the seeds implanted by low-energy N + beam.However, it was observed that various experiments with different-ion-fluence implantation showed the great divergent gene expression profiles, even different experimental replicates (Ya et al., 2012).So, it is difficult to identify and recognize the general-key functional genes that were ubiquitous in response to the stress of implantation with low-energy ion beam in rice.
In this study, we propose a strategy to find out the overlap differentially expressed genes (DEGs) in rice among the multiple microarrays on two independent implantation experiments with three ion fluences.These DEGs should be commonly differentially expressed and the key role in response to the stress of implantation with low-energy ion beam in rice.The results enable the identification of genes regulating response to implantation with low-energy ion beam, facilitating engineering of pathways critical to rice tolerance.

Rice seeds and culture
Dry seeds of rice cultivar Xindao-18 (Oryza sativa L. ssp.japonica) were used in ion implantation experiments.After implantation with the ion beam, all seeds were planted on sterile medium with 0.8% agar (Sigma) in a climate chamber in the dark at 28°C.After the seeds for the microarrays had been incubated for 96 h, the seedlings were divided into two groups.One group was used for the RNA isolation, while the other was used for investigation of the simplified seed vigor index from the 10-day-old seedlings grown in a climate chamber during a 12-h dark/12-h light cycle at 28°C.

Implantation of low-energy N + ion beam and investigation of simplified seed vigor index
The low-energy ion beam implantation of seeds was performed with the Ion Beam Bioengineering Facility (UIL.0.512,TNV, Russia).In the present study, we carried out two independent implantation experiments for microarray.In the first implantation experiments, the seeds were used at 62 days after harvesting and seed moisture content is 7.0%; the ion fluences used for energetic N + -ion-beam (40 KeV) implantation were at 3×10 17 N + /cm 2 , 6×10 17 N + /cm 2 and 9×10 17 N + /cm 2 , respectively.Controls included seeds that were in normal surroundings and a vacuum without ion implantation for 264 min that was similar to the time of implantation with fluence at 6×10 17 N + /cm 2 .In the second implantation experiments, seeds were used at seven months after harvesting and its seed moisture content is 6.5%; the ion fluences used for implantation with lowenergy (40 KeV) N + were at 2×10 17 N + /cm 2 , 5×10 17 N + /cm 2 and 8×10 17 N + /cm 2 .Controls included seeds that were in normal surroundings and a vacuum without ion implantation for 352 min that was similar to the time of implantation with fluence at 8×10 17 N + /cm 2 .For each ion fluence implantation, three independent biological replicates were used.Two hundred seeds were implanted in each replicate.The germination rate (from 100 seeds) was investigated from the 7-day-old seedlings, and all the seedlings that were used to investigate the germination rate (from 100 seeds) were oven dried at 80°C for 12 h to investigate the dry weight (g).

RNA extraction
We mixed thirty uniformed rice seedlings underling each ion fluence as a sample to prepare for mixed RNAs and constructed the RNA pool from three biological replicates.A total of mixed RNAs were isolated using RNA plant reagents (Tiangen Biotech) and purified by use of the RNeasy Plant Kit (Qiagen).

Agilent microarray hybridization and data analysis
The Agilent Microarray hybridization (Agilent-015241 Rice Gene Expression Microarray) and raw data analysis were carried out by the Shanghai Bio Company Ltd., including the procedures for cDNA and cRNA synthesis, cRNA Cy3 fluorescence labeling, hybridization, washing, scanning (Agilent G2565BA Microarray Scanner System), data collection, and normalization.This experiment was performed three times, resulting in three biological replication samples for each ion fluence for the significant statistics.
We collected the expression signals, and the present/absent calls from the raw data and analyzed them using the SBC Analysis System in one-way ANOVA (SAS, a web server, http://sas.ebioserivce.com),and sorted the differentially expressed transcripts data in Excel.Based on the statistics analysis, a transcript was considered significantly up-or down regulated if it met all of the following criteria:  1) showed a statistically significant differential expression at the adjusted p value< 0.05; 2) had a cut-off value at a 2-fold change; 3) had "present" calls on all of the three replicates samples for the controls and/or the implantation.

Detection of the key DEGs
We collect overlapping DEGs in multi-microarrays for the samples with different ion fluence and different experimental replicates.

Biological effects of the implantation with low-energy N + ion beam
In this study we investigate the biological effects of the implantation with low-energy N + ion beam according the rice simplified seed vigor index.The results showed that energetic N + (40 Kev) ion beam can produce biological effects of growth promotion (Table 1, in first implantation with ion fluence at 6×10 17 N + /cm 2 ) and growth inhibition (Table 2, in the first implantation with ion fluence at 9×10 17 N + /cm 2 , in the second implantation with ion fluence at 2×1017 N + /cm 2 ).Here, we selected the sample that is implanted by N + ion beam with fluence at 6×10 17 N + /cm 2 in the first implantation experiment and that is implanted by N + ion beam with fluence at 2×10 17 N + /cm 2 , 8×10 17 N + /cm 2 (a larger-fluence ion beam implantation) in the second implantation experiment for the micaroarrays.

Profiles of the DEGs
We detected the DEGs by comparing the expression signals value of the genes between the implanted samples and the blank control.The microarray analysis showed that there are 821 DEGs underlying the ionbeam fluence at 6×10 17 N + /cm 2 in the first implantation experiment (Table 3); 1256 DEGs underlying the ionbeam fluence at 2×10 17 N + /cm 2 and 1136 DEGs underlying the ion-beam fluence at 8×10 17 N + /cm 2 in the second implantation experiment (Table 4).
The DEGs number has greater difference between the samples implanted by different ion fluence.It suggested that a single independent microarray can not reflect the comprehensive and general key genes responsive to the ion-beam implantation stress.So we considered the genes that were differentially expressed in all microarrays date underlying three ion fluence implantation as the comprehensive and general DEGs associated with response to the ion-beam implantation stress in rice.By comparing the microarray data between the two independent implantation experiments resulting in different biological effect, we obtained 26 up-regulated (Table 5) and 6 down-regulated overlap general-key DEGs (Table 6) related to response to ion-beam implantation in rice.The short description (Tables 5 and   Hits refer to the number of DEGs clustered into certain pathways. 6) showed that genes related to kinase, transporters, signals, resistance and so on are involved in response to ion-beam implantation.

Gene ontology terms and pathway analysis of the DEGs
In order to investigate the functional category enrichment of these DEGs, we analyzed the functional features of these DEGs according the GO terms using the SAS system (a web server).One transcript could be classified into more than one function catalog.Results showed that these 26 up-regulated DEGs were classified into 11 functional groups and one unclassified groups (Table 7), and were enriched into 13 biological processes (Table 8).
The results also show an enrichment of signaling including kinase, transporter, transcription factor (TF) and so on, and these up-regulated DEGs were enriched in response process (38.5%, 10/26) (Table 8).It was indistinctly observed that genes related to antioxidant function and oxidation reduction process were involved in response to implantation, and this finding is coincident with many previous studies (Feng and Yu, 2006).The probe Os07g0638400 was involved in three KEEG pathways listed in Table 9.These pathways are all associated with phenylpropanoid which are a group of plant secondary metabolites derived from phenylalanine and having a wide variety of functions both as structural and signaling molecules.So we considered that phenylpropanoid should be an import compounds responsive to implantation with ion beam.
It showed that the six down-regulated DEGs were classified into 8 functional groups and one unclassified groups according to molecular function GO term analysis (Table 10), and were enriched in 10 biological processes according to biological process GO term analysis (Table 11).It was observed that down-regulated genes also showed an enrichment of signals including protein kinase, transporter, receptor, and transcription factor.However, these six down-regulated DEGs were not enriched into any KEEG pathways.
Microarray technology has been used in many plants, and function as a powerful tool for high-thought screening of genes responsive to different abiotic stresses including  salt, ABA (abscise acid), cold, heat and drought (Buchanan et al., 2005;Kawaura et al., 2008;Miyama and Tada, 2008;Rensink et al., 2005).However, little knowledge of the microarray for screening the genes responsive to implantation with low-energy ion beam in plant; even the molecular mechanism of the biological effects induced by ion-beam implantation is not enough illuminate.So it is necessary to carry out the microarray on high-thought screening of key genes in response to ion-beam implantation.A biological organism is a complex system; meanwhile, temporal and spatial changes in the biological structure greatly complicate the studies of the interactions between energetic ions and the living biological targets (Feng and Yu, 2006); this divergent physiology of each seeds could result in different response potential.In order to investigate the general-key genes responsive to ion-beam implantation, the overlapping DEGs are necessarily derived from the rice population in multiple ion-beam implantation experiments.
In present study, a total of 32 overlap DEGs, including 26 up-regulated and 6 down-regulated DEGs are observed, comprising 3.90% (32/821), 2.55% (32/1256), 2.81% (32/1136) of the total DEGs underlying three independent ion-fluence implantation respectively.This revealed that less than 10% transcripts were overlap differentially expressed.These 32 overlap DEGs will present target genes for the study on molecular mechanism of biological effects induced by implantation with low-energy ion-beam.
Stress-regulated proteins can be classified into two groups: proteins that take part in signal transduction and proteins that directly play a role in plant survival under stress conditions.Proteins of the first group include transcription factors, RNA-binding proteins, protein kinases and phosphatases (Xiong and Zhu, 2001).10 out of 26 overlap up-regulated transcripts involves response process, and 5, 4, 4 out of the 26 up-regulated DEGs are related to transport, signaling, protein modification (including protein kinases and phosphatases) respectively.This finding suggested that rice responded to the implantation with ion beam by the unknown signals pathway.
Our microarray data on the different biological effects of the ion-beam implantation revealed the general and key genes responsive to stress of implantation with the lowenergy ion beam during the rice germination.This suggests that the differentially expressed transcripts clustered into many groups were associated with the requirements of different events while adapting to the ion implantation.These data provide information on the candidate genes for further elucidation regarding the molecular mechanisms of the biological effects of ionbeam implantation and its use for improvement of corn.
Young Teachers in Universities of Henan Province (Grant No. 2010ggjs-168), National Natural Science Fund of China (Grant No.30800204) and The Key Project Science and Technology Research of the Education Department, Henan Province (Grant No. 12A180025).
Germination rate = Number of the seedlings/total seeds×100% and Simplified seed vigor index = Drought weight of the seedlings (g) × Germination rate × 100.Data were pooled from three independent experiments.

Table 1 .
Simplified vigor index of implanted seeds from the first implantation.

Table 2 .
Simplified vigor index of implanted seeds from the second implantation.

Table 3 .
DEGs number in the first implantation experiment.

Table 4 .
DEGs number in the second implantation experiment.

Table 5 .
The up-regulated general-key DEGs.Short descriptions were annotated according to RAP-DB (Rice Annotation Project Database).Fold change in each gene is not expressed as log2.The P-value threshold of 0.05 was used for significant differential expression.

Table 6 .
The down-regulated general-key DEGs.Short descriptions were annotated according to RAP-DB (Rice Annotation Project Database).Fold change in each gene is not expressed as log2.The P-value threshold of 0.05 was used for significant differential expression.

Table 7 .
Molecular function of the up DEGs.

Table 8 .
Biological process of the up DEGs.

Table 9 .
KEEG pathway enrichment of the up-regulated DEGs.

Table 10 .
Molecular function of down DEGs.

Table 11 .
Biological process of down DEGs.